From a83d27905a2e78b194e2cf8d9fe80803b39b9f64 Mon Sep 17 00:00:00 2001 From: Jonathan Cooper Date: Mon, 26 Mar 2018 08:51:09 +0100 Subject: [PATCH 1/3] Copy latest files from private repository --- HDFView.png | Bin 0 -> 109188 bytes MATLAB/README.md | 36 + MATLAB/setup.py | 42 + MATLAB/source/DisplayVideos.m | 800 ++++++ MATLAB/source/LabviewHeader.m | 210 ++ MATLAB/source/NwbFile.m | 318 +++ MATLAB/source/numpy2mat.m | 41 + MATLAB/source/resize_videos.m | 50 + MATLAB/source/tuple2mat.m | 18 + MATLAB/tests/SharedFixtures.m | 17 + MATLAB/tests/TestImport.m | 105 + MATLAB/tests/TestLabviewHeader.m | 71 + MATLAB/tests/TestNumpy2mat.m | 80 + MATLAB/tests/TestReadNwb.m | 82 + MATLAB/tests/TestRunner.m | 36 + MATLAB/tests/data/161215_15_58_52.sig | 1768 ++++++++++++ MATLAB/tests/data/sample_header.ini | 23 + MATLAB/tests/data/test_epochs.nwb | Bin 0 -> 194078 bytes Python/README.md | 84 + Python/requirements/legion.txt | 19 + Python/requirements/main.in | 10 + Python/requirements/main.txt | 17 + Python/requirements/test.txt | 1 + Python/setup.py | 43 + Python/silverlabnwb/__init__.py | 3 + Python/silverlabnwb/e-labview.py | 37 + Python/silverlabnwb/e-pixeltimes.py | 56 + Python/silverlabnwb/metadata.py | 103 + Python/silverlabnwb/metadata.yaml | 112 + Python/silverlabnwb/metadata_gui.py | 496 ++++ Python/silverlabnwb/nwb_file.py | 958 +++++++ Python/silverlabnwb/nwb_util.py | 87 + Python/silverlabnwb/script.py | 51 + Python/silverlabnwb/subsample_nwb.py | 282 ++ Python/test/data/161215_15_34_21.sig | 1791 ++++++++++++ Python/test/data/161215_15_58_52.sig | 1768 ++++++++++++ Python/test/data/170317_10_11_01.sig | 2430 +++++++++++++++++ Python/test/data/170322_14_06_43.sig | 738 +++++ Python/test/data/Experiment Header.ini | 20 + .../test/data/Speed_Data/Speed data 001.txt | 26 + Python/test/data/expected.yaml | 85 + Python/test/data/metadata.yaml | 10 + .../sample_miniscan_fred_170322_14_06_43.sig | 345 +++ .../sample_pointing_fred_170317_10_11_01.sig | 475 ++++ 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z=UBFh)G>+7+DY%!Ehj8ff7x;>ky+|x-6a3n7f-CruCl+|qo!VM`FA@kPMC{+*?H$h zOrE^cf44*STPe$0>D^y6Cr(`AmKC|A#XV}#A%icq_8L>YCS8$8{`T$LBa3sbrtR(R zg)+C_?rTlkEa^ItH~Y>Aaq+dgo<{-;^uaim(&_N(eGt;Na&`%9Rcg wV98_bE3rB0RsK7-vTEIqV_y5&CvJLUzlGa)_Vv?~qd_6z>FVdQ&MBb@0LX&k)&Kwi literal 0 HcmV?d00001 diff --git a/MATLAB/README.md b/MATLAB/README.md new file mode 100644 index 0000000..f68b2d4 --- /dev/null +++ b/MATLAB/README.md @@ -0,0 +1,36 @@ +# Matlab API for NWB use in the Silver Lab + +Quick usage example: + +``` matlab +nwb = NwbFile('Data/161215_15_34_21.nwb'); +gui = DisplayVideos(nwb); +``` + +For examples of using the API from Matlab analysis scripts, see +https://github.com/SilverLabUCL/Data-Analysis-Hana/blob/hdf5-experiment/RunUsingNwb.m + + +## Automated Matlab testing + +Tests are stored in the [tests](./tests) folder. +New tests are written as classes named like `TestSomething` within this folder. +It's probably easiest to start by copying the structure of an existing test. + +Tests may be run locally, +and are also run automatically when pushing to the `master` branch or creating/updating pull requests. + +### Local test running + +Within Matlab, change to the `MATLAB/tests` folder (or add it to your path) then run +``` +TestRunner() +``` + +### Automated tests + +Results are displayed at http://jenkins.rc.ucl.ac.uk/ - ask Jonathan Cooper to give your GitHub account permissions to see this. +Tests of the master branch are at http://jenkins.rc.ucl.ac.uk/job/SilverLab-main/ and for pull requests under http://jenkins.rc.ucl.ac.uk/job/SilverLab-pull-request/. + +You can also see results of specific builds linked from the pull requests / [commits](https://github.com/SilverLabUCL/SilverLab_NWBv1/commits/master) themselves. +Click on 'Console output' to see the actual test output (scrolling past a lot of test environment setup output!). diff --git a/MATLAB/setup.py b/MATLAB/setup.py new file mode 100644 index 0000000..3c35604 --- /dev/null +++ b/MATLAB/setup.py @@ -0,0 +1,42 @@ +# A little Python script to set the Matlab paths correctly for using NWB + +import argparse +import os +import re +import sys + + +def munge_path(path): + """Convert `path` to a native system path so Matlab understands it.""" + if sys.platform.startswith('win32'): + if re.match(r'/\s/.*', path): + path = os.path.realpath('{}:{}'.format(path[1], path[2:])) + elif sys.platform.startswith('cygwin'): + if re.match(r'/cygdrive/\s/.*', path): + path = os.path.realpath('{}:{}'.format(path[10], path[11:])) + return path + + +def setup_matlab(silverlab_path, nwb_api_path): + silverlab_path = munge_path(silverlab_path) + nwb_api_path = munge_path(os.path.join(nwb_api_path, 'matlab_bridge', 'matlab_bridge_api')) + print('Setting up Matlab with paths:') + print(' NWB API folder: {}'.format(nwb_api_path)) + print(' Our Matlab folder: {}'.format(silverlab_path)) + matlab_commands = [ + "pyversion '{}';".format(sys.executable), + "addpath('{}');".format(nwb_api_path), + "addpath(genpath('{}'));".format(silverlab_path), + "success = savepath();", + "if success == 1; error('Failed to save Matlab path - set manually'); else quit; end;" + ] + os.system('matlab -nosplash -nodesktop -r "{}"'.format(' '.join(matlab_commands))) + + +if __name__ == '__main__': + parser = argparse.ArgumentParser(description='Setup Matlab for NWB use.') + parser.add_argument('nwb_api_path', + help='path to the NWB API sources') + args = parser.parse_args() + our_matlab_path = os.path.join(os.path.dirname(__file__), 'source') + setup_matlab(our_matlab_path, args.nwb_api_path) diff --git a/MATLAB/source/DisplayVideos.m b/MATLAB/source/DisplayVideos.m new file mode 100644 index 0000000..d8d75cf --- /dev/null +++ b/MATLAB/source/DisplayVideos.m @@ -0,0 +1,800 @@ +classdef DisplayVideos < handle +%DISPLAYVIDEOS Show/control a GUI to play synced videos from an NWB file. +% +% This allows the parallel, time-synced display of multiple video +% streams, alongside other timeseries data displayed as static graphs. +% A vertical bar on the graphs indicates the current time point shown +% in the videos. + +% Read-only properties +properties (GetAccess = public, SetAccess = private) + % The NWB file object being displayed. + nwb; + % The main figure handle for the GUI window. + fig; + % Names of the videos to display. + video_names; + % Paths to the individual video files. + video_paths; + % Axes objects in which to display each video. + video_axes; + % Text uicontrols displaying the title of each video. + video_titles; + % Cell array with the starting_frame attribute for each video series. + start_frames; + % The current VideoReader instances for each video. + videos; + % The timeseries for each video. + video_times; + % The combined timeseries for all videos: sorted unique timestamps (s). + joint_t; + % Where in the joint timeseries each video has frames. + video_frames; + % Index of the last frame displayed, within the combined timeseries. + last_frame; + % Index of the last frame displayed for each video file. + last_frames; + % Structure containing UI controls. + buttons; + % Structure containing data labels. + data_labels; + % Axes for displaying per-ROI data, e.g. df/f + roi_axes; + % Axes for displaying single timeseries data, e.g. speed + ts_axes; + % Data being displayed on the ROI axes; (#trials, #rois, #times) array + roi_data; + % Times corresponding to roi_data. + roi_times; + % Data displayed on the timeseries axes; (#trials) cell array + ts_data; + % Times corresponding to ts_data. + ts_times; + % Handles for lines displaying the current time on data plots. + data_time_lines; + % Start times of each trial. + trial_times; +end + +% Properties calculated on the fly, rather than stored. +% See the corresponding get.(property) methods for their definition. +properties (Dependent) + % The timestamp (in seconds) of the currently displayed frame. + current_time; + % Which trial corresponds to the current timestamp. + current_trial; + % Whether the videos are currently playing. + playing; +end + +% Class properties, defining how large various GUI elements are. +properties (Access = protected) + % Height for buttons, text labels, and similar UI controls. + BUTTON_HEIGHT = 20; + % Default gap between elements. + GAP = 10; + % Desired height for data display. + DATA_HEIGHT = 600; + % Desired width for data display. + DATA_WIDTH = 1200; + % Instance property giving the overall dimensions of the video + % displays. + VIDEO_DIMS; +end + +properties (Access = public, Constant) + % Default width to display videos at + DEFAULT_VIDEO_WIDTH = 300; +end + +methods + function gui = DisplayVideos(nwb, width) + %DISPLAYVIDEOS Show a GUI to play synced videos from an NWB file. + % + % Synopsis: gui = DisplayVideos(nwb) + % + % Arguments: + % nwb: an NwbFile instance containing video data (inter alia) + % width: width to display videos at, in pixels (default DEFAULT_VIDEO_WIDTH) + % + % A GUI will be created with axes for each video defined within + % the file. + % + % Returns: + % a handle for the GUI figure window + + gui.nwb = nwb; + [~, nwb_name, ~] = fileparts(nwb.path); + + if nargin < 2 + width = gui.DEFAULT_VIDEO_WIDTH; + end + + % Initialise some of our instance properties + gui.video_names = nwb.video_names; + gui.video_paths = nwb.video_paths; + num_videos = length(gui.video_names); + gui.videos = cell(1, num_videos); + gui.last_frames = zeros(1, num_videos); + gui.start_frames = cell(num_videos, 1); + + gui.find_resized_videos(width); + gui.create_video_axes(width, nwb_name); + gui.determine_times(); + gui.create_buttons(); + gui.create_data_axes(); + gui.plot_speed(); + gui.plot_dff(); + gui.step(); % Show first frames + end + + function create_video_axes(gui, width, nwb_name) + %CREATE_VIDEO_AXES Create the axes for displaying videos. + + num_videos = length(gui.video_names); + % Figure out how much screen space we need for all videos etc. + gui.VIDEO_DIMS = [width 0]; + bottom_positions = zeros(1, num_videos); + dims = zeros(num_videos, 2); + for i=1:num_videos + dims(i, :) = gui.get_ts_item(gui.video_names{i}, 'dimension'); + scale = dims(i, 1) / width; + dims(i, 1) = width; + dims(i, 2) = round(dims(i, 2) / scale); + bottom_positions(i) = gui.BUTTON_HEIGHT + gui.GAP + gui.VIDEO_DIMS(2); + gui.VIDEO_DIMS(2) = gui.VIDEO_DIMS(2) + gui.GAP + dims(i, 2) + gui.BUTTON_HEIGHT; + end + + fig_width = width + 2*gui.GAP + gui.DATA_WIDTH; + fig_height = max(gui.VIDEO_DIMS(2), ... + gui.DATA_HEIGHT + gui.BUTTON_HEIGHT) ... + + gui.BUTTON_HEIGHT + 2*gui.GAP; + + % Create the window + gui.fig = figure('numbertitle', 'off', ... + 'name', ['Videos from ' nwb_name], ... + 'menubar', 'none', ... + 'toolbar', 'none', ... + 'resize', 'on', ... + 'position', [10 10 fig_width fig_height], ... + 'DeleteFcn', @gui.closing); + + % Create axes for each video, showing the initial frame + gui.video_axes = cell(1, num_videos); + gui.video_titles = cell(1, num_videos); + for i=1:num_videos + our_axes = axes(gui.fig, ... + 'Units', 'pixels', ... + 'Position', [gui.GAP/2, bottom_positions(i), ... + dims(i, 1), dims(i, 2)]); + our_axes.XTick = []; + our_axes.YTick = []; + gui.video_axes{i} = our_axes; + % Set video title using uicontrol. uicontrol is used so that text + % can be positioned in the context of the figure, not the axis. + gui.video_titles{i} = uicontrol('style', 'text', ... + 'String', gui.video_names{i}, ... + 'HorizontalAlignment', 'left', ... + 'Units', 'pixels', ... + 'Position', [gui.GAP * 2, ... + bottom_positions(i) + dims(i, 2), ... + 150, gui.BUTTON_HEIGHT], ... + 'Parent', gui.fig, ... + 'BackgroundColor', gui.fig.Color); + end + drawnow; + end + + function create_data_axes(gui) + %CREATE_DATA_AXES Create axes for displaying functional/speed data. + + left = gui.VIDEO_DIMS(1) + gui.GAP + gui.BUTTON_HEIGHT; + bottom = gui.BUTTON_HEIGHT + gui.GAP + gui.BUTTON_HEIGHT; + width = min(gui.DATA_WIDTH, gui.fig.Position(3) - left); + + % Single timeseries data, e.g. speed + gui.ts_axes = axes(gui.fig, 'Units', 'pixels', ... + 'XLimMode', 'manual', ... + 'ButtonDownFcn', @gui.cb_click, ... + 'OuterPosition', ... + [left, bottom, width, gui.DATA_HEIGHT/5]); + gui.tighten_axes(gui.ts_axes); + + % Per-ROI functional data + gui.roi_axes = axes(gui.fig, 'Units', 'pixels', ... + 'XLimMode', 'manual', ... + 'YLimMode', 'manual', ... + 'ButtonDownFcn', @gui.cb_click, ... + 'OuterPosition', ... + [left, bottom + gui.DATA_HEIGHT*0.2 + gui.GAP/2, ... + width, gui.DATA_HEIGHT*0.8]); + gui.tighten_axes(gui.roi_axes); + + % Structures to hold labels & time lines + gui.data_labels = struct('roi_y', '', 'ts_x', '', 'ts_y', ''); + gui.data_time_lines = cell(2, 1); + + drawnow; + end + + function plot_speed(gui) + %PLOT_SPEED Convenience method to plot speed data from our NWB file + % + % Synopsis: gui.plot_speed() + % + % Note that we negate the speed data stored in NWB, to match the + % experimentalists' convention for display. + + speed = gui.nwb.get_trials_data('speed_data'); + speed = cellfun(@(ts) -ts, speed, 'UniformOutput', false); + speed_t = gui.nwb.get_trials_data('speed_data', 'timestamps'); + gui.plot_ts_data(speed, speed_t, 'Time (s)', 'Speed'); + end + + function plot_dff(gui) + %PLOT_DFF Convenience method to compute & plot df/f. + % + % Synopsis: gui.plot_dff() + % + % TODO: Make choice of baseline flexible. + + disp('Calculating df/f...'); + [green, ~, dff_times] = gui.nwb.get_roi_data('Green'); + len = int32(size(green, 3) / 4); + baseline = mean(green(:,:,1:len), 3); + dff = (green - baseline) ./ baseline; + gui.plot_roi_data(dff, dff_times, 'df/f for ROI #'); + end + + function plot_ts_data(gui, data, times, label_x, label_y) + %PLOT_TS_DATA Plot timeseries data on the bottom axes. + % + % Synopsis: gui.plot_ts_data(data, times) + % + % Arguments: + % data: the data to plot, as a cell array (length #trials) of + % 1d timeseries arrays + % times: cell array of timestamps corresponding to each point in + % data + % label_x: label for the x axis + % label_y: label for the y axis + + gui.ts_data = data; + gui.ts_times = times; + gui.data_labels.ts_x = label_x; + gui.data_labels.ts_y = label_y; + gui.update_ts_data_display(); + end + + function plot_roi_data(gui, data, times, label_y) + %PLOT_ROI_DATA Plot some data on the top ROI axes. + % + % Synopsis: gui.plot_roi_data(data, times) + % + % Arguments: + % data: the data to plot, as a (#trials, #rois, #times) array + % times: array of timestamps corresponding to each point in data + % label_y: label for the y axis + + gui.roi_data = data; + gui.roi_times = times; + gui.data_labels.roi_y = label_y; + gui.update_roi_data_display(); + end + + function update_ts_data_display(gui) + %UPDATE_TS_DATA_DISPLAY Refresh the timeseries data axes. + % Internal helper method. + + trial = gui.current_trial; + data = gui.ts_data{trial}; + times = gui.ts_times{trial} - gui.trial_times(trial); + + plot(gui.ts_axes, times, data, 'k-', ... + 'LineWidth', 1, 'HitTest', 'off'); + xlim(gui.ts_axes, [0, times(end)]); + xlabel(gui.ts_axes, gui.data_labels.ts_x, ... + 'FontName', 'Helvetica', 'FontUnits', 'points', 'FontSize', 10); + ylabel(gui.ts_axes, gui.data_labels.ts_y, ... + 'FontName', 'Helvetica', 'FontUnits', 'points', 'FontSize', 10); + gui.ts_axes.ButtonDownFcn = @gui.cb_click; + drawnow; + end + + function update_roi_data_display(gui) + %UPDATE_ROI_DATA_DISPLAY Refresh the ROI data axes. + + trial = gui.current_trial; + trial_start = gui.trial_times(trial); + data = gui.roi_data; + times = gui.roi_times; + n_roi = size(data, 2); + + cla(gui.roi_axes); + hold(gui.roi_axes, 'on'); + alpha(gui.roi_axes, 0.5); + + for i = 1:n_roi + plot(gui.roi_axes, ... + squeeze(times(trial,i,:) - trial_start), ... + squeeze(i + data(trial,i,:)), 'k-', ... + 'HitTest', 'off'); + end; + xlim(gui.roi_axes, [0, max(times(trial, :, end)) - trial_start]); + ylim(gui.roi_axes, [0, n_roi]); + ylabel(gui.roi_axes, gui.data_labels.roi_y, ... + 'FontName', 'Helvetica', 'FontUnits', 'points', 'FontSize', 10); + gui.roi_axes.ButtonDownFcn = @gui.cb_click; + drawnow; + end + + function update_data_display(gui) + %UPDATE_DATA_DISPLAY Replot data, e.g. due to trial changing. + + gui.update_roi_data_display(); + gui.update_ts_data_display(); + end + + function show_data_time(gui) + %SHOW_DATA_TIME Indicate the current time on the data axes. + + t = gui.current_time - gui.trial_times(gui.current_trial); + data_axes = [gui.ts_axes, gui.roi_axes]; + for i=1:2 + ax = data_axes(i); + l = gui.data_time_lines{i}; + if isempty(l) || ~isgraphics(l) + gui.data_time_lines{i} = line(ax, ... + [t t], ax.YLim, 'Color', 'r'); + else + l.XData = [t t]; + l.YData = ax.YLim; + end + end + end + + function tighten_axes(~, ax) + %TIGHTEN_AXES Remove excess space around the central plot. + % Also sets font properties. + + ax.FontName = 'Helvetica'; + ax.FontUnits = 'points'; + ax.FontSize = 10; + ax.FontWeight = 'normal'; + ax.FontAngle = 'normal'; + + outerpos = ax.OuterPosition; + ti = ax.TightInset; + left = outerpos(1) + ti(1); + bottom = outerpos(2) + ti(2); + ax_width = outerpos(3) - ti(1) - ti(3); + ax_height = outerpos(4) - ti(2) - ti(4); + ax.Position = [left bottom ax_width ax_height]; + end + + function create_buttons(gui) + %CREATE_BUTTONS Add UI controls to control play-back. + + gui.buttons = struct; + left = gui.GAP / 2; + bottom = gui.GAP / 2; + % Restart button + width = 40; + gui.buttons.restart = uicontrol('Style', 'pushbutton', ... + 'String', 'Restart', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'Interruptible', 'off', ... + 'Callback', @gui.cb_restart); + left = left + width + gui.GAP; + % Play button + width = 40; + gui.buttons.play = uicontrol('Style', 'pushbutton', ... + 'String', 'Play', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'Callback', @gui.cb_play); + left = left + width + gui.GAP; + % Play mode menu + width = 80; + uicontrol('Style', 'text', 'String', 'Playback mode:', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'HorizontalAlignment', 'right', ... + 'BackgroundColor', gui.fig.Color); + left = left + width + 1; + width = 150; + gui.buttons.play_mode = uicontrol('Style', 'popupmenu', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'String', {'Frame-by-frame', 'Fast'}); + left = left + width + gui.GAP; + % Time slider + width = 30; + uicontrol('Style', 'text', 'String', 'Time:', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'HorizontalAlignment', 'right', ... + 'BackgroundColor', gui.fig.Color); + left = left + width + 1; + width = 150; + gui.buttons.time = uicontrol('Style', 'slider', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'Min', gui.joint_t(1), 'Max', gui.joint_t(end), ... + 'Value', gui.current_time, ... + 'SliderStep', [0.001 0.05], ... + 'Interruptible', 'off', ... + 'Callback', @gui.cb_time); + setappdata(gui.buttons.time, 'lastValue', gui.current_time); + left = left + width + gui.GAP; + % Trial dropdown menu + width = 30; + uicontrol('Style', 'text', 'String', 'Trial:', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'HorizontalAlignment', 'right', ... + 'BackgroundColor', gui.fig.Color); + left = left + width + 1; + width = 100; + gui.buttons.trial = uicontrol('Style', 'popupmenu', ... + 'Position', [left bottom width gui.BUTTON_HEIGHT], ... + 'String', arrayfun(@num2str, 1:gui.nwb.num_trials, 'UniformOutput', false), ... + 'Interruptible', 'off', ... + 'Callback', @gui.cb_trial); + % Display controls now + drawnow; + end + + function cb_trial(gui, source, ~) + % Callback function for the trial drop-down + if source.Value ~= gui.current_trial + trial_start = gui.trial_times(source.Value); + t = find(gui.joint_t >= trial_start, 1); + gui.display_frame(t); + end + end + + function cb_time(gui, source, ~) + % Callback function for the time slider + if source.Value == gui.current_time + % We're playing, and display_frame has 'reset' time already + source.Value = getappdata(source, 'lastValue'); + end + gui.set_time(source.Value); + end + + function cb_restart(gui, ~, ~) + % Callback function for the restart button + gui.display_frame(1); + end + + function cb_play(gui, ~, ~) + % Callback function for play/pause button + if ~gui.playing + gui.play(); + else + gui.stop(); + end + end + + function cb_click(gui, source, ~) + % Callback function for mouse click within axes + loc = source.CurrentPoint(1, 1); + if loc >= 0 && loc <= source.Position(3) + gui.set_time(loc + gui.trial_times(gui.current_trial)); + end + end + + function playing = get.playing(gui) + %PLAYING Determine whether the videos are currently playing + playing = ~strcmp(gui.buttons.play.String, 'Play'); + end + + function was_playing = stop(gui) + % Stop video playback + was_playing = gui.playing; + gui.buttons.play.String = 'Play'; + drawnow; % Let any playing callback complete and stop playback + end + + function closing(gui, varargin) + % Called when the user closes the main GUI window + if (isstruct(gui.buttons) && isfield(gui.buttons, 'play') && ... + isgraphics(gui.buttons.play)) + gui.stop(); + end + gui.videos = {}; % Close video files + end + + function determine_times(gui) + %DETERMINE_TIMES Figure out timestamp information + + num_videos = length(gui.video_names); + for i=1:num_videos + % Open (first) video file + gui.open_video(i, 1); + gui.last_frames(i) = 0; % Nothing shown yet + + % Check for multi-file videos + gui.start_frames{i} = gui.get_ts_attr(gui.video_names{i}, ... + 'external_file', 'starting_frame'); + end + + % Figure out merged timestamp information + gui.video_times = cell(num_videos, 1); + num_frames = cell(num_videos, 2); + for i=1:num_videos + gui.video_times{i} = gui.get_ts_item(gui.video_names{i}, 'timestamps'); + num_frames{i, 1} = numel(gui.video_times{i}); + if i == 1 + last = [0 0]; + else + last = num_frames{i-1, 2}; + end + num_frames{i, 2} = (last(end)+1):(last(end)+num_frames{i, 1}); + end + [gui.joint_t, ~, idx_backward] = unique(horzcat(gui.video_times{:})); + + % Calculate where in joint_t each video has frames + gui.video_frames = cell(num_videos, 1); + for i=1:num_videos + frames = NaN(size(gui.joint_t)); + frames(idx_backward(num_frames{i,2})) = 1:num_frames{i,1}; + gui.video_frames{i} = frames; + end + + % No frames yet shown + gui.last_frame = 0; + end + + function find_resized_videos(gui, width) + %FIND_RESIZED_VIDEOS Check for pre-resized videos. + % + % If the resize_videos() function has been used to generate + % versions of our videos at the size we want, update our paths to + % use those instead. + % + % Arguments: + % gui: the gui instance + % width: the width of video files to look for + + for i=1:length(gui.video_paths) + for j=1:length(gui.video_paths{i}) + path = gui.video_paths{i}{j}; + sized_path = gui.resized_path(path, width); + if exist(sized_path, 'file') + gui.video_paths{i}{j} = sized_path; + end + end + end + end + + function open_video(gui, video_index, file_index) + %OPEN_VIDEO Internal function to open a video file for reading. + % + % Arguments: + % gui: the gui instance + % video_index: which video this is in our list + % file_index: which .avi file to open for this video + + path = gui.video_paths{video_index}{file_index}; + disp(['Opening ' path]); + gui.videos{video_index} = VideoReader(path); + end + + function set_time(gui, time) + %SET_TIME Display the closest frame to the given time. + % + % Arguments: + % gui: the gui instance + % time: time in seconds to display; the latest frame not after + % this is selected + + t = find(gui.joint_t <= time, 1, 'last'); + gui.display_frame(t); + end + + function current_time = get.current_time(gui) + % The timestamp (in seconds) of the currently displayed frame. + if gui.last_frame == 0 + current_time = gui.joint_t(1); + else + current_time = gui.joint_t(gui.last_frame); + end + end + + function trial = get.current_trial(gui) + % Which trial corresponds to the current timestamp. + + if isempty(gui.trial_times) + % Retrieve trial start times from the NWB file. + n_trials = gui.nwb.num_trials; + gui.trial_times = zeros(n_trials, 1); + for i=1:n_trials + gui.trial_times(i) = gui.nwb.get('/epochs/trial_%04d/start_time', i); + end + end + trial = find(gui.trial_times <= gui.current_time, 1, 'last'); + if isempty(trial) + trial = 1; + end + end + + function set_title(gui, i, colour) + %SET_TITLE Update the title for video i. + % + % Displays the camera name and current time (in seconds relative + % to trial start) in the given colour. + trial = gui.current_trial; + trial_start = gui.trial_times(trial); + rel_time = gui.video_times{i}(gui.last_frames(i)) - trial_start; + gui.video_titles{i}.String = [gui.video_names{i} ', t = ' ... + num2str(rel_time) ' s']; + gui.video_titles{i}.ForegroundColor = colour; + end + + function display_frame(gui, t) + %DISPLAY_FRAME Show a single frame for each video. + % + % Typically used to show the next frame. + % + % Arguments: + % gui: the gui instance + % t: index of the frame to display within the joint timeseries + + num_videos = length(gui.videos); + title_cols = cell(1, num_videos); + for i=1:num_videos + our_t = gui.video_frames{i}(t); % Index to display within this video + our_last_frame = gui.last_frames(i); + if isnan(our_t) + % If we're jumping, find the most recent frame to show + if t ~= gui.last_frame + 1 + idx = find(~isnan(gui.video_frames{i}(1:t)), 1, 'last'); + our_t = gui.video_frames{i}(idx); + gui.last_frames(i) = our_t; + end + % Show an indication that this is a stale frame + title_cols{i} = 'red'; + else + gui.last_frames(i) = our_t; + title_cols{i} = 'black'; + end + if ~isnan(our_t) + % Figure out if we need to change video file + last_file = gui.calculate_file_index(i, our_last_frame); + curr_file = gui.calculate_file_index(i, our_t); + if last_file ~= curr_file + gui.open_video(i, curr_file); + end + % Read the requested frame + video = gui.videos{i}; + if our_last_frame ~= our_t - 1 + % Random access read - need to compute desired "time" + frame_offset = our_t - gui.start_frames{i}(curr_file) - 1; + video.CurrentTime = double(frame_offset) / video.FrameRate; + end + if ~video.hasFrame() + disp(['No next frame for ' num2str(i) ' at ' num2str(t)]); + title_cols{i} = 'magenta'; + continue; + end + frame = video.readFrame(); % Next frame read + % Show the frame + our_axes = gui.video_axes{i}; + if ~isgraphics(our_axes) % Just in case! + return; + end + frame = imresize(frame, our_axes.Position(3:4)); + image(our_axes, frame); + our_axes.Visible = 'off'; + end + end + % Update which frame was just displayed + last_trial = gui.current_trial; + gui.last_frame = t; + setappdata(gui.buttons.time, 'lastValue', gui.buttons.time.Value); + gui.buttons.time.Value = gui.joint_t(t); + % Update all video titles now so they get the correct trial offset + for i=1:num_videos + gui.set_title(i, title_cols{i}); + end + if last_trial ~= gui.current_trial + gui.buttons.trial.Value = gui.current_trial; + gui.update_data_display(); + end + gui.show_data_time(); + drawnow; % Allow other callbacks to be processed at this point + end + + function file_index = calculate_file_index(gui, i, t) + %FILE_INDEX Determine which .avi file contains the given time. + % + % Arguments: + % gui: the gui instance + % i: index of the video to query + % t: index of the frame to query + + is_after_start = gui.start_frames{i} < t; + file_index = find(is_after_start, 1, 'last'); % Take the last index + end + + function step(gui, count) + %STEP Display the next frame for all videos. + if nargin == 1 + count = 1; + end + gui.display_frame(gui.last_frame + count); + end + + function play(gui, duration, duration_type) + %PLAY Play a sequence of frames from all videos. + % + % By default will play until the end of the recordings, but a + % duration may be given to play just for that long. + % + % Arguments: + % gui: the gui instance + % duration: how many seconds/frames to play + % duration_type: optional; either 'seconds' (default) or 'frames' + + gui.buttons.play.String = 'Pause'; + + if nargin >= 2 + if nargin == 2 + duration_type = 'seconds'; + end + if strcmp(duration_type, 'frames') + end_frame = gui.last_frame + duration; + else + end_frame = find(... + gui.joint_t <= gui.current_time + duration, 1, 'last'); + end + else + end_frame = length(gui.joint_t); + end + if end_frame > length(gui.joint_t) + end_frame = length(gui.joint_t); + end + + % Figure out how many frames to skip for fast playback + fast = gui.buttons.play_mode.Value == 2; + if fast % Play ~10 frames / second + frame_duration = max(diff(gui.joint_t(1:30))); + skip_rate = floor(0.1 / frame_duration); + else + skip_rate = 1; % Play every frame + end + + while isgraphics(gui.fig) && gui.last_frame < end_frame && gui.playing + gui.step(skip_rate); + end + end + + function data = get_ts_item(gui, ts_name, item_name) + %GET_TS_ITEM Get a dataset from an acquired timeseries. + path = ['/acquisition/timeseries/' ts_name '/' item_name]; + data = gui.nwb.get(path); + end + + function value = get_ts_attr(gui, ts_name, item_name, attr_name) + %GET_TS_ATTR Get an attribute of a dataset within a timeseries. + path = ['/acquisition/timeseries/' ts_name '/' item_name]; + value = numpy2mat(gui.nwb.h5py.get(path).attrs{attr_name}); + end + +end % methods + +methods (Static) + function sized_path = resized_path(original_path, width) + %RESIZED_PATH Determine the a resized version of the given path. + % + % Synopsis: DisplayVideos.resized_path(original_path, width) + % + % Arguments: + % original_path: the original (video) path to consider + % width: the desired video width + % + % Returns a path like 'folder/base-width300.avi' when the original + % is called 'folder/base.mj2'. + + [base, name, ~] = fileparts(original_path); + sized_path = [base filesep name '-width' num2str(width) '.mj2']; + end +end + +end % class diff --git a/MATLAB/source/LabviewHeader.m b/MATLAB/source/LabviewHeader.m new file mode 100644 index 0000000..3489c61 --- /dev/null +++ b/MATLAB/source/LabviewHeader.m @@ -0,0 +1,210 @@ +classdef LabviewHeader < handle + %LABVIEWHEADER Provides access to information from a LabView .ini file. + % + % Construct instances of this class passing the path to an + % 'Experiment Header.ini' file, and then easily access any variable + % defined within any section of the file by name. + % + % Example: given a .ini file looking like: + % + % [LOGIN] + % User = "Angus" + % [GLOBAL PARAMETERS] + % number of poi = 150.000000 + % # averaged frames = 16.000000 + % laser power (%) = 60.000000 + % pockels = -1.000000 + % [MOVEMENT CORRECTION] + % MovCor Enabled? = TRUE + % Reference Size = "15 x 18 pixels" + % [STATISTICS] + % Z-stack duration (sec) = 56.674242 + % + % Loading this with + % + % header = LabviewHeader('file.ini', 'GLOBAL PARAMETERS'); + % + % will let you do things like: + % + % header.hasSection('GLOBAL PARAMETERS') -> true + % header.sections() -> {'GLOBAL PARAMETERS', 'LOGIN', ... + % 'MOVEMENT CORRECTION', 'STATISTICS'} + % header.hasItem('LOGIN', 'User') -> true + % header.item('LOGIN', 'User') -> 'Angus' + % header.item('# averaged frames') -> 16 + % header.defaultSection = 'MOVEMENT CORRECTION'; + % header.item('MovCor Enabled?') -> true + + methods + function obj = LabviewHeader(ini_path, default_section) + %LABVIEWHEADER Construct a new .ini file wrapper. + % + % Synopsis: obj = LabviewHeader(ini_path, default_section) + % + % Arguments: + % ini_path: optional path to .ini file to load + % default_section: optional default section in which to look up items + % + % If the path to the .ini file is not supplied, the load() + % method must be called to read a file before its contents can + % be accessed. + + obj.path = ''; + obj.info = containers.Map; + if nargin > 0 + obj.load(ini_path); + end + if nargin > 1 + obj.defaultSection = default_section; + else + obj.defaultSection = ''; + end + end + + function load(obj, ini_path) + %LOAD Load information from the given .ini file. + % + % Synopsis: obj.load(ini_path) + + obj.path = ini_path; + obj.info = containers.Map; + + current_section = ''; % Orphaned items go in an empty section + f = fopen(ini_path, 'r'); + c = onCleanup(@() fclose(f)); % Ensure file gets closed + while ~feof(f) + s = strtrim(fgetl(f)); + if isempty(s) || s(1) == ';' + continue; % Skip blank lines & comments + end; + if ( s(1)=='[' ) && (s(end)==']' ) + % Start of a section + current_section = s(2:end-1); + obj.info(current_section) = containers.Map; + else + % Item definition + [name, value_text] = strtok(s, '='); + name = strtrim(name); + assert(length(value_text) > 1, 'Malformed .ini line "%s"', s); + if isempty(current_section) && ~obj.info.isKey('') + % We only create an empty section if necessary! + obj.info('') = containers.Map; + end + value = parseValue(value_text(2:end)); % Remove '=' from start + section = obj.info(current_section); + section(name) = value; %#ok + end + end + end + + function present = hasSection(obj, section) + %HASSECTION Check whether a section exists in the header. + % + % Synopsis: present = obj.hasSection(section) + + present = obj.info.isKey(section); + end + + function sections = sections(obj) + %SECTIONS Get a cell array listing the header's sections. + % + % Synopsis: sections = obj.sections() + % + % The return array contains the names of the sections in + % alphabetical order. + sections = obj.info.keys(); + end + + function present = hasItem(obj, section, name) + %HASITEM Check whether the header contains a specific item. + % + % Synopsis: present = obj.hasItem(section, name) + % Synopsis: present = obj.hasItem(name) + % + % Checks for existence of an item with the given name inside + % the given section. If only one argument is given, the + % defaultSection property is used for the section name. + + if nargin == 2 + name = section; + section = obj.defaultSection; + end + present = obj.info.isKey(section) && obj.info(section).isKey(name); + end + + function value = item(obj, section, name) + %ITEM Get the value of a specific item within the header. + % + % Synopsis: value = obj.item(section, name) + % Synopsis: value = obj.item(name) + % + % Returns the value of the item with given name inside the + % given section, if present, and throws an error if the item is + % not present. If only one argument is given, the + % defaultSection property is used for the section name. + + if nargin == 2 + name = section; + section = obj.defaultSection; + end + if obj.hasItem(section, name) + sect = obj.info(section); + value = sect(name); + else + error('LabviewHeader:item:missing', 'No item "%s" in header section "%s".', name, section); + end + end + + function names = itemNames(obj, section) + %ITEMNAMES Lists the names of items within the given section. + % + % Synopsis: names = obj.itemNames(section) + % + % Names will be returned within a cell array in alphabetical + % order. An assertion is tripped if the section does not exist. + + if nargin == 1 + section = obj.defaultSection; + end + assert(obj.hasSection(section), 'No section named "%s".', section); + names = obj.info(section).keys(); + end + end + + properties (Access = public) + % Path to the .ini file wrapped by this object. + path; + % Default section to use for item lookup, if not specified in + % methods. + defaultSection; + end + + properties (Access = private) + % The actual header info, as a nested map. + info; + end +end + +function value = parseValue(s) + %PARSEVALUE Helper function to parse an item value. + % + % Will strip off leading/trailing whitespace and the = + % character. + % + % "any text" -> char array "any text" + % TRUE -> true + % FALSE -> false + % anything else is assumed to be a number + + s = strtrim(s); + if ~isempty(s) && (s(1) == '"' || s(1) == '''') + assert(s(1) == s(end), 'Mismatched string quotes in value: %s', s); + value = s(2:end-1); + elseif strcmp(s, 'TRUE') + value = true; + elseif strcmp(s, 'FALSE') + value = false; + else + value = str2double(s); + end +end diff --git a/MATLAB/source/NwbFile.m b/MATLAB/source/NwbFile.m new file mode 100644 index 0000000..eeb3b33 --- /dev/null +++ b/MATLAB/source/NwbFile.m @@ -0,0 +1,318 @@ +classdef NwbFile < handle + %NWBFILE Provides easy access to SilverLab NWB files. + % + % TODO: Documentation! + + properties (Access = public) + % Path to this NWB file. + path; + % File handle for use in Matlab's HDF5 interface. + file; + % h5py interface to the file. + h5py; + % Our Python API object. + file_obj; + end + + % Properties calculated on the fly, rather than stored. + % See the corresponding get.(property) methods for their definition. + properties (Dependent) + % How many trials are stored in the file. + num_trials; + % How many ROIs are stored in the file. + num_rois; + % How many times each point was imaged in a single trial. + num_cycles_per_trial; + % How long the microscope takes for a full cycle. + cycle_time; + % Names of timeseries containing video data. + video_names; + % Paths to the raw video files. + video_paths; + end + + methods + function nwb = NwbFile(path, mode, verbose) + %NWBFILE Open an NWB file for reading or writing. + % + % Synopsis: nwb = NwbFile(path, mode, verbose) + % + % Arguments: + % path: path to the NWB file + % mode: optional mode of file access. One of: + % 'r' - Readonly, file must exist + % 'r+' - Read/write, file must exist (default) + % 'w' - Create file, replacing if exists + % 'w-' - Create file, fail if exists + % 'a' - Read/write if exists, create otherwise + % verbose: whether to turn on logging output (default true) + % + % TODO: At present reading data is only possible in readonly + % mode; the only operation supported when writing is importing + % an entire Labview folder into a fresh file. + + if nargin < 1 + error('NwbFile:path:missing', 'No NWB file path supplied'); + end + if nargin < 2 + mode = 'r'; + end + if nargin < 3 + verbose = true; + end + + % Stop Matlab crashing if the HDF5 libraries don't quite match! + setenv('HDF5_DISABLE_VERSION_CHECK', '1'); + + nwb.path = path; + nwb.readonly = (mode == 'r'); + if nwb.readonly + nwb.h5py = py.h5py.File(path, mode); + nwb.file = H5F.open(path); + else + nwb.file_obj = py.silverlabnwb.NwbFile(path, mode, verbose); + end + end + + function n = get.num_trials(nwb) + %NUM_TRIALS The number of trials stored in this file. + n = double(py.len(nwb.h5py.get('/epochs'))); + end + + function n = get.num_rois(nwb) + %NUM_ROIS The number of ROIs stored in this file. + roi_spec = nwb.h5py.get('/processing/Acquired_ROIs/roi_spec'); + if roi_spec == py.None + error('NwbFile:rois:missing', 'No ROIs defined in file.'); + else + n = double(roi_spec.shape{1}); + end + end + + function n = get.num_cycles_per_trial(nwb) + %NUM_CYCLES_PER_TRIAL The number of microscope cycles/trial. + % + % That is, the number of times each point is imaged in each + % trial. Currently looks at the first imaging timeseries in + % the first trial, and assumes they're all the same. + trials = py.list(nwb.h5py.get('/epochs').keys()); + trial1 = nwb.h5py.get(['/epochs/' char(trials{1})]); + n = -1; + for tsname = cell(py.list(trial1.keys())) + ts = trial1.get(char(tsname{1})); + if py.hasattr(ts, 'get') && ... + ts.get('timeseries/pixel_time_offsets') ~= py.None + n = double(py.int(ts.get('count').value)); + break; + end + end + if n == -1 + error('NwbFile:imaging:missing', ... + 'No imaging timeseries defined in file.'); + end + end + + function t = get.cycle_time(nwb) + %CYCLE_TIME How long the microscope takes for a full cycle. + t = double(nwb.get('/general/optophysiology/cycle_time')); + end + + function names = get.video_names(nwb) + %VIDEO_NAMES Names of timeseries containing video data. + timeseries = cell(py.list(nwb.h5py.get(... + '/acquisition/timeseries/').keys())); + is_video = cellfun(@(name) name.endswith('Cam'), timeseries); + names = timeseries(is_video); + names = cellfun(@(n) char(py.str(n)), names, ... + 'UniformOutput', false); + end + + function paths = get.video_paths(nwb) + %VIDEO_PATHS Paths to raw video files. + % + % Returns a cell vector (length number of videos) where each + % entry is a cell vector (length number of files) with the + % absolute path to each video file for that video timeseries. + + [base_path, ~, ~] = fileparts(nwb.path); + names = nwb.video_names; + num_videos = length(names); + paths = cell(1, num_videos); + for i=1:num_videos + rel_paths = nwb.get(['/acquisition/timeseries/' ... + names{i} '/external_file']); + num_files = size(rel_paths, 1); + paths{i} = cell(1, num_files); + for j=1:num_files + paths{i}{j} = fullfile(base_path, rel_paths(j, :)); + end + end + end + + function array = get(nwb, obj_path, varargin) + %GET Retrieve a whole dataset from an NWB file. + % + % Synopsis: nwb.get(obj_path) + % + % Arguments: + % nwb: the NWB file object + % obj_path: path to the dataset within the file + % varargin: if given, obj_path is treated as a template and + % the full path constructed using sprintf + % + % Returns: + % the dataset as a Matlab array; either a numeric array + % for numeric data, or a cell array for text data + + if nargin > 2 + obj_path = sprintf(obj_path, varargin{:}); + end + + dataset_id = H5D.open(nwb.file, obj_path); + array = H5D.read(dataset_id); + % Matlab has the opposite dimension ordering by default + array = permute(array, ndims(array):-1:1); + H5D.close(dataset_id); + end + + function data = get_trial_data(nwb, trial, ts_name, data_name) + %GET_TRIAL_DATA Get the portion of a timeseries in a trial. + % + % Synopsis: + % nwb.get_trial_data(trial, ts_name) + % + % Arguments: + % trial: either a trial number or name of the group in the + % NWB file, e.g. trial_0001 + % ts_name: name of the timeseries group within the selected + % trial, e.g. ROI_001_Green + % data_name: name of the dataset to read; defaults to data + + assert(nargin >= 3 && nargin <= 4); + if nargin == 3 + data_name = 'data'; + end + % Find the dataset in the file + if isnumeric(trial) + trial = sprintf('trial_%04d', trial); + end + base = ['/epochs/' trial '/' ts_name '/']; + idx_start = nwb.get([base 'idx_start']); + count = nwb.get([base 'count']); + data_path = [base 'timeseries/' data_name]; + full_shape = tuple2mat(nwb.h5py.get(data_path).shape); + dataset_id = H5D.open(nwb.file, data_path); + + % Read just the portion we care about + ndim = length(full_shape); + read_dims = zeros(size(full_shape)); + read_dims(1) = count; + read_dims(2:end) = full_shape(2:end); + mem_space_id = H5S.create_simple(ndim, read_dims, read_dims); + file_space_id = H5D.get_space(dataset_id); + offset = zeros(size(full_shape)); + offset(1) = idx_start; + H5S.select_hyperslab(file_space_id, 'H5S_SELECT_SET', offset, [], [], read_dims); + data = H5D.read(dataset_id, 'H5ML_DEFAULT', mem_space_id, file_space_id, 'H5P_DEFAULT'); + H5D.close(dataset_id); + end + + function data = get_trials_data(nwb, ts_name, data_name, trials) + %GET_TRIALS_DATA Get the portions of a timeseries in trials. + % + % Synopsis: + % nwb.get_trials_data(trial, ts_name, trials) + % + % Arguments: + % ts_name: name of the timeseries group within the selected + % trials, e.g. ROI_001_Green + % data_name: name of the dataset to read; defaults to data + % trials: optional array or cell array of trial identifiers, + % which are either numbers or names. Defaults to all + % trials. + % + % Returns: cell array of timeseries data. + + assert(nargin >= 2 && nargin <= 4); + if nargin < 3 + data_name = 'data'; + end + if nargin < 4 + trials = 1:nwb.num_trials; + end + + data = cell(1, length(trials)); + i = 1; + for trial = trials + data{i} = nwb.get_trial_data(trial, ts_name, data_name); + i = i + 1; + end + end + + function [data, t_offsets, times] = get_roi_data(nwb, channel) + %GET_ROI_DATA Get functional data for all ROIs and trials. + % + % Synopsis: nwb.get_roi_data(channel) + % + % Arguments: + % nwb: the NWB file object + % channel: which channel to read ('Green' or 'Red') + % + % Returns: + % data: array of shape (num_trials, num_rois, num_times) + % t_offsets: (optional) time offsets at which each ROI was + % recorded + % times: (optional) array with timestamps for each point in + % data, of shape (num_trials, num_rois, num_times) + + n_trials = nwb.num_trials; + n_rois = nwb.num_rois; + n_times = nwb.num_cycles_per_trial; + + if nargout >= 2 + name_tpl = '/acquisition/timeseries/ROI_%03d_%s/pixel_time_offsets'; + first_t = nwb.get(name_tpl, 1, channel); + t_offsets = zeros(n_rois, numel(first_t)); + t_offsets(1, :) = first_t; + for j = 2:n_rois + t_offsets(j) = nwb.get(sprintf(name_tpl, j, channel)); + end + end + + data = zeros(n_trials, n_rois, n_times); + if nargout == 3 + times = zeros(n_trials, n_rois, n_times); + end + for i = 1:n_trials + for j = 1:n_rois + roi_name = sprintf('ROI_%03d_%s', j, channel); + data(i,j,:) = nwb.get_trial_data(i, roi_name); + if nargout == 3 + times(i,j,:) = nwb.get_trial_data(... + i, roi_name, 'timestamps') + t_offsets(j); + end + end + end + end + + function import_labview(nwb, folder) + %IMPORT_LABVIEW Import a Labview folder to NWB format. + % + % Synopsis: nwb.import_labview(folder) + % + % Arguments: + % nwb: the NWB file object + % folder: path to the folder to import + + assert(~nwb.readonly, 'Cannot import to a readonly file'); + %py.silverlabnwb.metadata_gui.run_editor(); + nwb.file_obj.import_labview_folder(folder); + end + end + + properties (Access = private) + % Whether we are able to write to the file. + readonly; + end + +end \ No newline at end of file diff --git a/MATLAB/source/numpy2mat.m b/MATLAB/source/numpy2mat.m new file mode 100644 index 0000000..92dabf2 --- /dev/null +++ b/MATLAB/source/numpy2mat.m @@ -0,0 +1,41 @@ +function result = numpy2mat( nparray ) +%NUMPY2MAT Convert a numpy.ndarray to a Matlab array +% +% Synopsis: result = numpy2mat(nparray) +% +% Arguments: +% nparray: a numpy n-dimensional array coming from Matlab's Python +% interface. Can be a numpy scalar too. +% +% Returns: +% a standard Matlab array containing the same data, in the natural +% layout for Matlab. The array data type will always be double. +% +% Based on https://uk.mathworks.com/matlabcentral/answers/157347-convert-python-numpy-array-to-double + +shape = tuple2mat(nparray.shape); +if numel(shape) <= 1 + % This is a simple operation + result = double(py.array.array('d', py.numpy.nditer(nparray))); +elseif length(shape) == 2 + % order='F' is used to get data in column-major order (as in Fortran + % 'F' and Matlab) + iter = py.numpy.nditer(nparray, pyargs('order', 'F')); + arr = double(py.array.array('d', iter)); + result = reshape(arr, shape); +else + % For multidimensional arrays more manipulation is required + % First recover in python order (C contiguous order) + iter = py.numpy.nditer(nparray, pyargs('order', 'C')); + result = double(py.array.array('d', iter)); + % Switch the order of the dimensions (as Python views this in the + % opposite order to Matlab) and reshape to the corresponding C-like + % array + result = reshape(result, fliplr(shape)); + % Now transpose rows and columns of the 2D sub-arrays to arrive at the + % correct Matlab structuring + result = permute(result, length(shape):-1:1); +end + +end + diff --git a/MATLAB/source/resize_videos.m b/MATLAB/source/resize_videos.m new file mode 100644 index 0000000..1198689 --- /dev/null +++ b/MATLAB/source/resize_videos.m @@ -0,0 +1,50 @@ +function resize_videos(nwb, width) +%RESIZE_VIDEOS Create resized versions of videos referenced in an NWB file +% +% Synopsis: resize_videos(nwb, width) +% +% Arguments: +% nwb: the NWB file to read to determine what videos to resize +% width: the desired width for each video; defaults to +% DisplayVideos.DEFAULT_VIDEO_WIDTH +% +% The scaling of each video will be maintained. Resized videos will be +% written to files in the same folders as the originals, with names like +% 'base-width300.mp4' when the original is called 'base.avi'. + +if nargin < 2 + width = DisplayVideos.DEFAULT_VIDEO_WIDTH; +end + +video_paths = nwb.video_paths; +num_videos = length(video_paths); + +for i=1:num_videos + num_files = length(video_paths{i}); + for j=1:num_files + video_path = video_paths{i}{j}; + output_path = DisplayVideos.resized_path(video_path, width); + disp(['Resizing ' video_path ' to ' output_path '...']); + + reader = vision.VideoFileReader(video_path, ... + 'VideoOutputDataType', 'uint8'); + writer = vision.VideoFileWriter(output_path, ... + 'FrameRate', reader.info.VideoFrameRate, ... + 'FileFormat', 'MJ2000'); +% 'FileFormat', 'MPEG4', 'Quality', 90); + + scale = reader.info.VideoSize(1) / width; + height = round(reader.info.VideoSize(2) / scale); + + while ~reader.isDone() + frame = reader.step(); + frame = imresize(frame, [width height]); + writer.step(frame); + end + + writer.release(); + reader.release(); + end +end + +end diff --git a/MATLAB/source/tuple2mat.m b/MATLAB/source/tuple2mat.m new file mode 100644 index 0000000..84d8bca --- /dev/null +++ b/MATLAB/source/tuple2mat.m @@ -0,0 +1,18 @@ +function result = tuple2mat(tuple, converter) +%TUPLE2MAT Convert a Python tuple to a Matlab array +% +% Synopsis: result = tuple2mat(tuple, converter) +% +% Arguments: +% tuple: the Python tuple to convert +% converter: optional function handle for converting items in the tuple; +% defaults to @double + +if nargin < 2 + converter = @double; +end + +result = cellfun(converter, cell(tuple)); + +end + diff --git a/MATLAB/tests/SharedFixtures.m b/MATLAB/tests/SharedFixtures.m new file mode 100644 index 0000000..0228af4 --- /dev/null +++ b/MATLAB/tests/SharedFixtures.m @@ -0,0 +1,17 @@ +function fixtures = SharedFixtures + %SHAREDFIXTURES Shared fixtures for Silver Lab Analysis Pipeline tests. + % + % Sets up paths so source files are found. + % Also defines a shared temporary folder. + + import matlab.unittest.fixtures.PathFixture; + + tests_folder = fileparts(mfilename('fullpath')); + source_folder = fullfile(tests_folder, '..', 'source'); + + fixtures = {... + PathFixture(source_folder, 'IncludingSubfolders', true), ... + matlab.unittest.fixtures.TemporaryFolderFixture}; + +end + diff --git a/MATLAB/tests/TestImport.m b/MATLAB/tests/TestImport.m new file mode 100644 index 0000000..6618613 --- /dev/null +++ b/MATLAB/tests/TestImport.m @@ -0,0 +1,105 @@ +classdef (SharedTestFixtures=SharedFixtures()) ... + TestImport < matlab.unittest.TestCase + %TESTIMPORT Test importing Labview to NWB gives correct data + + properties + end + + methods + function path = data_path(testCase) + path = getenv('SILVERLAB_DATA_DIR'); + testCase.assumeTrue(isdir(path)); + end + end + + methods (Test) + function testImportedHanaData(testCase) + %TESTIMPORTEDHANADATA Check data matches Hana's original code + + data_path = testCase.data_path(); + nwb_path = fullfile(data_path, '161215_15_34_21.nwb'); + testCase.assumeEqual(exist(nwb_path, 'file'), 2); + nwb = NwbFile(nwb_path); + ref = load(fullfile(data_path, '161215_15_34_21.mat')); + + % Basic experiment parameters + testCase.verifyEqual(nwb.num_trials, ref.Ntr); + testCase.verifyEqual(nwb.num_rois, ref.Nroi); + testCase.verifyEqual(nwb.num_cycles_per_trial, ref.Npt); + testCase.verifyEqual(nwb.num_cycles_per_trial, ref.Ncycl); + testCase.verifyEqual(nwb.cycle_time * 1e3, ref.Tcycl, ... + 'RelTol', 1e-6); % Our times are in seconds, original in ms + + % Coordinates for the imaging planes & ROIs + zdata = double(nwb.get('/general/optophysiology/zplane_pockels')); + zz_norm = zdata(:,2); + testCase.verifyEqual(zz_norm, ref.zz_norm, 'RelTol', 1e-6); + % TODO: Get these from the individual Zstack manifolds, rather + % than our custom dataset? + % To do this we'd need to: + % - Get (x,y) locations of each ROI within its Z plane from + % /processing/Acquired_ROIs/ImageSegmentation/ZstackNNN/ROI_NNN/pix_mask + % - Use these to find the right part of /general/optophysiology/ZstackNNNN/manifold + % (pick out entries (x, y, 1:3) for the (x,y,z) co-ords) + % (need to check if x & y are 0-based or 1-based) + roi_spec = double(nwb.get('/processing/Acquired_ROIs/roi_spec')); + Z0 = interp1(zdata(:,1), zz_norm, roi_spec(:,7)); + testCase.verifyEqual(Z0, ref.Z0, 'RelTol', 1e-6); + testCase.verifyEqual(roi_spec(:,5), round(ref.Xim)); + testCase.verifyEqual(roi_spec(:,6), round(ref.Yim)); + + % Functional data + [green_data, Troi, times] = nwb.get_roi_data('Green'); + testCase.verifyEqual(green_data, ref.allData_green, ... + 'RelTol', 1e-6); + testCase.verifyEqual(Troi .* 1e3, ref.Troi, ... + 'RelTol', 1e-6); % Our times are in seconds, original in ms + base_times = zeros(ref.Ntr, ref.Ncycl); + for i=1:ref.Ntr + base_times(i,:) = nwb.get_trial_data(i, 'ROI_001_Green', 'timestamps'); + end + ref_times = repmat(Troi.', 20, 1) + permute(base_times, [1 3 2]); + testCase.verifyEqual(times, ref_times); + + % Speed data + Ttrial = nwb.num_cycles_per_trial * nwb.cycle_time; % in seconds + T = linspace(0, Ttrial, Ttrial/0.001); + spDall = zeros(ref.Ntr, size(T, 2)); + for i = 1:ref.Ntr + spd_data = nwb.get_trial_data(i, 'speed_data'); + spd_times = nwb.get_trial_data(i, 'speed_data', 'timestamps'); + rel_times = spd_times - spd_times(1); + spDall(i,:) = interp1(rel_times, spd_data, T); + end + spDall = -spDall; + testCase.verifyEqual(spDall, ref.spDall, ... + 'RelTol', 1e-2, 'AbsTol', 1e-4); + end + + function testImportHana(testCase) + %TESTIMPORTHANA Check we can import some Hana data + + skip_imports = getenv('SILVERLAB_SKIP_IMPORTS'); + testCase.assumeFalse(strcmp(skip_imports, '1')); + + data_path = testCase.data_path(); + labview_path = fullfile(data_path, '161215_15_58_52 FunctAcq'); + testCase.assumeTrue(isdir(labview_path)); + + temp_folder = testCase.getSharedTestFixtures(... + 'matlab.unittest.fixtures.TemporaryFolderFixture').Folder; + nwb_path = fullfile(temp_folder, '161215_15_58_52.nwb'); + nwb = NwbFile(nwb_path, 'w'); + disp(['Importing ' labview_path '...']); + nwb.import_labview(labview_path); + nwb.file_obj.close(); + + disp('Checking signature matches...'); + sig_path = 'data/161215_15_58_52.sig'; + match = py.silverlabnwb.nwb_util.compare_to_signature(... + nwb_path, sig_path); + testCase.verifyTrue(match); + end + end + +end diff --git a/MATLAB/tests/TestLabviewHeader.m b/MATLAB/tests/TestLabviewHeader.m new file mode 100644 index 0000000..65acace --- /dev/null +++ b/MATLAB/tests/TestLabviewHeader.m @@ -0,0 +1,71 @@ +classdef (SharedTestFixtures=SharedFixtures()) ... + TestLabviewHeader < matlab.unittest.TestCase + %TESTLABVIEWHEADER Tests of the LabviewHeader class. + + properties + end + + methods (Test) + function testLoadingSampleHeader(testCase) + %TESTLOADINGSAMPLEHEADER Check a full-featured sample. + + header = LabviewHeader('data/sample_header.ini', 'LOGIN'); + testCase.checkHeaderContents(header); + end + + function testDefaultConstructor(testCase) + %TESTDEFAULTCONSTRUCTOR Check can construct and load separately. + + header = LabviewHeader(); + testCase.verifyEmpty(header.path); + testCase.verifyEmpty(header.defaultSection); + testCase.verifyEmpty(header.sections()); + testCase.verifyFalse(header.hasSection('blah')); + testCase.verifyFalse(header.hasItem('item')); + + header.defaultSection = 'LOGIN'; + header.load('data/sample_header.ini'); + testCase.checkHeaderContents(header); + end + end + + methods + function checkHeaderContents(testCase, header) + %CHECKHEADERCONTENTS Check the contents of the sample .ini. + + testCase.verifyMatches(header.path, '.*sample_header\.ini'); + testCase.verifyEqual(header.defaultSection, 'LOGIN'); + + testCase.verifyEqual(header.sections(), ... + {'', 'GLOBAL PARAMETERS', 'LOGIN', ... + 'MOVEMENT CORRECTION','STATISTICS'}); + testCase.verifyTrue(header.hasSection('LOGIN')); + + testCase.verifyTrue(header.hasItem('GLOBAL PARAMETERS', 'pockels')); + testCase.verifyTrue(header.hasItem('User')); + testCase.verifyEqual(header.item('User'), 'Angus'); + testCase.verifyEqual(header.item('', 'Orphan item'), 'Poor me!'); + + testCase.verifyEqual(header.itemNames(), {'User'}); + testCase.verifyEqual(header.itemNames('MOVEMENT CORRECTION'), ... + {'MovCor Enabled?', 'Reference Size'}); + + header.defaultSection = 'GLOBAL PARAMETERS'; + testCase.verifyEqual(header.item('# averaged frames'), 16.0); + testCase.verifyEqual(header.item('laser power (%)'), 60.0); + testCase.verifyEqual(header.item('pockels'), -1); + + testCase.verifyEqual(header.item('STATISTICS', 'Z-stack duration (sec)'), ... + 56.67, 'AbsTol', 0.01); + testCase.verifyEqual(header.item('STATISTICS', 'Z-stack duration (sec)'), ... + 56.674242, 'AbsTol', 0.000001); + testCase.verifyEqual(header.item('MOVEMENT CORRECTION', 'Reference Size'), ... + '15 x 18 pixels'); + + testCase.verifyError(@() header.item('blah'), 'LabviewHeader:item:missing'); + testCase.verifyError(@() header.item('LOGIN', 'oops'), 'LabviewHeader:item:missing'); + end + end + +end + diff --git a/MATLAB/tests/TestNumpy2mat.m b/MATLAB/tests/TestNumpy2mat.m new file mode 100644 index 0000000..331572c --- /dev/null +++ b/MATLAB/tests/TestNumpy2mat.m @@ -0,0 +1,80 @@ +classdef (SharedTestFixtures=SharedFixtures()) ... + TestNumpy2mat < matlab.unittest.TestCase + %TESTNUMPY2MAT Test the data conversion utilities + + properties + end + + methods (Test) + function testTuple(testCase) + %TESTTUPLE Check we can convert tuples + + actual = tuple2mat(py.tuple([1, 2])); + testCase.verifyEqual(actual, [1 2]); + testCase.verifyClass(actual, 'double'); + + actual = tuple2mat(py.tuple([1, 2]), @int64); + testCase.verifyEqual(actual, int64([1 2])); + testCase.verifyClass(actual, 'int64'); + end + + function testScalars(testCase) + %TESTSCALARS Check we can convert scalar values + + actual = numpy2mat(py.numpy.float64(1.0)); + testCase.verifyEqual(actual, 1.0); + testCase.verifyClass(actual, 'double'); + + actual = numpy2mat(py.numpy.int32(2)); + testCase.verifyEqual(actual, 2); + testCase.verifyClass(actual, 'double'); + end + + function test1d(testCase) + %TEST1D Check conversion of 1d arrays + + actual = numpy2mat(py.numpy.arange(5)); + testCase.verifyEqual(actual, 0:4); + testCase.verifyClass(actual, 'double'); + + actual = numpy2mat(py.numpy.arange(5, ... + pyargs('dtype', 'int8'))); + testCase.verifyEqual(actual, 0:4); + testCase.verifyClass(actual, 'double'); + end + + function test2d(testCase) + %TEST2D Check conversion of 2d arrays + + actual = numpy2mat(py.numpy.arange(6).reshape(... + py.int(2), py.int(3))); + testCase.verifyEqual(actual, [0 1 2; 3 4 5]); + testCase.verifyClass(actual, 'double'); + + actual = numpy2mat(py.numpy.arange(6, ... + pyargs('dtype', 'float32')).reshape(... + py.int(2), py.int(3))); + testCase.verifyEqual(actual, [0 1 2; 3 4 5]); + testCase.verifyClass(actual, 'double'); + end + + function test3d(testCase) + %TEST3D Check conversion of 3d arrays + + actual = numpy2mat(py.numpy.arange(24).reshape(... + py.int(2), py.int(3), py.int(4))); + expected = zeros(2,3,4); + expected(1, :, :) = [0 1 2 3; 4 5 6 7; 8 9 10 11]; + expected(2, :, :) = expected(1, :, :) + 12; + testCase.verifyEqual(actual, expected); + testCase.verifyClass(actual, 'double'); + + actual = numpy2mat(py.numpy.arange(24, ... + pyargs('dtype', 'uint16')).reshape(... + py.int(2), py.int(3), py.int(4))); + testCase.verifyEqual(actual, expected); + testCase.verifyClass(actual, 'double'); + end + end +end + diff --git a/MATLAB/tests/TestReadNwb.m b/MATLAB/tests/TestReadNwb.m new file mode 100644 index 0000000..43a4378 --- /dev/null +++ b/MATLAB/tests/TestReadNwb.m @@ -0,0 +1,82 @@ +classdef (SharedTestFixtures=SharedFixtures()) ... + TestReadNwb < matlab.unittest.TestCase + %TESTREADNWB Tests of reading NWB files + + properties + end + + methods (Test) + function testReadEpochData(testCase) + %TESTREADEPOCHDATA Check we can read the test_epochs output + + nwb = NwbFile('data/test_epochs.nwb'); + testCase.verifyEqual(nwb.get('/silverlab_api_version'), '0.1'); + testCase.verifyEqual(nwb.get('/session_description'), ... + 'Test epoch calculation'); + expected_speeds = single([... + 0.0, 0.0, 0.0, -2.79, -2.79, 0.0, -2.79, -2.79, -2.79, ... + 0.0, 0.0, -2.8, 0.0, ... + 0.0, -2.79, 0.0, ... + 0.0, 0.0, -2.8, 0.0, 0.0, 0.0, 0.0, ... + 0.0, 0.0, 0.0]); + testCase.verifyEqual(... + nwb.get('/acquisition/timeseries/speed_data/data'), ... + expected_speeds, 'AbsTol', 0.001); + testCase.verifyEqual(... + nwb.get('/epochs/trial_0002/start_time'), ... + 14.104865, 'AbsTol', 0.000001); + testCase.verifyEqual(... + nwb.get('/epochs/trial_0001/stop_time'), ... + 14.097292, 'AbsTol', 0.000001); + testCase.verifyEqual(... + nwb.get('/epochs/trial_0001/speed_data/count'), ... + int32(13)); + testCase.verifyEqual(... + nwb.get('/epochs/trial_0002/speed_data/idx_start'), ... + int32(16)); + + % Format string usage + testCase.verifyEqual(... + nwb.get('/epochs/trial_%04d/speed_data/idx_start', 2), ... + int32(16)); + testCase.verifyEqual(... + nwb.get('/epochs/trial_%04d/speed_data/%s', 2, 'idx_start'), ... + int32(16)); + + % Extracting one trial's data + testCase.verifyEqual(... + nwb.get_trial_data(1, 'speed_data'), ... + expected_speeds(1:13).', 'AbsTol', 0.001); + expected_times = [... + 0.000966, 0.003109, 0.005253, 0.365729, 0.367876, 0.370024, 0.372169, 0.374316, 0.376464, 0.378611, 14.093001, 14.095145, 14.097292, ... + 14.098427, 14.102718, 14.104865, ... + 14.105296, 14.107440, 14.109584, 14.111731, 14.113876, 28.200175, 28.202320, ... + 28.203617, 28.207918, 28.210062]; + testCase.verifyEqual(... + nwb.get_trial_data('trial_0002', 'speed_data', 'timestamps'), ... + expected_times(17:23).', 'AbsTol', 0.001); + + % Extracting multiple trials' data + testCase.verifyEqual(... + nwb.get_trials_data('speed_data'), ... + {expected_speeds(1:13).', expected_speeds(17:23).'}, ... + 'AbsTol', 0.001); + testCase.verifyEqual(... + nwb.get_trials_data('speed_data', 'timestamps', [2]), ... + {expected_times(17:23).'}, ... + 'AbsTol', 0.001); + + % Test our helper methods/properties too + testCase.verifyTrue(... + endsWith(nwb.path, 'data/test_epochs.nwb')); + testCase.verifyEqual(nwb.num_trials, 2); + + testCase.verifyError(@() nwb.num_rois, 'NwbFile:rois:missing'); + testCase.verifyError(@() nwb.num_cycles_per_trial, ... + 'NwbFile:imaging:missing'); + testCase.verifyError(@() nwb.cycle_time, ... + 'MATLAB:imagesci:hdf5lib:libraryError'); + end + end +end + diff --git a/MATLAB/tests/TestRunner.m b/MATLAB/tests/TestRunner.m new file mode 100644 index 0000000..bf0d987 --- /dev/null +++ b/MATLAB/tests/TestRunner.m @@ -0,0 +1,36 @@ +function result = TestRunner(do_coverage) +%TESTRUNNER Run the Silver Lab Analysis Pipeline tests. +% +% Pass true as an argument to generate a coverage report. + +if nargin < 1 + do_coverage = false; +end + +import matlab.unittest.TestRunner; +import matlab.unittest.TestSuite; +import matlab.unittest.plugins.CodeCoveragePlugin + +[tests_folder, ~, ~] = fileparts(mfilename('fullpath')); +source_folder = fullfile(tests_folder, '..', 'source'); + +suite_folder = TestSuite.fromFolder(tests_folder); +runner = TestRunner.withTextOutput; + +if do_coverage + % We have to setup our path fixture here, rather than per test, for the + % coverage plugin to work! + % https://uk.mathworks.com/matlabcentral/fileexchange/33972-coverage-report-generator + % may be a better option for the future... + fixtures = SharedFixtures(); + fixtures{1}.setup(); + c = onCleanup(@() fixtures{1}.teardown()); + runner.PrebuiltFixtures = fixtures{1}; + % At present this will only show coverage of the test code (if path changed), not source... + runner.addPlugin(CodeCoveragePlugin.forFolder(source_folder)); + result = runner.run(suite_folder); +else + result = runner.run(suite_folder); +end + +end \ No newline at end of file diff --git a/MATLAB/tests/data/161215_15_58_52.sig b/MATLAB/tests/data/161215_15_58_52.sig new file mode 100644 index 0000000..b03a300 --- /dev/null +++ b/MATLAB/tests/data/161215_15_58_52.sig @@ -0,0 +1,1768 @@ +<% Generating signature for 161215_15_58_52.nwb %> + +** No datasets hard links. +** No groups hard links. +** 91 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0022/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0022/description' + 2. 'to: "/general/optophysiology/Zstack0025/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0025/description' + 3. 'to: "/general/optophysiology/Zstack0028/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0028/description' + 4. 'to: "/general/optophysiology/Zstack0029/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/description' + 5. 'to: "/general/optophysiology/Zstack0032/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/description' + 6. 'to: "/general/optophysiology/Zstack0033/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/description' + 7. 'to: "/general/optophysiology/Zstack0034/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/description' + 8. 'to: "/general/optophysiology/Zstack0035/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/description' + 9. 'to: "/general/optophysiology/Zstack0039/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0039/description' + 10. 'to: "/general/optophysiology/Zstack0040/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0040/description' + 11. 'to: "/general/optophysiology/Zstack0046/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0046/description' + 12. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_079/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_079_Green/pixel_time_offsets + /acquisition/timeseries/ROI_079_Red/pixel_time_offsets' + 13. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_080/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_080_Green/pixel_time_offsets + /acquisition/timeseries/ROI_080_Red/pixel_time_offsets' + 14. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' + 15. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_002/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_002_Green/pixel_time_offsets + /acquisition/timeseries/ROI_002_Red/pixel_time_offsets' + 16. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_009/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_009_Green/pixel_time_offsets + /acquisition/timeseries/ROI_009_Red/pixel_time_offsets' + 17. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_010/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_010_Green/pixel_time_offsets + /acquisition/timeseries/ROI_010_Red/pixel_time_offsets' + 18. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_011/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_011_Green/pixel_time_offsets + /acquisition/timeseries/ROI_011_Red/pixel_time_offsets' + 19. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_012/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_012_Green/pixel_time_offsets + /acquisition/timeseries/ROI_012_Red/pixel_time_offsets' + 20. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_013/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_013_Green/pixel_time_offsets + /acquisition/timeseries/ROI_013_Red/pixel_time_offsets' + 21. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_003/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_003_Green/pixel_time_offsets + /acquisition/timeseries/ROI_003_Red/pixel_time_offsets' + 22. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_004/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_004_Green/pixel_time_offsets + /acquisition/timeseries/ROI_004_Red/pixel_time_offsets' + 23. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_005/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_005_Green/pixel_time_offsets + /acquisition/timeseries/ROI_005_Red/pixel_time_offsets' + 24. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_006/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_006_Green/pixel_time_offsets + /acquisition/timeseries/ROI_006_Red/pixel_time_offsets' + 25. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_007/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_007_Green/pixel_time_offsets + /acquisition/timeseries/ROI_007_Red/pixel_time_offsets' + 26. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_008/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_008_Green/pixel_time_offsets + /acquisition/timeseries/ROI_008_Red/pixel_time_offsets' + 27. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_050/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_050_Green/pixel_time_offsets + /acquisition/timeseries/ROI_050_Red/pixel_time_offsets' + 28. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_051/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_051_Green/pixel_time_offsets + /acquisition/timeseries/ROI_051_Red/pixel_time_offsets' + 29. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_014/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_014_Green/pixel_time_offsets + /acquisition/timeseries/ROI_014_Red/pixel_time_offsets' + 30. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_015/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_015_Green/pixel_time_offsets + /acquisition/timeseries/ROI_015_Red/pixel_time_offsets' + 31. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_016/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_016_Green/pixel_time_offsets + /acquisition/timeseries/ROI_016_Red/pixel_time_offsets' + 32. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_033/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_033_Green/pixel_time_offsets + /acquisition/timeseries/ROI_033_Red/pixel_time_offsets' + 33. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_034/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_034_Green/pixel_time_offsets + /acquisition/timeseries/ROI_034_Red/pixel_time_offsets' + 34. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_035/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_035_Green/pixel_time_offsets + /acquisition/timeseries/ROI_035_Red/pixel_time_offsets' + 35. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_036/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_036_Green/pixel_time_offsets + /acquisition/timeseries/ROI_036_Red/pixel_time_offsets' + 36. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_037/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_037_Green/pixel_time_offsets + /acquisition/timeseries/ROI_037_Red/pixel_time_offsets' + 37. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_038/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_038_Green/pixel_time_offsets + /acquisition/timeseries/ROI_038_Red/pixel_time_offsets' + 38. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_039/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_039_Green/pixel_time_offsets + /acquisition/timeseries/ROI_039_Red/pixel_time_offsets' + 39. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_040/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_040_Green/pixel_time_offsets + /acquisition/timeseries/ROI_040_Red/pixel_time_offsets' + 40. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_041/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_041_Green/pixel_time_offsets + /acquisition/timeseries/ROI_041_Red/pixel_time_offsets' + 41. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_042/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_042_Green/pixel_time_offsets + /acquisition/timeseries/ROI_042_Red/pixel_time_offsets' + 42. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_043/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_043_Green/pixel_time_offsets + /acquisition/timeseries/ROI_043_Red/pixel_time_offsets' + 43. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_044/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_044_Green/pixel_time_offsets + /acquisition/timeseries/ROI_044_Red/pixel_time_offsets' + 44. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_052/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_052_Green/pixel_time_offsets + /acquisition/timeseries/ROI_052_Red/pixel_time_offsets' + 45. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_053/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_053_Green/pixel_time_offsets + /acquisition/timeseries/ROI_053_Red/pixel_time_offsets' + 46. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_054/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_054_Green/pixel_time_offsets + /acquisition/timeseries/ROI_054_Red/pixel_time_offsets' + 47. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_055/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_055_Green/pixel_time_offsets + /acquisition/timeseries/ROI_055_Red/pixel_time_offsets' + 48. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_078/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_078_Green/pixel_time_offsets + /acquisition/timeseries/ROI_078_Red/pixel_time_offsets' + 49. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_017/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_017_Green/pixel_time_offsets + /acquisition/timeseries/ROI_017_Red/pixel_time_offsets' + 50. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_018/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_018_Green/pixel_time_offsets + /acquisition/timeseries/ROI_018_Red/pixel_time_offsets' + 51. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_019/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_019_Green/pixel_time_offsets + /acquisition/timeseries/ROI_019_Red/pixel_time_offsets' + 52. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_020/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_020_Green/pixel_time_offsets + /acquisition/timeseries/ROI_020_Red/pixel_time_offsets' + 53. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_021/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_021_Green/pixel_time_offsets + /acquisition/timeseries/ROI_021_Red/pixel_time_offsets' + 54. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_022/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_022_Green/pixel_time_offsets + /acquisition/timeseries/ROI_022_Red/pixel_time_offsets' + 55. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_023/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_023_Green/pixel_time_offsets + /acquisition/timeseries/ROI_023_Red/pixel_time_offsets' + 56. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_024/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_024_Green/pixel_time_offsets + /acquisition/timeseries/ROI_024_Red/pixel_time_offsets' + 57. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_025/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_025_Green/pixel_time_offsets + /acquisition/timeseries/ROI_025_Red/pixel_time_offsets' + 58. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_026/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_026_Green/pixel_time_offsets + /acquisition/timeseries/ROI_026_Red/pixel_time_offsets' + 59. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_045/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_045_Green/pixel_time_offsets + /acquisition/timeseries/ROI_045_Red/pixel_time_offsets' + 60. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_046/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_046_Green/pixel_time_offsets + /acquisition/timeseries/ROI_046_Red/pixel_time_offsets' + 61. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_047/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_047_Green/pixel_time_offsets + /acquisition/timeseries/ROI_047_Red/pixel_time_offsets' + 62. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_048/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_048_Green/pixel_time_offsets + /acquisition/timeseries/ROI_048_Red/pixel_time_offsets' + 63. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_056/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_056_Green/pixel_time_offsets + /acquisition/timeseries/ROI_056_Red/pixel_time_offsets' + 64. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_057/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_057_Green/pixel_time_offsets + /acquisition/timeseries/ROI_057_Red/pixel_time_offsets' + 65. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_058/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_058_Green/pixel_time_offsets + /acquisition/timeseries/ROI_058_Red/pixel_time_offsets' + 66. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_059/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_059_Green/pixel_time_offsets + /acquisition/timeseries/ROI_059_Red/pixel_time_offsets' + 67. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_060/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_060_Green/pixel_time_offsets + /acquisition/timeseries/ROI_060_Red/pixel_time_offsets' + 68. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_061/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_061_Green/pixel_time_offsets + /acquisition/timeseries/ROI_061_Red/pixel_time_offsets' + 69. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_062/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_062_Green/pixel_time_offsets + /acquisition/timeseries/ROI_062_Red/pixel_time_offsets' + 70. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_027/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_027_Green/pixel_time_offsets + /acquisition/timeseries/ROI_027_Red/pixel_time_offsets' + 71. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_028/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_028_Green/pixel_time_offsets + /acquisition/timeseries/ROI_028_Red/pixel_time_offsets' + 72. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_029/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_029_Green/pixel_time_offsets + /acquisition/timeseries/ROI_029_Red/pixel_time_offsets' + 73. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_030/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_030_Green/pixel_time_offsets + /acquisition/timeseries/ROI_030_Red/pixel_time_offsets' + 74. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_031/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_031_Green/pixel_time_offsets + /acquisition/timeseries/ROI_031_Red/pixel_time_offsets' + 75. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_032/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_032_Green/pixel_time_offsets + /acquisition/timeseries/ROI_032_Red/pixel_time_offsets' + 76. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_049/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_049_Green/pixel_time_offsets + /acquisition/timeseries/ROI_049_Red/pixel_time_offsets' + 77. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_063/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_063_Green/pixel_time_offsets + /acquisition/timeseries/ROI_063_Red/pixel_time_offsets' + 78. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_064/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_064_Green/pixel_time_offsets + /acquisition/timeseries/ROI_064_Red/pixel_time_offsets' + 79. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_065/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_065_Green/pixel_time_offsets + /acquisition/timeseries/ROI_065_Red/pixel_time_offsets' + 80. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_066/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_066_Green/pixel_time_offsets + /acquisition/timeseries/ROI_066_Red/pixel_time_offsets' + 81. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_067/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_067_Green/pixel_time_offsets + /acquisition/timeseries/ROI_067_Red/pixel_time_offsets' + 82. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_068/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_068_Green/pixel_time_offsets + /acquisition/timeseries/ROI_068_Red/pixel_time_offsets' + 83. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_069/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_069_Green/pixel_time_offsets + /acquisition/timeseries/ROI_069_Red/pixel_time_offsets' + 84. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_074/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_074_Green/pixel_time_offsets + /acquisition/timeseries/ROI_074_Red/pixel_time_offsets' + 85. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_075/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_075_Green/pixel_time_offsets + /acquisition/timeseries/ROI_075_Red/pixel_time_offsets' + 86. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_070/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_070_Green/pixel_time_offsets + /acquisition/timeseries/ROI_070_Red/pixel_time_offsets' + 87. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_071/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_071_Green/pixel_time_offsets + /acquisition/timeseries/ROI_071_Red/pixel_time_offsets' + 88. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_072/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_072_Green/pixel_time_offsets + /acquisition/timeseries/ROI_072_Red/pixel_time_offsets' + 89. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_073/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_073_Green/pixel_time_offsets + /acquisition/timeseries/ROI_073_Red/pixel_time_offsets' + 90. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_076/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_076_Green/pixel_time_offsets + /acquisition/timeseries/ROI_076_Red/pixel_time_offsets' + 91. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_077/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_077_Green/pixel_time_offsets + /acquisition/timeseries/ROI_077_Red/pixel_time_offsets' +** 172 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-20)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-20)' + 3. 'to: "/acquisition/timeseries/ROI_002_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_002_Green/timeseries (#=1-20)' + 4. 'to: "/acquisition/timeseries/ROI_002_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_002_Red/timeseries (#=1-20)' + 5. 'to: "/acquisition/timeseries/ROI_003_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_003_Green/timeseries (#=1-20)' + 6. 'to: "/acquisition/timeseries/ROI_003_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_003_Red/timeseries (#=1-20)' + 7. 'to: "/acquisition/timeseries/ROI_004_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_004_Green/timeseries (#=1-20)' + 8. 'to: "/acquisition/timeseries/ROI_004_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_004_Red/timeseries (#=1-20)' + 9. 'to: "/acquisition/timeseries/ROI_005_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_005_Green/timeseries (#=1-20)' + 10. 'to: "/acquisition/timeseries/ROI_005_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_005_Red/timeseries (#=1-20)' + 11. 'to: "/acquisition/timeseries/ROI_006_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_006_Green/timeseries (#=1-20)' + 12. 'to: "/acquisition/timeseries/ROI_006_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_006_Red/timeseries (#=1-20)' + 13. 'to: "/acquisition/timeseries/ROI_007_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_007_Green/timeseries (#=1-20)' + 14. 'to: "/acquisition/timeseries/ROI_007_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_007_Red/timeseries (#=1-20)' + 15. 'to: "/acquisition/timeseries/ROI_008_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_008_Green/timeseries (#=1-20)' + 16. 'to: "/acquisition/timeseries/ROI_008_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_008_Red/timeseries (#=1-20)' + 17. 'to: "/acquisition/timeseries/ROI_009_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_009_Green/timeseries (#=1-20)' + 18. 'to: "/acquisition/timeseries/ROI_009_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_009_Red/timeseries (#=1-20)' + 19. 'to: "/acquisition/timeseries/ROI_010_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_010_Green/timeseries (#=1-20)' + 20. 'to: "/acquisition/timeseries/ROI_010_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_010_Red/timeseries (#=1-20)' + 21. 'to: "/acquisition/timeseries/ROI_011_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_011_Green/timeseries (#=1-20)' + 22. 'to: "/acquisition/timeseries/ROI_011_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_011_Red/timeseries (#=1-20)' + 23. 'to: "/acquisition/timeseries/ROI_012_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_012_Green/timeseries (#=1-20)' + 24. 'to: "/acquisition/timeseries/ROI_012_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_012_Red/timeseries (#=1-20)' + 25. 'to: "/acquisition/timeseries/ROI_013_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_013_Green/timeseries (#=1-20)' + 26. 'to: "/acquisition/timeseries/ROI_013_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_013_Red/timeseries (#=1-20)' + 27. 'to: "/acquisition/timeseries/ROI_014_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_014_Green/timeseries (#=1-20)' + 28. 'to: "/acquisition/timeseries/ROI_014_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_014_Red/timeseries (#=1-20)' + 29. 'to: "/acquisition/timeseries/ROI_015_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_015_Green/timeseries (#=1-20)' + 30. 'to: "/acquisition/timeseries/ROI_015_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_015_Red/timeseries (#=1-20)' + 31. 'to: "/acquisition/timeseries/ROI_016_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_016_Green/timeseries (#=1-20)' + 32. 'to: "/acquisition/timeseries/ROI_016_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_016_Red/timeseries (#=1-20)' + 33. 'to: "/acquisition/timeseries/ROI_017_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_017_Green/timeseries (#=1-20)' + 34. 'to: "/acquisition/timeseries/ROI_017_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_017_Red/timeseries (#=1-20)' + 35. 'to: "/acquisition/timeseries/ROI_018_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_018_Green/timeseries (#=1-20)' + 36. 'to: "/acquisition/timeseries/ROI_018_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_018_Red/timeseries (#=1-20)' + 37. 'to: "/acquisition/timeseries/ROI_019_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_019_Green/timeseries (#=1-20)' + 38. 'to: "/acquisition/timeseries/ROI_019_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_019_Red/timeseries (#=1-20)' + 39. 'to: "/acquisition/timeseries/ROI_020_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_020_Green/timeseries (#=1-20)' + 40. 'to: "/acquisition/timeseries/ROI_020_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_020_Red/timeseries (#=1-20)' + 41. 'to: "/acquisition/timeseries/ROI_021_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_021_Green/timeseries (#=1-20)' + 42. 'to: "/acquisition/timeseries/ROI_021_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_021_Red/timeseries (#=1-20)' + 43. 'to: "/acquisition/timeseries/ROI_022_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_022_Green/timeseries (#=1-20)' + 44. 'to: "/acquisition/timeseries/ROI_022_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_022_Red/timeseries (#=1-20)' + 45. 'to: "/acquisition/timeseries/ROI_023_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_023_Green/timeseries (#=1-20)' + 46. 'to: "/acquisition/timeseries/ROI_023_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_023_Red/timeseries (#=1-20)' + 47. 'to: "/acquisition/timeseries/ROI_024_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_024_Green/timeseries (#=1-20)' + 48. 'to: "/acquisition/timeseries/ROI_024_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_024_Red/timeseries (#=1-20)' + 49. 'to: "/acquisition/timeseries/ROI_025_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_025_Green/timeseries (#=1-20)' + 50. 'to: "/acquisition/timeseries/ROI_025_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_025_Red/timeseries (#=1-20)' + 51. 'to: "/acquisition/timeseries/ROI_026_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_026_Green/timeseries (#=1-20)' + 52. 'to: "/acquisition/timeseries/ROI_026_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_026_Red/timeseries (#=1-20)' + 53. 'to: "/acquisition/timeseries/ROI_027_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_027_Green/timeseries (#=1-20)' + 54. 'to: "/acquisition/timeseries/ROI_027_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_027_Red/timeseries (#=1-20)' + 55. 'to: "/acquisition/timeseries/ROI_028_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_028_Green/timeseries (#=1-20)' + 56. 'to: "/acquisition/timeseries/ROI_028_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_028_Red/timeseries (#=1-20)' + 57. 'to: "/acquisition/timeseries/ROI_029_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_029_Green/timeseries (#=1-20)' + 58. 'to: "/acquisition/timeseries/ROI_029_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_029_Red/timeseries (#=1-20)' + 59. 'to: "/acquisition/timeseries/ROI_030_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_030_Green/timeseries (#=1-20)' + 60. 'to: "/acquisition/timeseries/ROI_030_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_030_Red/timeseries (#=1-20)' + 61. 'to: "/acquisition/timeseries/ROI_031_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_031_Green/timeseries (#=1-20)' + 62. 'to: "/acquisition/timeseries/ROI_031_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_031_Red/timeseries (#=1-20)' + 63. 'to: "/acquisition/timeseries/ROI_032_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_032_Green/timeseries (#=1-20)' + 64. 'to: "/acquisition/timeseries/ROI_032_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_032_Red/timeseries (#=1-20)' + 65. 'to: "/acquisition/timeseries/ROI_033_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_033_Green/timeseries (#=1-20)' + 66. 'to: "/acquisition/timeseries/ROI_033_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_033_Red/timeseries (#=1-20)' + 67. 'to: "/acquisition/timeseries/ROI_034_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_034_Green/timeseries (#=1-20)' + 68. 'to: "/acquisition/timeseries/ROI_034_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_034_Red/timeseries (#=1-20)' + 69. 'to: "/acquisition/timeseries/ROI_035_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_035_Green/timeseries (#=1-20)' + 70. 'to: "/acquisition/timeseries/ROI_035_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_035_Red/timeseries (#=1-20)' + 71. 'to: "/acquisition/timeseries/ROI_036_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_036_Green/timeseries (#=1-20)' + 72. 'to: "/acquisition/timeseries/ROI_036_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_036_Red/timeseries (#=1-20)' + 73. 'to: "/acquisition/timeseries/ROI_037_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_037_Green/timeseries (#=1-20)' + 74. 'to: "/acquisition/timeseries/ROI_037_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_037_Red/timeseries (#=1-20)' + 75. 'to: "/acquisition/timeseries/ROI_038_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_038_Green/timeseries (#=1-20)' + 76. 'to: "/acquisition/timeseries/ROI_038_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_038_Red/timeseries (#=1-20)' + 77. 'to: "/acquisition/timeseries/ROI_039_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_039_Green/timeseries (#=1-20)' + 78. 'to: "/acquisition/timeseries/ROI_039_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_039_Red/timeseries (#=1-20)' + 79. 'to: "/acquisition/timeseries/ROI_040_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_040_Green/timeseries (#=1-20)' + 80. 'to: "/acquisition/timeseries/ROI_040_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_040_Red/timeseries (#=1-20)' + 81. 'to: "/acquisition/timeseries/ROI_041_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_041_Green/timeseries (#=1-20)' + 82. 'to: "/acquisition/timeseries/ROI_041_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_041_Red/timeseries (#=1-20)' + 83. 'to: "/acquisition/timeseries/ROI_042_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_042_Green/timeseries (#=1-20)' + 84. 'to: "/acquisition/timeseries/ROI_042_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_042_Red/timeseries (#=1-20)' + 85. 'to: "/acquisition/timeseries/ROI_043_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_043_Green/timeseries (#=1-20)' + 86. 'to: "/acquisition/timeseries/ROI_043_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_043_Red/timeseries (#=1-20)' + 87. 'to: "/acquisition/timeseries/ROI_044_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_044_Green/timeseries (#=1-20)' + 88. 'to: "/acquisition/timeseries/ROI_044_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_044_Red/timeseries (#=1-20)' + 89. 'to: "/acquisition/timeseries/ROI_045_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_045_Green/timeseries (#=1-20)' + 90. 'to: "/acquisition/timeseries/ROI_045_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_045_Red/timeseries (#=1-20)' + 91. 'to: "/acquisition/timeseries/ROI_046_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_046_Green/timeseries (#=1-20)' + 92. 'to: "/acquisition/timeseries/ROI_046_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_046_Red/timeseries (#=1-20)' + 93. 'to: "/acquisition/timeseries/ROI_047_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_047_Green/timeseries (#=1-20)' + 94. 'to: "/acquisition/timeseries/ROI_047_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_047_Red/timeseries (#=1-20)' + 95. 'to: "/acquisition/timeseries/ROI_048_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_048_Green/timeseries (#=1-20)' + 96. 'to: "/acquisition/timeseries/ROI_048_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_048_Red/timeseries (#=1-20)' + 97. 'to: "/acquisition/timeseries/ROI_049_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_049_Green/timeseries (#=1-20)' + 98. 'to: "/acquisition/timeseries/ROI_049_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_049_Red/timeseries (#=1-20)' + 99. 'to: "/acquisition/timeseries/ROI_050_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_050_Green/timeseries (#=1-20)' +100. 'to: "/acquisition/timeseries/ROI_050_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_050_Red/timeseries (#=1-20)' +101. 'to: "/acquisition/timeseries/ROI_051_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_051_Green/timeseries (#=1-20)' +102. 'to: "/acquisition/timeseries/ROI_051_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_051_Red/timeseries (#=1-20)' +103. 'to: "/acquisition/timeseries/ROI_052_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_052_Green/timeseries (#=1-20)' +104. 'to: "/acquisition/timeseries/ROI_052_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_052_Red/timeseries (#=1-20)' +105. 'to: "/acquisition/timeseries/ROI_053_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_053_Green/timeseries (#=1-20)' +106. 'to: "/acquisition/timeseries/ROI_053_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_053_Red/timeseries (#=1-20)' +107. 'to: "/acquisition/timeseries/ROI_054_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_054_Green/timeseries (#=1-20)' +108. 'to: "/acquisition/timeseries/ROI_054_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_054_Red/timeseries (#=1-20)' +109. 'to: "/acquisition/timeseries/ROI_055_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_055_Green/timeseries (#=1-20)' +110. 'to: "/acquisition/timeseries/ROI_055_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_055_Red/timeseries (#=1-20)' +111. 'to: "/acquisition/timeseries/ROI_056_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_056_Green/timeseries (#=1-20)' +112. 'to: "/acquisition/timeseries/ROI_056_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_056_Red/timeseries (#=1-20)' +113. 'to: "/acquisition/timeseries/ROI_057_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_057_Green/timeseries (#=1-20)' +114. 'to: "/acquisition/timeseries/ROI_057_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_057_Red/timeseries (#=1-20)' +115. 'to: "/acquisition/timeseries/ROI_058_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_058_Green/timeseries (#=1-20)' +116. 'to: "/acquisition/timeseries/ROI_058_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_058_Red/timeseries (#=1-20)' +117. 'to: "/acquisition/timeseries/ROI_059_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_059_Green/timeseries (#=1-20)' +118. 'to: "/acquisition/timeseries/ROI_059_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_059_Red/timeseries (#=1-20)' +119. 'to: "/acquisition/timeseries/ROI_060_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_060_Green/timeseries (#=1-20)' +120. 'to: "/acquisition/timeseries/ROI_060_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_060_Red/timeseries (#=1-20)' +121. 'to: "/acquisition/timeseries/ROI_061_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_061_Green/timeseries (#=1-20)' +122. 'to: "/acquisition/timeseries/ROI_061_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_061_Red/timeseries (#=1-20)' +123. 'to: "/acquisition/timeseries/ROI_062_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_062_Green/timeseries (#=1-20)' +124. 'to: "/acquisition/timeseries/ROI_062_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_062_Red/timeseries (#=1-20)' +125. 'to: "/acquisition/timeseries/ROI_063_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_063_Green/timeseries (#=1-20)' +126. 'to: "/acquisition/timeseries/ROI_063_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_063_Red/timeseries (#=1-20)' +127. 'to: "/acquisition/timeseries/ROI_064_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_064_Green/timeseries (#=1-20)' +128. 'to: "/acquisition/timeseries/ROI_064_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_064_Red/timeseries (#=1-20)' +129. 'to: "/acquisition/timeseries/ROI_065_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_065_Green/timeseries (#=1-20)' +130. 'to: "/acquisition/timeseries/ROI_065_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_065_Red/timeseries (#=1-20)' +131. 'to: "/acquisition/timeseries/ROI_066_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_066_Green/timeseries (#=1-20)' +132. 'to: "/acquisition/timeseries/ROI_066_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_066_Red/timeseries (#=1-20)' +133. 'to: "/acquisition/timeseries/ROI_067_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_067_Green/timeseries (#=1-20)' +134. 'to: "/acquisition/timeseries/ROI_067_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_067_Red/timeseries (#=1-20)' +135. 'to: "/acquisition/timeseries/ROI_068_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_068_Green/timeseries (#=1-20)' +136. 'to: "/acquisition/timeseries/ROI_068_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_068_Red/timeseries (#=1-20)' +137. 'to: "/acquisition/timeseries/ROI_069_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_069_Green/timeseries (#=1-20)' +138. 'to: "/acquisition/timeseries/ROI_069_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_069_Red/timeseries (#=1-20)' +139. 'to: "/acquisition/timeseries/ROI_070_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_070_Green/timeseries (#=1-20)' +140. 'to: "/acquisition/timeseries/ROI_070_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_070_Red/timeseries (#=1-20)' +141. 'to: "/acquisition/timeseries/ROI_071_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_071_Green/timeseries (#=1-20)' +142. 'to: "/acquisition/timeseries/ROI_071_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_071_Red/timeseries (#=1-20)' +143. 'to: "/acquisition/timeseries/ROI_072_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_072_Green/timeseries (#=1-20)' +144. 'to: "/acquisition/timeseries/ROI_072_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_072_Red/timeseries (#=1-20)' +145. 'to: "/acquisition/timeseries/ROI_073_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_073_Green/timeseries (#=1-20)' +146. 'to: "/acquisition/timeseries/ROI_073_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_073_Red/timeseries (#=1-20)' +147. 'to: "/acquisition/timeseries/ROI_074_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_074_Green/timeseries (#=1-20)' +148. 'to: "/acquisition/timeseries/ROI_074_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_074_Red/timeseries (#=1-20)' +149. 'to: "/acquisition/timeseries/ROI_075_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_075_Green/timeseries (#=1-20)' +150. 'to: "/acquisition/timeseries/ROI_075_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_075_Red/timeseries (#=1-20)' +151. 'to: "/acquisition/timeseries/ROI_076_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_076_Green/timeseries (#=1-20)' +152. 'to: "/acquisition/timeseries/ROI_076_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_076_Red/timeseries (#=1-20)' +153. 'to: "/acquisition/timeseries/ROI_077_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_077_Green/timeseries (#=1-20)' +154. 'to: "/acquisition/timeseries/ROI_077_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_077_Red/timeseries (#=1-20)' +155. 'to: "/acquisition/timeseries/ROI_078_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_078_Green/timeseries (#=1-20)' +156. 'to: "/acquisition/timeseries/ROI_078_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_078_Red/timeseries (#=1-20)' +157. 'to: "/acquisition/timeseries/ROI_079_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_079_Green/timeseries (#=1-20)' +158. 'to: "/acquisition/timeseries/ROI_079_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_079_Red/timeseries (#=1-20)' +159. 'to: "/acquisition/timeseries/ROI_080_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_080_Green/timeseries (#=1-20)' +160. 'to: "/acquisition/timeseries/ROI_080_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_080_Red/timeseries (#=1-20)' +161. 'to: "/acquisition/timeseries/Zstack_Red_0022" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0022/reference_images/Zstack_image' +162. 'to: "/acquisition/timeseries/Zstack_Red_0025" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0025/reference_images/Zstack_image' +163. 'to: "/acquisition/timeseries/Zstack_Red_0028" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0028/reference_images/Zstack_image' +164. 'to: "/acquisition/timeseries/Zstack_Red_0029" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/reference_images/Zstack_image' +165. 'to: "/acquisition/timeseries/Zstack_Red_0032" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/reference_images/Zstack_image' +166. 'to: "/acquisition/timeseries/Zstack_Red_0033" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/reference_images/Zstack_image' +167. 'to: "/acquisition/timeseries/Zstack_Red_0034" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/reference_images/Zstack_image' +168. 'to: "/acquisition/timeseries/Zstack_Red_0035" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/reference_images/Zstack_image' +169. 'to: "/acquisition/timeseries/Zstack_Red_0039" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0039/reference_images/Zstack_image' +170. 'to: "/acquisition/timeseries/Zstack_Red_0040" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0040/reference_images/Zstack_image' +171. 'to: "/acquisition/timeseries/Zstack_Red_0046" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0046/reference_images/Zstack_image' +172. 'to: "/acquisition/timeseries/speed_data" 20 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-20)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 3609 attributes (sorted alphabetically) (289 combined): + 1. '/acquisition/timeseries/ROI_#_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-80)' + 2. '/acquisition/timeseries/ROI_#_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-80)' + 3. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 4. '/acquisition/timeseries/ROI_#_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-80)' + 5. '/acquisition/timeseries/ROI_#_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-80)' + 6. '/acquisition/timeseries/ROI_#_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-80)' + 7. '/acquisition/timeseries/ROI_#_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 8. '/acquisition/timeseries/ROI_#_Green/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-80)' + 9. '/acquisition/timeseries/ROI_#_Green/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-80)' + 10. '/acquisition/timeseries/ROI_#_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-80)' + 11. '/acquisition/timeseries/ROI_#_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-80)' + 13. '/acquisition/timeseries/ROI_#_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-80)' + 14. '/acquisition/timeseries/ROI_#_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-80)' + 15. '/acquisition/timeseries/ROI_#_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-80)' + 16. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 17. '/acquisition/timeseries/ROI_#_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-80)' + 18. '/acquisition/timeseries/ROI_#_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-80)' + 19. '/acquisition/timeseries/ROI_#_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-80)' + 20. '/acquisition/timeseries/ROI_#_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 21. '/acquisition/timeseries/ROI_#_Red/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-80)' + 22. '/acquisition/timeseries/ROI_#_Red/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-80)' + 23. '/acquisition/timeseries/ROI_#_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-80)' + 24. '/acquisition/timeseries/ROI_#_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 25. '/acquisition/timeseries/ROI_#_Red/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-80)' + 26. '/acquisition/timeseries/ROI_#_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-80)' + 27. '/acquisition/timeseries/ROI_002_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPc'' + 28. '/acquisition/timeseries/ROI_002_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPC'' + 29. '/acquisition/timeseries/ROI_003_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnJ'' + 30. '/acquisition/timeseries/ROI_003_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroj'' + 31. '/acquisition/timeseries/ROI_004_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMq'' + 32. '/acquisition/timeseries/ROI_004_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMQ'' + 33. '/acquisition/timeseries/ROI_005_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkX'' + 34. '/acquisition/timeseries/ROI_005_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklx'' + 35. '/acquisition/timeseries/ROI_006_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJE'' + 36. '/acquisition/timeseries/ROI_006_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKe'' + 37. '/acquisition/timeseries/ROI_007_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcil'' + 38. '/acquisition/timeseries/ROI_007_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiL'' + 39. '/acquisition/timeseries/ROI_008_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGS'' + 40. '/acquisition/timeseries/ROI_008_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHs'' + 41. '/acquisition/timeseries/ROI_009_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfz'' + 42. '/acquisition/timeseries/ROI_009_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfZ'' + 43. '/acquisition/timeseries/ROI_010_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzVCL'' + 44. '/acquisition/timeseries/ROI_010_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytWDl'' + 45. '/acquisition/timeseries/ROI_011_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCASbs'' + 46. '/acquisition/timeseries/ROI_011_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuTbS'' + 47. '/acquisition/timeseries/ROI_012_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBOzZ'' + 48. '/acquisition/timeseries/ROI_012_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvPAz'' + 49. '/acquisition/timeseries/ROI_013_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYG'' + 50. '/acquisition/timeseries/ROI_013_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZg'' + 51. '/acquisition/timeseries/ROI_014_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxn'' + 52. '/acquisition/timeseries/ROI_014_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxN'' + 53. '/acquisition/timeseries/ROI_015_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVU'' + 54. '/acquisition/timeseries/ROI_015_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWu'' + 55. '/acquisition/timeseries/ROI_016_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuB'' + 56. '/acquisition/timeseries/ROI_016_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBvb'' + 57. '/acquisition/timeseries/ROI_017_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTi'' + 58. '/acquisition/timeseries/ROI_017_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTI'' + 59. '/acquisition/timeseries/ROI_018_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrP'' + 60. '/acquisition/timeseries/ROI_018_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusp'' + 61. '/acquisition/timeseries/ROI_019_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQw'' + 62. '/acquisition/timeseries/ROI_019_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQW'' + 63. '/acquisition/timeseries/ROI_020_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnI'' + 64. '/acquisition/timeseries/ROI_020_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroi'' + 65. '/acquisition/timeseries/ROI_021_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMp'' + 66. '/acquisition/timeseries/ROI_021_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMP'' + 67. '/acquisition/timeseries/ROI_022_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkW'' + 68. '/acquisition/timeseries/ROI_022_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklw'' + 69. '/acquisition/timeseries/ROI_023_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJD'' + 70. '/acquisition/timeseries/ROI_023_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKd'' + 71. '/acquisition/timeseries/ROI_024_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcik'' + 72. '/acquisition/timeseries/ROI_024_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiK'' + 73. '/acquisition/timeseries/ROI_025_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGR'' + 74. '/acquisition/timeseries/ROI_025_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHr'' + 75. '/acquisition/timeseries/ROI_026_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfy'' + 76. '/acquisition/timeseries/ROI_026_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfY'' + 77. '/acquisition/timeseries/ROI_027_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREf'' + 78. '/acquisition/timeseries/ROI_027_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEF'' + 79. '/acquisition/timeseries/ROI_028_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcM'' + 80. '/acquisition/timeseries/ROI_028_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdm'' + 81. '/acquisition/timeseries/ROI_029_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBt'' + 82. '/acquisition/timeseries/ROI_029_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBT'' + 83. '/acquisition/timeseries/ROI_030_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYF'' + 84. '/acquisition/timeseries/ROI_030_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZf'' + 85. '/acquisition/timeseries/ROI_031_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxm'' + 86. '/acquisition/timeseries/ROI_031_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxM'' + 87. '/acquisition/timeseries/ROI_032_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVT'' + 88. '/acquisition/timeseries/ROI_032_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWt'' + 89. '/acquisition/timeseries/ROI_033_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuA'' + 90. '/acquisition/timeseries/ROI_033_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBva'' + 91. '/acquisition/timeseries/ROI_034_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTh'' + 92. '/acquisition/timeseries/ROI_034_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTH'' + 93. '/acquisition/timeseries/ROI_035_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrO'' + 94. '/acquisition/timeseries/ROI_035_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBuso'' + 95. '/acquisition/timeseries/ROI_036_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQv'' + 96. '/acquisition/timeseries/ROI_036_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQV'' + 97. '/acquisition/timeseries/ROI_037_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpc'' + 98. '/acquisition/timeseries/ROI_037_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpC'' + 99. '/acquisition/timeseries/ROI_038_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNJ'' +100. '/acquisition/timeseries/ROI_038_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOj'' +101. '/acquisition/timeseries/ROI_039_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmq'' +102. '/acquisition/timeseries/ROI_039_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmQ'' +103. '/acquisition/timeseries/ROI_040_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJC'' +104. '/acquisition/timeseries/ROI_040_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKc'' +105. '/acquisition/timeseries/ROI_041_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcij'' +106. '/acquisition/timeseries/ROI_041_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiJ'' +107. '/acquisition/timeseries/ROI_042_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGQ'' +108. '/acquisition/timeseries/ROI_042_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHq'' +109. '/acquisition/timeseries/ROI_043_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfx'' +110. '/acquisition/timeseries/ROI_043_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfX'' +111. '/acquisition/timeseries/ROI_044_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREe'' +112. '/acquisition/timeseries/ROI_044_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEE'' +113. '/acquisition/timeseries/ROI_045_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcL'' +114. '/acquisition/timeseries/ROI_045_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdl'' +115. '/acquisition/timeseries/ROI_046_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBs'' +116. '/acquisition/timeseries/ROI_046_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBS'' +117. '/acquisition/timeseries/ROI_047_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZZ'' +118. '/acquisition/timeseries/ROI_047_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIaz'' +119. '/acquisition/timeseries/ROI_048_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyG'' +120. '/acquisition/timeseries/ROI_048_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzg'' +121. '/acquisition/timeseries/ROI_049_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXn'' +122. '/acquisition/timeseries/ROI_049_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXN'' +123. '/acquisition/timeseries/ROI_050_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuz'' +124. '/acquisition/timeseries/ROI_050_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBuZ'' +125. '/acquisition/timeseries/ROI_051_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTg'' +126. '/acquisition/timeseries/ROI_051_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTG'' +127. '/acquisition/timeseries/ROI_052_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrN'' +128. '/acquisition/timeseries/ROI_052_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusn'' +129. '/acquisition/timeseries/ROI_053_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQu'' +130. '/acquisition/timeseries/ROI_053_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQU'' +131. '/acquisition/timeseries/ROI_054_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpb'' +132. '/acquisition/timeseries/ROI_054_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpB'' +133. '/acquisition/timeseries/ROI_055_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNI'' +134. '/acquisition/timeseries/ROI_055_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOi'' +135. '/acquisition/timeseries/ROI_056_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmp'' +136. '/acquisition/timeseries/ROI_056_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmP'' +137. '/acquisition/timeseries/ROI_057_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKW'' +138. '/acquisition/timeseries/ROI_057_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLw'' +139. '/acquisition/timeseries/ROI_058_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjD'' +140. '/acquisition/timeseries/ROI_058_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkd'' +141. '/acquisition/timeseries/ROI_059_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIk'' +142. '/acquisition/timeseries/ROI_059_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIK'' +143. '/acquisition/timeseries/ROI_060_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfw'' +144. '/acquisition/timeseries/ROI_060_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfW'' +145. '/acquisition/timeseries/ROI_061_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREd'' +146. '/acquisition/timeseries/ROI_061_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSED'' +147. '/acquisition/timeseries/ROI_062_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcK'' +148. '/acquisition/timeseries/ROI_062_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdk'' +149. '/acquisition/timeseries/ROI_063_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBr'' +150. '/acquisition/timeseries/ROI_063_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBR'' +151. '/acquisition/timeseries/ROI_064_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZY'' +152. '/acquisition/timeseries/ROI_064_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIay'' +153. '/acquisition/timeseries/ROI_065_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyF'' +154. '/acquisition/timeseries/ROI_065_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzf'' +155. '/acquisition/timeseries/ROI_066_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXm'' +156. '/acquisition/timeseries/ROI_066_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXM'' +157. '/acquisition/timeseries/ROI_067_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNwvT'' +158. '/acquisition/timeseries/ROI_067_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHxwt'' +159. '/acquisition/timeseries/ROI_068_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCOsUA'' +160. '/acquisition/timeseries/ROI_068_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyItVa'' +161. '/acquisition/timeseries/ROI_069_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPpth'' +162. '/acquisition/timeseries/ROI_069_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJqtH'' +163. '/acquisition/timeseries/ROI_070_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQt'' +164. '/acquisition/timeseries/ROI_070_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQT'' +165. '/acquisition/timeseries/ROI_071_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpa'' +166. '/acquisition/timeseries/ROI_071_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpA'' +167. '/acquisition/timeseries/ROI_072_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNH'' +168. '/acquisition/timeseries/ROI_072_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOh'' +169. '/acquisition/timeseries/ROI_073_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmo'' +170. '/acquisition/timeseries/ROI_073_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmO'' +171. '/acquisition/timeseries/ROI_074_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKV'' +172. '/acquisition/timeseries/ROI_074_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLv'' +173. '/acquisition/timeseries/ROI_075_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjC'' +174. '/acquisition/timeseries/ROI_075_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkc'' +175. '/acquisition/timeseries/ROI_076_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIj'' +176. '/acquisition/timeseries/ROI_076_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIJ'' +177. '/acquisition/timeseries/ROI_077_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCORgQ'' +178. '/acquisition/timeseries/ROI_077_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyIShq'' +179. '/acquisition/timeseries/ROI_078_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPNFx'' +180. '/acquisition/timeseries/ROI_078_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJOFX'' +181. '/acquisition/timeseries/ROI_079_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCQKee'' +182. '/acquisition/timeseries/ROI_079_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyKLeE'' +183. '/acquisition/timeseries/ROI_080_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBq'' +184. '/acquisition/timeseries/ROI_080_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBQ'' +185. '/acquisition/timeseries/Zstack_Green_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-49)' +186. '/acquisition/timeseries/Zstack_Green_# comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"' (#=1-49)' +187. '/acquisition/timeseries/Zstack_Green_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-49)' +188. '/acquisition/timeseries/Zstack_Green_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-49)' +189. '/acquisition/timeseries/Zstack_Green_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-49)' +190. '/acquisition/timeseries/Zstack_Green_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-49)' +191. '/acquisition/timeseries/Zstack_Green_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-49)' +192. '/acquisition/timeseries/Zstack_Green_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-49)' +193. '/acquisition/timeseries/Zstack_Green_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-49)' +194. '/acquisition/timeseries/Zstack_Green_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-49)' +195. '/acquisition/timeseries/Zstack_Green_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-49)' +196. '/acquisition/timeseries/Zstack_Green_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-49)' +197. '/acquisition/timeseries/Zstack_Red_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-49)' +198. '/acquisition/timeseries/Zstack_Red_# comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"' (#=1-49)' +199. '/acquisition/timeseries/Zstack_Red_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-49)' +200. '/acquisition/timeseries/Zstack_Red_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-49)' +201. '/acquisition/timeseries/Zstack_Red_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-49)' +202. '/acquisition/timeseries/Zstack_Red_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-49)' +203. '/acquisition/timeseries/Zstack_Red_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-49)' +204. '/acquisition/timeseries/Zstack_Red_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-49)' +205. '/acquisition/timeseries/Zstack_Red_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-49)' +206. '/acquisition/timeseries/Zstack_Red_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-49)' +207. '/acquisition/timeseries/Zstack_Red_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-49)' +208. '/acquisition/timeseries/Zstack_Red_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-49)' +209. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +210. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +211. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' +212. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' +213. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +214. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +215. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' +216. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' +217. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' +218. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' +219. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +220. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +221. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +222. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' +223. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' +224. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +225. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +226. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' +227. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' +228. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' +229. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' +230. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +231. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' +232. '/epochs/trial_# links: dtype=|S58, shape=(161,) size (9338) val='["'ROI_001_Green' is '/acquisition/timese...fUYCuY' (#=1-20)' +233. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-20)' +234. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' +235. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-49)' +236. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-49)' +237. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +238. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +239. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +240. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' +241. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +242. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +243. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' +244. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +245. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' +246. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +247. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' +248. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' +249. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' +250. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' +251. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' +252. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' +253. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' +254. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=79-80)' +255. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=79-80)' +256. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-2)' +257. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=1-2)' +258. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=9-13)' +259. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=9-13)' +260. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=3-8)' +261. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=3-8)' +262. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=50-51)' +263. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=50-51)' +264. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=14-16,33-44,52-55,78)' +265. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=14-16,33-44,52-55,78)' +266. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=17-26,45-48,56-62)' +267. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=17-26,45-48,56-62)' +268. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=27-32,49,63-69)' +269. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=27-32,49,63-69)' +270. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=74-75)' +271. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=74-75)' +272. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=70-73)' +273. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=70-73)' +274. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=76-77)' +275. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=76-77)' +276. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' +277. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +278. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +279. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +280. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +281. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +282. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +283. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +284. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +285. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +286. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +287. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +288. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +289. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 10616 datasets (sorted alphabetically) (856 combined): + 1. '/acquisition/timeseries/ROI_#_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-80)' + 2. '/acquisition/timeseries/ROI_#_Green/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-80)' + 3. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(175440, 1, 1) size (189644), compress=gzip val='[[[113]],[[113]],[[118]],[[111]],[[125]],...bYADGy'' + 4. '/acquisition/timeseries/ROI_#_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-80)' + 5. '/acquisition/timeseries/ROI_#_Green/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-80)' + 6. '/acquisition/timeseries/ROI_#_Green/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-80)' + 7. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0025"' (#=1-2)' + 8. '/acquisition/timeseries/ROI_#_Green/num_samples: dtype=int32, shape=() size (4) val='175440' (#=1-80)' + 9. '/acquisition/timeseries/ROI_#_Green/pmt_gain: dtype=float32, shape=() size (4) val='715' (#=1-80)' + 10. '/acquisition/timeseries/ROI_#_Green/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-80)' + 11. '/acquisition/timeseries/ROI_#_Green/scan_line_rate: dtype=float32, shape=() size (4) val='348.2' (#=1-80)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps: dtype=float64, shape=(175440,) size (1049139), compress=gzip val='[1.084e-19,0.002872,0.005744,0.008616,0.0...hsbIrX' (#=1-80)' + 13. '/acquisition/timeseries/ROI_#_Red/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-80)' + 14. '/acquisition/timeseries/ROI_#_Red/channel: dtype=|S3, shape=() size (3) val='"Red"' (#=1-80)' + 15. '/acquisition/timeseries/ROI_001_Red/data: dtype=float32, shape=(175440, 1, 1) size (130300), compress=gzip val='[[[114]],[[113]],[[115]],[[114]],[[112]],...dnWfDq'' + 16. '/acquisition/timeseries/ROI_#_Red/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-80)' + 17. '/acquisition/timeseries/ROI_#_Red/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-80)' + 18. '/acquisition/timeseries/ROI_#_Red/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-80)' + 19. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0025"' (#=1-2)' + 20. '/acquisition/timeseries/ROI_#_Red/num_samples: dtype=int32, shape=() size (4) val='175440' (#=1-80)' + 21. '/acquisition/timeseries/ROI_#_Red/pmt_gain: dtype=float32, shape=() size (4) val='505' (#=1-80)' + 22. '/acquisition/timeseries/ROI_#_Red/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-80)' + 23. '/acquisition/timeseries/ROI_#_Red/scan_line_rate: dtype=float32, shape=() size (4) val='348.2' (#=1-80)' + 24. '/acquisition/timeseries/ROI_#_Red/timestamps: dtype=float64, shape=(175440,) size (1049139), compress=gzip val='[1.084e-19,0.002872,0.005744,0.008616,0.0...hsbIrX' (#=1-80)' + 25. '/acquisition/timeseries/ROI_002_Green/data: dtype=float32, shape=(175440, 1, 1) size (194684), compress=gzip val='[[[115]],[[125]],[[112]],[[116]],[[117]],...hhZxuA'' + 26. '/acquisition/timeseries/ROI_002_Red/data: dtype=float32, shape=(175440, 1, 1) size (131350), compress=gzip val='[[[114]],[[117]],[[118]],[[117]],[[115]],...hyRoJF'' + 27. '/acquisition/timeseries/ROI_003_Green/data: dtype=float32, shape=(175440, 1, 1) size (251913), compress=gzip val='[[[147]],[[150]],[[118]],[[168]],[[153]],...cAiSbH'' + 28. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0029"' (#=3-8)' + 29. '/acquisition/timeseries/ROI_003_Red/data: dtype=float32, shape=(175440, 1, 1) size (130464), compress=gzip val='[[[114]],[[112]],[[113]],[[110]],[[114]],...djGJTF'' + 30. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0029"' (#=3-8)' + 31. '/acquisition/timeseries/ROI_004_Green/data: dtype=float32, shape=(175440, 1, 1) size (260244), compress=gzip val='[[[146]],[[150]],[[166]],[[140]],[[142]],...Jgbwl'' + 32. '/acquisition/timeseries/ROI_004_Red/data: dtype=float32, shape=(175440, 1, 1) size (130514), compress=gzip val='[[[111]],[[111]],[[110]],[[111]],[[112]],...topMc'' + 33. '/acquisition/timeseries/ROI_005_Green/data: dtype=float32, shape=(175440, 1, 1) size (251701), compress=gzip val='[[[149]],[[151]],[[122]],[[138]],[[149]],...diEzgJ'' + 34. '/acquisition/timeseries/ROI_005_Red/data: dtype=float32, shape=(175440, 1, 1) size (130180), compress=gzip val='[[[112]],[[109]],[[108]],[[114]],[[115]],...jxqgog'' + 35. '/acquisition/timeseries/ROI_006_Green/data: dtype=float32, shape=(175440, 1, 1) size (265087), compress=gzip val='[[[178]],[[133]],[[163]],[[211]],[[191]],...bQpin'' + 36. '/acquisition/timeseries/ROI_006_Red/data: dtype=float32, shape=(175440, 1, 1) size (130362), compress=gzip val='[[[112]],[[110]],[[111]],[[114]],[[116]],...imPjoD'' + 37. '/acquisition/timeseries/ROI_007_Green/data: dtype=float32, shape=(175440, 1, 1) size (257598), compress=gzip val='[[[142]],[[123]],[[151]],[[202]],[[137]],...ktAfjL'' + 38. '/acquisition/timeseries/ROI_007_Red/data: dtype=float32, shape=(175440, 1, 1) size (130554), compress=gzip val='[[[115]],[[114]],[[110]],[[109]],[[110]],...cdpkVl'' + 39. '/acquisition/timeseries/ROI_008_Green/data: dtype=float32, shape=(175440, 1, 1) size (263531), compress=gzip val='[[[157]],[[168]],[[163]],[[141]],[[128]],...gdcaXS'' + 40. '/acquisition/timeseries/ROI_008_Red/data: dtype=float32, shape=(175440, 1, 1) size (130113), compress=gzip val='[[[113]],[[110]],[[113]],[[114]],[[109]],...diBNWT'' + 41. '/acquisition/timeseries/ROI_009_Green/data: dtype=float32, shape=(175440, 1, 1) size (254589), compress=gzip val='[[[128]],[[147]],[[147]],[[145]],[[120]],...eAsYNf'' + 42. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0028"' (#=9-13)' + 43. '/acquisition/timeseries/ROI_009_Red/data: dtype=float32, shape=(175440, 1, 1) size (130244), compress=gzip val='[[[116]],[[117]],[[116]],[[111]],[[106]],...lnQOZf'' + 44. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0028"' (#=9-13)' + 45. '/acquisition/timeseries/ROI_010_Green/data: dtype=float32, shape=(175440, 1, 1) size (263779), compress=gzip val='[[[187]],[[166]],[[159]],[[139]],[[184]],...fiwbWb'' + 46. '/acquisition/timeseries/ROI_010_Red/data: dtype=float32, shape=(175440, 1, 1) size (130277), compress=gzip val='[[[110]],[[110]],[[113]],[[110]],[[112]],...bUrTJu'' + 47. '/acquisition/timeseries/ROI_011_Green/data: dtype=float32, shape=(175440, 1, 1) size (264168), compress=gzip val='[[[127]],[[130]],[[163]],[[162]],[[153]],...bNVdrm'' + 48. '/acquisition/timeseries/ROI_011_Red/data: dtype=float32, shape=(175440, 1, 1) size (130358), compress=gzip val='[[[112]],[[106]],[[105]],[[111]],[[113]],...hFlYBw'' + 49. '/acquisition/timeseries/ROI_012_Green/data: dtype=float32, shape=(175440, 1, 1) size (247290), compress=gzip val='[[[152]],[[132]],[[114]],[[120]],[[158]],...hRkBVy'' + 50. '/acquisition/timeseries/ROI_012_Red/data: dtype=float32, shape=(175440, 1, 1) size (130135), compress=gzip val='[[[109]],[[114]],[[111]],[[113]],[[110]],...biZcyg'' + 51. '/acquisition/timeseries/ROI_013_Green/data: dtype=float32, shape=(175440, 1, 1) size (187529), compress=gzip val='[[[116]],[[120]],[[125]],[[117]],[[137]],...krPfMX'' + 52. '/acquisition/timeseries/ROI_013_Red/data: dtype=float32, shape=(175440, 1, 1) size (129966), compress=gzip val='[[[110]],[[113]],[[113]],[[109]],[[111]],...kvoUSz'' + 53. '/acquisition/timeseries/ROI_014_Green/data: dtype=float32, shape=(175440, 1, 1) size (234547), compress=gzip val='[[[135]],[[142]],[[117]],[[118]],[[124]],...jsBHTg'' + 54. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"' (#=14-16,33-44,52-55,78)' + 55. '/acquisition/timeseries/ROI_014_Red/data: dtype=float32, shape=(175440, 1, 1) size (130784), compress=gzip val='[[[115]],[[113]],[[115]],[[121]],[[118]],...glZfDW'' + 56. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"' (#=14-16,33-44,52-55,78)' + 57. '/acquisition/timeseries/ROI_015_Green/data: dtype=float32, shape=(175440, 1, 1) size (238439), compress=gzip val='[[[141]],[[160]],[[113]],[[146]],[[146]],...iWZTiw'' + 58. '/acquisition/timeseries/ROI_015_Red/data: dtype=float32, shape=(175440, 1, 1) size (131086), compress=gzip val='[[[117]],[[124]],[[114]],[[116]],[[120]],...eaDHYF'' + 59. '/acquisition/timeseries/ROI_016_Green/data: dtype=float32, shape=(175440, 1, 1) size (238299), compress=gzip val='[[[115]],[[140]],[[163]],[[155]],[[129]],...fgpBth'' + 60. '/acquisition/timeseries/ROI_016_Red/data: dtype=float32, shape=(175440, 1, 1) size (130820), compress=gzip val='[[[119]],[[122]],[[117]],[[117]],[[120]],...kUzFJZ'' + 61. '/acquisition/timeseries/ROI_017_Green/data: dtype=float32, shape=(175440, 1, 1) size (217243), compress=gzip val='[[[116]],[[139]],[[129]],[[129]],[[137]],...iwkpZg'' + 62. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0034"' (#=17-26,45-48,56-62)' + 63. '/acquisition/timeseries/ROI_017_Red/data: dtype=float32, shape=(175440, 1, 1) size (130874), compress=gzip val='[[[116]],[[122]],[[116]],[[116]],[[117]],...bAZjQE'' + 64. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0034"' (#=17-26,45-48,56-62)' + 65. '/acquisition/timeseries/ROI_018_Green/data: dtype=float32, shape=(175440, 1, 1) size (210055), compress=gzip val='[[[115]],[[118]],[[139]],[[144]],[[115]],...dAiQjQ'' + 66. '/acquisition/timeseries/ROI_018_Red/data: dtype=float32, shape=(175440, 1, 1) size (130746), compress=gzip val='[[[117]],[[114]],[[116]],[[116]],[[114]],...iXdxjt'' + 67. 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'/epochs/trial_0019/speed_data/idx_start: dtype=int32, shape=() size (4) val='211457'' +463. '/epochs/trial_0019/start_time: dtype=float64, shape=() size (8) val='453.7'' +464. '/epochs/trial_0019/stop_time: dtype=float64, shape=() size (8) val='478.9'' +465. '/epochs/trial_0020/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +466. '/epochs/trial_0020/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='166668' (#=1-80)' +467. '/epochs/trial_0020/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +468. '/epochs/trial_0020/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='166668' (#=1-80)' +469. '/epochs/trial_0020/speed_data/idx_start: dtype=int32, shape=() size (4) val='223207'' +470. '/epochs/trial_0020/start_time: dtype=float64, shape=() size (8) val='478.9'' +471. '/epochs/trial_0020/stop_time: dtype=float64, shape=() size (8) val='504.1'' +472. '/file_create_date: dtype=--, shape=(1,) size (--), compress=gzip val='"--value removed for NWB signature--"'' +473. '/general/data_collection: dtype=|S80, shape=() size (80) val='"Text notes about data collection and ana...gWoCry'' +474. '/general/devices/AOL_microscope: dtype=|S57, shape=() size (57) val='"Random access 3d acousto-optic lens two-...ekQKnw'' +475. '/general/devices/air_puff_device: dtype=|S53, shape=() size (53) val='"Delivers an air puff stimulus to the mou...NXTbu'' +476. '/general/devices/mouse_wheel_device: dtype=|S24, shape=() size (24) val='"Records mouse speed data"'' +477. '/general/experiment_description: dtype=|S84, shape=() size (84) val='"A general description of the experiment ...LbatF'' +478. '/general/experimenter: dtype=|S8, shape=() size (8) val='"Hana Ros"'' +479. '/general/institution: dtype=|S25, shape=() size (25) val='"University College London"'' +480. '/general/lab: dtype=|S33, shape=() size (33) val='"Silver Lab (http://silverlab.org)"'' +481. '/general/labview_header: dtype=|S37, shape=(31, 3) size (638), compress=gzip val='[["LOGIN","User",""Hana""],["LOGIN","Prof...djtEQG'' +482. '/general/notes: dtype=|S62, shape=() size (62) val='"Notes about the experiment that don't fi...jyjZeD'' +483. '/general/optophysiology/Zstack#/description: dtype=|S17, shape=() size (17) val='"Reference Z stack"' (#=1-49)' +484. '/general/optophysiology/Zstack#/device: dtype=|S14, shape=() size (14) val='"AOL_microscope"' (#=1-49)' +485. '/general/optophysiology/Zstack#/excitation_lambda: dtype=|S22, shape=() size (22) val='"Excitation wavelength."' (#=1-49)' +486. '/general/optophysiology/Zstack#/green/description: dtype=|S48, shape=() size (48) val='"Green channel, typically used for active...hSPyys' (#=1-49)' +487. '/general/optophysiology/Zstack#/green/emission_lambda: dtype=|S38, shape=() size (38) val='"Emission wavelength for green channel."' (#=1-49)' +488. '/general/optophysiology/Zstack#/imaging_rate: dtype=|S72, shape=() size (72) val='"348.2076013719379262Hz (cycle time = 287...fQXvEy' (#=1-49)' +489. '/general/optophysiology/Zstack#/indicator: dtype=|S18, shape=() size (18) val='"Calcium indicator."' (#=1-49)' +490. '/general/optophysiology/Zstack#/location: dtype=|S94, shape=() size (94) val='"Anatomy gross description of imaging loc...fuLdPY' (#=1-49)' +491. '/general/optophysiology/Zstack0001/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-120],[0.4892,0,-120],[0.9785,0,-1...Wllpt'' +492. '/general/optophysiology/Zstack#/red/description: dtype=|S42, shape=() size (42) val='"Red channel, typically used for reference."' (#=1-49)' +493. '/general/optophysiology/Zstack#/red/emission_lambda: dtype=|S36, shape=() size (36) val='"Emission wavelength for red channel."' (#=1-49)' +494. '/general/optophysiology/Zstack#/reference_frame: dtype=|S27, shape=() size (27) val='"TODO: In lab book (partly?)"' (#=1-49)' +495. '/general/optophysiology/Zstack0002/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-115],[0.4892,0,-115],[0.9785,0,-1...joPgDZ'' +496. '/general/optophysiology/Zstack0003/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-110],[0.4892,0,-110],[0.9785,0,-1...gserWp'' +497. '/general/optophysiology/Zstack0004/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-105],[0.4892,0,-105],[0.9785,0,-1...dvtDoF'' +498. '/general/optophysiology/Zstack0005/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-100],[0.4892,0,-100],[0.9785,0,-1...yIOGV'' +499. '/general/optophysiology/Zstack0006/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-95],[0.4892,0,-95],[0.9785,0,-95]...iRmJVB'' +500. '/general/optophysiology/Zstack0007/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-90],[0.4892,0,-90],[0.9785,0,-90]...fUBVnR'' +501. '/general/optophysiology/Zstack0008/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-85],[0.4892,0,-85],[0.9785,0,-85]...cXRgGh'' +502. '/general/optophysiology/Zstack0009/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-80],[0.4892,0,-80],[0.9785,0,-80]...bgrYx'' +503. '/general/optophysiology/Zstack0010/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-75],[0.4892,0,-75],[0.9785,0,-75]...itKnnd'' +504. '/general/optophysiology/Zstack0011/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-70],[0.4892,0,-70],[0.9785,0,-70]...fwZyFt'' +505. '/general/optophysiology/Zstack0012/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-65],[0.4892,0,-65],[0.9785,0,-65]...cAoJXJ'' +506. '/general/optophysiology/Zstack0013/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-60],[0.4892,0,-60],[0.9785,0,-60]...dZOzXl'' +507. '/general/optophysiology/Zstack0014/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-55],[0.4892,0,-55],[0.9785,0,-55]...jvHGEh'' +508. '/general/optophysiology/Zstack0015/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-50],[0.4892,0,-50],[0.9785,0,-50]...dCmdoN'' +509. '/general/optophysiology/Zstack0016/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-45],[0.4892,0,-45],[0.9785,0,-45]...iYfjVJ'' +510. '/general/optophysiology/Zstack0017/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-40],[0.4892,0,-40],[0.9785,0,-40]...deJGGp'' +511. '/general/optophysiology/Zstack0018/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-35],[0.4892,0,-35],[0.9785,0,-35]...iACNnl'' +512. '/general/optophysiology/Zstack0019/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-30],[0.4892,0,-30],[0.9785,0,-30]...iCEjOJ'' +513. '/general/optophysiology/Zstack0020/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-25],[0.4892,0,-25],[0.9785,0,-25]...ifbNgl'' +514. '/general/optophysiology/Zstack0021/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-20],[0.4892,0,-20],[0.9785,0,-20]...hHzqxN'' +515. '/general/optophysiology/Zstack0022/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-15],[0.4892,0,-15],[0.9785,0,-15]...qSOAl'' +516. '/general/optophysiology/Zstack0023/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-10],[0.4892,0,-10],[0.9785,0,-10]...kLcFfF'' +517. '/general/optophysiology/Zstack0024/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-5],[0.4892,0,-5],[0.9785,0,-5],[1...dYDFaN'' +518. '/general/optophysiology/Zstack0025/manifold: dtype=float32, shape=(512, 512, 3) size (34372), compress=gzip val='[[[0,0,0],[0.4892,0,0],[0.9785,0,0],[1.46...iMZFkq'' +519. '/general/optophysiology/Zstack0026/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,5],[0.4892,0,5],[0.9785,0,5],[1.46...isYxvJ'' +520. '/general/optophysiology/Zstack0027/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,10],[0.4892,0,10],[0.9785,0,10],[1...dQjlQm'' +521. '/general/optophysiology/Zstack0028/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,15],[0.4892,0,15],[0.9785,0,15],[1...eLnGVh'' +522. '/general/optophysiology/Zstack0029/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,20],[0.4892,0,20],[0.9785,0,20],[1...MFyWt'' +523. '/general/optophysiology/Zstack0030/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,25],[0.4892,0,25],[0.9785,0,25],[1...bkhVER'' +524. '/general/optophysiology/Zstack0031/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,30],[0.4892,0,30],[0.9785,0,30],[1...bHKsnp'' +525. '/general/optophysiology/Zstack0032/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,35],[0.4892,0,35],[0.9785,0,35],[1...bFJtXS'' +526. '/general/optophysiology/Zstack0033/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,40],[0.4892,0,40],[0.9785,0,40],[1...hzeXnm'' +527. '/general/optophysiology/Zstack0034/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,45],[0.4892,0,45],[0.9785,0,45],[1...cdlQGq'' +528. '/general/optophysiology/Zstack0035/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,50],[0.4892,0,50],[0.9785,0,50],[1...hWHtVK'' +529. '/general/optophysiology/Zstack0036/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,55],[0.4892,0,55],[0.9785,0,55],[1...cANPcN'' +530. '/general/optophysiology/Zstack0037/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,60],[0.4892,0,60],[0.9785,0,60],[1...iujssh'' +531. '/general/optophysiology/Zstack0038/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,65],[0.4892,0,65],[0.9785,0,65],[1...gUJCsF'' +532. '/general/optophysiology/Zstack0039/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,70],[0.4892,0,70],[0.9785,0,70],[1...jRurap'' +533. '/general/optophysiology/Zstack0040/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,75],[0.4892,0,75],[0.9785,0,75],[1...byQvLJ'' +534. '/general/optophysiology/Zstack0041/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,80],[0.4892,0,80],[0.9785,0,80],[1...evBktt'' +535. '/general/optophysiology/Zstack0042/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,85],[0.4892,0,85],[0.9785,0,85],[1...hslZbd'' +536. '/general/optophysiology/Zstack0043/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,90],[0.4892,0,90],[0.9785,0,90],[1...koWNIN'' +537. '/general/optophysiology/Zstack0044/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,95],[0.4892,0,95],[0.9785,0,95],[1...bWsSuh'' +538. '/general/optophysiology/Zstack0045/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,100],[0.4892,0,100],[0.9785,0,100]...eTdHbR'' +539. '/general/optophysiology/Zstack0046/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,105],[0.4892,0,105],[0.9785,0,105]...hPOvJB'' +540. '/general/optophysiology/Zstack0047/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,110],[0.4892,0,110],[0.9785,0,110]...kMzkrl'' +541. '/general/optophysiology/Zstack0048/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,115],[0.4892,0,115],[0.9785,0,115]...ctVpcF'' +542. '/general/optophysiology/Zstack0049/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,120],[0.4892,0,120],[0.9785,0,120]...fqGdKp'' +543. '/general/optophysiology/cycle_time: dtype=float32, shape=() size (4) val='0.002872'' +544. '/general/optophysiology/frame_size: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' +545. '/general/optophysiology/imaging_mode: dtype=|S8, shape=() size (8) val='"pointing"'' +546. '/general/optophysiology/zplane_pockels: dtype=float32, shape=(49, 4) size (579), compress=gzip val='[[-120,0.4994,100,-120],[-115,0.4797,100,...iUevau'' +547. '/general/pharmacology: dtype=|S152, shape=() size (152) val='"Description of drugs used, including how...goKGik'' +548. '/general/protocol: dtype=|S76, shape=() size (76) val='"Experimental protocol, if applicable, e....bWYeFo'' +549. '/general/related_publications: dtype=|S70, shape=() size (70) val='"Optional list of related publications, i...gGeOxQ'' +550. '/general/session_id: dtype=|S15, shape=() size (15) val='"161215_15_58_52"'' +551. '/general/slices: dtype=|S127, shape=() size (127) val='"Description of slices, including informa...bwDbqR'' +552. '/general/specifications/e-labview.py: dtype=|S1534, shape=() size (1534) val='"# NWB extension to store LabView header ...fvMAMg'' +553. '/general/specifications/e-pixeltimes.py: dtype=|S2701, shape=() size (2701) val='"# NWB extension to store per-pixel time ...gVgtZh'' +554. '/general/specifications/nwb_core.py: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +555. '/general/stimulus: dtype=|S84, shape=() size (84) val='"Notes about stimuli, such as how and whe...DShaM'' +556. '/general/subject/age: dtype=|S25, shape=() size (25) val='"Age of subject. Optional."'' +557. '/general/subject/description: dtype=|S88, shape=() size (88) val='"Description of subject and where subject...fXgfBt'' +558. '/general/subject/genotype: dtype=|S59, shape=() size (59) val='"Genetic strain. If absent, assume Wild T...eOaNbr'' +559. '/general/subject/sex: dtype=|S28, shape=() size (28) val='"Gender of subject. Optional."'' +560. '/general/subject/species: dtype=|S29, shape=() size (29) val='"Species of subject. Optional."'' +561. '/general/subject/subject_id: dtype=|S80, shape=() size (80) val='"ID of animal/person used/participating i...hoSoPZ'' +562. '/general/subject/weight: dtype=|S88, shape=() size (88) val='"Weight at time of experiment, at time of...grFgyL'' +563. '/general/surgery: dtype=|S134, shape=() size (134) val='"Narrative description about surgery/surg...dKKeYq'' +564. '/general/virus: dtype=|S130, shape=() size (130) val='"Information about virus(es) used in expe...cMsZNh'' +565. '/identifier: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +566. '/nwb_version: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +567. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=79-80)' +568. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_079/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...bssQde'' +569. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_079/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[384,164]]'' +570. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/pix_mask_weight: dtype=float32, shape=(1,) size (12), compress=gzip val='[1]' (#=79-80)' +571. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_079/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002839]'' +572. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/roi_description: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=79-80)' +573. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_080/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...lbkyiG'' +574. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_080/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[224,331]]'' +575. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_080/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002868]'' +576. 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'/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(20,) size (171), compress=gzip val='[5,30.21,55.41,80.62,105.8,131,156.2,181....flSHgS'' +-------------------- +** Summary +3767 groups, 10616 datasets, 3609 attributes diff --git a/MATLAB/tests/data/sample_header.ini b/MATLAB/tests/data/sample_header.ini new file mode 100644 index 0000000..c1f8545 --- /dev/null +++ b/MATLAB/tests/data/sample_header.ini @@ -0,0 +1,23 @@ +; This is a comment. + +; Blank lines are OK. + +; Items outside any section are supported. + +Orphan item = 'Poor me!' + +[LOGIN] +User = "Angus" + +[GLOBAL PARAMETERS] +number of poi = 150.000000 +# averaged frames = 16.000000 +laser power (%) = 60.000000 +pockels = -1.000000 + +[MOVEMENT CORRECTION] +MovCor Enabled? = TRUE +Reference Size = "15 x 18 pixels" + +[STATISTICS] +Z-stack duration (sec) = 56.674242 diff --git a/MATLAB/tests/data/test_epochs.nwb b/MATLAB/tests/data/test_epochs.nwb new file mode 100644 index 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HcmV?d00001 diff --git a/Python/README.md b/Python/README.md new file mode 100644 index 0000000..9150d1d --- /dev/null +++ b/Python/README.md @@ -0,0 +1,84 @@ +# Python API for NWB use in the Silver Lab + +This Python package 'silverlabnwb' simplifies access to NWB data for typical Silver Lab experiments, +and converts data from Labview format into NWB. +It provides a few command-line utilities, as well as supporting access from other Python software. + +## Installation + +Our [installation script](../README.md) will install the SilverLabNwb package into a conda environment, +by default called `nwb`. +You need to activate this environment each time you want to use the package, +using one of the following commands depending on your system. +(These all assume Anaconda has been installed as the default Python; +if not you will need to provide the full path to its `activate` script.) + +Linux, Mac OS, and Windows with git-bash: +``` sh +source activate nwb +``` + +Windows with PowerShell or the default `cmd` prompt: +``` sh +activate nwb +``` + +## Usage + +Two main programs are provided: `labview2nwb` and `nwb_metadata_editor`. + +`labview2nwb` imports Labview data to the NWB format. +You need to provide it the path to the NWB file to create, +and the path to the folder containing Labview data. +At present it assumes that video data is in a folder adjacent to the Labview data; +this will be made more flexible in the future. + +For more details on usage run with the `-h` flag, i.e. +``` sh +labview2nwb -h +``` + +By default the import process will start by running a simple graphical editor, +allowing you to input metadata required or recommended by the NWB format, +but that is not available within the Labview data folder. + +`nwb_metadata_editor` runs the metadata editor in standalone mode. +It is useful for setting up details of new researchers or new experiments, +that can then be used quickly when importing experiment data. + +## Python library usage + +The main class is `silverlabnwb.NwbFile` defined in `nwb_file.py`. +All its methods are documented with docstrings. + +Quick examples: + +``` python +from silverlabnwb import NwbFile + +# Write a new file +with NwbFile(nwb_path, mode='w') as nwb: + nwb.import_labview_folder(labview_path) + +# Read an existing file +with NwbFile(nwb_path) as nwb: + print('Opened NWB with ID {}'.format(nwb['/identifier'])) +``` + +## Development + +Installing the package with the `-e` flag to `pip` in the install script means it is installed in 'developer' mode, +so that changes you make to the package sources are immediately reflected in the installed package. + +To run the automated tests, do: + +``` sh +pip install -r requirements/test.txt # First time only +pytest +``` + +There is also a utility script `nwb_check_signature` which checks an NWB file against a precomputed signature. +To generate a signature from an NWB file, use +``` sh +python -m nwb.h5diffsig /path/to/nwb_file.nwb -Na > /path/to/signature.sig +``` diff --git a/Python/requirements/legion.txt b/Python/requirements/legion.txt new file mode 100644 index 0000000..5a6d46a --- /dev/null +++ b/Python/requirements/legion.txt @@ -0,0 +1,19 @@ +# This file is copied manually from main.txt and the packages installed +# via conda (i.e. av, h5py) removed, so as not to break compatibility +# with Legion's Matlab. + +appdirs==1.4.3 +jsonschema==2.6.0 +npTDMS==0.11.0 +numpy==1.12.1 +nwb +olefile==0.44 +pandas==0.20.1 +Pillow==4.1.1 +py==1.4.33 +pytest==3.0.7 +python-dateutil==2.6.0 +pytz==2017.2 +PyYAML==3.12 +six==1.10.0 +tifffile==0.12.0 diff --git a/Python/requirements/main.in b/Python/requirements/main.in new file mode 100644 index 0000000..ce23835 --- /dev/null +++ b/Python/requirements/main.in @@ -0,0 +1,10 @@ +h5py +numpy +nwb +pandas +six +tifffile +npTDMS +av +appdirs +pyyaml diff --git a/Python/requirements/main.txt b/Python/requirements/main.txt new file mode 100644 index 0000000..be5a988 --- /dev/null +++ b/Python/requirements/main.txt @@ -0,0 +1,17 @@ +appdirs==1.4.3 +av==0.3.3 +h5py==2.7.0 +jsonschema==2.6.0 +npTDMS==0.11.0 +numpy==1.12.1 +nwb +olefile==0.44 +pandas==0.20.1 +Pillow==4.1.1 +py==1.4.33 +pytest==3.0.7 +python-dateutil==2.6.0 +pytz==2017.2 +PyYAML==3.12 +six==1.10.0 +tifffile==0.12.0 diff --git a/Python/requirements/test.txt b/Python/requirements/test.txt new file mode 100644 index 0000000..e079f8a --- /dev/null +++ b/Python/requirements/test.txt @@ -0,0 +1 @@ +pytest diff --git a/Python/setup.py b/Python/setup.py new file mode 100644 index 0000000..87bc375 --- /dev/null +++ b/Python/setup.py @@ -0,0 +1,43 @@ +from setuptools import setup, find_packages + +import sys + + +# Check which Python version this is, and set extra deps accordingly +if sys.version_info[0] == 2: + extra_deps = ['enum34'] +else: + extra_deps = [] + +setup(name='SilverLabNwb', + version='0.1', + description='Neuroscience data management and analysis in the Silver Lab', + url='https://github.com/SilverLabUCL/SilverLab_NWBv1', + author='Jonathan Cooper', + author_email='j.p.cooper@ucl.ac.uk', + classifiers=['Development Status :: 3 - Alpha', + 'Programming Language :: Python', + 'Programming Language :: Python :: 2', + 'Programming Language :: Python :: 3', + 'Operating System :: OS Independent', + 'Intended Audience :: Science/Research', + 'License :: Other/Proprietary License'], + install_requires=['nwb', 'h5py', 'numpy', 'pandas>=0.20', 'tifffile', + 'nptdms', 'av', 'appdirs', 'pyyaml', 'six'] + extra_deps, + packages=find_packages(exclude=['*test']), + package_data={ + # If any (sub-)package contains *.yaml files, include them: + '': ['*.yaml'] + }, + entry_points={ + 'console_scripts': [ + 'labview2nwb = silverlabnwb.script:import_labview', + 'nwb_check_signature = silverlabnwb.script:check_signature', + 'subsample_nwb = silverlabnwb.subsample_nwb:run' + ], + 'gui_scripts': [ + 'nwb_metadata_editor = silverlabnwb.metadata_gui:run_editor' + ] + }, + zip_safe=False + ) diff --git a/Python/silverlabnwb/__init__.py b/Python/silverlabnwb/__init__.py new file mode 100644 index 0000000..9956a39 --- /dev/null +++ b/Python/silverlabnwb/__init__.py @@ -0,0 +1,3 @@ + +# Import the main class provided by this package for convenience +from .nwb_file import NwbFile # noqa diff --git a/Python/silverlabnwb/e-labview.py b/Python/silverlabnwb/e-labview.py new file mode 100644 index 0000000..100b38c --- /dev/null +++ b/Python/silverlabnwb/e-labview.py @@ -0,0 +1,37 @@ +# NWB extension to store LabView header (.ini) information within the /general group. +# Created at the Silver Lab, UCL, UK. + +{"fs": {"labview": { + +"info": { + "name": "LabView header storage extension", + "version": "1.0.0", + "date": "Feb 16, 2017", + "author": "Jonathan Cooper", + "contact": "j.p.cooper@ucl.ac.uk", + "description": ("NWB extension to store raw metadata from LabView header (.ini) files." + " While some of this information also maps to standard NWB fields," + " it is useful to retain the raw fields for provenance.") +}, + +"schema": { + "labview_header": { + "description": ("LabView header fields represented as a 3-column text array." + " The columns represent 'Section', 'Field name' and 'Field value'."), + "data_type": "text", + # TODO: The actual type used by h5py/numpy can be 'object' because these are variable length strings, + # so this gives a warning. But 'object isn't a valid type for the NWB API, and text is more appropriate anyway! + "dimensions": ["total_num_fields", "cols"], + "cols" : { # definition of dimension "cols" + "type": "structure", + "components": [ + { "alias": "Section", "unit": "N/A" }, + { "alias": "Field name", "unit": "N/A" }, + { "alias": "Field value", "unit": "N/A" } ] } + }, + "/general/": { + "description": "Extension to core general to add labview_header.", + "include": { "labview_header": {}}, + }, +} +}}} \ No newline at end of file diff --git a/Python/silverlabnwb/e-pixeltimes.py b/Python/silverlabnwb/e-pixeltimes.py new file mode 100644 index 0000000..370677d --- /dev/null +++ b/Python/silverlabnwb/e-pixeltimes.py @@ -0,0 +1,56 @@ +# NWB extension to store per-pixel time offsets for TwoPhotonSeries and RoiResponseSeries. +# Created at the Silver Lab, UCL, UK. + +{"fs": {"pixeltimes": { + +"info": { + "name": "Per-pixel time offsets extension", + "version": "1.0.0", + "date": "Feb 22, 2017", + "author": "Jonathan Cooper", + "contact": "j.p.cooper@ucl.ac.uk", + "description": ("NWB extension to store per-pixel time offsets for AOL-acquired data." + " Due to the properties of the AOL microscope, each pixel in a 2d image," + " or in an ROI, is acquired at a slightly different time. A single " + " timestamp per ROI or image plane is therefore misleading." + " This extension adds a pixel_time_offsets dataset to RoiResponseSeries" + " and TwoPhotonSeries recording the offset from the frame timestamp for" + " each pixel.") +}, + +"schema": { + "/": { + "description": "Extension to add a roi_time_offsets dataset.", + "roi_time_offsets?": { + "description": ("The offset from the frame timestamp at which each ROI was acquired." + " Note that the offset is not time-varying, i.e. it is the same for" + " each frame. These offsets are given in the same units as for the" + " timestamps array, i.e. seconds."), + "data_type": "float64!", + "dimensions": ["num_ROIs"] + } + }, + "/": { + "description": "Extension to add a pixel_time_offsets dataset.", + "pixel_time_offsets?": { + "description": ("The offset from the frame timestamp at which each pixel was acquired." + " Note that the offset is not time-varying, i.e. it is the same for" + " each frame. These offsets are given in the same units as for the" + " timestamps array, i.e. seconds."), + "link": {"target_type": "pixel_time_offsets", "allow_subclasses": False}, + "data_type": "float64!" + } + }, + "/*": { + "pixel_time_offsets": { + "description": ("The offset from the frame timestamp at which each pixel in this ROI" + " was acquired." + " Note that the offset is not time-varying, i.e. it is the same for" + " each frame. These offsets are given in the same units as for the" + " timestamps array, i.e. seconds."), + "data_type": "float64!", + "dimensions": [["y"], ["y", "x"]] + } + } +} +}}} \ No newline at end of file diff --git a/Python/silverlabnwb/metadata.py b/Python/silverlabnwb/metadata.py new file mode 100644 index 0000000..984da71 --- /dev/null +++ b/Python/silverlabnwb/metadata.py @@ -0,0 +1,103 @@ + +''' +Handles loading the metadata YAML files. +''' + +import collections +import os + +import appdirs +import pkg_resources +import six +import yaml + + +def set_conf_dir(path=appdirs.user_config_dir('SilverLabNwb', 'SilverLab')): + """Set where to store / read user configuration files. + + Defaults to the system-specific default user configuration folder. + + :param path: path to a configuration folder + """ + global user_conf_dir, user_conf_path + user_conf_dir = path + user_conf_path = os.path.join(user_conf_dir, 'metadata.yaml') + + +set_conf_dir() # Set the default paths initially + + +def read_user_config(): + """Read the user configuration YAML files. + + We first read the default configuration supplied with this package. + Then we look in the user_config_dir (as defined by appdirs) for any + machine- & user-specific configuration settings, which override the + defaults. + """ + with pkg_resources.resource_stream(__name__, 'metadata.yaml') as defaults: + settings = read_config_file(defaults) + if os.path.isfile(user_conf_path): + with open(user_conf_path, 'r') as user_params: + settings = read_config_file(user_params, settings) + return settings + + +def read_config_file(stream, base_settings=None): + """Read a single YAML configuration file. + + :param stream: the open file object. + :param base_settings: if present, a settings dictionary to copy and update + with the contents of this file. + """ + if base_settings is None: + settings = {} + else: + settings = base_settings.copy() + recursive_dict_update(settings, strip_strings(yaml.safe_load(stream))) + return settings + + +def save_config_file(settings): + """Save a YAML user configuration file to the default path. + + Will try to create the user's configuration folder if it doesn't exist. + + :param settings: the settings dictionary to save + """ + if not os.path.isdir(user_conf_dir): + os.makedirs(user_conf_dir) + with open(user_conf_path, 'w') as user_params: + yaml.safe_dump(settings, user_params) + + +def recursive_dict_update(base_settings, new_settings): + """Recursively update settings dictionaries. + + Since our settings are nested dictionaries, we need to merge sub-levels rather + than overwriting when merging new settings. This method essentially does a + recursive base_settings.update(new_settings). + """ + for k, v in new_settings.items(): + if isinstance(v, collections.Mapping): + base_settings[k] = recursive_dict_update(base_settings.get(k, {}), v) + else: + base_settings[k] = new_settings[k] + return base_settings + + +def strip_strings(settings): + """Recursively strip all strings in a settings dict. + + :param settings: the settings dictionary to process + :returns: a new dictionary with all string settings stripped + """ + result = {} + for k, v in settings.items(): + if isinstance(v, six.string_types): + result[k] = v.strip() + elif isinstance(v, collections.Mapping): + result[k] = strip_strings(v) + else: + result[k] = v + return result diff --git a/Python/silverlabnwb/metadata.yaml b/Python/silverlabnwb/metadata.yaml new file mode 100644 index 0000000..7c8288a --- /dev/null +++ b/Python/silverlabnwb/metadata.yaml @@ -0,0 +1,112 @@ +# This file defines extra metadata for including within Silver Lab NWB files. +# Lines beginning with '#' characters are comments, and ignored by the software. +# For a guide to the syntax see http://pyyaml.org/wiki/PyYAMLDocumentation#YAMLsyntax + +# The first section defines information about researchers. The keys here are their +# 'User' fields as given in LabView. +people: + Fred: + name: Frederic Lanore + orcid: 0000-0003-4316-6855 + Hana: + name: Hana Ros + scopus_id: 33368223900 + +# Settings for particular experiments come next. This allows easy reuse of methods +# information, etc. that is common to many sessions. Each experiment is identified +# by a short label that is referenced in the session section at the end of this file. +experiments: + template: + description: > + A general description of the experiment goes here. + Can be from Methods. + Recommended. + data_collection: > + Text notes about data collection and analysis. E.g. take from methods. + Optional. + pharmacology: > + Description of drugs used, including how and when they were administered. + Anesthesia(s), painkiller(s), etc., plus dosage, concentration, etc. + Optional. + protocol: > + Experimental protocol, if applicable, e.g. include IACUC protocol. + Optional. + slices: > + Description of slices, including information about preparation thickness, + orientation, temperature and bath solution. + Optional. + stimulus: > + Notes about stimuli, such as how and where presented. Can be from Methods. + Optional. + subject: + # Information about the animal or person from which the data was measured. Optional. + age: Age of subject. Optional. + description: > + Description of subject and where subject came from (e.g., breeder, if animal). + Optional. + genotype: "Genetic strain. If absent, assume Wild Type (WT). Optional." + sex: Gender of subject. Optional. + species: Species of subject. Optional. + subject_id: "ID of animal/person used/participating in experiment (lab convention). Optional." + weight: > + Weight at time of experiment, at time of surgery and at other important times. + Optional. + surgery: > + Narrative description about surgery/surgeries, including date(s) and who performed surgery. + Much can be copied from Methods. + Optional. + virus: > + Information about virus(es) used in experiments, including virus ID, source, date made, + injection location, volume, etc. + Optional. + notes: > + Notes about the experiment that don't fit elsewhere. + Optional. + related_publications: > + Optional list of related publications, identified by DOI, PMID or URL. + optophysiology: + excitation_lambda: Excitation wavelength. + emission_lambda: + green: Emission wavelength for green channel. + red: Emission wavelength for red channel. + calcium_indicator: Calcium indicator. + location: > + Anatomy gross description of imaging location, e.g. vermis, visual cortex, depth of recording. + # We should also have a more detailed 'reference_frame' for each imaging plane, which describes + # position and reference frame of manifold based on position of first element in manifold. + # For example, text description of anotomical location or vectors needed to rotate to common + # anatomical axis (eg, AP/DV/ML). Not sure of the best way to input this, given we have lots of + # imaging planes! TODO. + stimulus_details: # Required, until it is recorded by Labview! + - name: air_puff + source: air_puff_device # Must match a device in the devices section + description: "Air puff stimulus" + comments: "Delivered 'instantaneously' at the specified times" + trial_time_offset: 5.0 # seconds + +# This section describes the hardware devices that could be used during an experiment. +# At present we assume the first 3 are always used, and the cameras are used iff +# corresponding video files are present. +# In the future this will need to be rig-specific, and the session below will indicate +# which rig was used. +# NB: The names used here must not be changed, as they are referenced within the code. However the +# descriptions can be improved upon. +# TODO: Include the make & model of camera, etc. +devices: + AOL_microscope: "Random access 3d acousto-optic lens two-photon microscope" + mouse_wheel_device: "Records mouse speed data" + air_puff_device: "Delivers an air puff stimulus to the mouse's whiskers" + BodyCam: "Video camera viewing the mouse body" + EyeCam: "30Hz video camera viewing the mouse face" + WhiskersCam: "300Hz video camera viewing the mouse's whiskers" + +# This section records the last 'session' by each researcher. The definitions are used +# as defaults for the next session, so multiple similar experiments will require very +# little modification. +sessions: + Fred: # Should match a user id in the 'people' section + description: One or two sentences describing the experiment and data in the file. + experiment: template # Should match an experiment defined above + Hana: # Should match a user id in the 'people' section + description: One or two sentences describing the experiment and data in the file. + experiment: template # Should match an experiment defined above diff --git a/Python/silverlabnwb/metadata_gui.py b/Python/silverlabnwb/metadata_gui.py new file mode 100644 index 0000000..dc439a5 --- /dev/null +++ b/Python/silverlabnwb/metadata_gui.py @@ -0,0 +1,496 @@ + +import collections +import six + +from six.moves import tkinter as T +from six.moves import tkinter_messagebox as messagebox +from six.moves import tkinter_ttk as ttk + +from . import metadata + + +def wrap_dict(metadata): + """Convert a metadata dict to use Tk variables to wrap entries.""" + wrapped = {} + for key, value in metadata.items(): + wrapped[key] = wrap_value(value) + return wrapped + + +def wrap_list(metadata): + """Convert a list of metadata components to use Tk variables.""" + return [wrap_value(item) for item in metadata] + + +def wrap_value(value): + """Wrap a value as a Tk variable, or nested structure thereof. + + String values will automatically be stripped. + """ + if isinstance(value, collections.Mapping): + wrapped = wrap_dict(value) + elif isinstance(value, list): + wrapped = wrap_list(value) + elif isinstance(value, str): + wrapped = T.StringVar() + wrapped.set(value.strip()) + elif isinstance(value, float): + wrapped = T.DoubleVar() + wrapped.set(value) + elif isinstance(value, six.integer_types): + wrapped = T.IntVar() + wrapped.set(value) + elif isinstance(value, bool): + wrapped = T.BooleanVar() + wrapped.set(value) + elif is_tkinter_variable(value): + # Clone the particular type of tkinter variable + wrapped = get_tk_type(value)() + value = value.get() + if hasattr(value, 'strip'): + value = value.strip() + wrapped.set(value) + else: + raise ValueError('Unexpected metadata item {} of type {}'.format(value, type(value))) + return wrapped + + +def is_tkinter_variable(value): + """Determine whether the given value is an instance of a tkinter Variable type. + + On Python 3 this is easy; on Python 2 it's a little more dubious. + """ + if six.PY2: + return hasattr(value, '_tk') + else: + return isinstance(value, T.Variable) + + +def get_tk_type(var): + """Get the actual tkinter Variable type used for the given variable. + + On Python 3 we can just use type(), but on Python 2 we have to examine base classes. + Uses the same logic as the YAML representer dispatch. + """ + if six.PY3: + return type(var) + else: + def get_classobj_bases(cls): + bases = [cls] + for base in cls.__bases__: + bases.extend(get_classobj_bases(base)) + return bases + import types + data_types = type(var).__mro__ + if type(var) is types.InstanceType: + data_types = get_classobj_bases(var.__class__) + list(data_types) + return data_types[0] + + +def add_yaml_representers(): + """Add YAML representers that convert Tk variables to their Python contents.""" + def get_repr(kind): + def representer(dumper, data): + data = data.get() + if six.PY2 and kind == 'str' and isinstance(data, unicode): + rep = dumper.represent_unicode + else: + rep = getattr(dumper, 'represent_' + kind) + return rep(data) + return representer + import yaml + yaml.SafeDumper.add_representer(T.StringVar, get_repr('str')) + yaml.SafeDumper.add_representer(T.DoubleVar, get_repr('float')) + yaml.SafeDumper.add_representer(T.IntVar, get_repr('int')) + yaml.SafeDumper.add_representer(T.BooleanVar, get_repr('bool')) + + +def strip_empty_vars(metadata): + """Return a copy of the metadata that has no empty StringVar instances.""" + if isinstance(metadata, collections.Mapping): + result = {} + for key, value in metadata.items(): + result[key] = strip_empty_vars(value) + if result[key] is None: + del result[key] + elif isinstance(metadata, list): + result = [stripped + for stripped in (strip_empty_vars(item) for item in metadata) + if stripped is not None] + elif (hasattr(metadata, 'get') and isinstance(metadata.get(), str) and + metadata.get().strip() == ''): + result = None + else: + result = metadata + return result + + +class MetadataEditor(ttk.Frame): + """A simple Tkinter GUI to help researchers fill in experiment metadata.""" + def __init__(self, master=None): + """Initialise the GUI.""" + ttk.Frame.__init__(self, master) + # Load the merged metadata from file, and extract the template experiment + user_metadata = metadata.read_user_config() + self.template_expt = user_metadata['experiments'].pop('template') + del user_metadata['devices'] # Until we support editing it + self.metadata = wrap_dict(user_metadata) + add_yaml_representers() + # self.original_metadata = copy.deepcopy(self.metadata) + # Action buttons + # ttk.Button(self, text="REVERT", command=self.revert).grid( + # row=0, column=0, sticky=T.W, padx=5, pady=5) + ttk.Button(self, text="SAVE", command=self.save).grid( + row=0, column=1, sticky=T.W, padx=5, pady=5) + ttk.Button(self, text="DONE", command=self.done).grid( + row=0, column=2, sticky=T.W, padx=5, pady=5) + # Content tabs + tabs = self.tabs = ttk.Notebook(self, padding=2) + self.session_tab = self.make_session_tab(tabs) + self.people_tab = self.make_people_tab(tabs) + self.expts_tab = self.make_expts_tab(tabs) + tabs.enable_traversal() + tabs.grid(row=1, column=0, columnspan=3) + # Resize support - make the content section take it all + self.rowconfigure(1, weight=1) + self.columnconfigure('all', weight=1) + tabs.rowconfigure('all', weight=1) + tabs.columnconfigure('all', weight=1) + self.pack(side="top", fill="both", expand=True) + + def save(self): + """Save current settings to file. + + TODO: Give the user some indication that this has happened! + """ + self.record_expt() # The only part that doesn't sync by itself + metadata.save_config_file(strip_empty_vars(self.metadata)) + + def done(self): + """Save settings and quit the editor.""" + self.save() + self.master.destroy() + + # def revert(self): + # """Revert all metadata changes made by this editor.""" + # self.metadata = copy.deepcopy(self.original_metadata) + # self.save() + + def make_people_tab(self, parent): + """Build the people tab and add it to the parent.""" + frame = ttk.Frame(parent) + # Choosing who to edit + ttk.Label(frame, text='Edit person:').grid(row=0, column=0, sticky='e') + person_list = ttk.Combobox(frame, state='readonly', width=10, + values=sorted(self.metadata['people'].keys())) + person_list.bind('<>', + lambda e: self.update_people_tab(person_list.get())) + person_list.grid(row=0, column=1, sticky='w') + # Section for adding new people + ttk.Label(frame, text='New person:').grid( + row=2, column=0, sticky='e') + new_person_var = T.StringVar() + ttk.Entry(frame, textvariable=new_person_var, width=10).grid( + row=2, column=1, sticky='w') + # TODO: Make hitting return in the Entry click the Add button + # TODO: Make the Add button stick next to the Entry box + ttk.Button(frame, text='Add', + command=lambda: self.add_person(new_person_var.get(), + person_list)).grid( + row=2, column=2, sticky='w') + # Fields to edit current person + widgets = self.session_widgets = {} + ttk.Label(frame, text='Full name:').grid(row=0, column=4, sticky='e') + widgets['name'] = ttk.Entry(frame) + widgets['name'].grid(row=0, column=5, sticky='w') + ttk.Label(frame, text='ORCID:').grid(row=1, column=4, sticky='e') + widgets['orcid'] = ttk.Entry(frame) + widgets['orcid'].grid(row=1, column=5, sticky='w') + ttk.Label(frame, text='SCOPUS ID:').grid(row=2, column=4, sticky='e') + widgets['scopus_id'] = ttk.Entry(frame) + widgets['scopus_id'].grid(row=2, column=5, sticky='w') + if self.metadata['people']: + person_list.set(person_list['values'][0]) + self.update_people_tab(person_list.get()) + # Resize support + frame.rowconfigure('all', weight=0) + frame.columnconfigure(0, weight=2) + frame.columnconfigure(3, weight=1) + frame.columnconfigure(6, weight=2) + parent.add(frame, text='People') + return frame + + def update_people_tab(self, person_id): + """Associate the entry boxes with the given person's details.""" + assert person_id in self.metadata['people'] + person = self.metadata['people'][person_id] + widgets = self.session_widgets + for key in ['name', 'orcid', 'scopus_id']: + if key not in person: + # Optional item was not present before + person[key] = T.StringVar() + widgets[key]['textvariable'] = person[key] + + def add_person(self, person_id, person_list_box): + """Add a new researcher.""" + # TODO: Update the 'edit person' dropdown to match person_id + existing_people = person_list_box['values'] + if person_id in existing_people: + messagebox.showerror(message='The person ID "{}" already exists'.format(person_id)) + return + if not person_id.isalnum(): + messagebox.showerror(message='A person ID can only contain letters and numbers') + return + person_list_box['values'] = sorted(existing_people + (person_id,)) + self.session_researcher_box['values'] = person_list_box['values'] + name_var = T.StringVar() + name_var.set(person_id) + self.metadata['people'][person_id] = {'name': name_var} + self.update_people_tab(person_id) + + def make_session_tab(self, parent): + """Build a tab for setting session properties.""" + frame = ttk.Frame(parent) + ttk.Label(frame, text='Description:').grid(row=2, column=0, sticky='e') + desc = ttk.Entry(frame, width=70) + desc.grid(row=2, column=1, sticky='w') + + ttk.Label(frame, text='Researcher:').grid(row=0, column=0, sticky='e') + researcher = ttk.Combobox(frame, state='readonly', + values=sorted(self.metadata['people'].keys())) + researcher.bind('<>', + lambda e: self.update_session(person=researcher.get(), + expt=experiment, + desc=desc)) + researcher.grid(row=0, column=1, sticky='w') + self.session_researcher_box = researcher + + ttk.Label(frame, text='Experiment:').grid(row=1, column=0, sticky='e') + experiment = ttk.Combobox(frame, state='readonly', + values=sorted(self.metadata['experiments'].keys())) + experiment.bind('<>', + lambda e: self.update_session(person=researcher.get(), + expt=experiment.get())) + experiment.grid(row=1, column=1, sticky='w') + self.session_experiment_box = experiment + + if 'last_session' not in self.metadata: + self.metadata['last_session'] = T.StringVar() + self.metadata['last_session'].set(researcher['values'][0]) + last_person = self.metadata['last_session'].get() + researcher.set(last_person) + self.update_session(person=researcher.get(), desc=desc, expt=experiment) + # Resize support & add to tabs + frame.rowconfigure('all', weight=0) + frame.columnconfigure('all', weight=1) + parent.add(frame, text='This session') + return frame + + def update_session(self, person, desc=None, expt=None): + """Update session info to reflect changes in the dropdowns.""" + self.metadata['last_session'].set(person) + if person not in self.metadata['sessions']: + self.metadata['sessions'][person] = { + 'description': T.StringVar(), + 'experiment': T.StringVar() + } + self.metadata['sessions'][person]['description'].set( + "One or two sentences describing the experiment and data in the file.") + if desc is not None: + desc['textvariable'] = self.metadata['sessions'][person]['description'] + if expt is not None: + expt_var = self.metadata['sessions'][person]['experiment'] + if isinstance(expt, str): + expt_var.set(expt) + else: + expt.set(expt_var.get()) + + def make_expts_tab(self, parent): + """Build a tab for setting experiment info.""" + expt_frame = ttk.Frame(parent) + # Control pane along the top + frame = ttk.Frame(expt_frame) + + ttk.Label(frame, text='Edit experiment:').grid(row=0, column=0, sticky='e') + experiment = ttk.Combobox(frame, state='readonly', width=15, + values=sorted(self.metadata['experiments'].keys())) + experiment.bind('<>', + lambda e: self.update_expts_tab(expt_id=experiment.get())) + experiment.grid(row=0, column=1, sticky='w') + self.experiment_shown = None + self.experiment_selector = experiment + + ttk.Label(frame, text='Clone experiment as:').grid(row=1, column=0, sticky='e') + clone_var = T.StringVar() + ttk.Entry(frame, textvariable=clone_var, width=15).grid(row=1, column=1, sticky='we') + self.clone_expt_button = ttk.Button( + frame, text='Clone', + command=lambda: self.add_expt(clone_var.get(), + clone=experiment.get())) + self.clone_expt_button.grid(row=1, column=2, sticky='w') + if not self.metadata['experiments']: + self.clone_expt_button.state(['disabled']) + + ttk.Label(frame, text='Add experiment:').grid(row=2, column=0, sticky='e') + add_var = T.StringVar() + ttk.Entry(frame, textvariable=add_var, width=15).grid(row=2, column=1, sticky='we') + ttk.Button(frame, text='Add', + command=lambda: self.add_expt(add_var.get())).grid( + row=2, column=2, sticky='w') + + frame.columnconfigure(0, weight=1) # Expand at the sides + frame.columnconfigure(3, weight=1) + frame.pack(side='top', fill='x', expand=True) + # Experiment property editing below the control pane; frame per 'item', + # all in a scrolling canvas + self.expts_canvas = canvas = T.Canvas(expt_frame, borderwidth=0) + canvas.pack(side='left', fill='both', expand=True) + frame = ttk.Frame(canvas) + scrollbar = ttk.Scrollbar(expt_frame, orient='vertical', command=canvas.yview) + scrollbar.pack(side='right', fill='y') + canvas.configure(yscrollcommand=scrollbar.set) + canvas.create_window((0, 0), window=frame, anchor='nw') + frame.bind("", self.on_expts_frame_configure) + # The contents + self.expts_boxes = {} + self.make_expts_part(frame, 'description') + self.make_expts_part(frame, 'optophysiology') + self.make_stim_frame(frame) + for part in ['data_collection', 'pharmacology', 'protocol', 'slices', 'stimulus', + 'subject', 'surgery', 'virus', 'related_publications', 'notes']: + self.make_expts_part(frame, part) + # Show current experiment, if any + if self.metadata['experiments']: + experiment.set(experiment['values'][0]) + self.update_expts_tab(expt_id=experiment.get()) + # Add to tabs + parent.add(expt_frame, text='Experiments') + return expt_frame + + def on_expts_frame_configure(self, event): + """Reset the scroll region to encompass the inner frame.""" + self.expts_canvas.configure(scrollregion=self.expts_canvas.bbox("all")) + + def add_expt(self, expt_id, clone=None): + """Create a new experiment and start editing it.""" + existing_expts = self.experiment_selector['values'] or () + if expt_id in existing_expts: + messagebox.showerror(message='The experiment ID "{}" already exists'.format(expt_id)) + return + if not expt_id or not expt_id[0].isalpha(): + messagebox.showerror(message='An experiment ID must start with a letter') + return + if clone is None: + clone = self.template_expt + else: + self.record_expt() + clone = self.metadata['experiments'][clone] + self.metadata['experiments'][expt_id] = wrap_dict(clone) + self.experiment_selector['values'] = sorted(existing_expts + (expt_id,)) + self.experiment_selector.set(expt_id) + self.session_experiment_box['values'] = self.experiment_selector['values'] + self.update_expts_tab(expt_id) + + def update_expts_tab(self, expt_id): + """Show the given experiment in the GUI for editing.""" + def do_subfields(box, expt_field): + for subfield, entry in box.items(): + if isinstance(entry, collections.Mapping): + do_subfields(entry, expt_field[subfield]) + else: + entry['textvariable'] = expt_field[subfield] + if expt_id == self.experiment_shown: + return + self.record_expt() + expt = self.metadata['experiments'][expt_id] + for field, box in self.expts_boxes.items(): + if isinstance(box, T.Text): + box.delete('1.0', 'end') + if field in expt: + box.insert('1.0', expt[field].get()) + elif isinstance(box, collections.Mapping): + do_subfields(box, expt[field]) + elif isinstance(box, list): + for i, item in enumerate(box): + do_subfields(item, expt[field][i]) + self.experiment_shown = expt_id + self.clone_expt_button.state(['!disabled']) + + def record_expt(self): + """Save the currently shown experiment fields as the selected experiment. + + We only need to worry about Text fields; Entry fields are tracked by their StringVar. + Fields that are empty are omitted. + """ + expt_id = self.experiment_shown + if expt_id is None: + return + expt = self.metadata['experiments'][expt_id] + for field, box in self.expts_boxes.items(): + if isinstance(box, T.Text): + contents = box.get('1.0', 'end').strip() + if contents: + expt[field] = T.StringVar() + expt[field].set(contents) + elif field in expt: + del expt[field] + + def make_label(self, parent, name, row=0, sticky='w'): + """Make the human-friendly label for a form section.""" + name = name.capitalize().replace('_', ' ') + ':' + ttk.Label(parent, text=name).grid(row=row, column=0, sticky=sticky) + + def make_expts_part(self, parent, part_name): + """Make a component frame for the experiment editor.""" + frame = ttk.Frame(parent) + self.make_label(frame, part_name) + if isinstance(self.template_expt[part_name], collections.Mapping): + # This is actually a related group of fields + self.expts_boxes[part_name] = boxes = {} + self.make_expts_fields(frame, self.template_expt[part_name], boxes) + else: + textbox = T.Text(frame, width=100, height=5, wrap='word') + textbox.grid(row=1, column=0, sticky='nesw') + textbox.insert('1.0', self.template_expt[part_name]) + self.expts_boxes[part_name] = textbox + frame.pack(side='top', fill='x', expand=True) + + def make_expts_fields(self, frame, template, boxes): + """Create a related group of fields for an experiment section.""" + for i, field in enumerate(template): + self.make_label(frame, field, row=i + 1, sticky='ne') + if isinstance(template[field], collections.Mapping): + # Another nesting level! + boxes[field] = {} + subframe = ttk.Frame(frame) + for j, subfield in enumerate(template[field]): + self.make_label(subframe, subfield, row=j, sticky='e') + boxes[field][subfield] = ttk.Entry(subframe, width=40) + boxes[field][subfield].grid(row=j, column=1, sticky='w') + subframe.grid(row=i + 1, column=1, sticky='we') + else: + boxes[field] = ttk.Entry(frame, width=70) + boxes[field].grid(row=i + 1, column=1, sticky='w') + + def make_stim_frame(self, parent): + """Create fields to edit the stimulus details. + + TODO: At present this restricts you to the same number of stimuli as the template. + """ + frame = ttk.Frame(parent) + part_name = 'stimulus_details' + self.make_label(frame, part_name) + self.expts_boxes[part_name] = [] + for stim in self.template_expt['stimulus_details']: + boxes = {} + self.expts_boxes[part_name].append(boxes) + self.make_expts_fields(frame, stim, boxes) + frame.pack(side='top', fill='x', expand=True) + + +def run_editor(): + '''Run the metadata editor.''' + app = MetadataEditor() + app.master.title("Silver Lab NWB Metadata Editor") + app.lift() # Raise to top of window stack + app.mainloop() diff --git a/Python/silverlabnwb/nwb_file.py b/Python/silverlabnwb/nwb_file.py new file mode 100644 index 0000000..c20a315 --- /dev/null +++ b/Python/silverlabnwb/nwb_file.py @@ -0,0 +1,958 @@ + +import collections +from enum import Enum +import glob +import os +import pkg_resources +import tempfile + +import av +import h5py +from nptdms import TdmsFile +import numpy as np +import pandas as pd +import six +import tifffile + +from nwb import nwb_file +from nwb import nwb_utils + +from . import metadata + + +class Modes(Enum): + """Scanning modes supported by the AOL microscope.""" + pointing = 1 + patch = 2 + miniscan = 2 + volume = 3 + + +class NwbFile(): + """Silver Lab wrapper for the NWB data format.data + + Designed to be used as a context manager, i.e. do something like: + >>> with NwbFile(output_file_path) as nwb: + ... nwb.import_labview_folder(folder_path) + + However, there is also an explicit close() method, and this will be called + when the object is deleted. + + Once a file has been opened, two main access mechanisms are provided: + - nwb.nwb_file - the NWB API interface to the file + - nwb.hdf_file - the h5py interface to the file + + You can also access nodes within the file using dictionary-style access, e.g. + `nwb['/path/to/node']`. + """ + + SILVERLAB_NWB_VERSION = '0.1' + + def __init__(self, nwb_path, mode='r', verbose=True): + """Create an interface to an NWB file. + + :param nwb_path: the NWB file to access + :param mode: mode of file access. As for the NWB API, must be one of: + 'r' - Readonly, file must exist + 'r+' - Read/write, file must exist + 'w' - Create file, replacing if exists + 'w-' - Create file, fail if exists + 'a' - Read/write if exists, create otherwise + :param verbose: if True, print status information as processing happens + """ + self.verbose = verbose + self.nwb_file = None + self.nwb_path = nwb_path + assert mode in {'r', 'r+', 'w', 'w-', 'a'} + self.nwb_open_mode = mode + if mode in {'r', 'r+'} or (mode == 'a' and os.path.isfile(nwb_path)): + self.open_nwb_file() + + def import_labview_folder(self, folder_path): + """Import all data from a Labview export folder into this NWB file. + + This calls three helper methods to do most of the work, to support unit tests + of just parts of the import code. + + This will automatically import video data only if the video folder is adjacent to + the main labview folder, with the same name but having ' VidRec' appended. If you + use a different layout you will need to call read_video_data() separately. + + :param folder_path: the folder to import + """ + assert os.path.isdir(folder_path) + folder_name = os.path.basename(folder_path) + session_id = folder_name.split(' ')[0] # Drop the ' FunctAcq' part + self.log('Importing Labview session', session_id, 'from', folder_path) + speed_data, expt_start_time = self.create_nwb_file(folder_path, session_id) + self.add_core_metadata() + self.import_labview_data(folder_path, folder_name, speed_data, expt_start_time) + self.log('All data imported') + + @property + def hdf_file(self): + """Access the h5py interface to this NWB file.""" + assert self.nwb_file is not None + return self.nwb_file.file_pointer + + def __getitem__(self, name): + """Provide access to nodes within this file just like h5py does. + + :param name: full path (within the file) of the HDF5 node to access + """ + return self.hdf_file[name] + + def open_nwb_file(self): + """Open an existing NWB file for reading and optionally modification. + + TODO: If allowing modification then the copy_append setting defaults to True and + we can't modify it via nwb_file.open - we'd need to call the underlying routines + directly if we want to avoid copying the original file! However, this copying + behaviour does guard against data corruption, so might well be desirable. + """ + self.log("Opening file {}", self.nwb_path) + self.nwb_file = nwb_file.open( + self.nwb_path, mode=self.nwb_open_mode, core_spec='-', + verbosity='all' if self.verbose else 'none') + + def create_nwb_file(self, folder_path, session_id): + """Create a new NWB file and add general lab/session metadata. + + :param folder_path: the Labview folder to import + :param session_id: the unique session ID for this experiment + :returns: (speed_data, expt_start_time) for passing to import_labview_data + """ + def rel(file_name): + """Return the path of a file name relative to the Labview folder.""" + return os.path.join(folder_path, file_name) + # Check we're allowed to create a new file + if not (self.nwb_open_mode == 'w' or (self.nwb_open_mode in {'a', 'w-'} and + not os.path.isfile(self.nwb_path))): + raise ValueError('Not allowed to create/overwrite {} in mode {}'.format( + self.nwb_path, self.nwb_open_mode)) + # Figure out the metadata required when creating a new NWB file + self.read_user_config() + header_fields = self.parse_experiment_header_ini(rel('Experiment Header.ini')) + speed_data, expt_start_time = self.read_speed_data(rel('Speed_Data/Speed data 001.txt')) + # Create the NWB file + extensions = ["e-labview.py", "e-pixeltimes.py"] + for i, ext in enumerate(extensions): + extensions[i] = pkg_resources.resource_filename(__name__, ext) + nwb_settings = { + 'file_name': self.nwb_path, + 'mode': self.nwb_open_mode, + 'start_time': expt_start_time.isoformat(), + 'identifier': nwb_utils.create_identifier(session_id), + 'description': self.session_description, + 'extensions': extensions + } + self.nwb_file = nwb_file.open(**nwb_settings) + self.add_general_info('session_id', session_id) + self.add_labview_header(header_fields) + # For potential future backwards compatibility, store the 'version' of this API + # that created the file. + self.nwb_file.set_custom_dataset('/silverlab_api_version', self.SILVERLAB_NWB_VERSION) + return speed_data, expt_start_time + + def add_core_metadata(self): + """Add core metadata from the YAML config file to the NWB file. + + This fills in many of the fields in /general. + """ + self.add_general_info('experimenter', self.user['name']) # TODO: Add ORCID etc. + self.add_general_info('experiment_description', self.experiment['description']) + self.add_general_info('institution', 'University College London') + self.add_general_info('lab', 'Silver Lab (http://silverlab.org)') + self.add_devices_info() + for field in ['data_collection', 'pharmacology', 'protocol', 'slices', 'stimulus', + 'subject', 'surgery', 'virus', 'related_publications', 'notes']: + if field in self.experiment: + value = self.experiment[field] + if isinstance(value, collections.Mapping): + for subfield in value: + self.nwb_file.set_dataset( + subfield, value[subfield], path='/general/' + field) + else: + self.add_general_info(field, value) + + def import_labview_data(self, folder_path, folder_name, speed_data, expt_start_time): + """Import the bulk of the Labview data to NWB. + + :param folder_path: the Labview folder to import + :param folder_name: the name of the Labview folder + :param speed_data: mouse speed data + :param expt_start_time: when the experiment started + """ + def rel(file_name): + """Return the path of a file name relative to the Labview folder.""" + return os.path.join(folder_path, file_name) + self.add_speed_data(speed_data, expt_start_time) + self.determine_trial_times() + self.add_stimulus() + self.read_cycle_relative_times(rel('Single cycle relative times.txt')) + self.read_zplane(rel('Zplane_Pockels_Values.dat')) + self.read_zstack(rel('Zstack Images')) + self.add_rois(rel('ROI.dat')) + self.read_functional_data(rel('Functional imaging TDMS data files')) + video_folder = os.path.join(os.path.dirname(folder_path), folder_name + ' VidRec') + if os.path.isdir(video_folder): + self.read_video_data(video_folder) + + def __enter__(self): + """Return this object itself as a context manager.""" + return self + + def __exit__(self, type, value, traceback): + """Close the NWB file when the context is exited.""" + self.close() + + def __del__(self): + """Close the NWB file when this object is destroyed.""" + self.close() + + def close(self): + """Close our NWB file.""" + if self.nwb_file: + self.nwb_file.close() + self.nwb_file = None + + def log(self, msg_template, *args, **kwargs): + """Log status information if in verbose mode. + + :param msg_template: message to log, optionally with {} placeholders + :param args: positional arguments to pass to msg_template.format + :param kwargs: keyword arguments to pass to msg_template.format + """ + if self.verbose: + import time + timestamp = time.strftime('%H:%M:%S ') + print(timestamp + msg_template.format(*args, **kwargs)) + + def read_user_config(self): + """Read the user configuration YAML files. + + We first read the default configuration supplied with this package. + Then we look in the user_config_dir (as defined by appdirs) for any + machine- & user-specific configuration settings, which override the + defaults. + """ + if os.path.isfile(metadata.user_conf_path): + self.log('Reading user metadata from {}', metadata.user_conf_path) + self.user_metadata = metadata.read_user_config() + return self.user_metadata + + def add_general_info(self, label, value): + general = self.nwb_file.get_node('/general') + general.set_dataset(label, value) + + def add_devices_info(self): + """Populate /general/devices with information about the rig. + + The names and descriptions of devices are taken from the metadata config file. + """ + general = self.nwb_file.get_node('/general') + devices = general.make_group('devices') + for device_name, desc in self.user_metadata['devices'].items(): + if not device_name.endswith('Cam'): + devices.set_dataset(id='', name=device_name, value=desc) + + def parse_experiment_header_ini(self, filename): + """Read the LabView .ini file and store fields for later processing. + + The information will be stored in self.labview_header as a nested dict + for easy access of key fields later. Those fields that are numbers will be + stored as floating point values; everything else will be strings. Values given + in double quotes will have the quotes removed. + + This method also uses the header info to set self.mode, which stores the + type of imaging being performed, and figure out which user's metadata to load. + + :param filename: path to the Labview header + :returns: the raw Labview fields as a list of lists of strings + """ + self.log('Parsing Labview header {}', filename) + ini = open(filename, 'r') + fields = [] + section = '' + self.labview_header = header = {} + for line in ini: + line = line.strip() + if len(line) > 0: + if line.startswith('['): + section = line[1:-1] + header[section] = {} + elif '=' in line: + words = line.split('=') + key, value = words[0].strip(), words[1].strip() + fields.append([section, key, value]) + try: + value = float(value) + except ValueError: + pass + if isinstance(value, str) and value[0] == value[-1] == '"': + value = value[1:-1] + header[section][key] = value + # Use the header to determine what kind of imaging is being performed. + if header['GLOBAL PARAMETERS']['number of poi'] > 0: + self.mode = Modes.pointing + elif header['GLOBAL PARAMETERS']['number of miniscans'] > 0: + self.mode = Modes.miniscan + else: + raise ValueError('Unsupported imaging type: numbers of poi and miniscans are zero.') + # Use the user specified in the header to select default session etc. metadata + user = header['LOGIN']['User'] + if user not in self.user_metadata['sessions']: + if 'last_session' in self.user_metadata: + self.log("Labview user '{}' not found in metadata;" + " using last session by '{}' instead.", + user, self.user_metadata['last_session']) + user = self.user_metadata['last_session'] + else: + raise ValueError("No session information found for user '{}' - please edit the" + " metadata.yaml file to include their details.".format(user)) + if user not in self.user_metadata['people']: + raise ValueError("No information found for user '{}' - please edit the metadata.yaml" + " file to include their details.".format(user)) + self.user = self.user_metadata['people'][user] + expt = self.user_metadata['sessions'][user]['experiment'] + if expt not in self.user_metadata['experiments']: + raise ValueError("Experiment '{}' not found in metadata.yaml.".format(expt)) + self.experiment = self.user_metadata['experiments'][expt] + self.session_description = self.user_metadata['sessions'][user]['description'] + return fields + + def add_labview_header(self, fields): + """Add the Labview header fields verbatim to the NWB file. + + We use a fixed length ASCII string array, null-padded to the length of the longest + string, at /general/labview_header. This is defined by one of our NWB extensions. + It is likely to be the most portable representation for this kind of data. + + :param fields: the raw Labview headers as a list of 3-element lists of strings + """ + general = self.nwb_file.get_node('/general') + general.set_dataset("labview_header", fields) + + def add_time_series_data(self, label, data, times, ts_attrs={}, data_attrs={}, + kind='TimeSeries'): + """Create a basic acquisition timeseries and add to the NWB file. + + :param label: Name of the group within /acquisition/timeseries. + :param data: The data array. + :param times: The timestamps array. + :param ts_attrs: Any attributes for the timeseries group itself. + :param data_attrs: Any attributes for the data array. + :param kind: What type of timeseries to create, e.g. TwoPhotonSeries. + :returns: The new timeseries group. + """ + nts = self.nwb_file.make_group( + "<{}>".format(kind), label, + path="/acquisition/timeseries", + attrs=ts_attrs) + nts.set_dataset("data", data, attrs=data_attrs) + nts.set_dataset("timestamps", times) + return nts + + def read_speed_data(self, file_name): + """Read acquired speed data from the raw data file. + + The columns in the file are: + - Date as MM/DD/YYYY + - Time at HH:MM:SS.UUUUUU + - Microseconds since start of trial + - Speed in rpm (1 rpm = 50 cm/s), always negative! + - Unsure; seems to be unused + + The date & time columns give the global experiment time. The third column is used + to identify where trials begin & end. It will reset both at the end of one trial, + then again at the start of the next, giving a short period of 'junk' data inbetween. + + :param file_name: path to the file + :returns: (speed_data, initial_time), where speed_data is the file contents as a + Pandas data table, and initial_time is the experiment start time, which sets the + session_start_time for the NWB file. + """ + self.log('Loading speed data from {}', file_name) + assert os.path.isfile(file_name) + speed_data = pd.read_table(file_name, header=None, usecols=[0, 1, 2, 3], index_col=0, + names=('Date', 'Time', 'Trial time', 'Speed'), + dtype={'Trial time': int, 'Speed': float}, + parse_dates=[[0, 1]], # Combine first two cols + dayfirst=True, infer_datetime_format=True, + memory_map=True) + initial_offset = pd.Timedelta(microseconds=speed_data['Trial time'][0]) + initial_time = speed_data.index[0] - initial_offset + return speed_data, initial_time + + def add_speed_data(self, speed_data, initial_time): + """Add acquired speed data the the NWB file. + + Creates the /acquisition/timeseries/speed_data and + /acquisition/timeseries/trial_times groups. + + :param speed_data: raw speed data loaded from file by read_speed_data(), as a + Pandas data table + :param initial_time: experiment start time, from read_speed_data() + """ + rel_times = (speed_data.index - initial_time).total_seconds().values + ts_attrs = {'source': '/general/devices/mouse_wheel_device', + 'description': 'Raw mouse speed data.', + 'comments': 'Speed is in rpm, with conversion factor to cm/s specified.'} + speed_attrs = {'unit': 'cm/s', 'conversion': 50.0 / 60.0, 'resolution': 0.001 * 50 / 60} + time_attrs = {'unit': 'second', 'conversion': 1e6, 'resolution': 1e-6} + self.add_time_series_data('speed_data', speed_data['Speed'].values, rel_times, + ts_attrs=ts_attrs, data_attrs=speed_attrs) + ts_attrs['description'] = 'Per-trial times for mouse speed data.' + self.add_time_series_data('trial_times', speed_data['Trial time'].values, rel_times, + ts_attrs=ts_attrs, data_attrs=time_attrs) + + def get_data(self, timeseries, dataset='data'): + """Get the data for a timeseries as a numpy array. + + :param timeseries: either an h5gate.Group or path to the timeseries + :param dataset: alternative name for the dataset if not 'data' + """ + if isinstance(timeseries, nwb_file.g.Group): + timeseries = timeseries.full_path + data_path = timeseries + '/' + dataset + return self[data_path].value + + def get_times(self, timeseries): + """Get the timestamps for a timeseries as a numpy array. + + Will handle both the case where there is a 'timestamps' dataset, and the case where + these must be determined from 'starting_time' and rate. + + :param timeseries: either an h5gate.Group or path to the timeseries + """ + if isinstance(timeseries, str): + timeseries = self.nwb_file.get_node(timeseries) + ts = self[timeseries.full_path] + if 'timestamps' in ts: + t = ts['timestamps'].value + else: + n = ts['num_samples'].value + t0 = ts['starting_time'].value + rate = ts['starting_time'].attrs['rate'] + t = t0 + np.arange(n) / rate + return t + + def determine_trial_times(self): + """Use the acquired speed data to determine the start & end times for each trial. + + Each trial will be defined as an epoch within the NWB file, and the relevant portions + of the speed data linked to these. The epochs will be named 'trial_001' etc. + + Trials are identified by the resets in the 'trial_times' timeseries. This stores + the relative times for each speed reading within a single trial. Hence when it + resets (i.e. one entry is less than the one before) this marks the end of a trial. + There is a short interval between trials which still has speed data recorded, so it's + the second reset which marks the start of the next trial. + """ + self.log('Calculating trial times from speed data') + trial_times_ts = self.nwb_file.get_node('/acquisition/timeseries/trial_times') + speed_data_ts = self.nwb_file.get_node('/acquisition/timeseries/speed_data') + trial_times = self.get_data(trial_times_ts) + # Prepend -1 so we pick up the first trial start + # Append -1 in case there isn't a reset recorded at the end of the last trial + deltas = np.ediff1d(trial_times, to_begin=-1, to_end=-1) + # Find resets and pair these up to mark start & end points + reset_idxs = (deltas < 0).nonzero()[0].copy() + assert reset_idxs.ndim == 1 + num_trials = reset_idxs.size // 2 # Drop the extra reset added at the end if + reset_idxs.resize((num_trials, 2)) # it's not needed + reset_idxs[:, 1] -= 1 # Select end of previous segment, not start of next + # Index the timestamps to find the actual start & end times of each trial. The start + # time is calculated using the offset value in the first reading within the trial. + rel_times = self.get_times(trial_times_ts) + epoch_times = rel_times[reset_idxs] + epoch_times[:, 0] -= trial_times[reset_idxs[:, 0]] * 1e-6 + # Create the epochs in the NWB file + # Note that we cannot use nwb_utils.add_epoch_ts since it would add the last previous + # junk speed reading to the start of the next trial, since they have exactly the same + # timestamp. Since we already know the start index and count of relevant entries in + # the timeseries, however, it's easy to set up the references directly. + expected_counts = np.diff(reset_idxs) + 1 + for i, (start_time, stop_time) in enumerate(epoch_times): + trial = 'trial_{:04d}'.format(i + 1) + epoch = nwb_utils.create_epoch(self.nwb_file, trial, start_time, stop_time) + ts_ref_in_epoch = epoch.make_group('', 'speed_data') + ts_ref_in_epoch.set_dataset('idx_start', int(reset_idxs[i, 0])) + ts_ref_in_epoch.set_dataset('count', int(expected_counts[i])) + ts_ref_in_epoch.make_group('timeseries', speed_data_ts) + + def add_stimulus(self): + '''Add information about the stimulus presented. + + This is taken from the metadata.yaml at present, since Labview does not record this + information. + + This adds a TimeSeries group to /stimulus/presentation containing the timings of air + puffs. At present the stimulus is always presented at the same time within each trial, + so the only argument is the delay from the start of the trial until the puff. The 'data' + for this time series is simply the text 'puff' at each occasion. + ''' + for stim in self.experiment['stimulus_details']: + ts = self.nwb_file.make_group( + '', stim['name'], path='/stimulus/presentation', + attrs={'source': stim['source'], + 'description': stim['description'], + 'comments': stim['comments']}) + trials = self['/epochs'] + puffs = ['puff'] * len(trials) + ts.set_dataset('data', puffs, attrs={'unit': 'n/a', 'conversion': float('nan'), + 'resolution': float('nan')}) + times = np.zeros((len(puffs),), dtype=np.float64) + for i, trial in enumerate(trials.values()): + times[i] = trial['start_time'].value + stim['trial_time_offset'] + ts.set_dataset('timestamps', times) + + def read_cycle_relative_times(self, file_path): + """Read the 'Single cycle relative times.txt' file and store the values in memory. + + Note that while the file has times in microseconds, we convert to seconds for consistency + with other timestamps in NWB. + """ + assert os.path.isfile(file_path) + self.cycle_relative_times = pd.read_table(file_path, names=('RelativeTime', 'CycleTime'), + dtype=np.float64) / 1e6 + + def read_functional_data(self, folder_path): + """Import functional data from Labview TDMS files. + + The folder contains files named like like "NNN.tdms", where NNN gives the trial number. + These files are thus per-trial, but a TimeSeries needs to contain all trials. We link to + portions corresponding to single trials from epochs. + + Each file contains data for 2 channels in the group 'Functional Imaging Data', where + 'Channel 0 Data' is Red and 'Channel 1 Data' is Green. Each channel contains data for all + pixels in all ROIs for all time within that trial, as a single 1d array. Within this array, + we have data first for all pixels in the first ROI at time 0, then the second ROI at time + 0, and so on through all ROIs, before moving to data from the next cycle. For 2d ROIs, it + scans first over the X dimension then over Y. + + While it might seem that this data is well suited to become RoiResponseSeries within + /processing/Acquired_ROIs/Fluoresence, that time series type assumes a single value per + ROI per time, which doesn't support storing raw data from multi-pixel ROIs. Instead, + the data will be stored within /acquisition/timeseries, in TwoPhotonSeries named like + ROI_NNN_Green, where NNN is the global (not per-imaging-plane) ROI number. + + We define the ROIs within their imaging planes first, storing zeros for the data, then + read each TDMS file to fill in real recordings. The channel data will have its dimensions + permuted to match the NWB (t, z, y, x) arrangement, and be stored in the appropriate + segment of the timeseries. At present all ROIs are 2d (or less, but can be represented as + such with length 1 dimensions), however this structure allows for extension to 3d in the + future. + + The single cycle time (self.cycle_relative_times['CycleTime'][0]) gives you the difference + in acquisition time between successive lines in a file. Time starts at the beginning of + the trial (epoch in NWB speak). This is the time to record in the timestamps field. Note + that even though these are evenly spaced we can't use starting_time and rate, since this + would not account for time between trials. + """ + self.log('Loading functional data from {}', folder_path) + assert os.path.isdir(folder_path) + # Figure out timestamps, measured in seconds + epoch_names = self['/epochs'].keys() + trials = [int(s[6:]) for s in epoch_names] + cycles_per_trial = int(self.labview_header['GLOBAL PARAMETERS']['number of cycles']) + num_times = cycles_per_trial * len(epoch_names) + cycle_time = self.cycle_relative_times['CycleTime'][0] + single_trial_times = np.arange(cycles_per_trial) * cycle_time + times = np.zeros((num_times,), dtype=float) + for i, epoch_name in enumerate(epoch_names): + trial_start = self['/epochs/' + epoch_name + '/start_time'] + times[i * cycles_per_trial: + (i + 1) * cycles_per_trial] = single_trial_times + trial_start + opto = self.nwb_file.make_group('optophysiology', abort=False) + opto.set_custom_dataset('cycle_time', cycle_time) + # Prepare attributes for timeseries groups and datasets (common to all instances) + data_attrs = {'unit': 'intensity', 'conversion': 1.0, 'resolution': float('NaN')} + ts_desc_template = 'Fluorescence data acquired from the {channel} channel in {roi_name}.' + ts_attrs = {'source': '/general/devices/AOL_microscope', + 'comments': 'The AOL microscope can acquire just the pixels comprising defined' + ' ROIs. This timeseries records those pixels over time for a' + ' single ROI & channel.'} + gains = {'Red': self.labview_header['GLOBAL PARAMETERS']['pmt 1'], + 'Green': self.labview_header['GLOBAL PARAMETERS']['pmt 2']} + # Iterate over ROIs, which are nested inside each imaging plane section + all_rois = {} + seg_iface = self['/processing/Acquired_ROIs/ImageSegmentation'] + for plane_name, plane in seg_iface.items(): + self.log(' Defining ROIs for plane {}', plane_name) + # Note that we can't read plane['roi_list'] to determine roi_names as the API only + # creates it when we close the file. + roi_names = [n for n in plane.keys() if n.startswith('ROI_')] + for roi_name in roi_names: + roi_num = int(roi_name[4:]) + roi = plane[roi_name] + all_rois[roi_num] = {} + for ch, channel in {'A': 'Red', 'B': 'Green'}.items(): + # Set zero data for now; we'll read the real data later + # TODO: The TDMS uses 64 bit floats; we may not really need that precision! + # The exported data seems to be rounded to unsigned ints. Issue #15. + roi_dimensions = roi['dimension'].value + data_shape = np.concatenate((roi_dimensions, [num_times]))[::-1] + data = np.zeros(data_shape, dtype=np.float64) + # Create the timeseries object and fill in standard metadata + ts_name = 'ROI_{:03d}_{}'.format(roi_num, channel) + ts_attrs['description'] = ts_desc_template.format(channel=channel.lower(), + roi_name=roi_name) + ts = self.add_time_series_data(ts_name, data=data, times=times, + kind='TwoPhotonSeries', + ts_attrs=ts_attrs, data_attrs=data_attrs) + all_rois[roi_num][channel] = self[ts.full_path + '/data'] + ts.set_dataset('dimension', roi_dimensions) + ts.set_dataset('format', 'raw') + ts.set_dataset('bits_per_pixel', 64) + pixel_size_in_m = (self.labview_header['GLOBAL PARAMETERS']['field of view'] / + 1e6 / + int(self.labview_header['GLOBAL PARAMETERS']['frame size'])) + ts.set_dataset('field_of_view', roi_dimensions * pixel_size_in_m) + ts.set_dataset('imaging_plane', plane_name) + ts.set_custom_dataset('roi_name', roi_name) + ts.set_dataset('pmt_gain', gains[channel]) + ts.set_dataset('scan_line_rate', 1 / cycle_time) + ts.set_custom_dataset('channel', channel) + # Save the time offset(s) for this ROI, as a link + ts.set_dataset('pixel_time_offsets', 'link:' + roi['pixel_time_offsets'].name) + # Link to these data within the epochs + for trial, epoch_name in enumerate(epoch_names): + epoch = self.nwb_file.get_node('/epochs/' + epoch_name) + series_ref_in_epoch = epoch.make_group('', ts_name) + series_ref_in_epoch.set_dataset('idx_start', trial * cycles_per_trial) + series_ref_in_epoch.set_dataset('count', cycles_per_trial) + series_ref_in_epoch.make_group('timeseries', ts) + # Iterate over trials, reading data from the TDMS file for each + num_rois = len(all_rois) + for trial_index, trial in enumerate(trials): + self.log(' Reading TDMS {}', trial_index + 1) + file_path = os.path.join(folder_path, '{:03d}.tdms'.format(trial_index + 1)) + tdms_file = TdmsFile(file_path, + memmap_dir=tempfile.gettempdir()) + time_segment = slice(trial_index * cycles_per_trial, + (trial_index + 1) * cycles_per_trial) + for ch, channel in {'0': 'Red', '1': 'Green'}.items(): + # Reshape the TDMS data into an nd array + # TODO: Consider precision: the round() here is to match the exported data... + ch_data = np.round(tdms_file.channel_data('Functional Imaging Data', + 'Channel {} Data'.format(ch))) + ch_data_shape = np.concatenate((roi_dimensions, [num_rois, cycles_per_trial]))[::-1] + ch_data = ch_data.reshape(ch_data_shape) + # Copy each ROI's data into the NWB + for roi_num, roi_channels in all_rois.items(): + roi_channels[channel][time_segment, ...] = ch_data[:, roi_num - 1, ...] + + def add_imaging_plane(self, name, manifold, description, + green=True, red=True): + """Add a new imaging plane definition to /general/optophysiology. + + :param name: A name for the NWB group representing this imaging plane. + :param manifold: 3d array giving the x,y,z coordinates in microns for each pixel + in the plane. If the plane is really a line, this can be an Nx1x3 array. + :param description: Brief text description of the plane, e.g. "Reference Z stack", + "Pointing mode acquisition sequence". + :param green: Whether to include the green channel. + :param red: Whether to include the red channel. + :returns: The NWB group defining the imaging plane. + """ + opto = self.nwb_file.make_group('optophysiology', abort=False) + plane_defn = opto.make_group('', name=name) + plane_defn.set_dataset('description', description) + plane_defn.set_dataset('device', 'AOL_microscope') + opto_metadata = self.experiment['optophysiology'] + plane_defn.set_dataset('excitation_lambda', opto_metadata['excitation_lambda']) + plane_defn.set_dataset('indicator', opto_metadata['calcium_indicator']) + plane_defn.set_dataset('location', opto_metadata['location']) + cycle_time = self.cycle_relative_times['CycleTime'][0] # seconds + cycle_rate = 1 / cycle_time # Hz + plane_defn.set_dataset( + 'imaging_rate', '{:.16f}Hz (cycle time = {:.16f} microseconds)'.format( + cycle_rate, cycle_time * 1e6)) + plane_defn.set_dataset('manifold', manifold, + attrs={'unit': 'metre', 'conversion': 1e6}) + plane_defn.set_dataset('reference_frame', 'TODO: In lab book (partly?)') + if green: + green_channel = plane_defn.make_group('', name='green') + green_channel.set_dataset('description', + 'Green channel, typically used for active signal.') + green_channel.set_dataset('emission_lambda', opto_metadata['emission_lambda']['green']) + if red: + red_channel = plane_defn.make_group('', name='red') + red_channel.set_dataset('description', 'Red channel, typically used for reference.') + red_channel.set_dataset('emission_lambda', opto_metadata['emission_lambda']['red']) + return plane_defn + + def read_zplane(self, zplane_path): + """Determine coordinates of reference image stack from Zplane_Pockels_Values.dat. + + This also uses information from the LabView .ini file to define image planes etc + in /general/optophysiology. + + The .dat file has 4 columns: Z offset from focal plane (micrometres), normalised Z, + 'Pockels' i.e. laser power in %, and z offset for drive motors. We save this raw + array as the extension dataset /general/optophysiology/zplane_pockels. + + Also sets up self.zplanes as a map from Z coordinate (in microns) to imaging plane name. + """ + self.log('Loading imaging plane information from {}', zplane_path) + assert os.path.isfile(zplane_path) + zplane_data = pd.read_table( + zplane_path, skiprows=2, skip_blank_lines=True, + names=('z', 'z_norm', 'laser_power', 'z_motor'), header=0, + index_col=False) + num_pixels = int(self.labview_header['GLOBAL PARAMETERS']['frame size']) + plane_width_in_microns = self.labview_header['GLOBAL PARAMETERS']['field of view'] + manifold = np.zeros((num_pixels, num_pixels, 3)) + x = np.linspace(0, plane_width_in_microns, num_pixels) + y = np.linspace(0, plane_width_in_microns, num_pixels) + xv, yv = np.meshgrid(x, y) + manifold[:, :, 0] = xv + manifold[:, :, 1] = yv + self.zplanes = {} + for plane in zplane_data.itertuples(): + manifold[:, :, 2] = plane.z + name = 'Zstack{:04d}'.format(plane.Index + 1) + self.zplanes[plane.z] = name + self.add_imaging_plane( + name=name, + description='Reference Z stack', + manifold=manifold) + self.nwb_file.set_custom_dataset( + '/general/optophysiology/zplane_pockels', + zplane_data.values, + attrs={'columns': zplane_data.columns.tolist()}) + self.nwb_file.set_custom_dataset( + '/general/optophysiology/frame_size', [num_pixels, num_pixels]) + + def read_zstack(self, zstack_folder): + """Add the reference Z stack images into /acquisition. + + The folder holds one .tif file per imaging plane per channel, with the planes ordered + as in the Zplane_Pockels_Values.dat file (see read_zplane) and hence the order matches + the ZstackNNNN planes added there. The file names are like GreenChannel_0001.tif. + + We create a single-image TwoPhotonSeries for each plane for each channel in + /acquisition/timeseries/Zstack__. + + Also fills in self.zstack as a mapping from [plane_name][channel_name] to node path. + """ + self.log('Loading reference Z stack from {}', zstack_folder) + assert os.path.isdir(zstack_folder) + opto = self['/general/optophysiology'] + gains = {'Red': self.labview_header['GLOBAL PARAMETERS']['pmt 1'], + 'Green': self.labview_header['GLOBAL PARAMETERS']['pmt 2']} + cycle_time = self.cycle_relative_times['CycleTime'][0] # seconds + cycle_rate = 1 / cycle_time # Hz + self.zstack = {} + for plane_name in (n for n in opto.keys() if n.startswith('Zstack')): + # plane_defn = opto[plane_name] + self.zstack[plane_name] = {} + for channel in ('Green', 'Red'): + plane_index = plane_name[6:] + group_name = 'Zstack_{}_{}'.format(channel, plane_index) + file_path = os.path.join(zstack_folder, + channel + 'Channel_' + plane_index + '.tif') + if not os.path.isfile(file_path): + print('Expected Zstack file "{}" missing; skipping.'.format(file_path)) + continue + img = tifffile.imread(file_path) + # Save img to NWB + ts_attrs = {'description': 'Initial reference Z stack plane', + 'comments': 'Contains single slice from {} channel'.format( + channel.lower()), + 'source': '/general/devices/AOL_microscope'} + data_attrs = {'unit': 'intensity', 'conversion': 1.0, + 'resolution': float('NaN')} + ts = self.add_time_series_data(group_name, data=img, times=np.array([0.0]), + kind='TwoPhotonSeries', + ts_attrs=ts_attrs, data_attrs=data_attrs) + self.zstack[plane_name][channel] = ts.full_path + num_pixels = int(self.labview_header['GLOBAL PARAMETERS']['frame size']) + width_in_metres = self.labview_header['GLOBAL PARAMETERS']['field of view'] / 1e6 + ts.set_dataset('dimension', [num_pixels, num_pixels]) + ts.set_dataset('format', 'tiff') + ts.set_dataset('bits_per_pixel', 16) + ts.set_dataset('field_of_view', [width_in_metres, width_in_metres]) + ts.set_dataset('imaging_plane', plane_name) + ts.set_dataset('pmt_gain', gains[channel]) + ts.set_dataset('scan_line_rate', cycle_rate) + ts.set_custom_dataset('channel', channel) + + def add_rois(self, roi_path): + """Add the locations of ROIs as an ImageSegmentation module. + + We read a ROI.dat file to determine ROI locations. This has many tab-separated columns: + ROI index; ROI ID; ROI Time (ns); Pixels in ROI; + X start; Y start; Z start; X stop; Y stop; Z stop; + Angle (deg); Composite ID; Number of lines; Frame Size; Zoom; + Laser Power (%); ROI group ID. + + Each ROI must lie within one of the Z planes in the reference Z stack. We therefore can + represent it as a rectangle (size 1x1 for pointing mode) within that plane. The relevant + slice slice from the Z stack is used as the reference image. We group the ROIs by Z + coordinate, since each imaging plane should only be listed once in the ImageSegmentation + module; within a given plane, the original relative ordering of ROIs is maintained. + + TODO: Consider adding an array dataset of object references to the ROI definitions - see + http://docs.h5py.org/en/latest/refs.html for details of how to do this. Would enable quick + access to all ROIs (in the defined order) without having to iterate over imaging planes + then sort. It's less of an issue with the timeseries ROI data, since that's in groups + organised by ROI number and channel name, so we can iterate there. Issue #16. + """ + self.log('Loading ROI locations from {}', roi_path) + assert os.path.isfile(roi_path) + roi_data = pd.read_table( + roi_path, header=0, index_col=False, dtype=np.float16, memory_map=True) + original_names = roi_data.columns.tolist() + roi_data.rename( + columns={'ROI index': 'roi_index', 'Pixels in ROI': 'num_pixels', + 'X start': 'x_start', 'Y start': 'y_start', 'Z start': 'z_start', + 'X stop': 'x_stop', 'Y stop': 'y_stop', 'Z stop': 'z_stop', + 'Laser Power (%)': 'laser_power'}, + inplace=True) + module = self.nwb_file.make_group( + '', 'Acquired_ROIs', + attrs={'description': 'ROI locations and acquired fluorescence readings made directly' + ' by the AOL microscope.'}) + module.set_custom_dataset('roi_spec', roi_data.values) + module.get_node('roi_spec').set_attr('columns', original_names, custom=True) + # Now we've stored the raw data (which needed to be single dtype) convert some cols to int + roi_data = roi_data.astype( + {'x_start': np.uint16, 'x_stop': np.uint16, 'y_start': np.uint16, 'y_stop': np.uint16, + 'num_pixels': int}) + seg_iface = module.make_group('ImageSegmentation', + attrs={'source': '/general/devices/AOL_microscope'}) + # Define the properties of the imaging plane itself, if not a Z plane + opto = self.nwb_file.make_group('optophysiology', abort=False) + opto.set_custom_dataset('imaging_mode', self.mode.name) + if self.mode is Modes.pointing: + # Sanity check that each ROI is a single pixel + assert np.all(roi_data.num_pixels == 1) + # Figure out which plane each ROI is in + assert (roi_data['z_start'] == roi_data['z_stop']).all() # Planes are flat in Z + grouped = roi_data.groupby('z_start', sort=False) + # Iterate over planes and define ROIs + for plane_name, roi_group in grouped: + plane_name = self.zplanes[plane_name] + plane = seg_iface.make_group('', name=plane_name) + plane.set_dataset('description', opto.get_node(plane_name + '/description')) + plane.set_dataset('imaging_plane_name', plane_name) + ref_imgs = plane.make_group('reference_images') + # Add a link to the Zstack image acquired for this plane as a reference image. + ref_imgs.make_group('', name='Zstack_image', + link='link:' + self.zstack[plane_name]['Red']) + for row in roi_group.itertuples(): + roi_name = 'ROI_{:03d}'.format(int(row.roi_index)) + # The ROI mask only gives x & y coordinates - z is defined by the imaging plane. + # The coordinates are also relative to the imaging plane, not absolute. However, our + # plane coordinates run from 0 to frame_size, so that's easy to compute. + pixels = np.zeros((row.num_pixels, 2), dtype=np.uint16) + weights = np.ones((pixels.shape[0],), dtype=float) + ref_width = ref_height = int( + self.labview_header['GLOBAL PARAMETERS']['frame size']) + # Pixels are located contiguously from start to stop coordinates. + num_x_pixels = row.x_stop - row.x_start + num_y_pixels = row.y_stop - row.y_start + if self.mode is Modes.pointing: + assert row.num_pixels == 1, 'Unexpectedly large ROI in pointing mode' + num_x_pixels = num_y_pixels = 1 + assert row.num_pixels == num_x_pixels * num_y_pixels, ( + 'ROI is not rectangular: {} != {} * {}'.format( + row.num_pixels, num_x_pixels, num_y_pixels)) + dimensions = np.array([num_x_pixels, num_y_pixels], dtype=np.int32) + for i in range(row.num_pixels): + pixels[i, 0] = row.x_start + (i % num_x_pixels) + pixels[i, 1] = row.y_start + (i // num_x_pixels) + nwb_utils.add_roi_mask_pixels( + seg_iface, plane_name, name=roi_name, desc=roi_name, + pixel_list=pixels, weights=weights, width=ref_width, height=ref_height) + # Record the time offset(s) for this ROI + roi = plane.get_node(roi_name) + time_offsets = self.cycle_relative_times['RelativeTime'] + if self.mode is Modes.pointing: + roi.set_dataset('pixel_time_offsets', [time_offsets[row.Index]]) + else: + # The relative time field records the start time for each row, not each pixel. + # We need to compute pixel times by adding on dwell time per pixel. + num_miniscans = self.labview_header['GLOBAL PARAMETERS']['number of miniscans'] + assert len(time_offsets) == num_miniscans + assert num_y_pixels == num_miniscans / len(roi_data) + dwell_time = self.labview_header['GLOBAL PARAMETERS']['dwelltime (us)'] / 1e6 + row_increments = np.arange(num_x_pixels) * dwell_time + start_index = row.Index * num_y_pixels + row_offsets = time_offsets[start_index:start_index + num_y_pixels].values + # Numpy's broadcasting lets us turn the 1d arrays into a 2d combined value + pixel_offsets = row_offsets[:, np.newaxis] + row_increments + roi.set_dataset('pixel_time_offsets', pixel_offsets) + # Record the ROI dimensions for ease of lookup when adding functional data + roi.set_custom_dataset('dimension', dimensions) + + def read_video_data(self, folder_path): + """Link to video data stored in the given folder. + + :param folder_path: folder containing videos of the experiment. + + Multiple video angles are supported. This method looks for files named like + 'Cam-relative times.txt' in the folder, each of which contains timing data for a + single video timeseries. These files contain two tab-separated columns, the first being + frame numbers, and the second time offsets from the start of the experiment in + milliseconds. + + The video data itself is stored in .avi files, potentially more than one per camera, + named like 'Cam-.avi', where the file number starts at 1. + + This method adds an ImageSeries in /acquisition/timeseries for each camera, linking to + the existing .avi files with relative paths. The timeseries are named 'Cam'. + """ + self.log('Loading video data from {}', folder_path) + assert os.path.isdir(folder_path) + nwb_dir = os.path.dirname(os.path.realpath(self.nwb_file.file_name)) + timing_suffix = '-relative times.txt' + timing_files = glob.glob(os.path.join(folder_path, '*' + timing_suffix)) + for timing_file_path in timing_files: + cam_name = os.path.basename(timing_file_path)[:-len(timing_suffix)] + self.log('Camera: {}', cam_name) + frame_rel_times = pd.read_table(timing_file_path, names=('Frame', 'RelTime')) + frame_rel_times['RelTime'] *= 1e-3 # Convert to seconds + # Determine properties of each .avi file + avi_files = glob.glob(os.path.join(folder_path, cam_name + '-*.avi')) + num_frames = np.zeros((len(avi_files),), dtype=np.int64) + video_file_paths = [''] * len(avi_files) + for avi_file in avi_files: + file_name = os.path.basename(avi_file) + self.log('Video: {}', file_name) + index = int(file_name[len(cam_name) + 1:-4]) - 1 + avi_file = os.path.realpath(avi_file) + try: + video_file_paths[index] = os.path.relpath(avi_file, nwb_dir) + except ValueError: + # Particularly on Windows, it's sometimes impossible to construct + # a relative path, so fall back to absolute + video_file_paths[index] = avi_file + container = av.open(avi_file) + vid = container.streams.video[0] + num_frames[index] = vid.frames + if index == 0: + vid_rate = vid.rate + vid_dimensions = [vid.width, vid.height] + bits_per_pixel = vid.format.components[0].bits + del container, vid + starting_frames = np.roll(np.cumsum(num_frames), 1) + starting_frames[0] = 0 + # Add camera to list of devices + self.nwb_file.set_dataset( + '', name=cam_name, path='/general/devices', + value=self.user_metadata['devices'][cam_name]) + # Create timeseries + ts = self.nwb_file.make_group( + '', cam_name, path='/acquisition/timeseries', + attrs={'source': '/general/devices/' + cam_name, + 'description': 'Video recording of mouse behaviour.', + 'comments': 'Frame rate {} s'.format(vid_rate)}) + ts.set_dataset('format', 'external') + ts.set_dataset('external_file', video_file_paths, + attrs={'starting_frame': starting_frames}) + ts.set_dataset('dimension', vid_dimensions) + ts.set_dataset('bits_per_pixel', bits_per_pixel) + ts.set_dataset('timestamps', frame_rel_times['RelTime'].values) diff --git a/Python/silverlabnwb/nwb_util.py b/Python/silverlabnwb/nwb_util.py new file mode 100644 index 0000000..f0289d8 --- /dev/null +++ b/Python/silverlabnwb/nwb_util.py @@ -0,0 +1,87 @@ +"""Standalone utility methods for working with NWB files.""" + +import difflib +import os +import six +import sys + +from nwb import h5diffsig + +try: + from contextlib import redirect_stdout +except ImportError: + # Python 2 support + from contextlib import contextmanager + + @contextmanager + def redirect_stdout(new_target): + old_target, sys.stdout = sys.stdout, new_target + try: + yield new_target + finally: + sys.stdout = old_target + + +def strip_ignorables(signature, ignore_external_file=False): + """Strip ignorable text from the given NWB signature. + + The NWB signature algorithm can place items that trivially vary (like file paths, + modification times) within <% ... %> tags. This method modifies the supplied list + of strings to strip these out from individual entries. + + :param signature: the signature to strip + :param ignore_external_file: if True, also strip external file paths + """ + import re + ignorable = re.compile(r'<%.*?%>') + if ignore_external_file: + ext_re = re.compile(r"( *\d+\. '/.+/external_file): dtype=") + for i, line in enumerate(signature): + signature[i] = ignorable.sub('<% ... %>', line) + if ignore_external_file: + m = ext_re.match(signature[i]) + if m: + signature[i] = m.group(1) + ': value ignored' + + +def get_signature(nwb_path): + """Get the signature for an NWB file as a string. + + :param nwb_path: path to the NWB file + """ + assert os.path.exists(nwb_path), 'NWB file {} does not exist'.format(nwb_path) + h5diffsig.filter_nwb = True + h5diffsig.alpha_sort = True + h5diffsig.single_file = True + output_buffer = six.StringIO() + with redirect_stdout(output_buffer): + h5diffsig.diff_files(nwb_path, nwb_path) + return output_buffer.getvalue().splitlines(True) + + +def compare_to_signature(nwb_path, sig_path, ignore_external_file=False): + """Compare an NWB file to an existing signature. + + The NWB API has functionality to compute a 'signature' for an NWB file, + and compare two files using this. Here we exploit the signature generation + capabilities to compare a new NWB file against a pre-computed signature. + + :param nwb_path: path to the NWB file + :param sig_path: path to file containing the signature + :param ignore_external_file: whether to ignore external file paths when comparing + """ + assert os.path.exists(sig_path), 'Signature file {} does not exist'.format(sig_path) + expected_sig = open(sig_path, 'r').readlines() + strip_ignorables(expected_sig, ignore_external_file=ignore_external_file) + actual_sig = get_signature(nwb_path) + strip_ignorables(actual_sig, ignore_external_file=ignore_external_file) + match = expected_sig == actual_sig + if match: + print('Signature matches') + else: + diff = difflib.unified_diff( + expected_sig, actual_sig, + fromfile=sig_path, tofile=nwb_path) + for line in diff: + six.print_(line, end='') + return match diff --git a/Python/silverlabnwb/script.py b/Python/silverlabnwb/script.py new file mode 100644 index 0000000..d3a1fe6 --- /dev/null +++ b/Python/silverlabnwb/script.py @@ -0,0 +1,51 @@ +''' +Command-line entrypoints for the Silver Lab pipeline. +''' + +import argparse + +from .nwb_file import NwbFile +from .metadata_gui import run_editor + + +def import_labview(): + """Command line script to import a Labview folder to NWB format.""" + parser = argparse.ArgumentParser(description='Import Labview to NWB.') + parser.add_argument('nwb_path', + help='path to the NWB file to write') + parser.add_argument('labview_path', + help='path to the Labview folder to import') + parser.add_argument('--no-gui', dest='gui', action='store_false', + help="don't show a GUI to edit metadata; just reuse the last session") + parser.add_argument('--check-sig', action='store_true', + help="check the generated NWB file against an existing signature." + " This expects a .sig file to be present next to the .nwb file.") + args = parser.parse_args() + + if args.gui: + run_editor() + + with NwbFile(args.nwb_path, mode='w') as nwb: + nwb.import_labview_folder(args.labview_path) + + if args.check_sig: + import os + sig_path = os.path.splitext(args.nwb_path)[0] + '.sig' + if os.path.exists(sig_path): + from .nwb_util import compare_to_signature + print('Comparing against signature file {}'.format(sig_path)) + compare_to_signature(args.nwb_path, sig_path) + else: + parser.error('No signature file {} found'.format(sig_path)) + + +def check_signature(): + """Command line script to check an NWB file against a pre-computed signature.""" + parser = argparse.ArgumentParser(description='Check an NWB file against a signature') + parser.add_argument('nwb_path', + help='path to the NWB file to check') + parser.add_argument('sig_path', + help='path to the signature to check against') + args = parser.parse_args() + from .nwb_util import compare_to_signature + compare_to_signature(args.nwb_path, args.sig_path) diff --git a/Python/silverlabnwb/subsample_nwb.py b/Python/silverlabnwb/subsample_nwb.py new file mode 100755 index 0000000..a4a24c3 --- /dev/null +++ b/Python/silverlabnwb/subsample_nwb.py @@ -0,0 +1,282 @@ +#!/usr/bin/env python + +"""A simple script to generate test datasets by subsampling. + +Given a Labview export folder and previously imported NWB file, +it will generate a new 'export' folder with a subset of the ROIs +and trials from the original, and compressed videos/images. +""" + + +import argparse +import av +import glob +import h5py +import nptdms +import numpy as np +import os +import subprocess + +from PIL import Image + + +def subsample_nwb(nwb, input_path, output_path, ntrials=2, nrois=10): + """Create a subset of an NWB Labview structure for testing purposes. + + :param nwb: h5py.File for the input NWB + :param output_path: folder to write output to + :param ntrials: how many trials to include + :param nrois: how many ROIs to include + """ + print('Processing', nwb.filename) + os.makedirs(output_path, exist_ok=True) + # Copy truncated ROI.dat + orig_nrois = copy_roi_dat(input_path, output_path, nrois) + # Copy modified header + copy_header( + input_path, output_path, + ntrials, nrois, orig_nrois) + # Figure out time duration for given ntrials + last_trial = nwb['/epochs/trial_{:04d}'.format(ntrials)] + end_time = last_trial['stop_time'].value + print('Trial {} ends at {}'.format(ntrials, end_time)) + # Copy truncated speed data + copy_speed_data(input_path, output_path, last_trial) + # Figure out which Zstack planes have ROIs + zstack_planes = find_used_planes(nwb, nrois) + # Copy pockels file + copy_pockels_file(input_path, output_path, zstack_planes) + # Copy & compress Zstack images + copy_zstack(input_path, output_path, zstack_planes) + # Copy subset of TDMS files + tdms_path = 'Functional imaging TDMS data files' + os.makedirs(os.path.join(output_path, tdms_path), exist_ok=True) + for tr in range(1, ntrials + 1): + tdms_name = '{:03d}.tdms'.format(tr) + tdms_in = os.path.join(input_path, tdms_path, tdms_name) + tdms_out = os.path.join(output_path, tdms_path, tdms_name) + copy_tdms(nwb, tdms_in, tdms_out, nrois) + # Find videos defined + video_names = [name for name in nwb['/acquisition/timeseries'].keys() + if name.endswith('Cam')] + print('Videos:', video_names) + # Compress videos + if video_names: + video_output_path = output_path + ' VidRec' + os.makedirs(video_output_path, exist_ok=True) + for name in video_names: + ts = nwb['/acquisition/timeseries/' + name] + old_path = ts['external_file'][0].decode() + new_path = os.path.join(video_output_path, os.path.basename(old_path)) + times = ts['timestamps'].value + frames_to_keep = np.count_nonzero(times <= end_time) + compress_video(old_path, new_path, frames_to_keep) + + +def find_used_planes(nwb, nrois): + used_planes = set() + seg_iface = nwb['/processing/Acquired_ROIs/ImageSegmentation'] + for plane_name in seg_iface.keys(): + plane_num = int(plane_name[-4:]) + for roi_name in seg_iface[plane_name].keys(): + if roi_name.startswith('ROI_'): + roi_num = int(roi_name[4:]) + if roi_num <= nrois: + used_planes.add(plane_num) + used_planes = list(used_planes) + used_planes.sort() + print('Relevant Zstack planes are:', used_planes) + return used_planes + + +def copy_zstack(input_path, output_path, zstack_planes): + dirname = 'Zstack Images' + sources = glob.glob(os.path.join(input_path, dirname, '*Channel*.tif')) + os.makedirs(os.path.join(output_path, dirname), exist_ok=True) + for source in sources: + dest = os.path.join(output_path, os.path.relpath(source, input_path)) + fname = os.path.basename(source) + stack_index = int(fname.split('_')[1][:-4]) + if stack_index in zstack_planes: + print('Copying frame {}'.format(fname)) + with Image.open(source) as im: + im.save(dest, format='TIFF', compression='tiff_lzw') + + +def copy_speed_data(input_path, output_path, last_trial): + fname = 'Speed_Data/Speed data 001.txt' + os.makedirs(os.path.join(output_path, 'Speed_Data'), exist_ok=True) + src = os.path.join(input_path, fname) + dest = os.path.join(output_path, fname) + speed_data_ts = last_trial['speed_data'] + end_index = speed_data_ts['idx_start'].value + speed_data_ts['count'].value + copy_and_truncate(src, dest, end_index + 1) + + +def copy_pockels_file(input_path, output_path, zstack_planes): + fname = 'Zplane_Pockels_Values.dat' + with open(os.path.join(output_path, fname), 'wt') as outf: + with open(os.path.join(input_path, fname), 'rt') as inf: + plane_index = -5 + for line in inf: + if plane_index < 1 or plane_index in zstack_planes: + outf.write(line) + # plane_index += 1 + + +def copy_header(input_path, output_path, ntrials, nrois, orig_nrois): + def get_value(line): + return float(line.split('=')[1].strip()) + roi_marker = 'number of poi' + miniscan_marker = 'number of miniscans' + trial_marker = 'number of trials' + fname = 'Experiment Header.ini' + src = os.path.join(input_path, fname) + dest = os.path.join(output_path, fname) + with open(dest, 'wt') as outf: + with open(src, 'rt') as inf: + for line in inf: + if line.startswith(roi_marker): + if get_value(line) > 0: + # Pointing mode experiment + line = '{} = {}\n'.format(roi_marker, nrois) + new_nscans = nrois + elif line.startswith(miniscan_marker): + n_scans = get_value(line) + if n_scans > 0: + # Patch mode experiment + new_nscans = n_scans / orig_nrois * nrois + line = '{} = {}\n'.format(miniscan_marker, new_nscans) + elif line.startswith(trial_marker): + line = '{} = {}\n'.format(trial_marker, ntrials) + outf.write(line) + # Only `new_nscans` lines of cycle times are now needed + cycle_fname = 'Single cycle relative times.txt' + copy_and_truncate(os.path.join(input_path, cycle_fname), + os.path.join(output_path, cycle_fname), + int(new_nscans)) + + +def copy_roi_dat(input_path, output_path, nrois): + filename = 'ROI.dat' + src = os.path.join(input_path, filename) + dest = os.path.join(output_path, filename) + copy_and_truncate(src, dest, nrois + 1) + with open(dest, 'wt') as outf: + with open(src, 'rt') as inf: + for i in range(nrois + 1): + outf.write(inf.readline()) + orig_nrois = nrois + for line in inf: + if line.strip(): + orig_nrois += 1 + print('Retaining {} ROIs of {}'.format(nrois, orig_nrois)) + return orig_nrois + + +def copy_and_truncate(src, dest, nlines): + print('Copying {} lines of {} to {}'.format(nlines, src, dest)) + with open(dest, 'wt') as outf: + with open(src, 'rt') as inf: + for i in range(nlines): + outf.write(inf.readline()) + + +def cycles_per_trial(nwb): + """Get the number of microscope cycles/trial. + + That is, the number of times each point is imaged in each + trial. Currently looks at the first imaging timeseries in + the first trial, and assumes they're all the same. + """ + trial1 = nwb['/epochs/trial_0001'] + for ts_name in trial1: + ts = trial1[ts_name] + is_image_series = ts['timeseries/pixel_time_offsets'] is not None + if is_image_series: + return ts['count'].value + else: + raise ValueError('No imaging timeseries found') + + +def copy_tdms(nwb, in_path, out_path, nrois): + num_all_rois = nwb['/processing/Acquired_ROIs/roi_spec'].shape[0] + print('Copying {} of {} ROIs from {} to {}'.format( + nrois, num_all_rois, in_path, out_path)) + in_tdms = nptdms.TdmsFile(in_path) + group_name = 'Functional Imaging Data' + with nptdms.TdmsWriter(out_path) as out_tdms: + root, group = in_tdms.object(), in_tdms.object(group_name) + out_tdms.write_segment([root, group]) + for ch, channel in {'0': 'Red', '1': 'Green'}.items(): + ch_name = 'Channel {} Data'.format(ch) + ch_obj = in_tdms.object(group_name, ch_name) + shape = (cycles_per_trial(nwb), num_all_rois, -1) + ch_data = ch_obj.data.reshape(shape) + subset = ch_data[:, :nrois, :].reshape(-1) + new_obj = nptdms.ChannelObject(group_name, ch_name, subset, properties={}) + out_tdms.write_segment([new_obj]) + + +def compress_video(input_path, output_path, nframes, width=300): + print('Compressing {} frames of "{}" to "{}"'.format( + nframes, input_path, output_path)) + input_file = av.open(input_path) + input_vid = input_file.streams.video[0] + assert input_vid.frames >= nframes, 'Only {} frames present in video'.format( + input_vid.frames) + scale = input_vid.width / width + height = int(round(input_vid.height / scale)) + if height % 2 == 1: + height += 1 + print('Input {}x{} @ {}, {}'.format( + input_vid.width, input_vid.height, input_vid.rate, input_vid.bit_rate)) + + # Create a ffmpeg command line for the compression & resizing + args = [ + 'ffmpeg', + '-i', input_path, + '-y', + '-frames:v', str(nframes), + '-s', '{}x{}'.format(width, height), + '-pix_fmt', 'yuvj420p', + '-codec:v', 'mjpeg', + output_path + ] + subprocess.check_call(args) + + # Copy truncated 'relative times' file + base = os.path.basename(input_path).split('-')[0] + times_name = base + '-relative times.txt' + src = os.path.join(os.path.dirname(input_path), times_name) + dest = os.path.join(os.path.dirname(output_path), times_name) + copy_and_truncate(src, dest, nframes) + + +def create_parser(): + parser = argparse.ArgumentParser( + description='Prepare subsampled test datasets for NWB import') + parser.add_argument('input_id', + help='experiment ID to subsample') + parser.add_argument('output_path', + help='output folder path to write') + parser.add_argument('--nrois', '-r', + type=int, default=10, + help='number of ROIs to retain') + parser.add_argument('--ntrials', '-t', + type=int, default=2, + help='number of trials to retain') + return parser + + +def run(): + args = create_parser().parse_args() + input_path = args.input_id + ' FunctAcq' + nwb_path = args.input_id + '.nwb' + with h5py.File(nwb_path, mode='r') as nwb: + subsample_nwb(nwb, input_path, args.output_path, + nrois=args.nrois, ntrials=args.ntrials) + + +if __name__ == '__main__': + run() diff --git a/Python/test/data/161215_15_34_21.sig b/Python/test/data/161215_15_34_21.sig new file mode 100644 index 0000000..85edbc6 --- /dev/null +++ b/Python/test/data/161215_15_34_21.sig @@ -0,0 +1,1791 @@ +<% Generating signature for 161215_15_34_21.nwb %> + +** No datasets hard links. +** No groups hard links. +** 90 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0027/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0027/description' + 2. 'to: "/general/optophysiology/Zstack0029/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/description' + 3. 'to: "/general/optophysiology/Zstack0030/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0030/description' + 4. 'to: "/general/optophysiology/Zstack0032/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/description' + 5. 'to: "/general/optophysiology/Zstack0033/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/description' + 6. 'to: "/general/optophysiology/Zstack0034/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/description' + 7. 'to: "/general/optophysiology/Zstack0035/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/description' + 8. 'to: "/general/optophysiology/Zstack0039/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0039/description' + 9. 'to: "/general/optophysiology/Zstack0040/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0040/description' + 10. 'to: "/general/optophysiology/Zstack0047/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0047/description' + 11. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' + 12. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_002/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_002_Green/pixel_time_offsets + /acquisition/timeseries/ROI_002_Red/pixel_time_offsets' + 13. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_003/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_003_Green/pixel_time_offsets + /acquisition/timeseries/ROI_003_Red/pixel_time_offsets' + 14. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_004/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_004_Green/pixel_time_offsets + /acquisition/timeseries/ROI_004_Red/pixel_time_offsets' + 15. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_005/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_005_Green/pixel_time_offsets + /acquisition/timeseries/ROI_005_Red/pixel_time_offsets' + 16. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_006/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_006_Green/pixel_time_offsets + /acquisition/timeseries/ROI_006_Red/pixel_time_offsets' + 17. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_007/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_007_Green/pixel_time_offsets + /acquisition/timeseries/ROI_007_Red/pixel_time_offsets' + 18. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_076/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_076_Green/pixel_time_offsets + /acquisition/timeseries/ROI_076_Red/pixel_time_offsets' + 19. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_077/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_077_Green/pixel_time_offsets + /acquisition/timeseries/ROI_077_Red/pixel_time_offsets' + 20. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_078/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_078_Green/pixel_time_offsets + /acquisition/timeseries/ROI_078_Red/pixel_time_offsets' + 21. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_079/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_079_Green/pixel_time_offsets + /acquisition/timeseries/ROI_079_Red/pixel_time_offsets' + 22. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_080/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_080_Green/pixel_time_offsets + /acquisition/timeseries/ROI_080_Red/pixel_time_offsets' + 23. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_008/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_008_Green/pixel_time_offsets + /acquisition/timeseries/ROI_008_Red/pixel_time_offsets' + 24. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_009/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_009_Green/pixel_time_offsets + /acquisition/timeseries/ROI_009_Red/pixel_time_offsets' + 25. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_010/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_010_Green/pixel_time_offsets + /acquisition/timeseries/ROI_010_Red/pixel_time_offsets' + 26. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_031/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_031_Green/pixel_time_offsets + /acquisition/timeseries/ROI_031_Red/pixel_time_offsets' + 27. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_014/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_014_Green/pixel_time_offsets + /acquisition/timeseries/ROI_014_Red/pixel_time_offsets' + 28. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_015/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_015_Green/pixel_time_offsets + /acquisition/timeseries/ROI_015_Red/pixel_time_offsets' + 29. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_016/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_016_Green/pixel_time_offsets + /acquisition/timeseries/ROI_016_Red/pixel_time_offsets' + 30. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_029/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_029_Green/pixel_time_offsets + /acquisition/timeseries/ROI_029_Red/pixel_time_offsets' + 31. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_030/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_030_Green/pixel_time_offsets + /acquisition/timeseries/ROI_030_Red/pixel_time_offsets' + 32. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_011/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_011_Green/pixel_time_offsets + /acquisition/timeseries/ROI_011_Red/pixel_time_offsets' + 33. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_012/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_012_Green/pixel_time_offsets + /acquisition/timeseries/ROI_012_Red/pixel_time_offsets' + 34. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_013/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_013_Green/pixel_time_offsets + /acquisition/timeseries/ROI_013_Red/pixel_time_offsets' + 35. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_017/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_017_Green/pixel_time_offsets + /acquisition/timeseries/ROI_017_Red/pixel_time_offsets' + 36. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_018/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_018_Green/pixel_time_offsets + /acquisition/timeseries/ROI_018_Red/pixel_time_offsets' + 37. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_019/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_019_Green/pixel_time_offsets + /acquisition/timeseries/ROI_019_Red/pixel_time_offsets' + 38. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_020/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_020_Green/pixel_time_offsets + /acquisition/timeseries/ROI_020_Red/pixel_time_offsets' + 39. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_021/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_021_Green/pixel_time_offsets + /acquisition/timeseries/ROI_021_Red/pixel_time_offsets' + 40. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_022/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_022_Green/pixel_time_offsets + /acquisition/timeseries/ROI_022_Red/pixel_time_offsets' + 41. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_023/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_023_Green/pixel_time_offsets + /acquisition/timeseries/ROI_023_Red/pixel_time_offsets' + 42. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_024/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_024_Green/pixel_time_offsets + /acquisition/timeseries/ROI_024_Red/pixel_time_offsets' + 43. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_025/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_025_Green/pixel_time_offsets + /acquisition/timeseries/ROI_025_Red/pixel_time_offsets' + 44. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_051/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_051_Green/pixel_time_offsets + /acquisition/timeseries/ROI_051_Red/pixel_time_offsets' + 45. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_052/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_052_Green/pixel_time_offsets + /acquisition/timeseries/ROI_052_Red/pixel_time_offsets' + 46. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_053/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_053_Green/pixel_time_offsets + /acquisition/timeseries/ROI_053_Red/pixel_time_offsets' + 47. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_054/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_054_Green/pixel_time_offsets + /acquisition/timeseries/ROI_054_Red/pixel_time_offsets' + 48. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_055/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_055_Green/pixel_time_offsets + /acquisition/timeseries/ROI_055_Red/pixel_time_offsets' + 49. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_056/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_056_Green/pixel_time_offsets + /acquisition/timeseries/ROI_056_Red/pixel_time_offsets' + 50. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_057/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_057_Green/pixel_time_offsets + /acquisition/timeseries/ROI_057_Red/pixel_time_offsets' + 51. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_058/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_058_Green/pixel_time_offsets + /acquisition/timeseries/ROI_058_Red/pixel_time_offsets' + 52. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_059/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_059_Green/pixel_time_offsets + /acquisition/timeseries/ROI_059_Red/pixel_time_offsets' + 53. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_060/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_060_Green/pixel_time_offsets + /acquisition/timeseries/ROI_060_Red/pixel_time_offsets' + 54. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_026/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_026_Green/pixel_time_offsets + /acquisition/timeseries/ROI_026_Red/pixel_time_offsets' + 55. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_027/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_027_Green/pixel_time_offsets + /acquisition/timeseries/ROI_027_Red/pixel_time_offsets' + 56. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_028/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_028_Green/pixel_time_offsets + /acquisition/timeseries/ROI_028_Red/pixel_time_offsets' + 57. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_032/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_032_Green/pixel_time_offsets + /acquisition/timeseries/ROI_032_Red/pixel_time_offsets' + 58. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_033/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_033_Green/pixel_time_offsets + /acquisition/timeseries/ROI_033_Red/pixel_time_offsets' + 59. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_034/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_034_Green/pixel_time_offsets + /acquisition/timeseries/ROI_034_Red/pixel_time_offsets' + 60. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_035/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_035_Green/pixel_time_offsets + /acquisition/timeseries/ROI_035_Red/pixel_time_offsets' + 61. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_036/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_036_Green/pixel_time_offsets + /acquisition/timeseries/ROI_036_Red/pixel_time_offsets' + 62. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_037/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_037_Green/pixel_time_offsets + /acquisition/timeseries/ROI_037_Red/pixel_time_offsets' + 63. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_045/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_045_Green/pixel_time_offsets + /acquisition/timeseries/ROI_045_Red/pixel_time_offsets' + 64. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_046/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_046_Green/pixel_time_offsets + /acquisition/timeseries/ROI_046_Red/pixel_time_offsets' + 65. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_047/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_047_Green/pixel_time_offsets + /acquisition/timeseries/ROI_047_Red/pixel_time_offsets' + 66. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_048/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_048_Green/pixel_time_offsets + /acquisition/timeseries/ROI_048_Red/pixel_time_offsets' + 67. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_049/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_049_Green/pixel_time_offsets + /acquisition/timeseries/ROI_049_Red/pixel_time_offsets' + 68. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_050/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_050_Green/pixel_time_offsets + /acquisition/timeseries/ROI_050_Red/pixel_time_offsets' + 69. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_038/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_038_Green/pixel_time_offsets + /acquisition/timeseries/ROI_038_Red/pixel_time_offsets' + 70. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_039/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_039_Green/pixel_time_offsets + /acquisition/timeseries/ROI_039_Red/pixel_time_offsets' + 71. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_040/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_040_Green/pixel_time_offsets + /acquisition/timeseries/ROI_040_Red/pixel_time_offsets' + 72. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_041/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_041_Green/pixel_time_offsets + /acquisition/timeseries/ROI_041_Red/pixel_time_offsets' + 73. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_042/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_042_Green/pixel_time_offsets + /acquisition/timeseries/ROI_042_Red/pixel_time_offsets' + 74. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_043/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_043_Green/pixel_time_offsets + /acquisition/timeseries/ROI_043_Red/pixel_time_offsets' + 75. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_044/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_044_Green/pixel_time_offsets + /acquisition/timeseries/ROI_044_Red/pixel_time_offsets' + 76. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_061/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_061_Green/pixel_time_offsets + /acquisition/timeseries/ROI_061_Red/pixel_time_offsets' + 77. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_062/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_062_Green/pixel_time_offsets + /acquisition/timeseries/ROI_062_Red/pixel_time_offsets' + 78. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_063/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_063_Green/pixel_time_offsets + /acquisition/timeseries/ROI_063_Red/pixel_time_offsets' + 79. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_064/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_064_Green/pixel_time_offsets + /acquisition/timeseries/ROI_064_Red/pixel_time_offsets' + 80. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_065/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_065_Green/pixel_time_offsets + /acquisition/timeseries/ROI_065_Red/pixel_time_offsets' + 81. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_066/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_066_Green/pixel_time_offsets + /acquisition/timeseries/ROI_066_Red/pixel_time_offsets' + 82. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_067/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_067_Green/pixel_time_offsets + /acquisition/timeseries/ROI_067_Red/pixel_time_offsets' + 83. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_068/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_068_Green/pixel_time_offsets + /acquisition/timeseries/ROI_068_Red/pixel_time_offsets' + 84. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_069/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_069_Green/pixel_time_offsets + /acquisition/timeseries/ROI_069_Red/pixel_time_offsets' + 85. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_070/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_070_Green/pixel_time_offsets + /acquisition/timeseries/ROI_070_Red/pixel_time_offsets' + 86. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_071/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_071_Green/pixel_time_offsets + /acquisition/timeseries/ROI_071_Red/pixel_time_offsets' + 87. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_072/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_072_Green/pixel_time_offsets + /acquisition/timeseries/ROI_072_Red/pixel_time_offsets' + 88. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_073/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_073_Green/pixel_time_offsets + /acquisition/timeseries/ROI_073_Red/pixel_time_offsets' + 89. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_074/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_074_Green/pixel_time_offsets + /acquisition/timeseries/ROI_074_Red/pixel_time_offsets' + 90. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_075/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_075_Green/pixel_time_offsets + /acquisition/timeseries/ROI_075_Red/pixel_time_offsets' +** 171 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-20)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-20)' + 3. 'to: "/acquisition/timeseries/ROI_002_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_002_Green/timeseries (#=1-20)' + 4. 'to: "/acquisition/timeseries/ROI_002_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_002_Red/timeseries (#=1-20)' + 5. 'to: "/acquisition/timeseries/ROI_003_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_003_Green/timeseries (#=1-20)' + 6. 'to: "/acquisition/timeseries/ROI_003_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_003_Red/timeseries (#=1-20)' + 7. 'to: "/acquisition/timeseries/ROI_004_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_004_Green/timeseries (#=1-20)' + 8. 'to: "/acquisition/timeseries/ROI_004_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_004_Red/timeseries (#=1-20)' + 9. 'to: "/acquisition/timeseries/ROI_005_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_005_Green/timeseries (#=1-20)' + 10. 'to: "/acquisition/timeseries/ROI_005_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_005_Red/timeseries (#=1-20)' + 11. 'to: "/acquisition/timeseries/ROI_006_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_006_Green/timeseries (#=1-20)' + 12. 'to: "/acquisition/timeseries/ROI_006_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_006_Red/timeseries (#=1-20)' + 13. 'to: "/acquisition/timeseries/ROI_007_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_007_Green/timeseries (#=1-20)' + 14. 'to: "/acquisition/timeseries/ROI_007_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_007_Red/timeseries (#=1-20)' + 15. 'to: "/acquisition/timeseries/ROI_008_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_008_Green/timeseries (#=1-20)' + 16. 'to: "/acquisition/timeseries/ROI_008_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_008_Red/timeseries (#=1-20)' + 17. 'to: "/acquisition/timeseries/ROI_009_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_009_Green/timeseries (#=1-20)' + 18. 'to: "/acquisition/timeseries/ROI_009_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_009_Red/timeseries (#=1-20)' + 19. 'to: "/acquisition/timeseries/ROI_010_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_010_Green/timeseries (#=1-20)' + 20. 'to: "/acquisition/timeseries/ROI_010_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_010_Red/timeseries (#=1-20)' + 21. 'to: "/acquisition/timeseries/ROI_011_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_011_Green/timeseries (#=1-20)' + 22. 'to: "/acquisition/timeseries/ROI_011_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_011_Red/timeseries (#=1-20)' + 23. 'to: "/acquisition/timeseries/ROI_012_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_012_Green/timeseries (#=1-20)' + 24. 'to: "/acquisition/timeseries/ROI_012_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_012_Red/timeseries (#=1-20)' + 25. 'to: "/acquisition/timeseries/ROI_013_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_013_Green/timeseries (#=1-20)' + 26. 'to: "/acquisition/timeseries/ROI_013_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_013_Red/timeseries (#=1-20)' + 27. 'to: "/acquisition/timeseries/ROI_014_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_014_Green/timeseries (#=1-20)' + 28. 'to: "/acquisition/timeseries/ROI_014_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_014_Red/timeseries (#=1-20)' + 29. 'to: "/acquisition/timeseries/ROI_015_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_015_Green/timeseries (#=1-20)' + 30. 'to: "/acquisition/timeseries/ROI_015_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_015_Red/timeseries (#=1-20)' + 31. 'to: "/acquisition/timeseries/ROI_016_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_016_Green/timeseries (#=1-20)' + 32. 'to: "/acquisition/timeseries/ROI_016_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_016_Red/timeseries (#=1-20)' + 33. 'to: "/acquisition/timeseries/ROI_017_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_017_Green/timeseries (#=1-20)' + 34. 'to: "/acquisition/timeseries/ROI_017_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_017_Red/timeseries (#=1-20)' + 35. 'to: "/acquisition/timeseries/ROI_018_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_018_Green/timeseries (#=1-20)' + 36. 'to: "/acquisition/timeseries/ROI_018_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_018_Red/timeseries (#=1-20)' + 37. 'to: "/acquisition/timeseries/ROI_019_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_019_Green/timeseries (#=1-20)' + 38. 'to: "/acquisition/timeseries/ROI_019_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_019_Red/timeseries (#=1-20)' + 39. 'to: "/acquisition/timeseries/ROI_020_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_020_Green/timeseries (#=1-20)' + 40. 'to: "/acquisition/timeseries/ROI_020_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_020_Red/timeseries (#=1-20)' + 41. 'to: "/acquisition/timeseries/ROI_021_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_021_Green/timeseries (#=1-20)' + 42. 'to: "/acquisition/timeseries/ROI_021_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_021_Red/timeseries (#=1-20)' + 43. 'to: "/acquisition/timeseries/ROI_022_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_022_Green/timeseries (#=1-20)' + 44. 'to: "/acquisition/timeseries/ROI_022_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_022_Red/timeseries (#=1-20)' + 45. 'to: "/acquisition/timeseries/ROI_023_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_023_Green/timeseries (#=1-20)' + 46. 'to: "/acquisition/timeseries/ROI_023_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_023_Red/timeseries (#=1-20)' + 47. 'to: "/acquisition/timeseries/ROI_024_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_024_Green/timeseries (#=1-20)' + 48. 'to: "/acquisition/timeseries/ROI_024_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_024_Red/timeseries (#=1-20)' + 49. 'to: "/acquisition/timeseries/ROI_025_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_025_Green/timeseries (#=1-20)' + 50. 'to: "/acquisition/timeseries/ROI_025_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_025_Red/timeseries (#=1-20)' + 51. 'to: "/acquisition/timeseries/ROI_026_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_026_Green/timeseries (#=1-20)' + 52. 'to: "/acquisition/timeseries/ROI_026_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_026_Red/timeseries (#=1-20)' + 53. 'to: "/acquisition/timeseries/ROI_027_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_027_Green/timeseries (#=1-20)' + 54. 'to: "/acquisition/timeseries/ROI_027_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_027_Red/timeseries (#=1-20)' + 55. 'to: "/acquisition/timeseries/ROI_028_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_028_Green/timeseries (#=1-20)' + 56. 'to: "/acquisition/timeseries/ROI_028_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_028_Red/timeseries (#=1-20)' + 57. 'to: "/acquisition/timeseries/ROI_029_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_029_Green/timeseries (#=1-20)' + 58. 'to: "/acquisition/timeseries/ROI_029_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_029_Red/timeseries (#=1-20)' + 59. 'to: "/acquisition/timeseries/ROI_030_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_030_Green/timeseries (#=1-20)' + 60. 'to: "/acquisition/timeseries/ROI_030_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_030_Red/timeseries (#=1-20)' + 61. 'to: "/acquisition/timeseries/ROI_031_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_031_Green/timeseries (#=1-20)' + 62. 'to: "/acquisition/timeseries/ROI_031_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_031_Red/timeseries (#=1-20)' + 63. 'to: "/acquisition/timeseries/ROI_032_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_032_Green/timeseries (#=1-20)' + 64. 'to: "/acquisition/timeseries/ROI_032_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_032_Red/timeseries (#=1-20)' + 65. 'to: "/acquisition/timeseries/ROI_033_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_033_Green/timeseries (#=1-20)' + 66. 'to: "/acquisition/timeseries/ROI_033_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_033_Red/timeseries (#=1-20)' + 67. 'to: "/acquisition/timeseries/ROI_034_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_034_Green/timeseries (#=1-20)' + 68. 'to: "/acquisition/timeseries/ROI_034_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_034_Red/timeseries (#=1-20)' + 69. 'to: "/acquisition/timeseries/ROI_035_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_035_Green/timeseries (#=1-20)' + 70. 'to: "/acquisition/timeseries/ROI_035_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_035_Red/timeseries (#=1-20)' + 71. 'to: "/acquisition/timeseries/ROI_036_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_036_Green/timeseries (#=1-20)' + 72. 'to: "/acquisition/timeseries/ROI_036_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_036_Red/timeseries (#=1-20)' + 73. 'to: "/acquisition/timeseries/ROI_037_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_037_Green/timeseries (#=1-20)' + 74. 'to: "/acquisition/timeseries/ROI_037_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_037_Red/timeseries (#=1-20)' + 75. 'to: "/acquisition/timeseries/ROI_038_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_038_Green/timeseries (#=1-20)' + 76. 'to: "/acquisition/timeseries/ROI_038_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_038_Red/timeseries (#=1-20)' + 77. 'to: "/acquisition/timeseries/ROI_039_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_039_Green/timeseries (#=1-20)' + 78. 'to: "/acquisition/timeseries/ROI_039_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_039_Red/timeseries (#=1-20)' + 79. 'to: "/acquisition/timeseries/ROI_040_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_040_Green/timeseries (#=1-20)' + 80. 'to: "/acquisition/timeseries/ROI_040_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_040_Red/timeseries (#=1-20)' + 81. 'to: "/acquisition/timeseries/ROI_041_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_041_Green/timeseries (#=1-20)' + 82. 'to: "/acquisition/timeseries/ROI_041_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_041_Red/timeseries (#=1-20)' + 83. 'to: "/acquisition/timeseries/ROI_042_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_042_Green/timeseries (#=1-20)' + 84. 'to: "/acquisition/timeseries/ROI_042_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_042_Red/timeseries (#=1-20)' + 85. 'to: "/acquisition/timeseries/ROI_043_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_043_Green/timeseries (#=1-20)' + 86. 'to: "/acquisition/timeseries/ROI_043_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_043_Red/timeseries (#=1-20)' + 87. 'to: "/acquisition/timeseries/ROI_044_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_044_Green/timeseries (#=1-20)' + 88. 'to: "/acquisition/timeseries/ROI_044_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_044_Red/timeseries (#=1-20)' + 89. 'to: "/acquisition/timeseries/ROI_045_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_045_Green/timeseries (#=1-20)' + 90. 'to: "/acquisition/timeseries/ROI_045_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_045_Red/timeseries (#=1-20)' + 91. 'to: "/acquisition/timeseries/ROI_046_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_046_Green/timeseries (#=1-20)' + 92. 'to: "/acquisition/timeseries/ROI_046_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_046_Red/timeseries (#=1-20)' + 93. 'to: "/acquisition/timeseries/ROI_047_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_047_Green/timeseries (#=1-20)' + 94. 'to: "/acquisition/timeseries/ROI_047_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_047_Red/timeseries (#=1-20)' + 95. 'to: "/acquisition/timeseries/ROI_048_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_048_Green/timeseries (#=1-20)' + 96. 'to: "/acquisition/timeseries/ROI_048_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_048_Red/timeseries (#=1-20)' + 97. 'to: "/acquisition/timeseries/ROI_049_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_049_Green/timeseries (#=1-20)' + 98. 'to: "/acquisition/timeseries/ROI_049_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_049_Red/timeseries (#=1-20)' + 99. 'to: "/acquisition/timeseries/ROI_050_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_050_Green/timeseries (#=1-20)' +100. 'to: "/acquisition/timeseries/ROI_050_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_050_Red/timeseries (#=1-20)' +101. 'to: "/acquisition/timeseries/ROI_051_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_051_Green/timeseries (#=1-20)' +102. 'to: "/acquisition/timeseries/ROI_051_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_051_Red/timeseries (#=1-20)' +103. 'to: "/acquisition/timeseries/ROI_052_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_052_Green/timeseries (#=1-20)' +104. 'to: "/acquisition/timeseries/ROI_052_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_052_Red/timeseries (#=1-20)' +105. 'to: "/acquisition/timeseries/ROI_053_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_053_Green/timeseries (#=1-20)' +106. 'to: "/acquisition/timeseries/ROI_053_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_053_Red/timeseries (#=1-20)' +107. 'to: "/acquisition/timeseries/ROI_054_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_054_Green/timeseries (#=1-20)' +108. 'to: "/acquisition/timeseries/ROI_054_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_054_Red/timeseries (#=1-20)' +109. 'to: "/acquisition/timeseries/ROI_055_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_055_Green/timeseries (#=1-20)' +110. 'to: "/acquisition/timeseries/ROI_055_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_055_Red/timeseries (#=1-20)' +111. 'to: "/acquisition/timeseries/ROI_056_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_056_Green/timeseries (#=1-20)' +112. 'to: "/acquisition/timeseries/ROI_056_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_056_Red/timeseries (#=1-20)' +113. 'to: "/acquisition/timeseries/ROI_057_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_057_Green/timeseries (#=1-20)' +114. 'to: "/acquisition/timeseries/ROI_057_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_057_Red/timeseries (#=1-20)' +115. 'to: "/acquisition/timeseries/ROI_058_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_058_Green/timeseries (#=1-20)' +116. 'to: "/acquisition/timeseries/ROI_058_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_058_Red/timeseries (#=1-20)' +117. 'to: "/acquisition/timeseries/ROI_059_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_059_Green/timeseries (#=1-20)' +118. 'to: "/acquisition/timeseries/ROI_059_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_059_Red/timeseries (#=1-20)' +119. 'to: "/acquisition/timeseries/ROI_060_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_060_Green/timeseries (#=1-20)' +120. 'to: "/acquisition/timeseries/ROI_060_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_060_Red/timeseries (#=1-20)' +121. 'to: "/acquisition/timeseries/ROI_061_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_061_Green/timeseries (#=1-20)' +122. 'to: "/acquisition/timeseries/ROI_061_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_061_Red/timeseries (#=1-20)' +123. 'to: "/acquisition/timeseries/ROI_062_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_062_Green/timeseries (#=1-20)' +124. 'to: "/acquisition/timeseries/ROI_062_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_062_Red/timeseries (#=1-20)' +125. 'to: "/acquisition/timeseries/ROI_063_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_063_Green/timeseries (#=1-20)' +126. 'to: "/acquisition/timeseries/ROI_063_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_063_Red/timeseries (#=1-20)' +127. 'to: "/acquisition/timeseries/ROI_064_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_064_Green/timeseries (#=1-20)' +128. 'to: "/acquisition/timeseries/ROI_064_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_064_Red/timeseries (#=1-20)' +129. 'to: "/acquisition/timeseries/ROI_065_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_065_Green/timeseries (#=1-20)' +130. 'to: "/acquisition/timeseries/ROI_065_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_065_Red/timeseries (#=1-20)' +131. 'to: "/acquisition/timeseries/ROI_066_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_066_Green/timeseries (#=1-20)' +132. 'to: "/acquisition/timeseries/ROI_066_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_066_Red/timeseries (#=1-20)' +133. 'to: "/acquisition/timeseries/ROI_067_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_067_Green/timeseries (#=1-20)' +134. 'to: "/acquisition/timeseries/ROI_067_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_067_Red/timeseries (#=1-20)' +135. 'to: "/acquisition/timeseries/ROI_068_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_068_Green/timeseries (#=1-20)' +136. 'to: "/acquisition/timeseries/ROI_068_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_068_Red/timeseries (#=1-20)' +137. 'to: "/acquisition/timeseries/ROI_069_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_069_Green/timeseries (#=1-20)' +138. 'to: "/acquisition/timeseries/ROI_069_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_069_Red/timeseries (#=1-20)' +139. 'to: "/acquisition/timeseries/ROI_070_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_070_Green/timeseries (#=1-20)' +140. 'to: "/acquisition/timeseries/ROI_070_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_070_Red/timeseries (#=1-20)' +141. 'to: "/acquisition/timeseries/ROI_071_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_071_Green/timeseries (#=1-20)' +142. 'to: "/acquisition/timeseries/ROI_071_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_071_Red/timeseries (#=1-20)' +143. 'to: "/acquisition/timeseries/ROI_072_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_072_Green/timeseries (#=1-20)' +144. 'to: "/acquisition/timeseries/ROI_072_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_072_Red/timeseries (#=1-20)' +145. 'to: "/acquisition/timeseries/ROI_073_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_073_Green/timeseries (#=1-20)' +146. 'to: "/acquisition/timeseries/ROI_073_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_073_Red/timeseries (#=1-20)' +147. 'to: "/acquisition/timeseries/ROI_074_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_074_Green/timeseries (#=1-20)' +148. 'to: "/acquisition/timeseries/ROI_074_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_074_Red/timeseries (#=1-20)' +149. 'to: "/acquisition/timeseries/ROI_075_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_075_Green/timeseries (#=1-20)' +150. 'to: "/acquisition/timeseries/ROI_075_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_075_Red/timeseries (#=1-20)' +151. 'to: "/acquisition/timeseries/ROI_076_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_076_Green/timeseries (#=1-20)' +152. 'to: "/acquisition/timeseries/ROI_076_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_076_Red/timeseries (#=1-20)' +153. 'to: "/acquisition/timeseries/ROI_077_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_077_Green/timeseries (#=1-20)' +154. 'to: "/acquisition/timeseries/ROI_077_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_077_Red/timeseries (#=1-20)' +155. 'to: "/acquisition/timeseries/ROI_078_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_078_Green/timeseries (#=1-20)' +156. 'to: "/acquisition/timeseries/ROI_078_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_078_Red/timeseries (#=1-20)' +157. 'to: "/acquisition/timeseries/ROI_079_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_079_Green/timeseries (#=1-20)' +158. 'to: "/acquisition/timeseries/ROI_079_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_079_Red/timeseries (#=1-20)' +159. 'to: "/acquisition/timeseries/ROI_080_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_080_Green/timeseries (#=1-20)' +160. 'to: "/acquisition/timeseries/ROI_080_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_080_Red/timeseries (#=1-20)' +161. 'to: "/acquisition/timeseries/Zstack_Red_0027" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0027/reference_images/Zstack_image' +162. 'to: "/acquisition/timeseries/Zstack_Red_0029" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/reference_images/Zstack_image' +163. 'to: "/acquisition/timeseries/Zstack_Red_0030" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0030/reference_images/Zstack_image' +164. 'to: "/acquisition/timeseries/Zstack_Red_0032" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/reference_images/Zstack_image' +165. 'to: "/acquisition/timeseries/Zstack_Red_0033" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/reference_images/Zstack_image' +166. 'to: "/acquisition/timeseries/Zstack_Red_0034" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/reference_images/Zstack_image' +167. 'to: "/acquisition/timeseries/Zstack_Red_0035" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/reference_images/Zstack_image' +168. 'to: "/acquisition/timeseries/Zstack_Red_0039" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0039/reference_images/Zstack_image' +169. 'to: "/acquisition/timeseries/Zstack_Red_0040" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0040/reference_images/Zstack_image' +170. 'to: "/acquisition/timeseries/Zstack_Red_0047" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0047/reference_images/Zstack_image' +171. 'to: "/acquisition/timeseries/speed_data" 20 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-20)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 3627 attributes (sorted alphabetically) (305 combined): + 1. '/acquisition/timeseries/EyeCam ancestry: dtype=|S11, shape=(2,) size (22) val='["TimeSeries","ImageSeries"]'' + 2. '/acquisition/timeseries/EyeCam comments: dtype=|S17, shape=() size (17) val='"Frame rate 1/30 s"'' + 3. '/acquisition/timeseries/EyeCam description: dtype=|S35, shape=() size (35) val='"Video recording of mouse behaviour."'' + 4. '/acquisition/timeseries/EyeCam help: dtype=|S45, shape=() size (45) val='"Storage object for time-series 2-D image data"'' + 5. '/acquisition/timeseries/EyeCam neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 6. '/acquisition/timeseries/EyeCam source: dtype=|S23, shape=() size (23) val='"/general/devices/EyeCam"'' + 7. '/acquisition/timeseries/EyeCam/external_file starting_frame: dtype=int64, shape=(1,) size (8) val='[0]'' + 8. '/acquisition/timeseries/EyeCam/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 9. '/acquisition/timeseries/EyeCam/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 10. '/acquisition/timeseries/ROI_#_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-80)' + 11. '/acquisition/timeseries/ROI_#_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-80)' + 12. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 13. '/acquisition/timeseries/ROI_#_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-80)' + 14. '/acquisition/timeseries/ROI_#_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-80)' + 15. '/acquisition/timeseries/ROI_#_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-80)' + 16. '/acquisition/timeseries/ROI_#_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 17. '/acquisition/timeseries/ROI_#_Green/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-80)' + 18. '/acquisition/timeseries/ROI_#_Green/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-80)' + 19. '/acquisition/timeseries/ROI_#_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-80)' + 20. '/acquisition/timeseries/ROI_#_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 21. '/acquisition/timeseries/ROI_#_Green/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-80)' + 22. '/acquisition/timeseries/ROI_#_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-80)' + 23. '/acquisition/timeseries/ROI_#_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-80)' + 24. '/acquisition/timeseries/ROI_#_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-80)' + 25. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 26. '/acquisition/timeseries/ROI_#_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-80)' + 27. '/acquisition/timeseries/ROI_#_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-80)' + 28. '/acquisition/timeseries/ROI_#_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-80)' + 29. '/acquisition/timeseries/ROI_#_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 30. '/acquisition/timeseries/ROI_#_Red/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-80)' + 31. '/acquisition/timeseries/ROI_#_Red/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-80)' + 32. '/acquisition/timeseries/ROI_#_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-80)' + 33. '/acquisition/timeseries/ROI_#_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 34. '/acquisition/timeseries/ROI_#_Red/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-80)' + 35. '/acquisition/timeseries/ROI_#_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-80)' + 36. '/acquisition/timeseries/ROI_002_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPc'' + 37. '/acquisition/timeseries/ROI_002_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPC'' + 38. '/acquisition/timeseries/ROI_003_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnJ'' + 39. '/acquisition/timeseries/ROI_003_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroj'' + 40. '/acquisition/timeseries/ROI_004_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMq'' + 41. '/acquisition/timeseries/ROI_004_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMQ'' + 42. '/acquisition/timeseries/ROI_005_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkX'' + 43. '/acquisition/timeseries/ROI_005_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklx'' + 44. '/acquisition/timeseries/ROI_006_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJE'' + 45. '/acquisition/timeseries/ROI_006_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKe'' + 46. '/acquisition/timeseries/ROI_007_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcil'' + 47. '/acquisition/timeseries/ROI_007_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiL'' + 48. '/acquisition/timeseries/ROI_008_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGS'' + 49. '/acquisition/timeseries/ROI_008_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHs'' + 50. '/acquisition/timeseries/ROI_009_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfz'' + 51. '/acquisition/timeseries/ROI_009_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfZ'' + 52. '/acquisition/timeseries/ROI_010_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzVCL'' + 53. '/acquisition/timeseries/ROI_010_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytWDl'' + 54. '/acquisition/timeseries/ROI_011_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCASbs'' + 55. '/acquisition/timeseries/ROI_011_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuTbS'' + 56. '/acquisition/timeseries/ROI_012_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBOzZ'' + 57. '/acquisition/timeseries/ROI_012_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvPAz'' + 58. '/acquisition/timeseries/ROI_013_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYG'' + 59. '/acquisition/timeseries/ROI_013_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZg'' + 60. '/acquisition/timeseries/ROI_014_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxn'' + 61. '/acquisition/timeseries/ROI_014_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxN'' + 62. '/acquisition/timeseries/ROI_015_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVU'' + 63. '/acquisition/timeseries/ROI_015_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWu'' + 64. '/acquisition/timeseries/ROI_016_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuB'' + 65. '/acquisition/timeseries/ROI_016_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBvb'' + 66. '/acquisition/timeseries/ROI_017_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTi'' + 67. '/acquisition/timeseries/ROI_017_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTI'' + 68. '/acquisition/timeseries/ROI_018_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrP'' + 69. '/acquisition/timeseries/ROI_018_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusp'' + 70. '/acquisition/timeseries/ROI_019_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQw'' + 71. '/acquisition/timeseries/ROI_019_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQW'' + 72. '/acquisition/timeseries/ROI_020_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnI'' + 73. '/acquisition/timeseries/ROI_020_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroi'' + 74. '/acquisition/timeseries/ROI_021_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMp'' + 75. '/acquisition/timeseries/ROI_021_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMP'' + 76. '/acquisition/timeseries/ROI_022_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkW'' + 77. '/acquisition/timeseries/ROI_022_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklw'' + 78. '/acquisition/timeseries/ROI_023_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJD'' + 79. '/acquisition/timeseries/ROI_023_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKd'' + 80. '/acquisition/timeseries/ROI_024_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcik'' + 81. '/acquisition/timeseries/ROI_024_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiK'' + 82. '/acquisition/timeseries/ROI_025_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGR'' + 83. '/acquisition/timeseries/ROI_025_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHr'' + 84. '/acquisition/timeseries/ROI_026_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfy'' + 85. '/acquisition/timeseries/ROI_026_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfY'' + 86. '/acquisition/timeseries/ROI_027_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREf'' + 87. '/acquisition/timeseries/ROI_027_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEF'' + 88. '/acquisition/timeseries/ROI_028_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcM'' + 89. '/acquisition/timeseries/ROI_028_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdm'' + 90. '/acquisition/timeseries/ROI_029_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBt'' + 91. '/acquisition/timeseries/ROI_029_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBT'' + 92. '/acquisition/timeseries/ROI_030_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYF'' + 93. '/acquisition/timeseries/ROI_030_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZf'' + 94. '/acquisition/timeseries/ROI_031_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxm'' + 95. '/acquisition/timeseries/ROI_031_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxM'' + 96. '/acquisition/timeseries/ROI_032_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVT'' + 97. '/acquisition/timeseries/ROI_032_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWt'' + 98. '/acquisition/timeseries/ROI_033_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuA'' + 99. '/acquisition/timeseries/ROI_033_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBva'' +100. '/acquisition/timeseries/ROI_034_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTh'' +101. '/acquisition/timeseries/ROI_034_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTH'' +102. '/acquisition/timeseries/ROI_035_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrO'' +103. '/acquisition/timeseries/ROI_035_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBuso'' +104. '/acquisition/timeseries/ROI_036_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQv'' +105. '/acquisition/timeseries/ROI_036_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQV'' +106. '/acquisition/timeseries/ROI_037_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpc'' +107. '/acquisition/timeseries/ROI_037_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpC'' +108. '/acquisition/timeseries/ROI_038_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNJ'' +109. '/acquisition/timeseries/ROI_038_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOj'' +110. '/acquisition/timeseries/ROI_039_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmq'' +111. '/acquisition/timeseries/ROI_039_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmQ'' +112. '/acquisition/timeseries/ROI_040_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJC'' +113. '/acquisition/timeseries/ROI_040_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKc'' +114. '/acquisition/timeseries/ROI_041_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcij'' +115. '/acquisition/timeseries/ROI_041_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiJ'' +116. '/acquisition/timeseries/ROI_042_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGQ'' +117. '/acquisition/timeseries/ROI_042_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHq'' +118. '/acquisition/timeseries/ROI_043_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfx'' +119. '/acquisition/timeseries/ROI_043_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfX'' +120. '/acquisition/timeseries/ROI_044_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREe'' +121. '/acquisition/timeseries/ROI_044_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEE'' +122. '/acquisition/timeseries/ROI_045_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcL'' +123. '/acquisition/timeseries/ROI_045_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdl'' +124. '/acquisition/timeseries/ROI_046_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBs'' +125. '/acquisition/timeseries/ROI_046_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBS'' +126. '/acquisition/timeseries/ROI_047_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZZ'' +127. '/acquisition/timeseries/ROI_047_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIaz'' +128. '/acquisition/timeseries/ROI_048_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyG'' +129. '/acquisition/timeseries/ROI_048_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzg'' +130. '/acquisition/timeseries/ROI_049_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXn'' +131. '/acquisition/timeseries/ROI_049_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXN'' +132. '/acquisition/timeseries/ROI_050_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuz'' +133. '/acquisition/timeseries/ROI_050_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBuZ'' +134. '/acquisition/timeseries/ROI_051_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTg'' +135. '/acquisition/timeseries/ROI_051_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTG'' +136. '/acquisition/timeseries/ROI_052_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrN'' +137. '/acquisition/timeseries/ROI_052_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusn'' +138. '/acquisition/timeseries/ROI_053_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQu'' +139. '/acquisition/timeseries/ROI_053_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQU'' +140. '/acquisition/timeseries/ROI_054_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpb'' +141. '/acquisition/timeseries/ROI_054_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpB'' +142. '/acquisition/timeseries/ROI_055_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNI'' +143. '/acquisition/timeseries/ROI_055_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOi'' +144. '/acquisition/timeseries/ROI_056_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmp'' +145. '/acquisition/timeseries/ROI_056_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmP'' +146. '/acquisition/timeseries/ROI_057_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKW'' +147. '/acquisition/timeseries/ROI_057_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLw'' +148. '/acquisition/timeseries/ROI_058_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjD'' +149. '/acquisition/timeseries/ROI_058_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkd'' +150. '/acquisition/timeseries/ROI_059_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIk'' +151. '/acquisition/timeseries/ROI_059_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIK'' +152. '/acquisition/timeseries/ROI_060_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfw'' +153. '/acquisition/timeseries/ROI_060_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfW'' +154. '/acquisition/timeseries/ROI_061_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREd'' +155. '/acquisition/timeseries/ROI_061_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSED'' +156. '/acquisition/timeseries/ROI_062_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcK'' +157. '/acquisition/timeseries/ROI_062_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdk'' +158. '/acquisition/timeseries/ROI_063_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBr'' +159. '/acquisition/timeseries/ROI_063_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBR'' +160. '/acquisition/timeseries/ROI_064_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZY'' +161. '/acquisition/timeseries/ROI_064_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIay'' +162. '/acquisition/timeseries/ROI_065_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyF'' +163. '/acquisition/timeseries/ROI_065_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzf'' +164. '/acquisition/timeseries/ROI_066_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXm'' +165. '/acquisition/timeseries/ROI_066_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXM'' +166. '/acquisition/timeseries/ROI_067_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNwvT'' +167. '/acquisition/timeseries/ROI_067_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHxwt'' +168. '/acquisition/timeseries/ROI_068_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCOsUA'' +169. '/acquisition/timeseries/ROI_068_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyItVa'' +170. '/acquisition/timeseries/ROI_069_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPpth'' +171. '/acquisition/timeseries/ROI_069_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJqtH'' +172. '/acquisition/timeseries/ROI_070_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQt'' +173. '/acquisition/timeseries/ROI_070_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQT'' +174. '/acquisition/timeseries/ROI_071_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpa'' +175. '/acquisition/timeseries/ROI_071_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpA'' +176. '/acquisition/timeseries/ROI_072_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNH'' +177. '/acquisition/timeseries/ROI_072_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOh'' +178. '/acquisition/timeseries/ROI_073_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmo'' +179. '/acquisition/timeseries/ROI_073_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmO'' +180. '/acquisition/timeseries/ROI_074_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKV'' +181. '/acquisition/timeseries/ROI_074_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLv'' +182. '/acquisition/timeseries/ROI_075_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjC'' +183. '/acquisition/timeseries/ROI_075_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkc'' +184. '/acquisition/timeseries/ROI_076_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIj'' +185. '/acquisition/timeseries/ROI_076_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIJ'' +186. '/acquisition/timeseries/ROI_077_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCORgQ'' +187. '/acquisition/timeseries/ROI_077_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyIShq'' +188. '/acquisition/timeseries/ROI_078_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPNFx'' +189. '/acquisition/timeseries/ROI_078_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJOFX'' +190. '/acquisition/timeseries/ROI_079_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCQKee'' +191. '/acquisition/timeseries/ROI_079_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyKLeE'' +192. '/acquisition/timeseries/ROI_080_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBq'' +193. '/acquisition/timeseries/ROI_080_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBQ'' +194. '/acquisition/timeseries/WhiskersCam ancestry: dtype=|S11, shape=(2,) size (22) val='["TimeSeries","ImageSeries"]'' +195. '/acquisition/timeseries/WhiskersCam comments: dtype=|S18, shape=() size (18) val='"Frame rate 1/300 s"'' +196. '/acquisition/timeseries/WhiskersCam description: dtype=|S35, shape=() size (35) val='"Video recording of mouse behaviour."'' +197. '/acquisition/timeseries/WhiskersCam help: dtype=|S45, shape=() size (45) val='"Storage object for time-series 2-D image data"'' +198. '/acquisition/timeseries/WhiskersCam neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +199. '/acquisition/timeseries/WhiskersCam source: dtype=|S28, shape=() size (28) val='"/general/devices/WhiskersCam"'' +200. '/acquisition/timeseries/WhiskersCam/external_file starting_frame: dtype=int64, shape=(2,) size (16) val='[0,64122]'' +201. '/acquisition/timeseries/WhiskersCam/timestamps interval: dtype=int32, shape=() size (4) val='1'' +202. '/acquisition/timeseries/WhiskersCam/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +203. '/acquisition/timeseries/Zstack_Green_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-49)' +204. '/acquisition/timeseries/Zstack_Green_# comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"' (#=1-49)' +205. '/acquisition/timeseries/Zstack_Green_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-49)' +206. '/acquisition/timeseries/Zstack_Green_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-49)' +207. '/acquisition/timeseries/Zstack_Green_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-49)' +208. '/acquisition/timeseries/Zstack_Green_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-49)' +209. '/acquisition/timeseries/Zstack_Green_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-49)' +210. '/acquisition/timeseries/Zstack_Green_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-49)' +211. '/acquisition/timeseries/Zstack_Green_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-49)' +212. '/acquisition/timeseries/Zstack_Green_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-49)' +213. '/acquisition/timeseries/Zstack_Green_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-49)' +214. '/acquisition/timeseries/Zstack_Green_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-49)' +215. '/acquisition/timeseries/Zstack_Red_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-49)' +216. '/acquisition/timeseries/Zstack_Red_# comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"' (#=1-49)' +217. '/acquisition/timeseries/Zstack_Red_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-49)' +218. '/acquisition/timeseries/Zstack_Red_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-49)' +219. '/acquisition/timeseries/Zstack_Red_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-49)' +220. '/acquisition/timeseries/Zstack_Red_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-49)' +221. '/acquisition/timeseries/Zstack_Red_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-49)' +222. '/acquisition/timeseries/Zstack_Red_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-49)' +223. '/acquisition/timeseries/Zstack_Red_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-49)' +224. '/acquisition/timeseries/Zstack_Red_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-49)' +225. '/acquisition/timeseries/Zstack_Red_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-49)' +226. '/acquisition/timeseries/Zstack_Red_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-49)' +227. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +228. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +229. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' +230. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' +231. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +232. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +233. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' +234. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' +235. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' +236. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' +237. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +238. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +239. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +240. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' +241. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' +242. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +243. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +244. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' +245. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' +246. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' +247. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' +248. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +249. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' +250. '/epochs/trial_# links: dtype=|S58, shape=(161,) size (9338) val='["'ROI_001_Green' is '/acquisition/timese...fUYCuY' (#=1-20)' +251. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-20)' +252. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' +253. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-49)' +254. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-49)' +255. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +256. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +257. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +258. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' +259. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +260. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +261. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' +262. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +263. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' +264. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +265. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' +266. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' +267. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' +268. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' +269. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' +270. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' +271. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' +272. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-2)' +273. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=1-2)' +274. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=3-7,76-80)' +275. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=3-7,76-80)' +276. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=8-10,31)' +277. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=8-10,31)' +278. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=14-16,29-30)' +279. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=14-16,29-30)' +280. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=11-13,17-25,51-60)' +281. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=11-13,17-25,51-60)' +282. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=26-28,32-37,45-50)' +283. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=26-28,32-37,45-50)' +284. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=38-44)' +285. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=38-44)' +286. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=61-65)' +287. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=61-65)' +288. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=66-67)' +289. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=66-67)' +290. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=68-75)' +291. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=68-75)' +292. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' +293. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +294. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +295. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +296. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +297. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +298. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +299. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +300. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +301. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +302. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +303. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +304. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +305. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 10628 datasets (sorted alphabetically) (867 combined): + 1. '/acquisition/timeseries/EyeCam/bits_per_pixel: dtype=int32, shape=() size (4) val='8'' + 2. '/acquisition/timeseries/EyeCam/dimension: dtype=int32, shape=(2,) size (16), compress=gzip val='[1280,960]'' + 3. '/acquisition/timeseries/EyeCam/external_file: dtype=|S44, shape=(1,) size (50), compress=gzip val='["161215_15_34_21 FunctAcq VidRec/EyeCam-1.avi"]'' + 4. '/acquisition/timeseries/EyeCam/format: dtype=|S8, shape=() size (8) val='"external"'' + 5. '/acquisition/timeseries/EyeCam/num_samples: dtype=int32, shape=() size (4) val='6304'' + 6. '/acquisition/timeseries/EyeCam/timestamps: dtype=float64, shape=(6304,) size (17842), compress=gzip val='[0,0.08,0.16,0.24,0.32,0.4,0.48,0.56,0.64...dJfrKc'' + 7. '/acquisition/timeseries/ROI_#_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-80)' + 8. '/acquisition/timeseries/ROI_#_Green/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-80)' + 9. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(175440, 1, 1) size (196115), compress=gzip val='[[[112]],[[113]],[[110]],[[159]],[[120]],...ghoYRS'' + 10. '/acquisition/timeseries/ROI_#_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-80)' + 11. '/acquisition/timeseries/ROI_#_Green/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-80)' + 12. '/acquisition/timeseries/ROI_#_Green/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-80)' + 13. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0027"' (#=1-2)' + 14. '/acquisition/timeseries/ROI_#_Green/num_samples: dtype=int32, shape=() size (4) val='175440' (#=1-80)' + 15. '/acquisition/timeseries/ROI_#_Green/pmt_gain: dtype=float32, shape=() size (4) val='715' (#=1-80)' + 16. '/acquisition/timeseries/ROI_#_Green/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-80)' + 17. '/acquisition/timeseries/ROI_#_Green/scan_line_rate: dtype=float32, shape=() size (4) val='348.7' (#=1-80)' + 18. '/acquisition/timeseries/ROI_#_Green/timestamps: dtype=float64, shape=(175440,) size (1046816), compress=gzip val='[0,0.002867,0.005735,0.008602,0.01147,0.0...bzxtxk' (#=1-80)' + 19. '/acquisition/timeseries/ROI_#_Red/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-80)' + 20. '/acquisition/timeseries/ROI_#_Red/channel: dtype=|S3, shape=() size (3) val='"Red"' (#=1-80)' + 21. '/acquisition/timeseries/ROI_001_Red/data: dtype=float32, shape=(175440, 1, 1) size (130665), compress=gzip val='[[[111]],[[112]],[[109]],[[113]],[[110]],...gNyPfP'' + 22. '/acquisition/timeseries/ROI_#_Red/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-80)' + 23. '/acquisition/timeseries/ROI_#_Red/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-80)' + 24. '/acquisition/timeseries/ROI_#_Red/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-80)' + 25. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0027"' (#=1-2)' + 26. '/acquisition/timeseries/ROI_#_Red/num_samples: dtype=int32, shape=() size (4) val='175440' (#=1-80)' + 27. '/acquisition/timeseries/ROI_#_Red/pmt_gain: dtype=float32, shape=() size (4) val='505' (#=1-80)' + 28. '/acquisition/timeseries/ROI_#_Red/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-80)' + 29. '/acquisition/timeseries/ROI_#_Red/scan_line_rate: dtype=float32, shape=() size (4) val='348.7' (#=1-80)' + 30. '/acquisition/timeseries/ROI_#_Red/timestamps: dtype=float64, shape=(175440,) size (1046816), compress=gzip val='[0,0.002867,0.005735,0.008602,0.01147,0.0...bzxtxk' (#=1-80)' + 31. '/acquisition/timeseries/ROI_002_Green/data: dtype=float32, shape=(175440, 1, 1) size (194769), compress=gzip val='[[[139]],[[117]],[[118]],[[128]],[[113]],...jIVlu'' + 32. '/acquisition/timeseries/ROI_002_Red/data: dtype=float32, shape=(175440, 1, 1) size (130017), compress=gzip val='[[[112]],[[107]],[[108]],[[111]],[[112]],...cRApRF'' + 33. '/acquisition/timeseries/ROI_003_Green/data: dtype=float32, shape=(175440, 1, 1) size (271773), compress=gzip val='[[[165]],[[154]],[[202]],[[170]],[[205]],...ijShvC'' + 34. 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'/epochs/trial_0009/stop_time: dtype=float64, shape=() size (8) val='226.5'' +404. '/epochs/trial_0010/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +405. '/epochs/trial_0010/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='78948' (#=1-80)' +406. '/epochs/trial_0010/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +407. '/epochs/trial_0010/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='78948' (#=1-80)' +408. '/epochs/trial_#/speed_data/count: dtype=int32, shape=() size (4) val='11727' (#=10,12-13,16,19-20)' +409. '/epochs/trial_0010/speed_data/idx_start: dtype=int32, shape=() size (4) val='105547'' +410. '/epochs/trial_0010/start_time: dtype=float64, shape=() size (8) val='226.5'' +411. '/epochs/trial_0010/stop_time: dtype=float64, shape=() size (8) val='251.7'' +412. '/epochs/trial_0011/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +413. '/epochs/trial_0011/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='87720' (#=1-80)' +414. '/epochs/trial_0011/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +415. '/epochs/trial_0011/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='87720' (#=1-80)' +416. '/epochs/trial_0011/speed_data/count: dtype=int32, shape=() size (4) val='11720'' +417. '/epochs/trial_0011/speed_data/idx_start: dtype=int32, shape=() size (4) val='117279'' +418. '/epochs/trial_0011/start_time: dtype=float64, shape=() size (8) val='251.7'' +419. '/epochs/trial_0011/stop_time: dtype=float64, shape=() size (8) val='276.9'' +420. '/epochs/trial_0012/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +421. '/epochs/trial_0012/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='96492' (#=1-80)' +422. '/epochs/trial_0012/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +423. '/epochs/trial_0012/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='96492' (#=1-80)' +424. '/epochs/trial_0012/speed_data/idx_start: dtype=int32, shape=() size (4) val='129004'' +425. '/epochs/trial_0012/start_time: dtype=float64, shape=() size (8) val='276.9'' +426. '/epochs/trial_0012/stop_time: dtype=float64, shape=() size (8) val='302'' +427. '/epochs/trial_0013/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +428. '/epochs/trial_0013/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='105264' (#=1-80)' +429. '/epochs/trial_0013/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +430. '/epochs/trial_0013/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='105264' (#=1-80)' +431. '/epochs/trial_0013/speed_data/idx_start: dtype=int32, shape=() size (4) val='140736'' +432. '/epochs/trial_0013/start_time: dtype=float64, shape=() size (8) val='302'' +433. '/epochs/trial_0013/stop_time: dtype=float64, shape=() size (8) val='327.2'' +434. '/epochs/trial_0014/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +435. '/epochs/trial_0014/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='114036' (#=1-80)' +436. '/epochs/trial_0014/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +437. '/epochs/trial_0014/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='114036' (#=1-80)' +438. '/epochs/trial_0014/speed_data/idx_start: dtype=int32, shape=() size (4) val='152467'' +439. '/epochs/trial_0014/start_time: dtype=float64, shape=() size (8) val='327.2'' +440. '/epochs/trial_0014/stop_time: dtype=float64, shape=() size (8) val='352.4'' +441. '/epochs/trial_0015/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +442. '/epochs/trial_0015/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='122808' (#=1-80)' +443. '/epochs/trial_0015/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +444. '/epochs/trial_0015/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='122808' (#=1-80)' +445. '/epochs/trial_0015/speed_data/idx_start: dtype=int32, shape=() size (4) val='164200'' +446. '/epochs/trial_0015/start_time: dtype=float64, shape=() size (8) val='352.4'' +447. '/epochs/trial_0015/stop_time: dtype=float64, shape=() size (8) val='377.5'' +448. '/epochs/trial_0016/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +449. '/epochs/trial_0016/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='131580' (#=1-80)' +450. '/epochs/trial_0016/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +451. '/epochs/trial_0016/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='131580' (#=1-80)' +452. '/epochs/trial_0016/speed_data/idx_start: dtype=int32, shape=() size (4) val='175925'' +453. '/epochs/trial_0016/start_time: dtype=float64, shape=() size (8) val='377.5'' +454. '/epochs/trial_0016/stop_time: dtype=float64, shape=() size (8) val='402.7'' +455. '/epochs/trial_0017/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +456. '/epochs/trial_0017/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='140352' (#=1-80)' +457. '/epochs/trial_0017/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +458. '/epochs/trial_0017/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='140352' (#=1-80)' +459. '/epochs/trial_0017/speed_data/idx_start: dtype=int32, shape=() size (4) val='187656'' +460. '/epochs/trial_0017/start_time: dtype=float64, shape=() size (8) val='402.7'' +461. '/epochs/trial_0017/stop_time: dtype=float64, shape=() size (8) val='427.9'' +462. '/epochs/trial_0018/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +463. '/epochs/trial_0018/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='149124' (#=1-80)' +464. '/epochs/trial_0018/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +465. '/epochs/trial_0018/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='149124' (#=1-80)' +466. '/epochs/trial_0018/speed_data/idx_start: dtype=int32, shape=() size (4) val='199388'' +467. '/epochs/trial_0018/start_time: dtype=float64, shape=() size (8) val='427.9'' +468. '/epochs/trial_0018/stop_time: dtype=float64, shape=() size (8) val='453'' +469. '/epochs/trial_0019/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +470. '/epochs/trial_0019/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='157896' (#=1-80)' +471. '/epochs/trial_0019/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +472. '/epochs/trial_0019/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='157896' (#=1-80)' +473. '/epochs/trial_0019/speed_data/idx_start: dtype=int32, shape=() size (4) val='211114'' +474. '/epochs/trial_0019/start_time: dtype=float64, shape=() size (8) val='453'' +475. '/epochs/trial_0019/stop_time: dtype=float64, shape=() size (8) val='478.2'' +476. '/epochs/trial_0020/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +477. '/epochs/trial_0020/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='166668' (#=1-80)' +478. '/epochs/trial_0020/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +479. '/epochs/trial_0020/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='166668' (#=1-80)' +480. '/epochs/trial_0020/speed_data/idx_start: dtype=int32, shape=() size (4) val='222846'' +481. '/epochs/trial_0020/start_time: dtype=float64, shape=() size (8) val='478.2'' +482. '/epochs/trial_0020/stop_time: dtype=float64, shape=() size (8) val='503.4'' +483. 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'/general/experimenter: dtype=|S8, shape=() size (8) val='"Hana Ros"'' +492. '/general/institution: dtype=|S25, shape=() size (25) val='"University College London"'' +493. '/general/lab: dtype=|S33, shape=() size (33) val='"Silver Lab (http://silverlab.org)"'' +494. '/general/labview_header: dtype=|S37, shape=(31, 3) size (639), compress=gzip val='[["LOGIN","User",""Hana""],["LOGIN","Prof...cTjtgC'' +495. '/general/notes: dtype=|S62, shape=() size (62) val='"Notes about the experiment that don't fi...jyjZeD'' +496. '/general/optophysiology/Zstack#/description: dtype=|S17, shape=() size (17) val='"Reference Z stack"' (#=1-49)' +497. '/general/optophysiology/Zstack#/device: dtype=|S14, shape=() size (14) val='"AOL_microscope"' (#=1-49)' +498. '/general/optophysiology/Zstack#/excitation_lambda: dtype=|S22, shape=() size (22) val='"Excitation wavelength."' (#=1-49)' +499. 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'/stimulus/presentation/air_puff/num_samples: dtype=int32, shape=() size (4) val='20'' +867. '/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(20,) size (171), compress=gzip val='[5,30.17,55.34,80.51,105.7,130.8,156,181....eMYOkH'' +-------------------- +** Summary +3767 groups, 10628 datasets, 3627 attributes diff --git a/Python/test/data/161215_15_58_52.sig b/Python/test/data/161215_15_58_52.sig new file mode 100644 index 0000000..b03a300 --- /dev/null +++ b/Python/test/data/161215_15_58_52.sig @@ -0,0 +1,1768 @@ +<% Generating signature for 161215_15_58_52.nwb %> + +** No datasets hard links. +** No groups hard links. +** 91 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0022/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0022/description' + 2. 'to: "/general/optophysiology/Zstack0025/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0025/description' + 3. 'to: "/general/optophysiology/Zstack0028/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0028/description' + 4. 'to: "/general/optophysiology/Zstack0029/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/description' + 5. 'to: "/general/optophysiology/Zstack0032/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/description' + 6. 'to: "/general/optophysiology/Zstack0033/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/description' + 7. 'to: "/general/optophysiology/Zstack0034/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/description' + 8. 'to: "/general/optophysiology/Zstack0035/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/description' + 9. 'to: "/general/optophysiology/Zstack0039/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0039/description' + 10. 'to: "/general/optophysiology/Zstack0040/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0040/description' + 11. 'to: "/general/optophysiology/Zstack0046/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0046/description' + 12. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_079/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_079_Green/pixel_time_offsets + /acquisition/timeseries/ROI_079_Red/pixel_time_offsets' + 13. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_080/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_080_Green/pixel_time_offsets + /acquisition/timeseries/ROI_080_Red/pixel_time_offsets' + 14. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' + 15. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_002/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_002_Green/pixel_time_offsets + /acquisition/timeseries/ROI_002_Red/pixel_time_offsets' + 16. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_009/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_009_Green/pixel_time_offsets + /acquisition/timeseries/ROI_009_Red/pixel_time_offsets' + 17. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_010/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_010_Green/pixel_time_offsets + /acquisition/timeseries/ROI_010_Red/pixel_time_offsets' + 18. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_011/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_011_Green/pixel_time_offsets + /acquisition/timeseries/ROI_011_Red/pixel_time_offsets' + 19. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_012/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_012_Green/pixel_time_offsets + /acquisition/timeseries/ROI_012_Red/pixel_time_offsets' + 20. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_013/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_013_Green/pixel_time_offsets + /acquisition/timeseries/ROI_013_Red/pixel_time_offsets' + 21. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_003/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_003_Green/pixel_time_offsets + /acquisition/timeseries/ROI_003_Red/pixel_time_offsets' + 22. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_004/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_004_Green/pixel_time_offsets + /acquisition/timeseries/ROI_004_Red/pixel_time_offsets' + 23. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_005/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_005_Green/pixel_time_offsets + /acquisition/timeseries/ROI_005_Red/pixel_time_offsets' + 24. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_006/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_006_Green/pixel_time_offsets + /acquisition/timeseries/ROI_006_Red/pixel_time_offsets' + 25. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_007/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_007_Green/pixel_time_offsets + /acquisition/timeseries/ROI_007_Red/pixel_time_offsets' + 26. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_008/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_008_Green/pixel_time_offsets + /acquisition/timeseries/ROI_008_Red/pixel_time_offsets' + 27. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_050/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_050_Green/pixel_time_offsets + /acquisition/timeseries/ROI_050_Red/pixel_time_offsets' + 28. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_051/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_051_Green/pixel_time_offsets + /acquisition/timeseries/ROI_051_Red/pixel_time_offsets' + 29. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_014/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_014_Green/pixel_time_offsets + /acquisition/timeseries/ROI_014_Red/pixel_time_offsets' + 30. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_015/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_015_Green/pixel_time_offsets + /acquisition/timeseries/ROI_015_Red/pixel_time_offsets' + 31. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_016/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_016_Green/pixel_time_offsets + /acquisition/timeseries/ROI_016_Red/pixel_time_offsets' + 32. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_033/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_033_Green/pixel_time_offsets + /acquisition/timeseries/ROI_033_Red/pixel_time_offsets' + 33. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_034/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_034_Green/pixel_time_offsets + /acquisition/timeseries/ROI_034_Red/pixel_time_offsets' + 34. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_035/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_035_Green/pixel_time_offsets + /acquisition/timeseries/ROI_035_Red/pixel_time_offsets' + 35. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_036/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_036_Green/pixel_time_offsets + /acquisition/timeseries/ROI_036_Red/pixel_time_offsets' + 36. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_037/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_037_Green/pixel_time_offsets + /acquisition/timeseries/ROI_037_Red/pixel_time_offsets' + 37. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_038/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_038_Green/pixel_time_offsets + /acquisition/timeseries/ROI_038_Red/pixel_time_offsets' + 38. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_039/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_039_Green/pixel_time_offsets + /acquisition/timeseries/ROI_039_Red/pixel_time_offsets' + 39. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_040/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_040_Green/pixel_time_offsets + /acquisition/timeseries/ROI_040_Red/pixel_time_offsets' + 40. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_041/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_041_Green/pixel_time_offsets + /acquisition/timeseries/ROI_041_Red/pixel_time_offsets' + 41. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_042/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_042_Green/pixel_time_offsets + /acquisition/timeseries/ROI_042_Red/pixel_time_offsets' + 42. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_043/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_043_Green/pixel_time_offsets + /acquisition/timeseries/ROI_043_Red/pixel_time_offsets' + 43. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_044/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_044_Green/pixel_time_offsets + /acquisition/timeseries/ROI_044_Red/pixel_time_offsets' + 44. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_052/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_052_Green/pixel_time_offsets + /acquisition/timeseries/ROI_052_Red/pixel_time_offsets' + 45. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_053/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_053_Green/pixel_time_offsets + /acquisition/timeseries/ROI_053_Red/pixel_time_offsets' + 46. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_054/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_054_Green/pixel_time_offsets + /acquisition/timeseries/ROI_054_Red/pixel_time_offsets' + 47. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_055/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_055_Green/pixel_time_offsets + /acquisition/timeseries/ROI_055_Red/pixel_time_offsets' + 48. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_078/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_078_Green/pixel_time_offsets + /acquisition/timeseries/ROI_078_Red/pixel_time_offsets' + 49. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_017/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_017_Green/pixel_time_offsets + /acquisition/timeseries/ROI_017_Red/pixel_time_offsets' + 50. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_018/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_018_Green/pixel_time_offsets + /acquisition/timeseries/ROI_018_Red/pixel_time_offsets' + 51. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_019/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_019_Green/pixel_time_offsets + /acquisition/timeseries/ROI_019_Red/pixel_time_offsets' + 52. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_020/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_020_Green/pixel_time_offsets + /acquisition/timeseries/ROI_020_Red/pixel_time_offsets' + 53. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_021/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_021_Green/pixel_time_offsets + /acquisition/timeseries/ROI_021_Red/pixel_time_offsets' + 54. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_022/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_022_Green/pixel_time_offsets + /acquisition/timeseries/ROI_022_Red/pixel_time_offsets' + 55. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_023/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_023_Green/pixel_time_offsets + /acquisition/timeseries/ROI_023_Red/pixel_time_offsets' + 56. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_024/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_024_Green/pixel_time_offsets + /acquisition/timeseries/ROI_024_Red/pixel_time_offsets' + 57. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_025/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_025_Green/pixel_time_offsets + /acquisition/timeseries/ROI_025_Red/pixel_time_offsets' + 58. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_026/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_026_Green/pixel_time_offsets + /acquisition/timeseries/ROI_026_Red/pixel_time_offsets' + 59. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_045/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_045_Green/pixel_time_offsets + /acquisition/timeseries/ROI_045_Red/pixel_time_offsets' + 60. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_046/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_046_Green/pixel_time_offsets + /acquisition/timeseries/ROI_046_Red/pixel_time_offsets' + 61. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_047/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_047_Green/pixel_time_offsets + /acquisition/timeseries/ROI_047_Red/pixel_time_offsets' + 62. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_048/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_048_Green/pixel_time_offsets + /acquisition/timeseries/ROI_048_Red/pixel_time_offsets' + 63. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_056/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_056_Green/pixel_time_offsets + /acquisition/timeseries/ROI_056_Red/pixel_time_offsets' + 64. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_057/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_057_Green/pixel_time_offsets + /acquisition/timeseries/ROI_057_Red/pixel_time_offsets' + 65. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_058/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_058_Green/pixel_time_offsets + /acquisition/timeseries/ROI_058_Red/pixel_time_offsets' + 66. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_059/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_059_Green/pixel_time_offsets + /acquisition/timeseries/ROI_059_Red/pixel_time_offsets' + 67. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_060/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_060_Green/pixel_time_offsets + /acquisition/timeseries/ROI_060_Red/pixel_time_offsets' + 68. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_061/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_061_Green/pixel_time_offsets + /acquisition/timeseries/ROI_061_Red/pixel_time_offsets' + 69. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_062/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_062_Green/pixel_time_offsets + /acquisition/timeseries/ROI_062_Red/pixel_time_offsets' + 70. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_027/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_027_Green/pixel_time_offsets + /acquisition/timeseries/ROI_027_Red/pixel_time_offsets' + 71. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_028/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_028_Green/pixel_time_offsets + /acquisition/timeseries/ROI_028_Red/pixel_time_offsets' + 72. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_029/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_029_Green/pixel_time_offsets + /acquisition/timeseries/ROI_029_Red/pixel_time_offsets' + 73. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_030/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_030_Green/pixel_time_offsets + /acquisition/timeseries/ROI_030_Red/pixel_time_offsets' + 74. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_031/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_031_Green/pixel_time_offsets + /acquisition/timeseries/ROI_031_Red/pixel_time_offsets' + 75. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_032/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_032_Green/pixel_time_offsets + /acquisition/timeseries/ROI_032_Red/pixel_time_offsets' + 76. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_049/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_049_Green/pixel_time_offsets + /acquisition/timeseries/ROI_049_Red/pixel_time_offsets' + 77. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_063/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_063_Green/pixel_time_offsets + /acquisition/timeseries/ROI_063_Red/pixel_time_offsets' + 78. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_064/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_064_Green/pixel_time_offsets + /acquisition/timeseries/ROI_064_Red/pixel_time_offsets' + 79. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_065/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_065_Green/pixel_time_offsets + /acquisition/timeseries/ROI_065_Red/pixel_time_offsets' + 80. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_066/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_066_Green/pixel_time_offsets + /acquisition/timeseries/ROI_066_Red/pixel_time_offsets' + 81. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_067/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_067_Green/pixel_time_offsets + /acquisition/timeseries/ROI_067_Red/pixel_time_offsets' + 82. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_068/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_068_Green/pixel_time_offsets + /acquisition/timeseries/ROI_068_Red/pixel_time_offsets' + 83. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_069/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_069_Green/pixel_time_offsets + /acquisition/timeseries/ROI_069_Red/pixel_time_offsets' + 84. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_074/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_074_Green/pixel_time_offsets + /acquisition/timeseries/ROI_074_Red/pixel_time_offsets' + 85. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_075/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_075_Green/pixel_time_offsets + /acquisition/timeseries/ROI_075_Red/pixel_time_offsets' + 86. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_070/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_070_Green/pixel_time_offsets + /acquisition/timeseries/ROI_070_Red/pixel_time_offsets' + 87. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_071/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_071_Green/pixel_time_offsets + /acquisition/timeseries/ROI_071_Red/pixel_time_offsets' + 88. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_072/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_072_Green/pixel_time_offsets + /acquisition/timeseries/ROI_072_Red/pixel_time_offsets' + 89. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_073/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_073_Green/pixel_time_offsets + /acquisition/timeseries/ROI_073_Red/pixel_time_offsets' + 90. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_076/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_076_Green/pixel_time_offsets + /acquisition/timeseries/ROI_076_Red/pixel_time_offsets' + 91. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_077/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_077_Green/pixel_time_offsets + /acquisition/timeseries/ROI_077_Red/pixel_time_offsets' +** 172 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-20)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-20)' + 3. 'to: "/acquisition/timeseries/ROI_002_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_002_Green/timeseries (#=1-20)' + 4. 'to: "/acquisition/timeseries/ROI_002_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_002_Red/timeseries (#=1-20)' + 5. 'to: "/acquisition/timeseries/ROI_003_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_003_Green/timeseries (#=1-20)' + 6. 'to: "/acquisition/timeseries/ROI_003_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_003_Red/timeseries (#=1-20)' + 7. 'to: "/acquisition/timeseries/ROI_004_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_004_Green/timeseries (#=1-20)' + 8. 'to: "/acquisition/timeseries/ROI_004_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_004_Red/timeseries (#=1-20)' + 9. 'to: "/acquisition/timeseries/ROI_005_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_005_Green/timeseries (#=1-20)' + 10. 'to: "/acquisition/timeseries/ROI_005_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_005_Red/timeseries (#=1-20)' + 11. 'to: "/acquisition/timeseries/ROI_006_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_006_Green/timeseries (#=1-20)' + 12. 'to: "/acquisition/timeseries/ROI_006_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_006_Red/timeseries (#=1-20)' + 13. 'to: "/acquisition/timeseries/ROI_007_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_007_Green/timeseries (#=1-20)' + 14. 'to: "/acquisition/timeseries/ROI_007_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_007_Red/timeseries (#=1-20)' + 15. 'to: "/acquisition/timeseries/ROI_008_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_008_Green/timeseries (#=1-20)' + 16. 'to: "/acquisition/timeseries/ROI_008_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_008_Red/timeseries (#=1-20)' + 17. 'to: "/acquisition/timeseries/ROI_009_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_009_Green/timeseries (#=1-20)' + 18. 'to: "/acquisition/timeseries/ROI_009_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_009_Red/timeseries (#=1-20)' + 19. 'to: "/acquisition/timeseries/ROI_010_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_010_Green/timeseries (#=1-20)' + 20. 'to: "/acquisition/timeseries/ROI_010_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_010_Red/timeseries (#=1-20)' + 21. 'to: "/acquisition/timeseries/ROI_011_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_011_Green/timeseries (#=1-20)' + 22. 'to: "/acquisition/timeseries/ROI_011_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_011_Red/timeseries (#=1-20)' + 23. 'to: "/acquisition/timeseries/ROI_012_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_012_Green/timeseries (#=1-20)' + 24. 'to: "/acquisition/timeseries/ROI_012_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_012_Red/timeseries (#=1-20)' + 25. 'to: "/acquisition/timeseries/ROI_013_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_013_Green/timeseries (#=1-20)' + 26. 'to: "/acquisition/timeseries/ROI_013_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_013_Red/timeseries (#=1-20)' + 27. 'to: "/acquisition/timeseries/ROI_014_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_014_Green/timeseries (#=1-20)' + 28. 'to: "/acquisition/timeseries/ROI_014_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_014_Red/timeseries (#=1-20)' + 29. 'to: "/acquisition/timeseries/ROI_015_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_015_Green/timeseries (#=1-20)' + 30. 'to: "/acquisition/timeseries/ROI_015_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_015_Red/timeseries (#=1-20)' + 31. 'to: "/acquisition/timeseries/ROI_016_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_016_Green/timeseries (#=1-20)' + 32. 'to: "/acquisition/timeseries/ROI_016_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_016_Red/timeseries (#=1-20)' + 33. 'to: "/acquisition/timeseries/ROI_017_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_017_Green/timeseries (#=1-20)' + 34. 'to: "/acquisition/timeseries/ROI_017_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_017_Red/timeseries (#=1-20)' + 35. 'to: "/acquisition/timeseries/ROI_018_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_018_Green/timeseries (#=1-20)' + 36. 'to: "/acquisition/timeseries/ROI_018_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_018_Red/timeseries (#=1-20)' + 37. 'to: "/acquisition/timeseries/ROI_019_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_019_Green/timeseries (#=1-20)' + 38. 'to: "/acquisition/timeseries/ROI_019_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_019_Red/timeseries (#=1-20)' + 39. 'to: "/acquisition/timeseries/ROI_020_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_020_Green/timeseries (#=1-20)' + 40. 'to: "/acquisition/timeseries/ROI_020_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_020_Red/timeseries (#=1-20)' + 41. 'to: "/acquisition/timeseries/ROI_021_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_021_Green/timeseries (#=1-20)' + 42. 'to: "/acquisition/timeseries/ROI_021_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_021_Red/timeseries (#=1-20)' + 43. 'to: "/acquisition/timeseries/ROI_022_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_022_Green/timeseries (#=1-20)' + 44. 'to: "/acquisition/timeseries/ROI_022_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_022_Red/timeseries (#=1-20)' + 45. 'to: "/acquisition/timeseries/ROI_023_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_023_Green/timeseries (#=1-20)' + 46. 'to: "/acquisition/timeseries/ROI_023_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_023_Red/timeseries (#=1-20)' + 47. 'to: "/acquisition/timeseries/ROI_024_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_024_Green/timeseries (#=1-20)' + 48. 'to: "/acquisition/timeseries/ROI_024_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_024_Red/timeseries (#=1-20)' + 49. 'to: "/acquisition/timeseries/ROI_025_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_025_Green/timeseries (#=1-20)' + 50. 'to: "/acquisition/timeseries/ROI_025_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_025_Red/timeseries (#=1-20)' + 51. 'to: "/acquisition/timeseries/ROI_026_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_026_Green/timeseries (#=1-20)' + 52. 'to: "/acquisition/timeseries/ROI_026_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_026_Red/timeseries (#=1-20)' + 53. 'to: "/acquisition/timeseries/ROI_027_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_027_Green/timeseries (#=1-20)' + 54. 'to: "/acquisition/timeseries/ROI_027_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_027_Red/timeseries (#=1-20)' + 55. 'to: "/acquisition/timeseries/ROI_028_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_028_Green/timeseries (#=1-20)' + 56. 'to: "/acquisition/timeseries/ROI_028_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_028_Red/timeseries (#=1-20)' + 57. 'to: "/acquisition/timeseries/ROI_029_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_029_Green/timeseries (#=1-20)' + 58. 'to: "/acquisition/timeseries/ROI_029_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_029_Red/timeseries (#=1-20)' + 59. 'to: "/acquisition/timeseries/ROI_030_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_030_Green/timeseries (#=1-20)' + 60. 'to: "/acquisition/timeseries/ROI_030_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_030_Red/timeseries (#=1-20)' + 61. 'to: "/acquisition/timeseries/ROI_031_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_031_Green/timeseries (#=1-20)' + 62. 'to: "/acquisition/timeseries/ROI_031_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_031_Red/timeseries (#=1-20)' + 63. 'to: "/acquisition/timeseries/ROI_032_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_032_Green/timeseries (#=1-20)' + 64. 'to: "/acquisition/timeseries/ROI_032_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_032_Red/timeseries (#=1-20)' + 65. 'to: "/acquisition/timeseries/ROI_033_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_033_Green/timeseries (#=1-20)' + 66. 'to: "/acquisition/timeseries/ROI_033_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_033_Red/timeseries (#=1-20)' + 67. 'to: "/acquisition/timeseries/ROI_034_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_034_Green/timeseries (#=1-20)' + 68. 'to: "/acquisition/timeseries/ROI_034_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_034_Red/timeseries (#=1-20)' + 69. 'to: "/acquisition/timeseries/ROI_035_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_035_Green/timeseries (#=1-20)' + 70. 'to: "/acquisition/timeseries/ROI_035_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_035_Red/timeseries (#=1-20)' + 71. 'to: "/acquisition/timeseries/ROI_036_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_036_Green/timeseries (#=1-20)' + 72. 'to: "/acquisition/timeseries/ROI_036_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_036_Red/timeseries (#=1-20)' + 73. 'to: "/acquisition/timeseries/ROI_037_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_037_Green/timeseries (#=1-20)' + 74. 'to: "/acquisition/timeseries/ROI_037_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_037_Red/timeseries (#=1-20)' + 75. 'to: "/acquisition/timeseries/ROI_038_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_038_Green/timeseries (#=1-20)' + 76. 'to: "/acquisition/timeseries/ROI_038_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_038_Red/timeseries (#=1-20)' + 77. 'to: "/acquisition/timeseries/ROI_039_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_039_Green/timeseries (#=1-20)' + 78. 'to: "/acquisition/timeseries/ROI_039_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_039_Red/timeseries (#=1-20)' + 79. 'to: "/acquisition/timeseries/ROI_040_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_040_Green/timeseries (#=1-20)' + 80. 'to: "/acquisition/timeseries/ROI_040_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_040_Red/timeseries (#=1-20)' + 81. 'to: "/acquisition/timeseries/ROI_041_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_041_Green/timeseries (#=1-20)' + 82. 'to: "/acquisition/timeseries/ROI_041_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_041_Red/timeseries (#=1-20)' + 83. 'to: "/acquisition/timeseries/ROI_042_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_042_Green/timeseries (#=1-20)' + 84. 'to: "/acquisition/timeseries/ROI_042_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_042_Red/timeseries (#=1-20)' + 85. 'to: "/acquisition/timeseries/ROI_043_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_043_Green/timeseries (#=1-20)' + 86. 'to: "/acquisition/timeseries/ROI_043_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_043_Red/timeseries (#=1-20)' + 87. 'to: "/acquisition/timeseries/ROI_044_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_044_Green/timeseries (#=1-20)' + 88. 'to: "/acquisition/timeseries/ROI_044_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_044_Red/timeseries (#=1-20)' + 89. 'to: "/acquisition/timeseries/ROI_045_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_045_Green/timeseries (#=1-20)' + 90. 'to: "/acquisition/timeseries/ROI_045_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_045_Red/timeseries (#=1-20)' + 91. 'to: "/acquisition/timeseries/ROI_046_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_046_Green/timeseries (#=1-20)' + 92. 'to: "/acquisition/timeseries/ROI_046_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_046_Red/timeseries (#=1-20)' + 93. 'to: "/acquisition/timeseries/ROI_047_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_047_Green/timeseries (#=1-20)' + 94. 'to: "/acquisition/timeseries/ROI_047_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_047_Red/timeseries (#=1-20)' + 95. 'to: "/acquisition/timeseries/ROI_048_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_048_Green/timeseries (#=1-20)' + 96. 'to: "/acquisition/timeseries/ROI_048_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_048_Red/timeseries (#=1-20)' + 97. 'to: "/acquisition/timeseries/ROI_049_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_049_Green/timeseries (#=1-20)' + 98. 'to: "/acquisition/timeseries/ROI_049_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_049_Red/timeseries (#=1-20)' + 99. 'to: "/acquisition/timeseries/ROI_050_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_050_Green/timeseries (#=1-20)' +100. 'to: "/acquisition/timeseries/ROI_050_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_050_Red/timeseries (#=1-20)' +101. 'to: "/acquisition/timeseries/ROI_051_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_051_Green/timeseries (#=1-20)' +102. 'to: "/acquisition/timeseries/ROI_051_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_051_Red/timeseries (#=1-20)' +103. 'to: "/acquisition/timeseries/ROI_052_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_052_Green/timeseries (#=1-20)' +104. 'to: "/acquisition/timeseries/ROI_052_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_052_Red/timeseries (#=1-20)' +105. 'to: "/acquisition/timeseries/ROI_053_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_053_Green/timeseries (#=1-20)' +106. 'to: "/acquisition/timeseries/ROI_053_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_053_Red/timeseries (#=1-20)' +107. 'to: "/acquisition/timeseries/ROI_054_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_054_Green/timeseries (#=1-20)' +108. 'to: "/acquisition/timeseries/ROI_054_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_054_Red/timeseries (#=1-20)' +109. 'to: "/acquisition/timeseries/ROI_055_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_055_Green/timeseries (#=1-20)' +110. 'to: "/acquisition/timeseries/ROI_055_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_055_Red/timeseries (#=1-20)' +111. 'to: "/acquisition/timeseries/ROI_056_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_056_Green/timeseries (#=1-20)' +112. 'to: "/acquisition/timeseries/ROI_056_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_056_Red/timeseries (#=1-20)' +113. 'to: "/acquisition/timeseries/ROI_057_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_057_Green/timeseries (#=1-20)' +114. 'to: "/acquisition/timeseries/ROI_057_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_057_Red/timeseries (#=1-20)' +115. 'to: "/acquisition/timeseries/ROI_058_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_058_Green/timeseries (#=1-20)' +116. 'to: "/acquisition/timeseries/ROI_058_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_058_Red/timeseries (#=1-20)' +117. 'to: "/acquisition/timeseries/ROI_059_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_059_Green/timeseries (#=1-20)' +118. 'to: "/acquisition/timeseries/ROI_059_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_059_Red/timeseries (#=1-20)' +119. 'to: "/acquisition/timeseries/ROI_060_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_060_Green/timeseries (#=1-20)' +120. 'to: "/acquisition/timeseries/ROI_060_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_060_Red/timeseries (#=1-20)' +121. 'to: "/acquisition/timeseries/ROI_061_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_061_Green/timeseries (#=1-20)' +122. 'to: "/acquisition/timeseries/ROI_061_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_061_Red/timeseries (#=1-20)' +123. 'to: "/acquisition/timeseries/ROI_062_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_062_Green/timeseries (#=1-20)' +124. 'to: "/acquisition/timeseries/ROI_062_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_062_Red/timeseries (#=1-20)' +125. 'to: "/acquisition/timeseries/ROI_063_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_063_Green/timeseries (#=1-20)' +126. 'to: "/acquisition/timeseries/ROI_063_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_063_Red/timeseries (#=1-20)' +127. 'to: "/acquisition/timeseries/ROI_064_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_064_Green/timeseries (#=1-20)' +128. 'to: "/acquisition/timeseries/ROI_064_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_064_Red/timeseries (#=1-20)' +129. 'to: "/acquisition/timeseries/ROI_065_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_065_Green/timeseries (#=1-20)' +130. 'to: "/acquisition/timeseries/ROI_065_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_065_Red/timeseries (#=1-20)' +131. 'to: "/acquisition/timeseries/ROI_066_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_066_Green/timeseries (#=1-20)' +132. 'to: "/acquisition/timeseries/ROI_066_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_066_Red/timeseries (#=1-20)' +133. 'to: "/acquisition/timeseries/ROI_067_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_067_Green/timeseries (#=1-20)' +134. 'to: "/acquisition/timeseries/ROI_067_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_067_Red/timeseries (#=1-20)' +135. 'to: "/acquisition/timeseries/ROI_068_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_068_Green/timeseries (#=1-20)' +136. 'to: "/acquisition/timeseries/ROI_068_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_068_Red/timeseries (#=1-20)' +137. 'to: "/acquisition/timeseries/ROI_069_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_069_Green/timeseries (#=1-20)' +138. 'to: "/acquisition/timeseries/ROI_069_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_069_Red/timeseries (#=1-20)' +139. 'to: "/acquisition/timeseries/ROI_070_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_070_Green/timeseries (#=1-20)' +140. 'to: "/acquisition/timeseries/ROI_070_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_070_Red/timeseries (#=1-20)' +141. 'to: "/acquisition/timeseries/ROI_071_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_071_Green/timeseries (#=1-20)' +142. 'to: "/acquisition/timeseries/ROI_071_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_071_Red/timeseries (#=1-20)' +143. 'to: "/acquisition/timeseries/ROI_072_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_072_Green/timeseries (#=1-20)' +144. 'to: "/acquisition/timeseries/ROI_072_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_072_Red/timeseries (#=1-20)' +145. 'to: "/acquisition/timeseries/ROI_073_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_073_Green/timeseries (#=1-20)' +146. 'to: "/acquisition/timeseries/ROI_073_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_073_Red/timeseries (#=1-20)' +147. 'to: "/acquisition/timeseries/ROI_074_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_074_Green/timeseries (#=1-20)' +148. 'to: "/acquisition/timeseries/ROI_074_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_074_Red/timeseries (#=1-20)' +149. 'to: "/acquisition/timeseries/ROI_075_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_075_Green/timeseries (#=1-20)' +150. 'to: "/acquisition/timeseries/ROI_075_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_075_Red/timeseries (#=1-20)' +151. 'to: "/acquisition/timeseries/ROI_076_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_076_Green/timeseries (#=1-20)' +152. 'to: "/acquisition/timeseries/ROI_076_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_076_Red/timeseries (#=1-20)' +153. 'to: "/acquisition/timeseries/ROI_077_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_077_Green/timeseries (#=1-20)' +154. 'to: "/acquisition/timeseries/ROI_077_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_077_Red/timeseries (#=1-20)' +155. 'to: "/acquisition/timeseries/ROI_078_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_078_Green/timeseries (#=1-20)' +156. 'to: "/acquisition/timeseries/ROI_078_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_078_Red/timeseries (#=1-20)' +157. 'to: "/acquisition/timeseries/ROI_079_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_079_Green/timeseries (#=1-20)' +158. 'to: "/acquisition/timeseries/ROI_079_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_079_Red/timeseries (#=1-20)' +159. 'to: "/acquisition/timeseries/ROI_080_Green" 20 groups (1 combined): + /epochs/trial_#/ROI_080_Green/timeseries (#=1-20)' +160. 'to: "/acquisition/timeseries/ROI_080_Red" 20 groups (1 combined): + /epochs/trial_#/ROI_080_Red/timeseries (#=1-20)' +161. 'to: "/acquisition/timeseries/Zstack_Red_0022" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0022/reference_images/Zstack_image' +162. 'to: "/acquisition/timeseries/Zstack_Red_0025" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0025/reference_images/Zstack_image' +163. 'to: "/acquisition/timeseries/Zstack_Red_0028" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0028/reference_images/Zstack_image' +164. 'to: "/acquisition/timeseries/Zstack_Red_0029" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/reference_images/Zstack_image' +165. 'to: "/acquisition/timeseries/Zstack_Red_0032" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/reference_images/Zstack_image' +166. 'to: "/acquisition/timeseries/Zstack_Red_0033" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/reference_images/Zstack_image' +167. 'to: "/acquisition/timeseries/Zstack_Red_0034" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/reference_images/Zstack_image' +168. 'to: "/acquisition/timeseries/Zstack_Red_0035" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/reference_images/Zstack_image' +169. 'to: "/acquisition/timeseries/Zstack_Red_0039" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0039/reference_images/Zstack_image' +170. 'to: "/acquisition/timeseries/Zstack_Red_0040" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0040/reference_images/Zstack_image' +171. 'to: "/acquisition/timeseries/Zstack_Red_0046" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0046/reference_images/Zstack_image' +172. 'to: "/acquisition/timeseries/speed_data" 20 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-20)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 3609 attributes (sorted alphabetically) (289 combined): + 1. '/acquisition/timeseries/ROI_#_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-80)' + 2. '/acquisition/timeseries/ROI_#_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-80)' + 3. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 4. '/acquisition/timeseries/ROI_#_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-80)' + 5. '/acquisition/timeseries/ROI_#_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-80)' + 6. '/acquisition/timeseries/ROI_#_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-80)' + 7. '/acquisition/timeseries/ROI_#_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 8. '/acquisition/timeseries/ROI_#_Green/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-80)' + 9. '/acquisition/timeseries/ROI_#_Green/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-80)' + 10. '/acquisition/timeseries/ROI_#_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-80)' + 11. '/acquisition/timeseries/ROI_#_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-80)' + 13. '/acquisition/timeseries/ROI_#_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-80)' + 14. '/acquisition/timeseries/ROI_#_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-80)' + 15. '/acquisition/timeseries/ROI_#_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-80)' + 16. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 17. '/acquisition/timeseries/ROI_#_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-80)' + 18. '/acquisition/timeseries/ROI_#_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-80)' + 19. '/acquisition/timeseries/ROI_#_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-80)' + 20. '/acquisition/timeseries/ROI_#_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 21. '/acquisition/timeseries/ROI_#_Red/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-80)' + 22. '/acquisition/timeseries/ROI_#_Red/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-80)' + 23. '/acquisition/timeseries/ROI_#_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-80)' + 24. '/acquisition/timeseries/ROI_#_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-80)' + 25. '/acquisition/timeseries/ROI_#_Red/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-80)' + 26. '/acquisition/timeseries/ROI_#_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-80)' + 27. '/acquisition/timeseries/ROI_002_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPc'' + 28. '/acquisition/timeseries/ROI_002_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPC'' + 29. '/acquisition/timeseries/ROI_003_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnJ'' + 30. '/acquisition/timeseries/ROI_003_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroj'' + 31. '/acquisition/timeseries/ROI_004_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMq'' + 32. '/acquisition/timeseries/ROI_004_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMQ'' + 33. '/acquisition/timeseries/ROI_005_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkX'' + 34. '/acquisition/timeseries/ROI_005_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklx'' + 35. '/acquisition/timeseries/ROI_006_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJE'' + 36. '/acquisition/timeseries/ROI_006_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKe'' + 37. '/acquisition/timeseries/ROI_007_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcil'' + 38. '/acquisition/timeseries/ROI_007_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiL'' + 39. '/acquisition/timeseries/ROI_008_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGS'' + 40. '/acquisition/timeseries/ROI_008_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHs'' + 41. '/acquisition/timeseries/ROI_009_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfz'' + 42. '/acquisition/timeseries/ROI_009_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfZ'' + 43. '/acquisition/timeseries/ROI_010_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzVCL'' + 44. '/acquisition/timeseries/ROI_010_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytWDl'' + 45. '/acquisition/timeseries/ROI_011_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCASbs'' + 46. '/acquisition/timeseries/ROI_011_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuTbS'' + 47. '/acquisition/timeseries/ROI_012_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBOzZ'' + 48. '/acquisition/timeseries/ROI_012_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvPAz'' + 49. '/acquisition/timeseries/ROI_013_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYG'' + 50. '/acquisition/timeseries/ROI_013_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZg'' + 51. '/acquisition/timeseries/ROI_014_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxn'' + 52. '/acquisition/timeseries/ROI_014_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxN'' + 53. '/acquisition/timeseries/ROI_015_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVU'' + 54. '/acquisition/timeseries/ROI_015_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWu'' + 55. '/acquisition/timeseries/ROI_016_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuB'' + 56. '/acquisition/timeseries/ROI_016_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBvb'' + 57. '/acquisition/timeseries/ROI_017_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTi'' + 58. '/acquisition/timeseries/ROI_017_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTI'' + 59. '/acquisition/timeseries/ROI_018_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrP'' + 60. '/acquisition/timeseries/ROI_018_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusp'' + 61. '/acquisition/timeseries/ROI_019_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQw'' + 62. '/acquisition/timeseries/ROI_019_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQW'' + 63. '/acquisition/timeseries/ROI_020_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnI'' + 64. '/acquisition/timeseries/ROI_020_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroi'' + 65. '/acquisition/timeseries/ROI_021_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMp'' + 66. '/acquisition/timeseries/ROI_021_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMP'' + 67. '/acquisition/timeseries/ROI_022_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkW'' + 68. '/acquisition/timeseries/ROI_022_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklw'' + 69. '/acquisition/timeseries/ROI_023_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJD'' + 70. '/acquisition/timeseries/ROI_023_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKd'' + 71. '/acquisition/timeseries/ROI_024_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcik'' + 72. '/acquisition/timeseries/ROI_024_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiK'' + 73. '/acquisition/timeseries/ROI_025_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGR'' + 74. '/acquisition/timeseries/ROI_025_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHr'' + 75. '/acquisition/timeseries/ROI_026_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfy'' + 76. '/acquisition/timeseries/ROI_026_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfY'' + 77. '/acquisition/timeseries/ROI_027_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREf'' + 78. '/acquisition/timeseries/ROI_027_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEF'' + 79. '/acquisition/timeseries/ROI_028_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcM'' + 80. '/acquisition/timeseries/ROI_028_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdm'' + 81. '/acquisition/timeseries/ROI_029_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBt'' + 82. '/acquisition/timeseries/ROI_029_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBT'' + 83. '/acquisition/timeseries/ROI_030_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYF'' + 84. '/acquisition/timeseries/ROI_030_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZf'' + 85. '/acquisition/timeseries/ROI_031_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxm'' + 86. '/acquisition/timeseries/ROI_031_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxM'' + 87. '/acquisition/timeseries/ROI_032_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVT'' + 88. '/acquisition/timeseries/ROI_032_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWt'' + 89. '/acquisition/timeseries/ROI_033_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuA'' + 90. '/acquisition/timeseries/ROI_033_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBva'' + 91. '/acquisition/timeseries/ROI_034_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTh'' + 92. '/acquisition/timeseries/ROI_034_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTH'' + 93. '/acquisition/timeseries/ROI_035_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrO'' + 94. '/acquisition/timeseries/ROI_035_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBuso'' + 95. '/acquisition/timeseries/ROI_036_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQv'' + 96. '/acquisition/timeseries/ROI_036_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQV'' + 97. '/acquisition/timeseries/ROI_037_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpc'' + 98. '/acquisition/timeseries/ROI_037_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpC'' + 99. '/acquisition/timeseries/ROI_038_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNJ'' +100. '/acquisition/timeseries/ROI_038_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOj'' +101. '/acquisition/timeseries/ROI_039_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmq'' +102. '/acquisition/timeseries/ROI_039_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmQ'' +103. '/acquisition/timeseries/ROI_040_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJC'' +104. '/acquisition/timeseries/ROI_040_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKc'' +105. '/acquisition/timeseries/ROI_041_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcij'' +106. '/acquisition/timeseries/ROI_041_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiJ'' +107. '/acquisition/timeseries/ROI_042_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGQ'' +108. '/acquisition/timeseries/ROI_042_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHq'' +109. '/acquisition/timeseries/ROI_043_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfx'' +110. '/acquisition/timeseries/ROI_043_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfX'' +111. '/acquisition/timeseries/ROI_044_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREe'' +112. '/acquisition/timeseries/ROI_044_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEE'' +113. '/acquisition/timeseries/ROI_045_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcL'' +114. '/acquisition/timeseries/ROI_045_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdl'' +115. '/acquisition/timeseries/ROI_046_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBs'' +116. '/acquisition/timeseries/ROI_046_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBS'' +117. '/acquisition/timeseries/ROI_047_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZZ'' +118. '/acquisition/timeseries/ROI_047_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIaz'' +119. '/acquisition/timeseries/ROI_048_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyG'' +120. '/acquisition/timeseries/ROI_048_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzg'' +121. '/acquisition/timeseries/ROI_049_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXn'' +122. '/acquisition/timeseries/ROI_049_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXN'' +123. '/acquisition/timeseries/ROI_050_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuz'' +124. '/acquisition/timeseries/ROI_050_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBuZ'' +125. '/acquisition/timeseries/ROI_051_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTg'' +126. '/acquisition/timeseries/ROI_051_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTG'' +127. '/acquisition/timeseries/ROI_052_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrN'' +128. '/acquisition/timeseries/ROI_052_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusn'' +129. '/acquisition/timeseries/ROI_053_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQu'' +130. '/acquisition/timeseries/ROI_053_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQU'' +131. '/acquisition/timeseries/ROI_054_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpb'' +132. '/acquisition/timeseries/ROI_054_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpB'' +133. '/acquisition/timeseries/ROI_055_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNI'' +134. '/acquisition/timeseries/ROI_055_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOi'' +135. '/acquisition/timeseries/ROI_056_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmp'' +136. '/acquisition/timeseries/ROI_056_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmP'' +137. '/acquisition/timeseries/ROI_057_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKW'' +138. '/acquisition/timeseries/ROI_057_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLw'' +139. '/acquisition/timeseries/ROI_058_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjD'' +140. '/acquisition/timeseries/ROI_058_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkd'' +141. '/acquisition/timeseries/ROI_059_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIk'' +142. '/acquisition/timeseries/ROI_059_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIK'' +143. '/acquisition/timeseries/ROI_060_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfw'' +144. '/acquisition/timeseries/ROI_060_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfW'' +145. '/acquisition/timeseries/ROI_061_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREd'' +146. '/acquisition/timeseries/ROI_061_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSED'' +147. '/acquisition/timeseries/ROI_062_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcK'' +148. '/acquisition/timeseries/ROI_062_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdk'' +149. '/acquisition/timeseries/ROI_063_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBr'' +150. '/acquisition/timeseries/ROI_063_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBR'' +151. '/acquisition/timeseries/ROI_064_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZY'' +152. '/acquisition/timeseries/ROI_064_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIay'' +153. '/acquisition/timeseries/ROI_065_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyF'' +154. '/acquisition/timeseries/ROI_065_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzf'' +155. '/acquisition/timeseries/ROI_066_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXm'' +156. '/acquisition/timeseries/ROI_066_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXM'' +157. '/acquisition/timeseries/ROI_067_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNwvT'' +158. '/acquisition/timeseries/ROI_067_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHxwt'' +159. '/acquisition/timeseries/ROI_068_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCOsUA'' +160. '/acquisition/timeseries/ROI_068_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyItVa'' +161. '/acquisition/timeseries/ROI_069_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPpth'' +162. '/acquisition/timeseries/ROI_069_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJqtH'' +163. '/acquisition/timeseries/ROI_070_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQt'' +164. '/acquisition/timeseries/ROI_070_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQT'' +165. '/acquisition/timeseries/ROI_071_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpa'' +166. '/acquisition/timeseries/ROI_071_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpA'' +167. '/acquisition/timeseries/ROI_072_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNH'' +168. '/acquisition/timeseries/ROI_072_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOh'' +169. '/acquisition/timeseries/ROI_073_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmo'' +170. '/acquisition/timeseries/ROI_073_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmO'' +171. '/acquisition/timeseries/ROI_074_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKV'' +172. '/acquisition/timeseries/ROI_074_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLv'' +173. '/acquisition/timeseries/ROI_075_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjC'' +174. '/acquisition/timeseries/ROI_075_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkc'' +175. '/acquisition/timeseries/ROI_076_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIj'' +176. '/acquisition/timeseries/ROI_076_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIJ'' +177. '/acquisition/timeseries/ROI_077_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCORgQ'' +178. '/acquisition/timeseries/ROI_077_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyIShq'' +179. '/acquisition/timeseries/ROI_078_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPNFx'' +180. '/acquisition/timeseries/ROI_078_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJOFX'' +181. '/acquisition/timeseries/ROI_079_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCQKee'' +182. '/acquisition/timeseries/ROI_079_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyKLeE'' +183. '/acquisition/timeseries/ROI_080_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBq'' +184. '/acquisition/timeseries/ROI_080_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBQ'' +185. '/acquisition/timeseries/Zstack_Green_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-49)' +186. '/acquisition/timeseries/Zstack_Green_# comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"' (#=1-49)' +187. '/acquisition/timeseries/Zstack_Green_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-49)' +188. '/acquisition/timeseries/Zstack_Green_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-49)' +189. '/acquisition/timeseries/Zstack_Green_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-49)' +190. '/acquisition/timeseries/Zstack_Green_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-49)' +191. '/acquisition/timeseries/Zstack_Green_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-49)' +192. '/acquisition/timeseries/Zstack_Green_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-49)' +193. '/acquisition/timeseries/Zstack_Green_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-49)' +194. '/acquisition/timeseries/Zstack_Green_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-49)' +195. '/acquisition/timeseries/Zstack_Green_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-49)' +196. '/acquisition/timeseries/Zstack_Green_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-49)' +197. '/acquisition/timeseries/Zstack_Red_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-49)' +198. '/acquisition/timeseries/Zstack_Red_# comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"' (#=1-49)' +199. '/acquisition/timeseries/Zstack_Red_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-49)' +200. '/acquisition/timeseries/Zstack_Red_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-49)' +201. '/acquisition/timeseries/Zstack_Red_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-49)' +202. '/acquisition/timeseries/Zstack_Red_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-49)' +203. '/acquisition/timeseries/Zstack_Red_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-49)' +204. '/acquisition/timeseries/Zstack_Red_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-49)' +205. '/acquisition/timeseries/Zstack_Red_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-49)' +206. '/acquisition/timeseries/Zstack_Red_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-49)' +207. '/acquisition/timeseries/Zstack_Red_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-49)' +208. '/acquisition/timeseries/Zstack_Red_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-49)' +209. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +210. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +211. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' +212. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' +213. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +214. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +215. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' +216. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' +217. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' +218. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' +219. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +220. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +221. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +222. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' +223. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' +224. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +225. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +226. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' +227. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' +228. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' +229. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' +230. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +231. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' +232. '/epochs/trial_# links: dtype=|S58, shape=(161,) size (9338) val='["'ROI_001_Green' is '/acquisition/timese...fUYCuY' (#=1-20)' +233. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-20)' +234. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' +235. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-49)' +236. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-49)' +237. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +238. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +239. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +240. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' +241. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +242. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +243. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' +244. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +245. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' +246. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +247. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' +248. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' +249. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' +250. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' +251. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' +252. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' +253. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' +254. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=79-80)' +255. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=79-80)' +256. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-2)' +257. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0025/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=1-2)' +258. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=9-13)' +259. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0028/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=9-13)' +260. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=3-8)' +261. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=3-8)' +262. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=50-51)' +263. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=50-51)' +264. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=14-16,33-44,52-55,78)' +265. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=14-16,33-44,52-55,78)' +266. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=17-26,45-48,56-62)' +267. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=17-26,45-48,56-62)' +268. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=27-32,49,63-69)' +269. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=27-32,49,63-69)' +270. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=74-75)' +271. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=74-75)' +272. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=70-73)' +273. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=70-73)' +274. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=76-77)' +275. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=76-77)' +276. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' +277. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +278. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +279. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +280. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +281. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +282. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +283. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +284. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +285. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +286. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +287. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +288. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +289. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 10616 datasets (sorted alphabetically) (856 combined): + 1. '/acquisition/timeseries/ROI_#_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-80)' + 2. '/acquisition/timeseries/ROI_#_Green/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-80)' + 3. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(175440, 1, 1) size (189644), compress=gzip val='[[[113]],[[113]],[[118]],[[111]],[[125]],...bYADGy'' + 4. '/acquisition/timeseries/ROI_#_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-80)' + 5. '/acquisition/timeseries/ROI_#_Green/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-80)' + 6. '/acquisition/timeseries/ROI_#_Green/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-80)' + 7. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0025"' (#=1-2)' + 8. '/acquisition/timeseries/ROI_#_Green/num_samples: dtype=int32, shape=() size (4) val='175440' (#=1-80)' + 9. '/acquisition/timeseries/ROI_#_Green/pmt_gain: dtype=float32, shape=() size (4) val='715' (#=1-80)' + 10. '/acquisition/timeseries/ROI_#_Green/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-80)' + 11. '/acquisition/timeseries/ROI_#_Green/scan_line_rate: dtype=float32, shape=() size (4) val='348.2' (#=1-80)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps: dtype=float64, shape=(175440,) size (1049139), compress=gzip val='[1.084e-19,0.002872,0.005744,0.008616,0.0...hsbIrX' (#=1-80)' + 13. '/acquisition/timeseries/ROI_#_Red/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-80)' + 14. '/acquisition/timeseries/ROI_#_Red/channel: dtype=|S3, shape=() size (3) val='"Red"' (#=1-80)' + 15. '/acquisition/timeseries/ROI_001_Red/data: dtype=float32, shape=(175440, 1, 1) size (130300), compress=gzip val='[[[114]],[[113]],[[115]],[[114]],[[112]],...dnWfDq'' + 16. '/acquisition/timeseries/ROI_#_Red/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-80)' + 17. '/acquisition/timeseries/ROI_#_Red/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-80)' + 18. '/acquisition/timeseries/ROI_#_Red/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-80)' + 19. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0025"' (#=1-2)' + 20. '/acquisition/timeseries/ROI_#_Red/num_samples: dtype=int32, shape=() size (4) val='175440' (#=1-80)' + 21. '/acquisition/timeseries/ROI_#_Red/pmt_gain: dtype=float32, shape=() size (4) val='505' (#=1-80)' + 22. '/acquisition/timeseries/ROI_#_Red/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-80)' + 23. '/acquisition/timeseries/ROI_#_Red/scan_line_rate: dtype=float32, shape=() size (4) val='348.2' (#=1-80)' + 24. '/acquisition/timeseries/ROI_#_Red/timestamps: dtype=float64, shape=(175440,) size (1049139), compress=gzip val='[1.084e-19,0.002872,0.005744,0.008616,0.0...hsbIrX' (#=1-80)' + 25. '/acquisition/timeseries/ROI_002_Green/data: dtype=float32, shape=(175440, 1, 1) size (194684), compress=gzip val='[[[115]],[[125]],[[112]],[[116]],[[117]],...hhZxuA'' + 26. '/acquisition/timeseries/ROI_002_Red/data: dtype=float32, shape=(175440, 1, 1) size (131350), compress=gzip val='[[[114]],[[117]],[[118]],[[117]],[[115]],...hyRoJF'' + 27. '/acquisition/timeseries/ROI_003_Green/data: dtype=float32, shape=(175440, 1, 1) size (251913), compress=gzip val='[[[147]],[[150]],[[118]],[[168]],[[153]],...cAiSbH'' + 28. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0029"' (#=3-8)' + 29. '/acquisition/timeseries/ROI_003_Red/data: dtype=float32, shape=(175440, 1, 1) size (130464), compress=gzip val='[[[114]],[[112]],[[113]],[[110]],[[114]],...djGJTF'' + 30. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0029"' (#=3-8)' + 31. '/acquisition/timeseries/ROI_004_Green/data: dtype=float32, shape=(175440, 1, 1) size (260244), compress=gzip val='[[[146]],[[150]],[[166]],[[140]],[[142]],...Jgbwl'' + 32. '/acquisition/timeseries/ROI_004_Red/data: dtype=float32, shape=(175440, 1, 1) size (130514), compress=gzip val='[[[111]],[[111]],[[110]],[[111]],[[112]],...topMc'' + 33. '/acquisition/timeseries/ROI_005_Green/data: dtype=float32, shape=(175440, 1, 1) size (251701), compress=gzip val='[[[149]],[[151]],[[122]],[[138]],[[149]],...diEzgJ'' + 34. '/acquisition/timeseries/ROI_005_Red/data: dtype=float32, shape=(175440, 1, 1) size (130180), compress=gzip val='[[[112]],[[109]],[[108]],[[114]],[[115]],...jxqgog'' + 35. '/acquisition/timeseries/ROI_006_Green/data: dtype=float32, shape=(175440, 1, 1) size (265087), compress=gzip val='[[[178]],[[133]],[[163]],[[211]],[[191]],...bQpin'' + 36. '/acquisition/timeseries/ROI_006_Red/data: dtype=float32, shape=(175440, 1, 1) size (130362), compress=gzip val='[[[112]],[[110]],[[111]],[[114]],[[116]],...imPjoD'' + 37. '/acquisition/timeseries/ROI_007_Green/data: dtype=float32, shape=(175440, 1, 1) size (257598), compress=gzip val='[[[142]],[[123]],[[151]],[[202]],[[137]],...ktAfjL'' + 38. '/acquisition/timeseries/ROI_007_Red/data: dtype=float32, shape=(175440, 1, 1) size (130554), compress=gzip val='[[[115]],[[114]],[[110]],[[109]],[[110]],...cdpkVl'' + 39. '/acquisition/timeseries/ROI_008_Green/data: dtype=float32, shape=(175440, 1, 1) size (263531), compress=gzip val='[[[157]],[[168]],[[163]],[[141]],[[128]],...gdcaXS'' + 40. '/acquisition/timeseries/ROI_008_Red/data: dtype=float32, shape=(175440, 1, 1) size (130113), compress=gzip val='[[[113]],[[110]],[[113]],[[114]],[[109]],...diBNWT'' + 41. '/acquisition/timeseries/ROI_009_Green/data: dtype=float32, shape=(175440, 1, 1) size (254589), compress=gzip val='[[[128]],[[147]],[[147]],[[145]],[[120]],...eAsYNf'' + 42. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0028"' (#=9-13)' + 43. '/acquisition/timeseries/ROI_009_Red/data: dtype=float32, shape=(175440, 1, 1) size (130244), compress=gzip val='[[[116]],[[117]],[[116]],[[111]],[[106]],...lnQOZf'' + 44. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0028"' (#=9-13)' + 45. '/acquisition/timeseries/ROI_010_Green/data: dtype=float32, shape=(175440, 1, 1) size (263779), compress=gzip val='[[[187]],[[166]],[[159]],[[139]],[[184]],...fiwbWb'' + 46. '/acquisition/timeseries/ROI_010_Red/data: dtype=float32, shape=(175440, 1, 1) size (130277), compress=gzip val='[[[110]],[[110]],[[113]],[[110]],[[112]],...bUrTJu'' + 47. '/acquisition/timeseries/ROI_011_Green/data: dtype=float32, shape=(175440, 1, 1) size (264168), compress=gzip val='[[[127]],[[130]],[[163]],[[162]],[[153]],...bNVdrm'' + 48. '/acquisition/timeseries/ROI_011_Red/data: dtype=float32, shape=(175440, 1, 1) size (130358), compress=gzip val='[[[112]],[[106]],[[105]],[[111]],[[113]],...hFlYBw'' + 49. '/acquisition/timeseries/ROI_012_Green/data: dtype=float32, shape=(175440, 1, 1) size (247290), compress=gzip val='[[[152]],[[132]],[[114]],[[120]],[[158]],...hRkBVy'' + 50. '/acquisition/timeseries/ROI_012_Red/data: dtype=float32, shape=(175440, 1, 1) size (130135), compress=gzip val='[[[109]],[[114]],[[111]],[[113]],[[110]],...biZcyg'' + 51. '/acquisition/timeseries/ROI_013_Green/data: dtype=float32, shape=(175440, 1, 1) size (187529), compress=gzip val='[[[116]],[[120]],[[125]],[[117]],[[137]],...krPfMX'' + 52. '/acquisition/timeseries/ROI_013_Red/data: dtype=float32, shape=(175440, 1, 1) size (129966), compress=gzip val='[[[110]],[[113]],[[113]],[[109]],[[111]],...kvoUSz'' + 53. '/acquisition/timeseries/ROI_014_Green/data: dtype=float32, shape=(175440, 1, 1) size (234547), compress=gzip val='[[[135]],[[142]],[[117]],[[118]],[[124]],...jsBHTg'' + 54. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"' (#=14-16,33-44,52-55,78)' + 55. '/acquisition/timeseries/ROI_014_Red/data: dtype=float32, shape=(175440, 1, 1) size (130784), compress=gzip val='[[[115]],[[113]],[[115]],[[121]],[[118]],...glZfDW'' + 56. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"' (#=14-16,33-44,52-55,78)' + 57. '/acquisition/timeseries/ROI_015_Green/data: dtype=float32, shape=(175440, 1, 1) size (238439), compress=gzip val='[[[141]],[[160]],[[113]],[[146]],[[146]],...iWZTiw'' + 58. '/acquisition/timeseries/ROI_015_Red/data: dtype=float32, shape=(175440, 1, 1) size (131086), compress=gzip val='[[[117]],[[124]],[[114]],[[116]],[[120]],...eaDHYF'' + 59. '/acquisition/timeseries/ROI_016_Green/data: dtype=float32, shape=(175440, 1, 1) size (238299), compress=gzip val='[[[115]],[[140]],[[163]],[[155]],[[129]],...fgpBth'' + 60. '/acquisition/timeseries/ROI_016_Red/data: dtype=float32, shape=(175440, 1, 1) size (130820), compress=gzip val='[[[119]],[[122]],[[117]],[[117]],[[120]],...kUzFJZ'' + 61. '/acquisition/timeseries/ROI_017_Green/data: dtype=float32, shape=(175440, 1, 1) size (217243), compress=gzip val='[[[116]],[[139]],[[129]],[[129]],[[137]],...iwkpZg'' + 62. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0034"' (#=17-26,45-48,56-62)' + 63. '/acquisition/timeseries/ROI_017_Red/data: dtype=float32, shape=(175440, 1, 1) size (130874), compress=gzip val='[[[116]],[[122]],[[116]],[[116]],[[117]],...bAZjQE'' + 64. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0034"' (#=17-26,45-48,56-62)' + 65. '/acquisition/timeseries/ROI_018_Green/data: dtype=float32, shape=(175440, 1, 1) size (210055), compress=gzip val='[[[115]],[[118]],[[139]],[[144]],[[115]],...dAiQjQ'' + 66. '/acquisition/timeseries/ROI_018_Red/data: dtype=float32, shape=(175440, 1, 1) size (130746), compress=gzip val='[[[117]],[[114]],[[116]],[[116]],[[114]],...iXdxjt'' + 67. '/acquisition/timeseries/ROI_019_Green/data: dtype=float32, shape=(175440, 1, 1) size (185269), compress=gzip val='[[[115]],[[150]],[[129]],[[138]],[[110]],...cFHYTr'' + 68. '/acquisition/timeseries/ROI_019_Red/data: dtype=float32, shape=(175440, 1, 1) size (130212), compress=gzip val='[[[115]],[[112]],[[112]],[[109]],[[107]],...emETPb'' + 69. '/acquisition/timeseries/ROI_020_Green/data: dtype=float32, shape=(175440, 1, 1) size (296595), compress=gzip val='[[[570]],[[483]],[[446]],[[399]],[[395]],...iqLzEy'' + 70. '/acquisition/timeseries/ROI_020_Red/data: dtype=float32, shape=(175440, 1, 1) size (130832), compress=gzip val='[[[113]],[[114]],[[112]],[[114]],[[111]],...ilRfBv'' + 71. '/acquisition/timeseries/ROI_021_Green/data: dtype=float32, shape=(175440, 1, 1) size (283226), compress=gzip val='[[[251]],[[223]],[[196]],[[238]],[[303]],...fqNBgy'' + 72. '/acquisition/timeseries/ROI_021_Red/data: dtype=float32, shape=(175440, 1, 1) size (130553), compress=gzip val='[[[108]],[[112]],[[110]],[[112]],[[110]],...dtfImb'' + 73. 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'/acquisition/timeseries/ROI_027_Green/data: dtype=float32, shape=(175440, 1, 1) size (286953), compress=gzip val='[[[330]],[[331]],[[384]],[[346]],[[257]],...guKvBs'' + 84. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0035"' (#=27-32,49,63-69)' + 85. '/acquisition/timeseries/ROI_027_Red/data: dtype=float32, shape=(175440, 1, 1) size (130907), compress=gzip val='[[[112]],[[114]],[[111]],[[112]],[[115]],...kKmtxb'' + 86. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0035"' (#=27-32,49,63-69)' + 87. '/acquisition/timeseries/ROI_028_Green/data: dtype=float32, shape=(175440, 1, 1) size (290091), compress=gzip val='[[[275]],[[308]],[[274]],[[368]],[[383]],...eLOZtc'' + 88. '/acquisition/timeseries/ROI_028_Red/data: dtype=float32, shape=(175440, 1, 1) size (130670), compress=gzip val='[[[112]],[[114]],[[109]],[[111]],[[112]],...bajiKh'' + 89. 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'/epochs/trial_0006/stop_time: dtype=float64, shape=() size (8) val='151.2'' +373. '/epochs/trial_0007/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +374. '/epochs/trial_0007/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='52632' (#=1-80)' +375. '/epochs/trial_0007/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +376. '/epochs/trial_0007/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='52632' (#=1-80)' +377. '/epochs/trial_0007/speed_data/idx_start: dtype=int32, shape=() size (4) val='70470'' +378. '/epochs/trial_0007/start_time: dtype=float64, shape=() size (8) val='151.2'' +379. '/epochs/trial_0007/stop_time: dtype=float64, shape=() size (8) val='176.4'' +380. '/epochs/trial_0008/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +381. '/epochs/trial_0008/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='61404' (#=1-80)' +382. 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'/epochs/trial_0016/start_time: dtype=float64, shape=() size (8) val='378.1'' +443. '/epochs/trial_0016/stop_time: dtype=float64, shape=() size (8) val='403.3'' +444. '/epochs/trial_0017/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +445. '/epochs/trial_0017/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='140352' (#=1-80)' +446. '/epochs/trial_0017/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +447. '/epochs/trial_0017/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='140352' (#=1-80)' +448. '/epochs/trial_0017/speed_data/idx_start: dtype=int32, shape=() size (4) val='187958'' +449. '/epochs/trial_0017/start_time: dtype=float64, shape=() size (8) val='403.3'' +450. '/epochs/trial_0017/stop_time: dtype=float64, shape=() size (8) val='428.5'' +451. '/epochs/trial_0018/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +452. '/epochs/trial_0018/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='149124' (#=1-80)' +453. '/epochs/trial_0018/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +454. '/epochs/trial_0018/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='149124' (#=1-80)' +455. '/epochs/trial_0018/speed_data/idx_start: dtype=int32, shape=() size (4) val='199708'' +456. '/epochs/trial_0018/start_time: dtype=float64, shape=() size (8) val='428.5'' +457. '/epochs/trial_0018/stop_time: dtype=float64, shape=() size (8) val='453.7'' +458. '/epochs/trial_0019/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +459. '/epochs/trial_0019/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='157896' (#=1-80)' +460. '/epochs/trial_0019/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +461. '/epochs/trial_0019/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='157896' (#=1-80)' +462. '/epochs/trial_0019/speed_data/idx_start: dtype=int32, shape=() size (4) val='211457'' +463. '/epochs/trial_0019/start_time: dtype=float64, shape=() size (8) val='453.7'' +464. '/epochs/trial_0019/stop_time: dtype=float64, shape=() size (8) val='478.9'' +465. '/epochs/trial_0020/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +466. '/epochs/trial_0020/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='166668' (#=1-80)' +467. '/epochs/trial_0020/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-80)' +468. '/epochs/trial_0020/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='166668' (#=1-80)' +469. '/epochs/trial_0020/speed_data/idx_start: dtype=int32, shape=() size (4) val='223207'' +470. '/epochs/trial_0020/start_time: dtype=float64, shape=() size (8) val='478.9'' +471. '/epochs/trial_0020/stop_time: dtype=float64, shape=() size (8) val='504.1'' +472. 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'/general/optophysiology/Zstack#/reference_frame: dtype=|S27, shape=() size (27) val='"TODO: In lab book (partly?)"' (#=1-49)' +495. '/general/optophysiology/Zstack0002/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-115],[0.4892,0,-115],[0.9785,0,-1...joPgDZ'' +496. '/general/optophysiology/Zstack0003/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-110],[0.4892,0,-110],[0.9785,0,-1...gserWp'' +497. '/general/optophysiology/Zstack0004/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-105],[0.4892,0,-105],[0.9785,0,-1...dvtDoF'' +498. '/general/optophysiology/Zstack0005/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-100],[0.4892,0,-100],[0.9785,0,-1...yIOGV'' +499. '/general/optophysiology/Zstack0006/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-95],[0.4892,0,-95],[0.9785,0,-95]...iRmJVB'' +500. '/general/optophysiology/Zstack0007/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-90],[0.4892,0,-90],[0.9785,0,-90]...fUBVnR'' +501. '/general/optophysiology/Zstack0008/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-85],[0.4892,0,-85],[0.9785,0,-85]...cXRgGh'' +502. '/general/optophysiology/Zstack0009/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-80],[0.4892,0,-80],[0.9785,0,-80]...bgrYx'' +503. '/general/optophysiology/Zstack0010/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-75],[0.4892,0,-75],[0.9785,0,-75]...itKnnd'' +504. '/general/optophysiology/Zstack0011/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-70],[0.4892,0,-70],[0.9785,0,-70]...fwZyFt'' +505. '/general/optophysiology/Zstack0012/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-65],[0.4892,0,-65],[0.9785,0,-65]...cAoJXJ'' +506. '/general/optophysiology/Zstack0013/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-60],[0.4892,0,-60],[0.9785,0,-60]...dZOzXl'' +507. '/general/optophysiology/Zstack0014/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-55],[0.4892,0,-55],[0.9785,0,-55]...jvHGEh'' +508. '/general/optophysiology/Zstack0015/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-50],[0.4892,0,-50],[0.9785,0,-50]...dCmdoN'' +509. '/general/optophysiology/Zstack0016/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-45],[0.4892,0,-45],[0.9785,0,-45]...iYfjVJ'' +510. '/general/optophysiology/Zstack0017/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-40],[0.4892,0,-40],[0.9785,0,-40]...deJGGp'' +511. '/general/optophysiology/Zstack0018/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-35],[0.4892,0,-35],[0.9785,0,-35]...iACNnl'' +512. '/general/optophysiology/Zstack0019/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-30],[0.4892,0,-30],[0.9785,0,-30]...iCEjOJ'' +513. '/general/optophysiology/Zstack0020/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-25],[0.4892,0,-25],[0.9785,0,-25]...ifbNgl'' +514. '/general/optophysiology/Zstack0021/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-20],[0.4892,0,-20],[0.9785,0,-20]...hHzqxN'' +515. '/general/optophysiology/Zstack0022/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-15],[0.4892,0,-15],[0.9785,0,-15]...qSOAl'' +516. '/general/optophysiology/Zstack0023/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-10],[0.4892,0,-10],[0.9785,0,-10]...kLcFfF'' +517. '/general/optophysiology/Zstack0024/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-5],[0.4892,0,-5],[0.9785,0,-5],[1...dYDFaN'' +518. '/general/optophysiology/Zstack0025/manifold: dtype=float32, shape=(512, 512, 3) size (34372), compress=gzip val='[[[0,0,0],[0.4892,0,0],[0.9785,0,0],[1.46...iMZFkq'' +519. '/general/optophysiology/Zstack0026/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,5],[0.4892,0,5],[0.9785,0,5],[1.46...isYxvJ'' +520. '/general/optophysiology/Zstack0027/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,10],[0.4892,0,10],[0.9785,0,10],[1...dQjlQm'' +521. '/general/optophysiology/Zstack0028/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,15],[0.4892,0,15],[0.9785,0,15],[1...eLnGVh'' +522. '/general/optophysiology/Zstack0029/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,20],[0.4892,0,20],[0.9785,0,20],[1...MFyWt'' +523. '/general/optophysiology/Zstack0030/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,25],[0.4892,0,25],[0.9785,0,25],[1...bkhVER'' +524. '/general/optophysiology/Zstack0031/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,30],[0.4892,0,30],[0.9785,0,30],[1...bHKsnp'' +525. '/general/optophysiology/Zstack0032/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,35],[0.4892,0,35],[0.9785,0,35],[1...bFJtXS'' +526. '/general/optophysiology/Zstack0033/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,40],[0.4892,0,40],[0.9785,0,40],[1...hzeXnm'' +527. '/general/optophysiology/Zstack0034/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,45],[0.4892,0,45],[0.9785,0,45],[1...cdlQGq'' +528. '/general/optophysiology/Zstack0035/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,50],[0.4892,0,50],[0.9785,0,50],[1...hWHtVK'' +529. '/general/optophysiology/Zstack0036/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,55],[0.4892,0,55],[0.9785,0,55],[1...cANPcN'' +530. '/general/optophysiology/Zstack0037/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,60],[0.4892,0,60],[0.9785,0,60],[1...iujssh'' +531. '/general/optophysiology/Zstack0038/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,65],[0.4892,0,65],[0.9785,0,65],[1...gUJCsF'' +532. '/general/optophysiology/Zstack0039/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,70],[0.4892,0,70],[0.9785,0,70],[1...jRurap'' +533. '/general/optophysiology/Zstack0040/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,75],[0.4892,0,75],[0.9785,0,75],[1...byQvLJ'' +534. '/general/optophysiology/Zstack0041/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,80],[0.4892,0,80],[0.9785,0,80],[1...evBktt'' +535. '/general/optophysiology/Zstack0042/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,85],[0.4892,0,85],[0.9785,0,85],[1...hslZbd'' +536. '/general/optophysiology/Zstack0043/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,90],[0.4892,0,90],[0.9785,0,90],[1...koWNIN'' +537. '/general/optophysiology/Zstack0044/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,95],[0.4892,0,95],[0.9785,0,95],[1...bWsSuh'' +538. '/general/optophysiology/Zstack0045/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,100],[0.4892,0,100],[0.9785,0,100]...eTdHbR'' +539. '/general/optophysiology/Zstack0046/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,105],[0.4892,0,105],[0.9785,0,105]...hPOvJB'' +540. '/general/optophysiology/Zstack0047/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,110],[0.4892,0,110],[0.9785,0,110]...kMzkrl'' +541. '/general/optophysiology/Zstack0048/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,115],[0.4892,0,115],[0.9785,0,115]...ctVpcF'' +542. '/general/optophysiology/Zstack0049/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,120],[0.4892,0,120],[0.9785,0,120]...fqGdKp'' +543. '/general/optophysiology/cycle_time: dtype=float32, shape=() size (4) val='0.002872'' +544. '/general/optophysiology/frame_size: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' +545. '/general/optophysiology/imaging_mode: dtype=|S8, shape=() size (8) val='"pointing"'' +546. '/general/optophysiology/zplane_pockels: dtype=float32, shape=(49, 4) size (579), compress=gzip val='[[-120,0.4994,100,-120],[-115,0.4797,100,...iUevau'' +547. '/general/pharmacology: dtype=|S152, shape=() size (152) val='"Description of drugs used, including how...goKGik'' +548. '/general/protocol: dtype=|S76, shape=() size (76) val='"Experimental protocol, if applicable, e....bWYeFo'' +549. '/general/related_publications: dtype=|S70, shape=() size (70) val='"Optional list of related publications, i...gGeOxQ'' +550. '/general/session_id: dtype=|S15, shape=() size (15) val='"161215_15_58_52"'' +551. '/general/slices: dtype=|S127, shape=() size (127) val='"Description of slices, including informa...bwDbqR'' +552. '/general/specifications/e-labview.py: dtype=|S1534, shape=() size (1534) val='"# NWB extension to store LabView header ...fvMAMg'' +553. '/general/specifications/e-pixeltimes.py: dtype=|S2701, shape=() size (2701) val='"# NWB extension to store per-pixel time ...gVgtZh'' +554. '/general/specifications/nwb_core.py: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +555. '/general/stimulus: dtype=|S84, shape=() size (84) val='"Notes about stimuli, such as how and whe...DShaM'' +556. '/general/subject/age: dtype=|S25, shape=() size (25) val='"Age of subject. Optional."'' +557. '/general/subject/description: dtype=|S88, shape=() size (88) val='"Description of subject and where subject...fXgfBt'' +558. '/general/subject/genotype: dtype=|S59, shape=() size (59) val='"Genetic strain. If absent, assume Wild T...eOaNbr'' +559. '/general/subject/sex: dtype=|S28, shape=() size (28) val='"Gender of subject. Optional."'' +560. '/general/subject/species: dtype=|S29, shape=() size (29) val='"Species of subject. Optional."'' +561. '/general/subject/subject_id: dtype=|S80, shape=() size (80) val='"ID of animal/person used/participating i...hoSoPZ'' +562. '/general/subject/weight: dtype=|S88, shape=() size (88) val='"Weight at time of experiment, at time of...grFgyL'' +563. '/general/surgery: dtype=|S134, shape=() size (134) val='"Narrative description about surgery/surg...dKKeYq'' +564. '/general/virus: dtype=|S130, shape=() size (130) val='"Information about virus(es) used in expe...cMsZNh'' +565. '/identifier: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +566. '/nwb_version: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +567. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=79-80)' +568. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_079/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...bssQde'' +569. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0022/ROI_079/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[384,164]]'' +570. 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'/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_075/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[233,362]]'' +822. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/ROI_075/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002725]'' +823. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0039/roi_list: dtype=|S7, shape=(2,) size (18), compress=gzip val='["ROI_074","ROI_075"]'' +824. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=70-73)' +825. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_070/img_mask: dtype=float32, shape=(512, 512) size (2502), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...laWzdu'' +826. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_070/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[406,402]]'' +827. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/pix_mask_weight: dtype=float32, shape=(1,) size (12), compress=gzip val='[1]' (#=70-73)' +828. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_070/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002583]'' +829. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_#/roi_description: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=70-73)' +830. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_071/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...hOZsoi'' +831. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_071/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[232,358]]'' +832. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_071/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002611]'' +833. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_072/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...juTXIi'' +834. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_072/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[230,362]]'' +835. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_072/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.00264]'' +836. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_073/img_mask: dtype=float32, shape=(512, 512) size (2502), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...idCoHS'' +837. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_073/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[235,360]]'' +838. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/ROI_073/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002668]'' +839. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0040/roi_list: dtype=|S7, shape=(4,) size (24), compress=gzip val='["ROI_070","ROI_071","ROI_072","ROI_073"]'' +840. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=76-77)' +841. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_076/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...gQVpVe'' +842. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_076/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[248,261]]'' +843. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/pix_mask_weight: dtype=float32, shape=(1,) size (12), compress=gzip val='[1]' (#=76-77)' +844. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_076/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002754]'' +845. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/roi_description: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=76-77)' +846. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_077/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...gcJzIi'' +847. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_077/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[259,263]]'' +848. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_077/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.002782]'' +849. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/roi_list: dtype=|S7, shape=(2,) size (18), compress=gzip val='["ROI_076","ROI_077"]'' +850. '/processing/Acquired_ROIs/roi_spec: dtype=float16, shape=(80, 17) size (771), compress=gzip val='[[1,0,4000,1,334,142,0,334,142,0,0,0,0,51...kZnhww'' +851. '/session_description: dtype=|S68, shape=() size (68) val='"One or two sentences describing the expe...ezufjX'' +852. '/session_start_time: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +853. '/silverlab_api_version: dtype=|S3, shape=() size (3) val='"0.1"'' +854. '/stimulus/presentation/air_puff/data: dtype=|S4, shape=(20,) size (15), compress=gzip val='["puff","puff","puff","puff","puff","puff...eebwbb'' +855. '/stimulus/presentation/air_puff/num_samples: dtype=int32, shape=() size (4) val='20'' +856. '/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(20,) size (171), compress=gzip val='[5,30.21,55.41,80.62,105.8,131,156.2,181....flSHgS'' +-------------------- +** Summary +3767 groups, 10616 datasets, 3609 attributes diff --git a/Python/test/data/170317_10_11_01.sig b/Python/test/data/170317_10_11_01.sig new file mode 100644 index 0000000..d5f472f --- /dev/null +++ b/Python/test/data/170317_10_11_01.sig @@ -0,0 +1,2430 @@ +<% Generating signature for 170317_10_11_01.nwb %> + +** No datasets hard links. +** No groups hard links. +** 136 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0014/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0014/description' + 2. 'to: "/general/optophysiology/Zstack0015/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0015/description' + 3. 'to: "/general/optophysiology/Zstack0017/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0017/description' + 4. 'to: "/general/optophysiology/Zstack0018/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0018/description' + 5. 'to: "/general/optophysiology/Zstack0020/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0020/description' + 6. 'to: "/general/optophysiology/Zstack0031/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0031/description' + 7. 'to: "/general/optophysiology/Zstack0032/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/description' + 8. 'to: "/general/optophysiology/Zstack0033/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/description' + 9. 'to: "/general/optophysiology/Zstack0034/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/description' + 10. 'to: "/general/optophysiology/Zstack0035/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/description' + 11. 'to: "/general/optophysiology/Zstack0044/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0044/description' + 12. 'to: "/general/optophysiology/Zstack0045/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0045/description' + 13. 'to: "/general/optophysiology/Zstack0046/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0046/description' + 14. 'to: "/general/optophysiology/Zstack0047/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0047/description' + 15. 'to: "/general/optophysiology/Zstack0048/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0048/description' + 16. 'to: "/general/optophysiology/Zstack0049/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0049/description' + 17. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' + 18. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_002/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_002_Green/pixel_time_offsets + /acquisition/timeseries/ROI_002_Red/pixel_time_offsets' + 19. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_003/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_003_Green/pixel_time_offsets + /acquisition/timeseries/ROI_003_Red/pixel_time_offsets' + 20. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_004/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_004_Green/pixel_time_offsets + /acquisition/timeseries/ROI_004_Red/pixel_time_offsets' + 21. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_005/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_005_Green/pixel_time_offsets + /acquisition/timeseries/ROI_005_Red/pixel_time_offsets' + 22. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_006/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_006_Green/pixel_time_offsets + /acquisition/timeseries/ROI_006_Red/pixel_time_offsets' + 23. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_007/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_007_Green/pixel_time_offsets + /acquisition/timeseries/ROI_007_Red/pixel_time_offsets' + 24. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_008/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_008_Green/pixel_time_offsets + /acquisition/timeseries/ROI_008_Red/pixel_time_offsets' + 25. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_009/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_009_Green/pixel_time_offsets + /acquisition/timeseries/ROI_009_Red/pixel_time_offsets' + 26. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_010/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_010_Green/pixel_time_offsets + /acquisition/timeseries/ROI_010_Red/pixel_time_offsets' + 27. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_011/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_011_Green/pixel_time_offsets + /acquisition/timeseries/ROI_011_Red/pixel_time_offsets' + 28. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_012/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_012_Green/pixel_time_offsets + /acquisition/timeseries/ROI_012_Red/pixel_time_offsets' + 29. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0015/ROI_013/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_013_Green/pixel_time_offsets + /acquisition/timeseries/ROI_013_Red/pixel_time_offsets' + 30. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0015/ROI_014/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_014_Green/pixel_time_offsets + /acquisition/timeseries/ROI_014_Red/pixel_time_offsets' + 31. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0015/ROI_015/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_015_Green/pixel_time_offsets + /acquisition/timeseries/ROI_015_Red/pixel_time_offsets' + 32. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0015/ROI_016/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_016_Green/pixel_time_offsets + /acquisition/timeseries/ROI_016_Red/pixel_time_offsets' + 33. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0015/ROI_017/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_017_Green/pixel_time_offsets + /acquisition/timeseries/ROI_017_Red/pixel_time_offsets' + 34. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_018/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_018_Green/pixel_time_offsets + /acquisition/timeseries/ROI_018_Red/pixel_time_offsets' + 35. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_019/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_019_Green/pixel_time_offsets + /acquisition/timeseries/ROI_019_Red/pixel_time_offsets' + 36. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_020/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_020_Green/pixel_time_offsets + /acquisition/timeseries/ROI_020_Red/pixel_time_offsets' + 37. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_021/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_021_Green/pixel_time_offsets + /acquisition/timeseries/ROI_021_Red/pixel_time_offsets' + 38. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_022/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_022_Green/pixel_time_offsets + /acquisition/timeseries/ROI_022_Red/pixel_time_offsets' + 39. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_023/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_023_Green/pixel_time_offsets + /acquisition/timeseries/ROI_023_Red/pixel_time_offsets' + 40. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_024/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_024_Green/pixel_time_offsets + /acquisition/timeseries/ROI_024_Red/pixel_time_offsets' + 41. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_025/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_025_Green/pixel_time_offsets + /acquisition/timeseries/ROI_025_Red/pixel_time_offsets' + 42. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_026/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_026_Green/pixel_time_offsets + /acquisition/timeseries/ROI_026_Red/pixel_time_offsets' + 43. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_027/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_027_Green/pixel_time_offsets + /acquisition/timeseries/ROI_027_Red/pixel_time_offsets' + 44. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_028/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_028_Green/pixel_time_offsets + /acquisition/timeseries/ROI_028_Red/pixel_time_offsets' + 45. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_029/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_029_Green/pixel_time_offsets + /acquisition/timeseries/ROI_029_Red/pixel_time_offsets' + 46. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_030/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_030_Green/pixel_time_offsets + /acquisition/timeseries/ROI_030_Red/pixel_time_offsets' + 47. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_031/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_031_Green/pixel_time_offsets + /acquisition/timeseries/ROI_031_Red/pixel_time_offsets' + 48. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_032/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_032_Green/pixel_time_offsets + /acquisition/timeseries/ROI_032_Red/pixel_time_offsets' + 49. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_033/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_033_Green/pixel_time_offsets + /acquisition/timeseries/ROI_033_Red/pixel_time_offsets' + 50. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_034/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_034_Green/pixel_time_offsets + /acquisition/timeseries/ROI_034_Red/pixel_time_offsets' + 51. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_035/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_035_Green/pixel_time_offsets + /acquisition/timeseries/ROI_035_Red/pixel_time_offsets' + 52. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_036/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_036_Green/pixel_time_offsets + /acquisition/timeseries/ROI_036_Red/pixel_time_offsets' + 53. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_037/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_037_Green/pixel_time_offsets + /acquisition/timeseries/ROI_037_Red/pixel_time_offsets' + 54. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_038/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_038_Green/pixel_time_offsets + /acquisition/timeseries/ROI_038_Red/pixel_time_offsets' + 55. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_039/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_039_Green/pixel_time_offsets + /acquisition/timeseries/ROI_039_Red/pixel_time_offsets' + 56. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_040/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_040_Green/pixel_time_offsets + /acquisition/timeseries/ROI_040_Red/pixel_time_offsets' + 57. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_041/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_041_Green/pixel_time_offsets + /acquisition/timeseries/ROI_041_Red/pixel_time_offsets' + 58. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_042/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_042_Green/pixel_time_offsets + /acquisition/timeseries/ROI_042_Red/pixel_time_offsets' + 59. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_043/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_043_Green/pixel_time_offsets + /acquisition/timeseries/ROI_043_Red/pixel_time_offsets' + 60. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_044/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_044_Green/pixel_time_offsets + /acquisition/timeseries/ROI_044_Red/pixel_time_offsets' + 61. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_045/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_045_Green/pixel_time_offsets + /acquisition/timeseries/ROI_045_Red/pixel_time_offsets' + 62. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_046/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_046_Green/pixel_time_offsets + /acquisition/timeseries/ROI_046_Red/pixel_time_offsets' + 63. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_047/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_047_Green/pixel_time_offsets + /acquisition/timeseries/ROI_047_Red/pixel_time_offsets' + 64. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_048/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_048_Green/pixel_time_offsets + /acquisition/timeseries/ROI_048_Red/pixel_time_offsets' + 65. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_049/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_049_Green/pixel_time_offsets + /acquisition/timeseries/ROI_049_Red/pixel_time_offsets' + 66. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_050/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_050_Green/pixel_time_offsets + /acquisition/timeseries/ROI_050_Red/pixel_time_offsets' + 67. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_051/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_051_Green/pixel_time_offsets + /acquisition/timeseries/ROI_051_Red/pixel_time_offsets' + 68. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_052/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_052_Green/pixel_time_offsets + /acquisition/timeseries/ROI_052_Red/pixel_time_offsets' + 69. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_053/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_053_Green/pixel_time_offsets + /acquisition/timeseries/ROI_053_Red/pixel_time_offsets' + 70. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_054/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_054_Green/pixel_time_offsets + /acquisition/timeseries/ROI_054_Red/pixel_time_offsets' + 71. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_055/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_055_Green/pixel_time_offsets + /acquisition/timeseries/ROI_055_Red/pixel_time_offsets' + 72. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_056/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_056_Green/pixel_time_offsets + /acquisition/timeseries/ROI_056_Red/pixel_time_offsets' + 73. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_057/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_057_Green/pixel_time_offsets + /acquisition/timeseries/ROI_057_Red/pixel_time_offsets' + 74. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_058/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_058_Green/pixel_time_offsets + /acquisition/timeseries/ROI_058_Red/pixel_time_offsets' + 75. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_059/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_059_Green/pixel_time_offsets + /acquisition/timeseries/ROI_059_Red/pixel_time_offsets' + 76. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_060/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_060_Green/pixel_time_offsets + /acquisition/timeseries/ROI_060_Red/pixel_time_offsets' + 77. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_061/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_061_Green/pixel_time_offsets + /acquisition/timeseries/ROI_061_Red/pixel_time_offsets' + 78. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_062/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_062_Green/pixel_time_offsets + /acquisition/timeseries/ROI_062_Red/pixel_time_offsets' + 79. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_063/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_063_Green/pixel_time_offsets + /acquisition/timeseries/ROI_063_Red/pixel_time_offsets' + 80. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_064/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_064_Green/pixel_time_offsets + /acquisition/timeseries/ROI_064_Red/pixel_time_offsets' + 81. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_065/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_065_Green/pixel_time_offsets + /acquisition/timeseries/ROI_065_Red/pixel_time_offsets' + 82. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_066/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_066_Green/pixel_time_offsets + /acquisition/timeseries/ROI_066_Red/pixel_time_offsets' + 83. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_067/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_067_Green/pixel_time_offsets + /acquisition/timeseries/ROI_067_Red/pixel_time_offsets' + 84. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_068/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_068_Green/pixel_time_offsets + /acquisition/timeseries/ROI_068_Red/pixel_time_offsets' + 85. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_069/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_069_Green/pixel_time_offsets + /acquisition/timeseries/ROI_069_Red/pixel_time_offsets' + 86. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_070/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_070_Green/pixel_time_offsets + /acquisition/timeseries/ROI_070_Red/pixel_time_offsets' + 87. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_071/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_071_Green/pixel_time_offsets + /acquisition/timeseries/ROI_071_Red/pixel_time_offsets' + 88. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_072/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_072_Green/pixel_time_offsets + /acquisition/timeseries/ROI_072_Red/pixel_time_offsets' + 89. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0044/ROI_073/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_073_Green/pixel_time_offsets + /acquisition/timeseries/ROI_073_Red/pixel_time_offsets' + 90. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0044/ROI_074/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_074_Green/pixel_time_offsets + /acquisition/timeseries/ROI_074_Red/pixel_time_offsets' + 91. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0044/ROI_075/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_075_Green/pixel_time_offsets + /acquisition/timeseries/ROI_075_Red/pixel_time_offsets' + 92. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0044/ROI_076/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_076_Green/pixel_time_offsets + /acquisition/timeseries/ROI_076_Red/pixel_time_offsets' + 93. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_077/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_077_Green/pixel_time_offsets + /acquisition/timeseries/ROI_077_Red/pixel_time_offsets' + 94. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_078/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_078_Green/pixel_time_offsets + /acquisition/timeseries/ROI_078_Red/pixel_time_offsets' + 95. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_079/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_079_Green/pixel_time_offsets + /acquisition/timeseries/ROI_079_Red/pixel_time_offsets' + 96. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_080/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_080_Green/pixel_time_offsets + /acquisition/timeseries/ROI_080_Red/pixel_time_offsets' + 97. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_081/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_081_Green/pixel_time_offsets + /acquisition/timeseries/ROI_081_Red/pixel_time_offsets' + 98. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_082/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_082_Green/pixel_time_offsets + /acquisition/timeseries/ROI_082_Red/pixel_time_offsets' + 99. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_083/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_083_Green/pixel_time_offsets + /acquisition/timeseries/ROI_083_Red/pixel_time_offsets' +100. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_084/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_084_Green/pixel_time_offsets + /acquisition/timeseries/ROI_084_Red/pixel_time_offsets' +101. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_085/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_085_Green/pixel_time_offsets + /acquisition/timeseries/ROI_085_Red/pixel_time_offsets' +102. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_086/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_086_Green/pixel_time_offsets + /acquisition/timeseries/ROI_086_Red/pixel_time_offsets' +103. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_087/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_087_Green/pixel_time_offsets + /acquisition/timeseries/ROI_087_Red/pixel_time_offsets' +104. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_088/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_088_Green/pixel_time_offsets + /acquisition/timeseries/ROI_088_Red/pixel_time_offsets' +105. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_089/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_089_Green/pixel_time_offsets + /acquisition/timeseries/ROI_089_Red/pixel_time_offsets' +106. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_090/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_090_Green/pixel_time_offsets + /acquisition/timeseries/ROI_090_Red/pixel_time_offsets' +107. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_091/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_091_Green/pixel_time_offsets + /acquisition/timeseries/ROI_091_Red/pixel_time_offsets' +108. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_092/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_092_Green/pixel_time_offsets + /acquisition/timeseries/ROI_092_Red/pixel_time_offsets' +109. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_093/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_093_Green/pixel_time_offsets + /acquisition/timeseries/ROI_093_Red/pixel_time_offsets' +110. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_094/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_094_Green/pixel_time_offsets + /acquisition/timeseries/ROI_094_Red/pixel_time_offsets' +111. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_095/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_095_Green/pixel_time_offsets + /acquisition/timeseries/ROI_095_Red/pixel_time_offsets' +112. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_096/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_096_Green/pixel_time_offsets + /acquisition/timeseries/ROI_096_Red/pixel_time_offsets' +113. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_097/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_097_Green/pixel_time_offsets + /acquisition/timeseries/ROI_097_Red/pixel_time_offsets' +114. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_098/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_098_Green/pixel_time_offsets + /acquisition/timeseries/ROI_098_Red/pixel_time_offsets' +115. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_099/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_099_Green/pixel_time_offsets + /acquisition/timeseries/ROI_099_Red/pixel_time_offsets' +116. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_100/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_100_Green/pixel_time_offsets + /acquisition/timeseries/ROI_100_Red/pixel_time_offsets' +117. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_101/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_101_Green/pixel_time_offsets + /acquisition/timeseries/ROI_101_Red/pixel_time_offsets' +118. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_102/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_102_Green/pixel_time_offsets + /acquisition/timeseries/ROI_102_Red/pixel_time_offsets' +119. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_103/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_103_Green/pixel_time_offsets + /acquisition/timeseries/ROI_103_Red/pixel_time_offsets' +120. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_104/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_104_Green/pixel_time_offsets + /acquisition/timeseries/ROI_104_Red/pixel_time_offsets' +121. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_105/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_105_Green/pixel_time_offsets + /acquisition/timeseries/ROI_105_Red/pixel_time_offsets' +122. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_106/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_106_Green/pixel_time_offsets + /acquisition/timeseries/ROI_106_Red/pixel_time_offsets' +123. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_107/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_107_Green/pixel_time_offsets + /acquisition/timeseries/ROI_107_Red/pixel_time_offsets' +124. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_108/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_108_Green/pixel_time_offsets + /acquisition/timeseries/ROI_108_Red/pixel_time_offsets' +125. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_109/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_109_Green/pixel_time_offsets + /acquisition/timeseries/ROI_109_Red/pixel_time_offsets' +126. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_110/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_110_Green/pixel_time_offsets + /acquisition/timeseries/ROI_110_Red/pixel_time_offsets' +127. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_111/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_111_Green/pixel_time_offsets + /acquisition/timeseries/ROI_111_Red/pixel_time_offsets' +128. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_112/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_112_Green/pixel_time_offsets + /acquisition/timeseries/ROI_112_Red/pixel_time_offsets' +129. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_113/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_113_Green/pixel_time_offsets + /acquisition/timeseries/ROI_113_Red/pixel_time_offsets' +130. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_114/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_114_Green/pixel_time_offsets + /acquisition/timeseries/ROI_114_Red/pixel_time_offsets' +131. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_115/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_115_Green/pixel_time_offsets + /acquisition/timeseries/ROI_115_Red/pixel_time_offsets' +132. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_116/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_116_Green/pixel_time_offsets + /acquisition/timeseries/ROI_116_Red/pixel_time_offsets' +133. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_117/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_117_Green/pixel_time_offsets + /acquisition/timeseries/ROI_117_Red/pixel_time_offsets' +134. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_118/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_118_Green/pixel_time_offsets + /acquisition/timeseries/ROI_118_Red/pixel_time_offsets' +135. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_119/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_119_Green/pixel_time_offsets + /acquisition/timeseries/ROI_119_Red/pixel_time_offsets' +136. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_120/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_120_Green/pixel_time_offsets + /acquisition/timeseries/ROI_120_Red/pixel_time_offsets' +** 257 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-18)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-18)' + 3. 'to: "/acquisition/timeseries/ROI_002_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_002_Green/timeseries (#=1-18)' + 4. 'to: "/acquisition/timeseries/ROI_002_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_002_Red/timeseries (#=1-18)' + 5. 'to: "/acquisition/timeseries/ROI_003_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_003_Green/timeseries (#=1-18)' + 6. 'to: "/acquisition/timeseries/ROI_003_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_003_Red/timeseries (#=1-18)' + 7. 'to: "/acquisition/timeseries/ROI_004_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_004_Green/timeseries (#=1-18)' + 8. 'to: "/acquisition/timeseries/ROI_004_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_004_Red/timeseries (#=1-18)' + 9. 'to: "/acquisition/timeseries/ROI_005_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_005_Green/timeseries (#=1-18)' + 10. 'to: "/acquisition/timeseries/ROI_005_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_005_Red/timeseries (#=1-18)' + 11. 'to: "/acquisition/timeseries/ROI_006_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_006_Green/timeseries (#=1-18)' + 12. 'to: "/acquisition/timeseries/ROI_006_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_006_Red/timeseries (#=1-18)' + 13. 'to: "/acquisition/timeseries/ROI_007_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_007_Green/timeseries (#=1-18)' + 14. 'to: "/acquisition/timeseries/ROI_007_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_007_Red/timeseries (#=1-18)' + 15. 'to: "/acquisition/timeseries/ROI_008_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_008_Green/timeseries (#=1-18)' + 16. 'to: "/acquisition/timeseries/ROI_008_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_008_Red/timeseries (#=1-18)' + 17. 'to: "/acquisition/timeseries/ROI_009_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_009_Green/timeseries (#=1-18)' + 18. 'to: "/acquisition/timeseries/ROI_009_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_009_Red/timeseries (#=1-18)' + 19. 'to: "/acquisition/timeseries/ROI_010_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_010_Green/timeseries (#=1-18)' + 20. 'to: "/acquisition/timeseries/ROI_010_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_010_Red/timeseries (#=1-18)' + 21. 'to: "/acquisition/timeseries/ROI_011_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_011_Green/timeseries (#=1-18)' + 22. 'to: "/acquisition/timeseries/ROI_011_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_011_Red/timeseries (#=1-18)' + 23. 'to: "/acquisition/timeseries/ROI_012_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_012_Green/timeseries (#=1-18)' + 24. 'to: "/acquisition/timeseries/ROI_012_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_012_Red/timeseries (#=1-18)' + 25. 'to: "/acquisition/timeseries/ROI_013_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_013_Green/timeseries (#=1-18)' + 26. 'to: "/acquisition/timeseries/ROI_013_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_013_Red/timeseries (#=1-18)' + 27. 'to: "/acquisition/timeseries/ROI_014_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_014_Green/timeseries (#=1-18)' + 28. 'to: "/acquisition/timeseries/ROI_014_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_014_Red/timeseries (#=1-18)' + 29. 'to: "/acquisition/timeseries/ROI_015_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_015_Green/timeseries (#=1-18)' + 30. 'to: "/acquisition/timeseries/ROI_015_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_015_Red/timeseries (#=1-18)' + 31. 'to: "/acquisition/timeseries/ROI_016_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_016_Green/timeseries (#=1-18)' + 32. 'to: "/acquisition/timeseries/ROI_016_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_016_Red/timeseries (#=1-18)' + 33. 'to: "/acquisition/timeseries/ROI_017_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_017_Green/timeseries (#=1-18)' + 34. 'to: "/acquisition/timeseries/ROI_017_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_017_Red/timeseries (#=1-18)' + 35. 'to: "/acquisition/timeseries/ROI_018_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_018_Green/timeseries (#=1-18)' + 36. 'to: "/acquisition/timeseries/ROI_018_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_018_Red/timeseries (#=1-18)' + 37. 'to: "/acquisition/timeseries/ROI_019_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_019_Green/timeseries (#=1-18)' + 38. 'to: "/acquisition/timeseries/ROI_019_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_019_Red/timeseries (#=1-18)' + 39. 'to: "/acquisition/timeseries/ROI_020_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_020_Green/timeseries (#=1-18)' + 40. 'to: "/acquisition/timeseries/ROI_020_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_020_Red/timeseries (#=1-18)' + 41. 'to: "/acquisition/timeseries/ROI_021_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_021_Green/timeseries (#=1-18)' + 42. 'to: "/acquisition/timeseries/ROI_021_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_021_Red/timeseries (#=1-18)' + 43. 'to: "/acquisition/timeseries/ROI_022_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_022_Green/timeseries (#=1-18)' + 44. 'to: "/acquisition/timeseries/ROI_022_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_022_Red/timeseries (#=1-18)' + 45. 'to: "/acquisition/timeseries/ROI_023_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_023_Green/timeseries (#=1-18)' + 46. 'to: "/acquisition/timeseries/ROI_023_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_023_Red/timeseries (#=1-18)' + 47. 'to: "/acquisition/timeseries/ROI_024_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_024_Green/timeseries (#=1-18)' + 48. 'to: "/acquisition/timeseries/ROI_024_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_024_Red/timeseries (#=1-18)' + 49. 'to: "/acquisition/timeseries/ROI_025_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_025_Green/timeseries (#=1-18)' + 50. 'to: "/acquisition/timeseries/ROI_025_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_025_Red/timeseries (#=1-18)' + 51. 'to: "/acquisition/timeseries/ROI_026_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_026_Green/timeseries (#=1-18)' + 52. 'to: "/acquisition/timeseries/ROI_026_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_026_Red/timeseries (#=1-18)' + 53. 'to: "/acquisition/timeseries/ROI_027_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_027_Green/timeseries (#=1-18)' + 54. 'to: "/acquisition/timeseries/ROI_027_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_027_Red/timeseries (#=1-18)' + 55. 'to: "/acquisition/timeseries/ROI_028_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_028_Green/timeseries (#=1-18)' + 56. 'to: "/acquisition/timeseries/ROI_028_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_028_Red/timeseries (#=1-18)' + 57. 'to: "/acquisition/timeseries/ROI_029_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_029_Green/timeseries (#=1-18)' + 58. 'to: "/acquisition/timeseries/ROI_029_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_029_Red/timeseries (#=1-18)' + 59. 'to: "/acquisition/timeseries/ROI_030_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_030_Green/timeseries (#=1-18)' + 60. 'to: "/acquisition/timeseries/ROI_030_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_030_Red/timeseries (#=1-18)' + 61. 'to: "/acquisition/timeseries/ROI_031_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_031_Green/timeseries (#=1-18)' + 62. 'to: "/acquisition/timeseries/ROI_031_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_031_Red/timeseries (#=1-18)' + 63. 'to: "/acquisition/timeseries/ROI_032_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_032_Green/timeseries (#=1-18)' + 64. 'to: "/acquisition/timeseries/ROI_032_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_032_Red/timeseries (#=1-18)' + 65. 'to: "/acquisition/timeseries/ROI_033_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_033_Green/timeseries (#=1-18)' + 66. 'to: "/acquisition/timeseries/ROI_033_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_033_Red/timeseries (#=1-18)' + 67. 'to: "/acquisition/timeseries/ROI_034_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_034_Green/timeseries (#=1-18)' + 68. 'to: "/acquisition/timeseries/ROI_034_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_034_Red/timeseries (#=1-18)' + 69. 'to: "/acquisition/timeseries/ROI_035_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_035_Green/timeseries (#=1-18)' + 70. 'to: "/acquisition/timeseries/ROI_035_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_035_Red/timeseries (#=1-18)' + 71. 'to: "/acquisition/timeseries/ROI_036_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_036_Green/timeseries (#=1-18)' + 72. 'to: "/acquisition/timeseries/ROI_036_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_036_Red/timeseries (#=1-18)' + 73. 'to: "/acquisition/timeseries/ROI_037_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_037_Green/timeseries (#=1-18)' + 74. 'to: "/acquisition/timeseries/ROI_037_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_037_Red/timeseries (#=1-18)' + 75. 'to: "/acquisition/timeseries/ROI_038_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_038_Green/timeseries (#=1-18)' + 76. 'to: "/acquisition/timeseries/ROI_038_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_038_Red/timeseries (#=1-18)' + 77. 'to: "/acquisition/timeseries/ROI_039_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_039_Green/timeseries (#=1-18)' + 78. 'to: "/acquisition/timeseries/ROI_039_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_039_Red/timeseries (#=1-18)' + 79. 'to: "/acquisition/timeseries/ROI_040_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_040_Green/timeseries (#=1-18)' + 80. 'to: "/acquisition/timeseries/ROI_040_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_040_Red/timeseries (#=1-18)' + 81. 'to: "/acquisition/timeseries/ROI_041_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_041_Green/timeseries (#=1-18)' + 82. 'to: "/acquisition/timeseries/ROI_041_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_041_Red/timeseries (#=1-18)' + 83. 'to: "/acquisition/timeseries/ROI_042_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_042_Green/timeseries (#=1-18)' + 84. 'to: "/acquisition/timeseries/ROI_042_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_042_Red/timeseries (#=1-18)' + 85. 'to: "/acquisition/timeseries/ROI_043_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_043_Green/timeseries (#=1-18)' + 86. 'to: "/acquisition/timeseries/ROI_043_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_043_Red/timeseries (#=1-18)' + 87. 'to: "/acquisition/timeseries/ROI_044_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_044_Green/timeseries (#=1-18)' + 88. 'to: "/acquisition/timeseries/ROI_044_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_044_Red/timeseries (#=1-18)' + 89. 'to: "/acquisition/timeseries/ROI_045_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_045_Green/timeseries (#=1-18)' + 90. 'to: "/acquisition/timeseries/ROI_045_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_045_Red/timeseries (#=1-18)' + 91. 'to: "/acquisition/timeseries/ROI_046_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_046_Green/timeseries (#=1-18)' + 92. 'to: "/acquisition/timeseries/ROI_046_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_046_Red/timeseries (#=1-18)' + 93. 'to: "/acquisition/timeseries/ROI_047_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_047_Green/timeseries (#=1-18)' + 94. 'to: "/acquisition/timeseries/ROI_047_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_047_Red/timeseries (#=1-18)' + 95. 'to: "/acquisition/timeseries/ROI_048_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_048_Green/timeseries (#=1-18)' + 96. 'to: "/acquisition/timeseries/ROI_048_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_048_Red/timeseries (#=1-18)' + 97. 'to: "/acquisition/timeseries/ROI_049_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_049_Green/timeseries (#=1-18)' + 98. 'to: "/acquisition/timeseries/ROI_049_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_049_Red/timeseries (#=1-18)' + 99. 'to: "/acquisition/timeseries/ROI_050_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_050_Green/timeseries (#=1-18)' +100. 'to: "/acquisition/timeseries/ROI_050_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_050_Red/timeseries (#=1-18)' +101. 'to: "/acquisition/timeseries/ROI_051_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_051_Green/timeseries (#=1-18)' +102. 'to: "/acquisition/timeseries/ROI_051_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_051_Red/timeseries (#=1-18)' +103. 'to: "/acquisition/timeseries/ROI_052_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_052_Green/timeseries (#=1-18)' +104. 'to: "/acquisition/timeseries/ROI_052_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_052_Red/timeseries (#=1-18)' +105. 'to: "/acquisition/timeseries/ROI_053_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_053_Green/timeseries (#=1-18)' +106. 'to: "/acquisition/timeseries/ROI_053_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_053_Red/timeseries (#=1-18)' +107. 'to: "/acquisition/timeseries/ROI_054_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_054_Green/timeseries (#=1-18)' +108. 'to: "/acquisition/timeseries/ROI_054_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_054_Red/timeseries (#=1-18)' +109. 'to: "/acquisition/timeseries/ROI_055_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_055_Green/timeseries (#=1-18)' +110. 'to: "/acquisition/timeseries/ROI_055_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_055_Red/timeseries (#=1-18)' +111. 'to: "/acquisition/timeseries/ROI_056_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_056_Green/timeseries (#=1-18)' +112. 'to: "/acquisition/timeseries/ROI_056_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_056_Red/timeseries (#=1-18)' +113. 'to: "/acquisition/timeseries/ROI_057_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_057_Green/timeseries (#=1-18)' +114. 'to: "/acquisition/timeseries/ROI_057_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_057_Red/timeseries (#=1-18)' +115. 'to: "/acquisition/timeseries/ROI_058_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_058_Green/timeseries (#=1-18)' +116. 'to: "/acquisition/timeseries/ROI_058_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_058_Red/timeseries (#=1-18)' +117. 'to: "/acquisition/timeseries/ROI_059_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_059_Green/timeseries (#=1-18)' +118. 'to: "/acquisition/timeseries/ROI_059_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_059_Red/timeseries (#=1-18)' +119. 'to: "/acquisition/timeseries/ROI_060_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_060_Green/timeseries (#=1-18)' +120. 'to: "/acquisition/timeseries/ROI_060_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_060_Red/timeseries (#=1-18)' +121. 'to: "/acquisition/timeseries/ROI_061_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_061_Green/timeseries (#=1-18)' +122. 'to: "/acquisition/timeseries/ROI_061_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_061_Red/timeseries (#=1-18)' +123. 'to: "/acquisition/timeseries/ROI_062_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_062_Green/timeseries (#=1-18)' +124. 'to: "/acquisition/timeseries/ROI_062_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_062_Red/timeseries (#=1-18)' +125. 'to: "/acquisition/timeseries/ROI_063_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_063_Green/timeseries (#=1-18)' +126. 'to: "/acquisition/timeseries/ROI_063_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_063_Red/timeseries (#=1-18)' +127. 'to: "/acquisition/timeseries/ROI_064_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_064_Green/timeseries (#=1-18)' +128. 'to: "/acquisition/timeseries/ROI_064_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_064_Red/timeseries (#=1-18)' +129. 'to: "/acquisition/timeseries/ROI_065_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_065_Green/timeseries (#=1-18)' +130. 'to: "/acquisition/timeseries/ROI_065_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_065_Red/timeseries (#=1-18)' +131. 'to: "/acquisition/timeseries/ROI_066_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_066_Green/timeseries (#=1-18)' +132. 'to: "/acquisition/timeseries/ROI_066_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_066_Red/timeseries (#=1-18)' +133. 'to: "/acquisition/timeseries/ROI_067_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_067_Green/timeseries (#=1-18)' +134. 'to: "/acquisition/timeseries/ROI_067_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_067_Red/timeseries (#=1-18)' +135. 'to: "/acquisition/timeseries/ROI_068_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_068_Green/timeseries (#=1-18)' +136. 'to: "/acquisition/timeseries/ROI_068_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_068_Red/timeseries (#=1-18)' +137. 'to: "/acquisition/timeseries/ROI_069_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_069_Green/timeseries (#=1-18)' +138. 'to: "/acquisition/timeseries/ROI_069_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_069_Red/timeseries (#=1-18)' +139. 'to: "/acquisition/timeseries/ROI_070_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_070_Green/timeseries (#=1-18)' +140. 'to: "/acquisition/timeseries/ROI_070_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_070_Red/timeseries (#=1-18)' +141. 'to: "/acquisition/timeseries/ROI_071_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_071_Green/timeseries (#=1-18)' +142. 'to: "/acquisition/timeseries/ROI_071_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_071_Red/timeseries (#=1-18)' +143. 'to: "/acquisition/timeseries/ROI_072_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_072_Green/timeseries (#=1-18)' +144. 'to: "/acquisition/timeseries/ROI_072_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_072_Red/timeseries (#=1-18)' +145. 'to: "/acquisition/timeseries/ROI_073_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_073_Green/timeseries (#=1-18)' +146. 'to: "/acquisition/timeseries/ROI_073_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_073_Red/timeseries (#=1-18)' +147. 'to: "/acquisition/timeseries/ROI_074_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_074_Green/timeseries (#=1-18)' +148. 'to: "/acquisition/timeseries/ROI_074_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_074_Red/timeseries (#=1-18)' +149. 'to: "/acquisition/timeseries/ROI_075_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_075_Green/timeseries (#=1-18)' +150. 'to: "/acquisition/timeseries/ROI_075_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_075_Red/timeseries (#=1-18)' +151. 'to: "/acquisition/timeseries/ROI_076_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_076_Green/timeseries (#=1-18)' +152. 'to: "/acquisition/timeseries/ROI_076_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_076_Red/timeseries (#=1-18)' +153. 'to: "/acquisition/timeseries/ROI_077_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_077_Green/timeseries (#=1-18)' +154. 'to: "/acquisition/timeseries/ROI_077_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_077_Red/timeseries (#=1-18)' +155. 'to: "/acquisition/timeseries/ROI_078_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_078_Green/timeseries (#=1-18)' +156. 'to: "/acquisition/timeseries/ROI_078_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_078_Red/timeseries (#=1-18)' +157. 'to: "/acquisition/timeseries/ROI_079_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_079_Green/timeseries (#=1-18)' +158. 'to: "/acquisition/timeseries/ROI_079_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_079_Red/timeseries (#=1-18)' +159. 'to: "/acquisition/timeseries/ROI_080_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_080_Green/timeseries (#=1-18)' +160. 'to: "/acquisition/timeseries/ROI_080_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_080_Red/timeseries (#=1-18)' +161. 'to: "/acquisition/timeseries/ROI_081_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_081_Green/timeseries (#=1-18)' +162. 'to: "/acquisition/timeseries/ROI_081_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_081_Red/timeseries (#=1-18)' +163. 'to: "/acquisition/timeseries/ROI_082_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_082_Green/timeseries (#=1-18)' +164. 'to: "/acquisition/timeseries/ROI_082_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_082_Red/timeseries (#=1-18)' +165. 'to: "/acquisition/timeseries/ROI_083_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_083_Green/timeseries (#=1-18)' +166. 'to: "/acquisition/timeseries/ROI_083_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_083_Red/timeseries (#=1-18)' +167. 'to: "/acquisition/timeseries/ROI_084_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_084_Green/timeseries (#=1-18)' +168. 'to: "/acquisition/timeseries/ROI_084_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_084_Red/timeseries (#=1-18)' +169. 'to: "/acquisition/timeseries/ROI_085_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_085_Green/timeseries (#=1-18)' +170. 'to: "/acquisition/timeseries/ROI_085_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_085_Red/timeseries (#=1-18)' +171. 'to: "/acquisition/timeseries/ROI_086_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_086_Green/timeseries (#=1-18)' +172. 'to: "/acquisition/timeseries/ROI_086_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_086_Red/timeseries (#=1-18)' +173. 'to: "/acquisition/timeseries/ROI_087_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_087_Green/timeseries (#=1-18)' +174. 'to: "/acquisition/timeseries/ROI_087_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_087_Red/timeseries (#=1-18)' +175. 'to: "/acquisition/timeseries/ROI_088_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_088_Green/timeseries (#=1-18)' +176. 'to: "/acquisition/timeseries/ROI_088_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_088_Red/timeseries (#=1-18)' +177. 'to: "/acquisition/timeseries/ROI_089_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_089_Green/timeseries (#=1-18)' +178. 'to: "/acquisition/timeseries/ROI_089_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_089_Red/timeseries (#=1-18)' +179. 'to: "/acquisition/timeseries/ROI_090_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_090_Green/timeseries (#=1-18)' +180. 'to: "/acquisition/timeseries/ROI_090_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_090_Red/timeseries (#=1-18)' +181. 'to: "/acquisition/timeseries/ROI_091_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_091_Green/timeseries (#=1-18)' +182. 'to: "/acquisition/timeseries/ROI_091_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_091_Red/timeseries (#=1-18)' +183. 'to: "/acquisition/timeseries/ROI_092_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_092_Green/timeseries (#=1-18)' +184. 'to: "/acquisition/timeseries/ROI_092_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_092_Red/timeseries (#=1-18)' +185. 'to: "/acquisition/timeseries/ROI_093_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_093_Green/timeseries (#=1-18)' +186. 'to: "/acquisition/timeseries/ROI_093_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_093_Red/timeseries (#=1-18)' +187. 'to: "/acquisition/timeseries/ROI_094_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_094_Green/timeseries (#=1-18)' +188. 'to: "/acquisition/timeseries/ROI_094_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_094_Red/timeseries (#=1-18)' +189. 'to: "/acquisition/timeseries/ROI_095_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_095_Green/timeseries (#=1-18)' +190. 'to: "/acquisition/timeseries/ROI_095_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_095_Red/timeseries (#=1-18)' +191. 'to: "/acquisition/timeseries/ROI_096_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_096_Green/timeseries (#=1-18)' +192. 'to: "/acquisition/timeseries/ROI_096_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_096_Red/timeseries (#=1-18)' +193. 'to: "/acquisition/timeseries/ROI_097_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_097_Green/timeseries (#=1-18)' +194. 'to: "/acquisition/timeseries/ROI_097_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_097_Red/timeseries (#=1-18)' +195. 'to: "/acquisition/timeseries/ROI_098_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_098_Green/timeseries (#=1-18)' +196. 'to: "/acquisition/timeseries/ROI_098_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_098_Red/timeseries (#=1-18)' +197. 'to: "/acquisition/timeseries/ROI_099_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_099_Green/timeseries (#=1-18)' +198. 'to: "/acquisition/timeseries/ROI_099_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_099_Red/timeseries (#=1-18)' +199. 'to: "/acquisition/timeseries/ROI_100_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_100_Green/timeseries (#=1-18)' +200. 'to: "/acquisition/timeseries/ROI_100_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_100_Red/timeseries (#=1-18)' +201. 'to: "/acquisition/timeseries/ROI_101_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_101_Green/timeseries (#=1-18)' +202. 'to: "/acquisition/timeseries/ROI_101_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_101_Red/timeseries (#=1-18)' +203. 'to: "/acquisition/timeseries/ROI_102_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_102_Green/timeseries (#=1-18)' +204. 'to: "/acquisition/timeseries/ROI_102_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_102_Red/timeseries (#=1-18)' +205. 'to: "/acquisition/timeseries/ROI_103_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_103_Green/timeseries (#=1-18)' +206. 'to: "/acquisition/timeseries/ROI_103_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_103_Red/timeseries (#=1-18)' +207. 'to: "/acquisition/timeseries/ROI_104_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_104_Green/timeseries (#=1-18)' +208. 'to: "/acquisition/timeseries/ROI_104_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_104_Red/timeseries (#=1-18)' +209. 'to: "/acquisition/timeseries/ROI_105_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_105_Green/timeseries (#=1-18)' +210. 'to: "/acquisition/timeseries/ROI_105_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_105_Red/timeseries (#=1-18)' +211. 'to: "/acquisition/timeseries/ROI_106_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_106_Green/timeseries (#=1-18)' +212. 'to: "/acquisition/timeseries/ROI_106_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_106_Red/timeseries (#=1-18)' +213. 'to: "/acquisition/timeseries/ROI_107_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_107_Green/timeseries (#=1-18)' +214. 'to: "/acquisition/timeseries/ROI_107_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_107_Red/timeseries (#=1-18)' +215. 'to: "/acquisition/timeseries/ROI_108_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_108_Green/timeseries (#=1-18)' +216. 'to: "/acquisition/timeseries/ROI_108_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_108_Red/timeseries (#=1-18)' +217. 'to: "/acquisition/timeseries/ROI_109_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_109_Green/timeseries (#=1-18)' +218. 'to: "/acquisition/timeseries/ROI_109_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_109_Red/timeseries (#=1-18)' +219. 'to: "/acquisition/timeseries/ROI_110_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_110_Green/timeseries (#=1-18)' +220. 'to: "/acquisition/timeseries/ROI_110_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_110_Red/timeseries (#=1-18)' +221. 'to: "/acquisition/timeseries/ROI_111_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_111_Green/timeseries (#=1-18)' +222. 'to: "/acquisition/timeseries/ROI_111_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_111_Red/timeseries (#=1-18)' +223. 'to: "/acquisition/timeseries/ROI_112_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_112_Green/timeseries (#=1-18)' +224. 'to: "/acquisition/timeseries/ROI_112_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_112_Red/timeseries (#=1-18)' +225. 'to: "/acquisition/timeseries/ROI_113_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_113_Green/timeseries (#=1-18)' +226. 'to: "/acquisition/timeseries/ROI_113_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_113_Red/timeseries (#=1-18)' +227. 'to: "/acquisition/timeseries/ROI_114_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_114_Green/timeseries (#=1-18)' +228. 'to: "/acquisition/timeseries/ROI_114_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_114_Red/timeseries (#=1-18)' +229. 'to: "/acquisition/timeseries/ROI_115_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_115_Green/timeseries (#=1-18)' +230. 'to: "/acquisition/timeseries/ROI_115_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_115_Red/timeseries (#=1-18)' +231. 'to: "/acquisition/timeseries/ROI_116_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_116_Green/timeseries (#=1-18)' +232. 'to: "/acquisition/timeseries/ROI_116_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_116_Red/timeseries (#=1-18)' +233. 'to: "/acquisition/timeseries/ROI_117_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_117_Green/timeseries (#=1-18)' +234. 'to: "/acquisition/timeseries/ROI_117_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_117_Red/timeseries (#=1-18)' +235. 'to: "/acquisition/timeseries/ROI_118_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_118_Green/timeseries (#=1-18)' +236. 'to: "/acquisition/timeseries/ROI_118_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_118_Red/timeseries (#=1-18)' +237. 'to: "/acquisition/timeseries/ROI_119_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_119_Green/timeseries (#=1-18)' +238. 'to: "/acquisition/timeseries/ROI_119_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_119_Red/timeseries (#=1-18)' +239. 'to: "/acquisition/timeseries/ROI_120_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_120_Green/timeseries (#=1-18)' +240. 'to: "/acquisition/timeseries/ROI_120_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_120_Red/timeseries (#=1-18)' +241. 'to: "/acquisition/timeseries/Zstack_Red_0014" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0014/reference_images/Zstack_image' +242. 'to: "/acquisition/timeseries/Zstack_Red_0015" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0015/reference_images/Zstack_image' +243. 'to: "/acquisition/timeseries/Zstack_Red_0017" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0017/reference_images/Zstack_image' +244. 'to: "/acquisition/timeseries/Zstack_Red_0018" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0018/reference_images/Zstack_image' +245. 'to: "/acquisition/timeseries/Zstack_Red_0020" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0020/reference_images/Zstack_image' +246. 'to: "/acquisition/timeseries/Zstack_Red_0031" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0031/reference_images/Zstack_image' +247. 'to: "/acquisition/timeseries/Zstack_Red_0032" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0032/reference_images/Zstack_image' +248. 'to: "/acquisition/timeseries/Zstack_Red_0033" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/reference_images/Zstack_image' +249. 'to: "/acquisition/timeseries/Zstack_Red_0034" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0034/reference_images/Zstack_image' +250. 'to: "/acquisition/timeseries/Zstack_Red_0035" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0035/reference_images/Zstack_image' +251. 'to: "/acquisition/timeseries/Zstack_Red_0044" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0044/reference_images/Zstack_image' +252. 'to: "/acquisition/timeseries/Zstack_Red_0045" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0045/reference_images/Zstack_image' +253. 'to: "/acquisition/timeseries/Zstack_Red_0046" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0046/reference_images/Zstack_image' +254. 'to: "/acquisition/timeseries/Zstack_Red_0047" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0047/reference_images/Zstack_image' +255. 'to: "/acquisition/timeseries/Zstack_Red_0048" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0048/reference_images/Zstack_image' +256. 'to: "/acquisition/timeseries/Zstack_Red_0049" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0049/reference_images/Zstack_image' +257. 'to: "/acquisition/timeseries/speed_data" 18 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-18)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 5505 attributes (sorted alphabetically) (343 combined): + 1. '/acquisition/timeseries/ROI_#_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-120)' + 2. '/acquisition/timeseries/ROI_#_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-120)' + 3. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 4. '/acquisition/timeseries/ROI_#_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-120)' + 5. '/acquisition/timeseries/ROI_#_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-120)' + 6. '/acquisition/timeseries/ROI_#_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-120)' + 7. '/acquisition/timeseries/ROI_#_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-120)' + 8. '/acquisition/timeseries/ROI_#_Green/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-120)' + 9. '/acquisition/timeseries/ROI_#_Green/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-120)' + 10. '/acquisition/timeseries/ROI_#_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-120)' + 11. '/acquisition/timeseries/ROI_#_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-120)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-120)' + 13. '/acquisition/timeseries/ROI_#_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-120)' + 14. '/acquisition/timeseries/ROI_#_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-120)' + 15. '/acquisition/timeseries/ROI_#_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-120)' + 16. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 17. '/acquisition/timeseries/ROI_#_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-120)' + 18. '/acquisition/timeseries/ROI_#_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-120)' + 19. '/acquisition/timeseries/ROI_#_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-120)' + 20. '/acquisition/timeseries/ROI_#_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-120)' + 21. '/acquisition/timeseries/ROI_#_Red/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-120)' + 22. '/acquisition/timeseries/ROI_#_Red/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-120)' + 23. '/acquisition/timeseries/ROI_#_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-120)' + 24. '/acquisition/timeseries/ROI_#_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-120)' + 25. '/acquisition/timeseries/ROI_#_Red/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-120)' + 26. '/acquisition/timeseries/ROI_#_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-120)' + 27. '/acquisition/timeseries/ROI_002_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPc'' + 28. '/acquisition/timeseries/ROI_002_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPC'' + 29. '/acquisition/timeseries/ROI_003_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnJ'' + 30. '/acquisition/timeseries/ROI_003_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroj'' + 31. '/acquisition/timeseries/ROI_004_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMq'' + 32. '/acquisition/timeseries/ROI_004_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMQ'' + 33. '/acquisition/timeseries/ROI_005_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkX'' + 34. '/acquisition/timeseries/ROI_005_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklx'' + 35. '/acquisition/timeseries/ROI_006_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJE'' + 36. '/acquisition/timeseries/ROI_006_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKe'' + 37. '/acquisition/timeseries/ROI_007_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcil'' + 38. '/acquisition/timeseries/ROI_007_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiL'' + 39. '/acquisition/timeseries/ROI_008_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGS'' + 40. '/acquisition/timeseries/ROI_008_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHs'' + 41. '/acquisition/timeseries/ROI_009_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfz'' + 42. '/acquisition/timeseries/ROI_009_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfZ'' + 43. '/acquisition/timeseries/ROI_010_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzVCL'' + 44. '/acquisition/timeseries/ROI_010_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytWDl'' + 45. '/acquisition/timeseries/ROI_011_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCASbs'' + 46. '/acquisition/timeseries/ROI_011_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuTbS'' + 47. '/acquisition/timeseries/ROI_012_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBOzZ'' + 48. '/acquisition/timeseries/ROI_012_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvPAz'' + 49. '/acquisition/timeseries/ROI_013_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYG'' + 50. '/acquisition/timeseries/ROI_013_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZg'' + 51. '/acquisition/timeseries/ROI_014_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxn'' + 52. '/acquisition/timeseries/ROI_014_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxN'' + 53. '/acquisition/timeseries/ROI_015_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVU'' + 54. '/acquisition/timeseries/ROI_015_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWu'' + 55. '/acquisition/timeseries/ROI_016_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuB'' + 56. '/acquisition/timeseries/ROI_016_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBvb'' + 57. '/acquisition/timeseries/ROI_017_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTi'' + 58. '/acquisition/timeseries/ROI_017_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTI'' + 59. '/acquisition/timeseries/ROI_018_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrP'' + 60. '/acquisition/timeseries/ROI_018_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusp'' + 61. '/acquisition/timeseries/ROI_019_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQw'' + 62. '/acquisition/timeseries/ROI_019_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQW'' + 63. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnI' (#=20,101)' + 64. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroi' (#=20,101)' + 65. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMp' (#=21,102)' + 66. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMP' (#=21,102)' + 67. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkW' (#=22,103)' + 68. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklw' (#=22,103)' + 69. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJD' (#=23,104)' + 70. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKd' (#=23,104)' + 71. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcik' (#=24,105)' + 72. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiK' (#=24,105)' + 73. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGR' (#=25,106)' + 74. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHr' (#=25,106)' + 75. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfy' (#=26,107)' + 76. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfY' (#=26,107)' + 77. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREf' (#=27,108)' + 78. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEF' (#=27,108)' + 79. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcM' (#=28,109)' + 80. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdm' (#=28,109)' + 81. '/acquisition/timeseries/ROI_029_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBt'' + 82. '/acquisition/timeseries/ROI_029_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBT'' + 83. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCKYF' (#=30,111)' + 84. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywLZf' (#=30,111)' + 85. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDHxm' (#=31,112)' + 86. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxIxM' (#=31,112)' + 87. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEDVT' (#=32,113)' + 88. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyyEWt' (#=32,113)' + 89. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuA' (#=33,114)' + 90. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBva' (#=33,114)' + 91. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTh' (#=34,115)' + 92. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTH' (#=34,115)' + 93. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrO' (#=35,116)' + 94. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBuso' (#=35,116)' + 95. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQv' (#=36,117)' + 96. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQV' (#=36,117)' + 97. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpc' (#=37,118)' + 98. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpC' (#=37,118)' + 99. '/acquisition/timeseries/ROI_#_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNJ' (#=38,119)' +100. '/acquisition/timeseries/ROI_#_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOj' (#=38,119)' +101. '/acquisition/timeseries/ROI_039_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmq'' +102. '/acquisition/timeseries/ROI_039_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmQ'' +103. '/acquisition/timeseries/ROI_040_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJC'' +104. '/acquisition/timeseries/ROI_040_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKc'' +105. '/acquisition/timeseries/ROI_041_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcij'' +106. '/acquisition/timeseries/ROI_041_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiJ'' +107. '/acquisition/timeseries/ROI_042_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGQ'' +108. '/acquisition/timeseries/ROI_042_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHq'' +109. '/acquisition/timeseries/ROI_043_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfx'' +110. '/acquisition/timeseries/ROI_043_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfX'' +111. '/acquisition/timeseries/ROI_044_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREe'' +112. '/acquisition/timeseries/ROI_044_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSEE'' +113. '/acquisition/timeseries/ROI_045_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcL'' +114. '/acquisition/timeseries/ROI_045_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdl'' +115. '/acquisition/timeseries/ROI_046_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBs'' +116. '/acquisition/timeseries/ROI_046_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBS'' +117. '/acquisition/timeseries/ROI_047_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZZ'' +118. '/acquisition/timeseries/ROI_047_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIaz'' +119. '/acquisition/timeseries/ROI_048_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyG'' +120. '/acquisition/timeseries/ROI_048_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzg'' +121. '/acquisition/timeseries/ROI_049_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXn'' +122. '/acquisition/timeseries/ROI_049_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXN'' +123. '/acquisition/timeseries/ROI_050_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFAuz'' +124. '/acquisition/timeseries/ROI_050_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzBuZ'' +125. '/acquisition/timeseries/ROI_051_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGwTg'' +126. '/acquisition/timeseries/ROI_051_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAxTG'' +127. '/acquisition/timeseries/ROI_052_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHtrN'' +128. '/acquisition/timeseries/ROI_052_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBusn'' +129. '/acquisition/timeseries/ROI_053_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQu'' +130. '/acquisition/timeseries/ROI_053_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQU'' +131. '/acquisition/timeseries/ROI_054_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpb'' +132. '/acquisition/timeseries/ROI_054_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpB'' +133. '/acquisition/timeseries/ROI_055_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNI'' +134. '/acquisition/timeseries/ROI_055_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOi'' +135. '/acquisition/timeseries/ROI_056_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmp'' +136. '/acquisition/timeseries/ROI_056_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmP'' +137. '/acquisition/timeseries/ROI_057_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKW'' +138. '/acquisition/timeseries/ROI_057_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLw'' +139. '/acquisition/timeseries/ROI_058_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjD'' +140. '/acquisition/timeseries/ROI_058_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkd'' +141. '/acquisition/timeseries/ROI_059_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIk'' +142. '/acquisition/timeseries/ROI_059_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIK'' +143. '/acquisition/timeseries/ROI_060_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfw'' +144. '/acquisition/timeseries/ROI_060_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfW'' +145. '/acquisition/timeseries/ROI_061_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCHREd'' +146. '/acquisition/timeseries/ROI_061_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyBSED'' +147. '/acquisition/timeseries/ROI_062_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIOcK'' +148. '/acquisition/timeseries/ROI_062_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCPdk'' +149. '/acquisition/timeseries/ROI_063_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBr'' +150. '/acquisition/timeseries/ROI_063_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBR'' +151. '/acquisition/timeseries/ROI_064_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZY'' +152. '/acquisition/timeseries/ROI_064_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIay'' +153. '/acquisition/timeseries/ROI_065_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyF'' +154. '/acquisition/timeseries/ROI_065_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEzf'' +155. '/acquisition/timeseries/ROI_066_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXm'' +156. '/acquisition/timeseries/ROI_066_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXM'' +157. '/acquisition/timeseries/ROI_067_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNwvT'' +158. '/acquisition/timeseries/ROI_067_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHxwt'' +159. '/acquisition/timeseries/ROI_068_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCOsUA'' +160. '/acquisition/timeseries/ROI_068_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyItVa'' +161. '/acquisition/timeseries/ROI_069_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPpth'' +162. '/acquisition/timeseries/ROI_069_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJqtH'' +163. '/acquisition/timeseries/ROI_070_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCIpQt'' +164. '/acquisition/timeseries/ROI_070_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyCqQT'' +165. '/acquisition/timeseries/ROI_071_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJmpa'' +166. '/acquisition/timeseries/ROI_071_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDnpA'' +167. '/acquisition/timeseries/ROI_072_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKiNH'' +168. '/acquisition/timeseries/ROI_072_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEjOh'' +169. '/acquisition/timeseries/ROI_073_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmo'' +170. '/acquisition/timeseries/ROI_073_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmO'' +171. '/acquisition/timeseries/ROI_074_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKV'' +172. '/acquisition/timeseries/ROI_074_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLv'' +173. '/acquisition/timeseries/ROI_075_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjC'' +174. '/acquisition/timeseries/ROI_075_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkc'' +175. '/acquisition/timeseries/ROI_076_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIj'' +176. '/acquisition/timeseries/ROI_076_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVIJ'' +177. '/acquisition/timeseries/ROI_077_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCORgQ'' +178. '/acquisition/timeseries/ROI_077_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyIShq'' +179. '/acquisition/timeseries/ROI_078_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPNFx'' +180. '/acquisition/timeseries/ROI_078_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJOFX'' +181. '/acquisition/timeseries/ROI_079_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCQKee'' +182. '/acquisition/timeseries/ROI_079_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyKLeE'' +183. '/acquisition/timeseries/ROI_080_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCJKBq'' +184. '/acquisition/timeseries/ROI_080_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyDLBQ'' +185. '/acquisition/timeseries/ROI_081_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCKGZX'' +186. '/acquisition/timeseries/ROI_081_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyEIax'' +187. '/acquisition/timeseries/ROI_082_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLDyE'' +188. '/acquisition/timeseries/ROI_082_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFEze'' +189. '/acquisition/timeseries/ROI_083_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMzXl'' +190. '/acquisition/timeseries/ROI_083_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGAXL'' +191. '/acquisition/timeseries/ROI_084_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNwvS'' +192. '/acquisition/timeseries/ROI_084_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHxws'' +193. '/acquisition/timeseries/ROI_085_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCOsUz'' +194. '/acquisition/timeseries/ROI_085_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyItUZ'' +195. '/acquisition/timeseries/ROI_086_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPptg'' +196. '/acquisition/timeseries/ROI_086_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJqtG'' +197. '/acquisition/timeseries/ROI_087_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCQlRN'' +198. '/acquisition/timeseries/ROI_087_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyKmSn'' +199. '/acquisition/timeseries/ROI_088_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCRiqu'' +200. '/acquisition/timeseries/ROI_088_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyLjqU'' +201. '/acquisition/timeseries/ROI_089_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCSePb'' +202. '/acquisition/timeseries/ROI_089_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyMfPB'' +203. '/acquisition/timeseries/ROI_090_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCLfmn'' +204. '/acquisition/timeseries/ROI_090_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyFgmN'' +205. '/acquisition/timeseries/ROI_091_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMbKU'' +206. '/acquisition/timeseries/ROI_091_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGcLu'' +207. '/acquisition/timeseries/ROI_092_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCMYjB'' +208. '/acquisition/timeseries/ROI_092_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyGZkb'' +209. '/acquisition/timeseries/ROI_093_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCNUIi'' +210. '/acquisition/timeseries/ROI_093_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyHVII'' +211. '/acquisition/timeseries/ROI_094_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCORgP'' +212. '/acquisition/timeseries/ROI_094_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyIShp'' +213. '/acquisition/timeseries/ROI_095_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCPNFw'' +214. '/acquisition/timeseries/ROI_095_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyJOFW'' +215. '/acquisition/timeseries/ROI_096_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCQKed'' +216. '/acquisition/timeseries/ROI_096_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyKLeD'' +217. '/acquisition/timeseries/ROI_097_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCRGCK'' +218. '/acquisition/timeseries/ROI_097_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyLHDk'' +219. '/acquisition/timeseries/ROI_098_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCSDbr'' +220. '/acquisition/timeseries/ROI_098_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyMEbR'' +221. '/acquisition/timeseries/ROI_099_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCTzzY'' +222. '/acquisition/timeseries/ROI_099_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyNAAy'' +223. '/acquisition/timeseries/ROI_100_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPb'' +224. '/acquisition/timeseries/ROI_100_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPB'' +225. '/acquisition/timeseries/ROI_110_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBOzY'' +226. '/acquisition/timeseries/ROI_110_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvPAy'' +227. '/acquisition/timeseries/ROI_120_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkV'' +228. '/acquisition/timeseries/ROI_120_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklv'' +229. '/acquisition/timeseries/Zstack_Green_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-79)' +230. '/acquisition/timeseries/Zstack_Green_# comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"' (#=1-79)' +231. '/acquisition/timeseries/Zstack_Green_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-79)' +232. '/acquisition/timeseries/Zstack_Green_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-79)' +233. '/acquisition/timeseries/Zstack_Green_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-79)' +234. '/acquisition/timeseries/Zstack_Green_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-79)' +235. '/acquisition/timeseries/Zstack_Green_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-79)' +236. '/acquisition/timeseries/Zstack_Green_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-79)' +237. '/acquisition/timeseries/Zstack_Green_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-79)' +238. '/acquisition/timeseries/Zstack_Green_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-79)' +239. '/acquisition/timeseries/Zstack_Green_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-79)' +240. '/acquisition/timeseries/Zstack_Green_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-79)' +241. '/acquisition/timeseries/Zstack_Red_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-79)' +242. '/acquisition/timeseries/Zstack_Red_# comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"' (#=1-79)' +243. '/acquisition/timeseries/Zstack_Red_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-79)' +244. '/acquisition/timeseries/Zstack_Red_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-79)' +245. '/acquisition/timeseries/Zstack_Red_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-79)' +246. '/acquisition/timeseries/Zstack_Red_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-79)' +247. '/acquisition/timeseries/Zstack_Red_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-79)' +248. '/acquisition/timeseries/Zstack_Red_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-79)' +249. '/acquisition/timeseries/Zstack_Red_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-79)' +250. '/acquisition/timeseries/Zstack_Red_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-79)' +251. '/acquisition/timeseries/Zstack_Red_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-79)' +252. '/acquisition/timeseries/Zstack_Red_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-79)' +253. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +254. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +255. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' +256. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' +257. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +258. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +259. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' +260. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' +261. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' +262. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' +263. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +264. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +265. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +266. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' +267. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' +268. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +269. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +270. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' +271. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' +272. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' +273. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' +274. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +275. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' +276. '/epochs/trial_# links: dtype=|S58, shape=(241,) size (13978) val='["'ROI_001_Green' is '/acquisition/timese...jFrmoG' (#=1-18)' +277. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-18)' +278. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' +279. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-79)' +280. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-79)' +281. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +282. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +283. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +284. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' +285. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +286. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +287. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' +288. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +289. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' +290. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +291. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' +292. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' +293. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' +294. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' +295. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' +296. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' +297. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' +298. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-12)' +299. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=1-12)' +300. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0015/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=13-17)' +301. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0015/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=13-17)' +302. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=18-25)' +303. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0017/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=18-25)' +304. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=26-34)' +305. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0018/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=26-34)' +306. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=35-41)' +307. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0020/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=35-41)' +308. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=42-49)' +309. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0031/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=42-49)' +310. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=50-54)' +311. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0032/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=50-54)' +312. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=55-60)' +313. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=55-60)' +314. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=61-68)' +315. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0034/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=61-68)' +316. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=69-72)' +317. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0035/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=69-72)' +318. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0044/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=73-76)' +319. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0044/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=73-76)' +320. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=77-84)' +321. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0045/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=77-84)' +322. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=85-95)' +323. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0046/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=85-95)' +324. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=96-105)' +325. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=96-105)' +326. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=106-112)' +327. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0048/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=106-112)' +328. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=113-120)' +329. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=113-120)' +330. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' +331. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +332. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +333. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +334. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +335. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +336. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +337. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +338. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +339. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +340. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +341. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +342. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +343. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 15078 datasets (sorted alphabetically) (1164 combined): + 1. '/acquisition/timeseries/ROI_#_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-120)' + 2. '/acquisition/timeseries/ROI_#_Green/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-120)' + 3. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(52722, 1, 1) size (47951), compress=gzip val='[[[119]],[[122]],[[116]],[[123]],[[122]],...hGMrqn'' + 4. '/acquisition/timeseries/ROI_#_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-120)' + 5. '/acquisition/timeseries/ROI_#_Green/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[3.418e-07,3.418e-07]' (#=1-120)' + 6. '/acquisition/timeseries/ROI_#_Green/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-120)' + 7. 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'/epochs/trial_0008/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='20503' (#=1-120)' +535. '/epochs/trial_0008/speed_data/idx_start: dtype=int32, shape=() size (4) val='45042'' +536. '/epochs/trial_0008/start_time: dtype=float64, shape=() size (8) val='96.64'' +537. '/epochs/trial_0008/stop_time: dtype=float64, shape=() size (8) val='110.4'' +538. '/epochs/trial_0009/ROI_#_Green/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +539. '/epochs/trial_0009/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='23432' (#=1-120)' +540. '/epochs/trial_0009/ROI_#_Red/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +541. '/epochs/trial_0009/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='23432' (#=1-120)' +542. '/epochs/trial_0009/speed_data/idx_start: dtype=int32, shape=() size (4) val='51477'' +543. '/epochs/trial_0009/start_time: dtype=float64, shape=() size (8) val='110.4'' +544. 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'/epochs/trial_0012/start_time: dtype=float64, shape=() size (8) val='151.9'' +565. '/epochs/trial_0012/stop_time: dtype=float64, shape=() size (8) val='165.7'' +566. '/epochs/trial_0013/ROI_#_Green/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +567. '/epochs/trial_0013/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='35148' (#=1-120)' +568. '/epochs/trial_0013/ROI_#_Red/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +569. '/epochs/trial_0013/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='35148' (#=1-120)' +570. '/epochs/trial_0013/speed_data/idx_start: dtype=int32, shape=() size (4) val='77217'' +571. '/epochs/trial_0013/start_time: dtype=float64, shape=() size (8) val='165.7'' +572. '/epochs/trial_0013/stop_time: dtype=float64, shape=() size (8) val='179.5'' +573. '/epochs/trial_0014/ROI_#_Green/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +574. '/epochs/trial_0014/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='38077' (#=1-120)' +575. '/epochs/trial_0014/ROI_#_Red/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +576. '/epochs/trial_0014/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='38077' (#=1-120)' +577. '/epochs/trial_0014/speed_data/idx_start: dtype=int32, shape=() size (4) val='83652'' +578. '/epochs/trial_0014/start_time: dtype=float64, shape=() size (8) val='179.5'' +579. '/epochs/trial_0014/stop_time: dtype=float64, shape=() size (8) val='193.3'' +580. '/epochs/trial_0015/ROI_#_Green/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +581. '/epochs/trial_0015/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='41006' (#=1-120)' +582. '/epochs/trial_0015/ROI_#_Red/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +583. '/epochs/trial_0015/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='41006' (#=1-120)' +584. '/epochs/trial_0015/speed_data/idx_start: dtype=int32, shape=() size (4) val='90087'' +585. '/epochs/trial_0015/start_time: dtype=float64, shape=() size (8) val='193.3'' +586. '/epochs/trial_0015/stop_time: dtype=float64, shape=() size (8) val='207.1'' +587. '/epochs/trial_0016/ROI_#_Green/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +588. '/epochs/trial_0016/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='43935' (#=1-120)' +589. '/epochs/trial_0016/ROI_#_Red/count: dtype=int32, shape=() size (4) val='2929' (#=1-120)' +590. '/epochs/trial_0016/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='43935' (#=1-120)' +591. '/epochs/trial_0016/speed_data/idx_start: dtype=int32, shape=() size (4) val='96522'' +592. '/epochs/trial_0016/start_time: dtype=float64, shape=() size (8) val='207.1'' +593. '/epochs/trial_0016/stop_time: dtype=float64, shape=() size (8) val='220.9'' +594. 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'/epochs/trial_0018/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='49793' (#=1-120)' +605. '/epochs/trial_0018/speed_data/idx_start: dtype=int32, shape=() size (4) val='109393'' +606. '/epochs/trial_0018/start_time: dtype=float64, shape=() size (8) val='234.7'' +607. '/epochs/trial_0018/stop_time: dtype=float64, shape=() size (8) val='248.5'' +608. '/file_create_date: dtype=--, shape=(1,) size (--), compress=gzip val='"--value removed for NWB signature--"'' +609. '/general/data_collection: dtype=|S80, shape=() size (80) val='"Text notes about data collection and ana...gWoCry'' +610. '/general/devices/AOL_microscope: dtype=|S57, shape=() size (57) val='"Random access 3d acousto-optic lens two-...ekQKnw'' +611. '/general/devices/air_puff_device: dtype=|S53, shape=() size (53) val='"Delivers an air puff stimulus to the mou...NXTbu'' +612. '/general/devices/mouse_wheel_device: dtype=|S24, shape=() size (24) val='"Records mouse speed data"'' +613. '/general/experiment_description: dtype=|S84, shape=() size (84) val='"A general description of the experiment ...LbatF'' +614. '/general/experimenter: dtype=|S15, shape=() size (15) val='"Frederic Lanore"'' +615. '/general/institution: dtype=|S25, shape=() size (25) val='"University College London"'' +616. '/general/lab: dtype=|S33, shape=() size (33) val='"Silver Lab (http://silverlab.org)"'' +617. '/general/labview_header: dtype=|S37, shape=(31, 3) size (650), compress=gzip val='[["LOGIN","User",""Fred""],["LOGIN","Prof...fhDztr'' +618. '/general/notes: dtype=|S62, shape=() size (62) val='"Notes about the experiment that don't fi...jyjZeD'' +619. '/general/optophysiology/Zstack#/description: dtype=|S17, shape=() size (17) val='"Reference Z stack"' (#=1-79)' +620. '/general/optophysiology/Zstack#/device: dtype=|S14, shape=() size (14) val='"AOL_microscope"' (#=1-79)' +621. 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'/general/optophysiology/Zstack0029/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,22],[0.3425,0,22],[0.6849,0,22],[1...qCAyJ'' +659. '/general/optophysiology/Zstack0030/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,20],[0.3425,0,20],[0.6849,0,20],[1...jiXJNh'' +660. '/general/optophysiology/Zstack0031/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,18],[0.3425,0,18],[0.6849,0,18],[1...gMejfp'' +661. '/general/optophysiology/Zstack0032/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,16],[0.3425,0,16],[0.6849,0,16],[1...epkIxx'' +662. '/general/optophysiology/Zstack0033/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,14],[0.3425,0,14],[0.6849,0,14],[1...kKMred'' +663. 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'/general/optophysiology/Zstack0074/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-68],[0.3425,0,-68],[0.6849,0,-68]...kwPGOF'' +704. '/general/optophysiology/Zstack0075/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-70],[0.3425,0,-70],[0.6849,0,-70]...cEcZzR'' +705. '/general/optophysiology/Zstack0076/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-72],[0.3425,0,-72],[0.6849,0,-72]...gaFcht'' +706. '/general/optophysiology/Zstack0077/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-74],[0.3425,0,-74],[0.6849,0,-74]...jxheOV'' +707. '/general/optophysiology/Zstack0078/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-76],[0.3425,0,-76],[0.6849,0,-76]...bEuxAh'' +708. '/general/optophysiology/Zstack0079/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-78],[0.3425,0,-78],[0.6849,0,-78]...faWAhJ'' +709. '/general/optophysiology/cycle_time: dtype=float32, shape=() size (4) val='0.004699'' +710. '/general/optophysiology/frame_size: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' +711. '/general/optophysiology/imaging_mode: dtype=|S8, shape=() size (8) val='"pointing"'' +712. '/general/optophysiology/zplane_pockels: dtype=float32, shape=(79, 4) size (690), compress=gzip val='[[78,78,60.25,37],[76,76,60.32,35],[74,74...erpSPT'' +713. '/general/pharmacology: dtype=|S152, shape=() size (152) val='"Description of drugs used, including how...goKGik'' +714. '/general/protocol: dtype=|S76, shape=() size (76) val='"Experimental protocol, if applicable, e....bWYeFo'' +715. '/general/related_publications: dtype=|S70, shape=() size (70) val='"Optional list of related publications, i...gGeOxQ'' +716. '/general/session_id: dtype=|S15, shape=() size (15) val='"170317_10_11_01"'' +717. '/general/slices: dtype=|S127, shape=() size (127) val='"Description of slices, including informa...bwDbqR'' +718. '/general/specifications/e-labview.py: dtype=|S1534, shape=() size (1534) val='"# NWB extension to store LabView header ...fvMAMg'' +719. '/general/specifications/e-pixeltimes.py: dtype=|S2701, shape=() size (2701) val='"# NWB extension to store per-pixel time ...gVgtZh'' +720. '/general/specifications/nwb_core.py: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +721. '/general/stimulus: dtype=|S84, shape=() size (84) val='"Notes about stimuli, such as how and whe...DShaM'' +722. '/general/subject/age: dtype=|S25, shape=() size (25) val='"Age of subject. Optional."'' +723. '/general/subject/description: dtype=|S88, shape=() size (88) val='"Description of subject and where subject...fXgfBt'' +724. '/general/subject/genotype: dtype=|S59, shape=() size (59) val='"Genetic strain. If absent, assume Wild T...eOaNbr'' +725. '/general/subject/sex: dtype=|S28, shape=() size (28) val='"Gender of subject. Optional."'' +726. '/general/subject/species: dtype=|S29, shape=() size (29) val='"Species of subject. Optional."'' +727. '/general/subject/subject_id: dtype=|S80, shape=() size (80) val='"ID of animal/person used/participating i...hoSoPZ'' +728. '/general/subject/weight: dtype=|S88, shape=() size (88) val='"Weight at time of experiment, at time of...grFgyL'' +729. '/general/surgery: dtype=|S134, shape=() size (134) val='"Narrative description about surgery/surg...dKKeYq'' +730. '/general/virus: dtype=|S130, shape=() size (130) val='"Information about virus(es) used in expe...cMsZNh'' +731. '/identifier: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +732. '/nwb_version: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +733. 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'/stimulus/presentation/air_puff/num_samples: dtype=int32, shape=() size (4) val='18'' +1164. '/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(18,) size (155), compress=gzip val='[5,18.81,32.61,46.42,60.22,74.03,87.83,10...hMTaeA'' +-------------------- +** Summary +5163 groups, 15078 datasets, 5505 attributes diff --git a/Python/test/data/170322_14_06_43.sig b/Python/test/data/170322_14_06_43.sig new file mode 100644 index 0000000..ef41347 --- /dev/null +++ b/Python/test/data/170322_14_06_43.sig @@ -0,0 +1,738 @@ +<% Generating signature for 170322_14_06_43.nwb %> + +** No datasets hard links. +** No groups hard links. +** 13 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0033/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/description' + 2. 'to: "/general/optophysiology/Zstack0036/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0036/description' + 3. 'to: "/general/optophysiology/Zstack0037/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0037/description' + 4. 'to: "/general/optophysiology/Zstack0047/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0047/description' + 5. 'to: "/general/optophysiology/Zstack0049/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0049/description' + 6. 'to: "/general/optophysiology/Zstack0052/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0052/description' + 7. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' + 8. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_002/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_002_Green/pixel_time_offsets + /acquisition/timeseries/ROI_002_Red/pixel_time_offsets' + 9. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0036/ROI_004/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_004_Green/pixel_time_offsets + /acquisition/timeseries/ROI_004_Red/pixel_time_offsets' + 10. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0037/ROI_003/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_003_Green/pixel_time_offsets + /acquisition/timeseries/ROI_003_Red/pixel_time_offsets' + 11. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_005_Green/pixel_time_offsets + /acquisition/timeseries/ROI_005_Red/pixel_time_offsets' + 12. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_006_Green/pixel_time_offsets + /acquisition/timeseries/ROI_006_Red/pixel_time_offsets' + 13. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_007_Green/pixel_time_offsets + /acquisition/timeseries/ROI_007_Red/pixel_time_offsets' +** 21 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-18)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-18)' + 3. 'to: "/acquisition/timeseries/ROI_002_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_002_Green/timeseries (#=1-18)' + 4. 'to: "/acquisition/timeseries/ROI_002_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_002_Red/timeseries (#=1-18)' + 5. 'to: "/acquisition/timeseries/ROI_003_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_003_Green/timeseries (#=1-18)' + 6. 'to: "/acquisition/timeseries/ROI_003_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_003_Red/timeseries (#=1-18)' + 7. 'to: "/acquisition/timeseries/ROI_004_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_004_Green/timeseries (#=1-18)' + 8. 'to: "/acquisition/timeseries/ROI_004_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_004_Red/timeseries (#=1-18)' + 9. 'to: "/acquisition/timeseries/ROI_005_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_005_Green/timeseries (#=1-18)' + 10. 'to: "/acquisition/timeseries/ROI_005_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_005_Red/timeseries (#=1-18)' + 11. 'to: "/acquisition/timeseries/ROI_006_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_006_Green/timeseries (#=1-18)' + 12. 'to: "/acquisition/timeseries/ROI_006_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_006_Red/timeseries (#=1-18)' + 13. 'to: "/acquisition/timeseries/ROI_007_Green" 18 groups (1 combined): + /epochs/trial_#/ROI_007_Green/timeseries (#=1-18)' + 14. 'to: "/acquisition/timeseries/ROI_007_Red" 18 groups (1 combined): + /epochs/trial_#/ROI_007_Red/timeseries (#=1-18)' + 15. 'to: "/acquisition/timeseries/Zstack_Red_0033" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/reference_images/Zstack_image' + 16. 'to: "/acquisition/timeseries/Zstack_Red_0036" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0036/reference_images/Zstack_image' + 17. 'to: "/acquisition/timeseries/Zstack_Red_0037" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0037/reference_images/Zstack_image' + 18. 'to: "/acquisition/timeseries/Zstack_Red_0047" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0047/reference_images/Zstack_image' + 19. 'to: "/acquisition/timeseries/Zstack_Red_0049" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0049/reference_images/Zstack_image' + 20. 'to: "/acquisition/timeseries/Zstack_Red_0052" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0052/reference_images/Zstack_image' + 21. 'to: "/acquisition/timeseries/speed_data" 18 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-18)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 2315 attributes (sorted alphabetically) (133 combined): + 1. '/acquisition/timeseries/ROI_#_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-7)' + 2. '/acquisition/timeseries/ROI_#_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-7)' + 3. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 4. '/acquisition/timeseries/ROI_#_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-7)' + 5. '/acquisition/timeseries/ROI_#_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-7)' + 6. '/acquisition/timeseries/ROI_#_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-7)' + 7. '/acquisition/timeseries/ROI_#_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-7)' + 8. '/acquisition/timeseries/ROI_#_Green/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-7)' + 9. '/acquisition/timeseries/ROI_#_Green/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-7)' + 10. '/acquisition/timeseries/ROI_#_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-7)' + 11. '/acquisition/timeseries/ROI_#_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-7)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-7)' + 13. '/acquisition/timeseries/ROI_#_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-7)' + 14. '/acquisition/timeseries/ROI_#_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-7)' + 15. '/acquisition/timeseries/ROI_#_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-7)' + 16. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 17. '/acquisition/timeseries/ROI_#_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-7)' + 18. '/acquisition/timeseries/ROI_#_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-7)' + 19. '/acquisition/timeseries/ROI_#_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-7)' + 20. '/acquisition/timeseries/ROI_#_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-7)' + 21. '/acquisition/timeseries/ROI_#_Red/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-7)' + 22. '/acquisition/timeseries/ROI_#_Red/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-7)' + 23. '/acquisition/timeseries/ROI_#_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-7)' + 24. '/acquisition/timeseries/ROI_#_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-7)' + 25. '/acquisition/timeseries/ROI_#_Red/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-7)' + 26. '/acquisition/timeseries/ROI_#_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-7)' + 27. '/acquisition/timeseries/ROI_002_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPc'' + 28. '/acquisition/timeseries/ROI_002_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPC'' + 29. '/acquisition/timeseries/ROI_003_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnJ'' + 30. '/acquisition/timeseries/ROI_003_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroj'' + 31. '/acquisition/timeseries/ROI_004_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMq'' + 32. '/acquisition/timeseries/ROI_004_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMQ'' + 33. '/acquisition/timeseries/ROI_005_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkX'' + 34. '/acquisition/timeseries/ROI_005_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklx'' + 35. '/acquisition/timeseries/ROI_006_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJE'' + 36. '/acquisition/timeseries/ROI_006_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKe'' + 37. '/acquisition/timeseries/ROI_007_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcil'' + 38. '/acquisition/timeseries/ROI_007_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiL'' + 39. '/acquisition/timeseries/Zstack_Green_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-78)' + 40. '/acquisition/timeseries/Zstack_Green_# comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"' (#=1-78)' + 41. '/acquisition/timeseries/Zstack_Green_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-78)' + 42. '/acquisition/timeseries/Zstack_Green_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-78)' + 43. '/acquisition/timeseries/Zstack_Green_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-78)' + 44. '/acquisition/timeseries/Zstack_Green_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-78)' + 45. '/acquisition/timeseries/Zstack_Green_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-78)' + 46. '/acquisition/timeseries/Zstack_Green_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-78)' + 47. '/acquisition/timeseries/Zstack_Green_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-78)' + 48. '/acquisition/timeseries/Zstack_Green_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-78)' + 49. '/acquisition/timeseries/Zstack_Green_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-78)' + 50. '/acquisition/timeseries/Zstack_Green_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-78)' + 51. '/acquisition/timeseries/Zstack_Red_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-78)' + 52. '/acquisition/timeseries/Zstack_Red_# comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"' (#=1-78)' + 53. '/acquisition/timeseries/Zstack_Red_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=1-78)' + 54. '/acquisition/timeseries/Zstack_Red_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-78)' + 55. '/acquisition/timeseries/Zstack_Red_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-78)' + 56. '/acquisition/timeseries/Zstack_Red_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-78)' + 57. '/acquisition/timeseries/Zstack_Red_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-78)' + 58. '/acquisition/timeseries/Zstack_Red_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-78)' + 59. '/acquisition/timeseries/Zstack_Red_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-78)' + 60. '/acquisition/timeseries/Zstack_Red_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-78)' + 61. '/acquisition/timeseries/Zstack_Red_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-78)' + 62. '/acquisition/timeseries/Zstack_Red_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-78)' + 63. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 64. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' + 65. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' + 66. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' + 67. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 68. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' + 69. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' + 70. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' + 71. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' + 72. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 73. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 74. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 75. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' + 76. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' + 77. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' + 78. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 79. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' + 80. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' + 81. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' + 82. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' + 83. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 84. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 85. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' + 86. '/epochs/trial_# links: dtype=|S58, shape=(15,) size (870) val='["'ROI_001_Green' is '/acquisition/timese...bIPIvq' (#=1-18)' + 87. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-18)' + 88. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' + 89. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-78)' + 90. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-78)' + 91. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 92. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 93. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 94. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' + 95. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 96. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' + 97. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' + 98. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' + 99. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' +100. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +101. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' +102. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' +103. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' +104. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' +105. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' +106. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' +107. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' +108. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-2)' +109. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=1-2)' +110. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0036/ROI_004/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +111. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0036/ROI_004/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"'' +112. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0037/ROI_003/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +113. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0037/ROI_003/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"'' +114. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +115. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"'' +116. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +117. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"'' +118. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +119. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"'' +120. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' +121. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +122. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +123. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +124. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +125. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +126. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +127. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +128. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +129. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +130. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +131. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +132. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +133. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 3498 datasets (sorted alphabetically) (513 combined): + 1. '/acquisition/timeseries/ROI_#_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-7)' + 2. '/acquisition/timeseries/ROI_#_Green/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-7)' + 3. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(6606, 60, 202) size (108238644), compress=gzip val='[[[128,132,131,136,138,133,121,122,138,12...jNVheQ'' + 4. '/acquisition/timeseries/ROI_#_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]' (#=1-7)' + 5. '/acquisition/timeseries/ROI_#_Green/field_of_view: dtype=float32, shape=(2,) size (16), compress=gzip val='[6.904e-05,2.051e-05]' (#=1-7)' + 6. '/acquisition/timeseries/ROI_#_Green/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-7)' + 7. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"' (#=1-2)' + 8. '/acquisition/timeseries/ROI_#_Green/num_samples: dtype=int32, shape=() size (4) val='6606' (#=1-7)' + 9. '/acquisition/timeseries/ROI_#_Green/pmt_gain: dtype=float32, shape=() size (4) val='700' (#=1-7)' + 10. '/acquisition/timeseries/ROI_#_Green/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-7)' + 11. '/acquisition/timeseries/ROI_#_Green/scan_line_rate: dtype=float32, shape=() size (4) val='30.03' (#=1-7)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps: dtype=float64, shape=(6606,) size (47887), compress=gzip val='[2.168e-19,0.0333,0.06661,0.09991,0.1332,...jpeWpL' (#=1-7)' + 13. '/acquisition/timeseries/ROI_#_Red/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-7)' + 14. '/acquisition/timeseries/ROI_#_Red/channel: dtype=|S3, shape=() size (3) val='"Red"' (#=1-7)' + 15. '/acquisition/timeseries/ROI_001_Red/data: dtype=float32, shape=(6606, 60, 202) size (97858623), compress=gzip val='[[[88,119,104,102,124,108,112,114,118,116...hzZnhQ'' + 16. '/acquisition/timeseries/ROI_#_Red/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]' (#=1-7)' + 17. '/acquisition/timeseries/ROI_#_Red/field_of_view: dtype=float32, shape=(2,) size (16), compress=gzip val='[6.904e-05,2.051e-05]' (#=1-7)' + 18. '/acquisition/timeseries/ROI_#_Red/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-7)' + 19. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"' (#=1-2)' + 20. '/acquisition/timeseries/ROI_#_Red/num_samples: dtype=int32, shape=() size (4) val='6606' (#=1-7)' + 21. '/acquisition/timeseries/ROI_#_Red/pmt_gain: dtype=float32, shape=() size (4) val='650' (#=1-7)' + 22. '/acquisition/timeseries/ROI_#_Red/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-7)' + 23. '/acquisition/timeseries/ROI_#_Red/scan_line_rate: dtype=float32, shape=() size (4) val='30.03' (#=1-7)' + 24. '/acquisition/timeseries/ROI_#_Red/timestamps: dtype=float64, shape=(6606,) size (47887), compress=gzip val='[2.168e-19,0.0333,0.06661,0.09991,0.1332,...jpeWpL' (#=1-7)' + 25. '/acquisition/timeseries/ROI_002_Green/data: dtype=float32, shape=(6606, 60, 202) size (111660226), compress=gzip val='[[[130,399,109,115,116,113,370,127,125,12...hZdmdh'' + 26. '/acquisition/timeseries/ROI_002_Red/data: dtype=float32, shape=(6606, 60, 202) size (97827675), compress=gzip val='[[[115,100,110,128,110,97,101,108,106,101...irqrYi'' + 27. '/acquisition/timeseries/ROI_003_Green/data: dtype=float32, shape=(6606, 60, 202) size (109699456), compress=gzip val='[[[207,128,110,343,127,113,246,102,105,12...fPYnFL'' + 28. '/acquisition/timeseries/ROI_003_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0037"'' + 29. '/acquisition/timeseries/ROI_003_Red/data: dtype=float32, shape=(6606, 60, 202) size (97240459), compress=gzip val='[[[102,115,106,114,115,104,130,155,215,25...bSVlz'' + 30. '/acquisition/timeseries/ROI_003_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0037"'' + 31. '/acquisition/timeseries/ROI_004_Green/data: dtype=float32, shape=(6606, 60, 202) size (111621964), compress=gzip val='[[[137,124,124,123,114,127,137,145,130,11...ifnOzC'' + 32. '/acquisition/timeseries/ROI_004_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0036"'' + 33. '/acquisition/timeseries/ROI_004_Red/data: dtype=float32, shape=(6606, 60, 202) size (98473404), compress=gzip val='[[[119,90,119,114,123,110,96,121,110,113,...kCOkOW'' + 34. '/acquisition/timeseries/ROI_004_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0036"'' + 35. '/acquisition/timeseries/ROI_005_Green/data: dtype=float32, shape=(6606, 60, 202) size (105256769), compress=gzip val='[[[134,116,134,120,136,108,117,136,128,13...jhqzQy'' + 36. '/acquisition/timeseries/ROI_005_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0047"'' + 37. '/acquisition/timeseries/ROI_005_Red/data: dtype=float32, shape=(6606, 60, 202) size (96273665), compress=gzip val='[[[115,129,106,107,110,102,107,99,119,108...jnzJdl'' + 38. '/acquisition/timeseries/ROI_005_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0047"'' + 39. '/acquisition/timeseries/ROI_006_Green/data: dtype=float32, shape=(6606, 60, 202) size (106196393), compress=gzip val='[[[143,126,154,92,112,124,143,125,109,139...cLytUQ'' + 40. '/acquisition/timeseries/ROI_006_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0049"'' + 41. '/acquisition/timeseries/ROI_006_Red/data: dtype=float32, shape=(6606, 60, 202) size (97323819), compress=gzip val='[[[92,106,116,95,103,112,89,92,104,103,11...hSlQjl'' + 42. '/acquisition/timeseries/ROI_006_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0049"'' + 43. '/acquisition/timeseries/ROI_007_Green/data: dtype=float32, shape=(6606, 60, 202) size (111316585), compress=gzip val='[[[121,139,116,131,125,122,121,116,92,122...gUQRaQ'' + 44. '/acquisition/timeseries/ROI_007_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0052"'' + 45. '/acquisition/timeseries/ROI_007_Red/data: dtype=float32, shape=(6606, 60, 202) size (97927577), compress=gzip val='[[[102,112,107,123,118,113,122,113,111,10...pVDdZ'' + 46. '/acquisition/timeseries/ROI_007_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0052"'' + 47. '/acquisition/timeseries/Zstack_Green_#/bits_per_pixel: dtype=int32, shape=() size (4) val='16' (#=1-78)' + 48. '/acquisition/timeseries/Zstack_Green_#/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-78)' + 49. '/acquisition/timeseries/Zstack_Green_0001/data: dtype=uint16, shape=(512, 512) size (242391), compress=gzip val='[[144,130,129,123,132,127,136,124,127,110...gzhuIr'' + 50. '/acquisition/timeseries/Zstack_Green_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]' (#=1-78)' + 51. '/acquisition/timeseries/Zstack_Green_#/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[0.000175,0.000175]' (#=1-78)' + 52. '/acquisition/timeseries/Zstack_Green_#/format: dtype=|S4, shape=() size (4) val='"tiff"' (#=1-78)' + 53. '/acquisition/timeseries/Zstack_Green_#/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack#"' (#=1-78)' + 54. '/acquisition/timeseries/Zstack_Green_#/num_samples: dtype=int32, shape=() size (4) val='1' (#=1-78)' + 55. '/acquisition/timeseries/Zstack_Green_#/pmt_gain: dtype=float32, shape=() size (4) val='700' (#=1-78)' + 56. '/acquisition/timeseries/Zstack_Green_#/scan_line_rate: dtype=float32, shape=() size (4) val='30.03' (#=1-78)' + 57. '/acquisition/timeseries/Zstack_Green_#/timestamps: dtype=float64, shape=(1,) size (11), compress=gzip val='[0]' (#=1-78)' + 58. '/acquisition/timeseries/Zstack_Green_0002/data: dtype=uint16, shape=(512, 512) size (243788), compress=gzip val='[[137,132,131,128,127,130,124,133,114,120...dTLkvr'' + 59. '/acquisition/timeseries/Zstack_Green_0003/data: dtype=uint16, shape=(512, 512) size (245510), compress=gzip val='[[137,132,119,129,116,124,128,130,120,138...jhSaAb'' + 60. '/acquisition/timeseries/Zstack_Green_0004/data: dtype=uint16, shape=(512, 512) size (247167), compress=gzip val='[[128,132,125,135,126,123,177,135,120,126...flbdqC'' + 61. '/acquisition/timeseries/Zstack_Green_0005/data: dtype=uint16, shape=(512, 512) size (249408), compress=gzip val='[[152,128,124,124,129,124,128,128,134,132...DxnWD'' + 62. '/acquisition/timeseries/Zstack_Green_0006/data: dtype=uint16, shape=(512, 512) size (251440), compress=gzip val='[[139,126,130,128,133,128,123,127,126,127...fqSdnY'' + 63. '/acquisition/timeseries/Zstack_Green_0007/data: dtype=uint16, shape=(512, 512) size (254597), compress=gzip val='[[135,112,129,114,129,114,133,124,123,131...kcYlmb'' + 64. '/acquisition/timeseries/Zstack_Green_0008/data: dtype=uint16, shape=(512, 512) size (257614), compress=gzip val='[[131,129,127,126,121,120,136,126,124,128...epfXqx'' + 65. '/acquisition/timeseries/Zstack_Green_0009/data: dtype=uint16, shape=(512, 512) size (259402), compress=gzip val='[[132,122,138,116,128,127,122,127,120,117...cHCJeM'' + 66. '/acquisition/timeseries/Zstack_Green_0010/data: dtype=uint16, shape=(512, 512) size (262313), compress=gzip val='[[134,127,135,134,127,125,137,129,136,123...haIhpr'' + 67. '/acquisition/timeseries/Zstack_Green_0011/data: dtype=uint16, shape=(512, 512) size (264041), compress=gzip val='[[145,124,127,126,123,124,127,136,123,118...dxQMKW'' + 68. '/acquisition/timeseries/Zstack_Green_0012/data: dtype=uint16, shape=(512, 512) size (266608), compress=gzip val='[[132,122,125,128,125,124,120,120,141,122...kiORFj'' + 69. '/acquisition/timeseries/Zstack_Green_0013/data: dtype=uint16, shape=(512, 512) size (268613), compress=gzip val='[[129,117,123,134,129,115,131,125,128,129...fSTZZI'' + 70. '/acquisition/timeseries/Zstack_Green_0014/data: dtype=uint16, shape=(512, 512) size (270549), compress=gzip val='[[138,130,124,128,139,132,134,121,124,126...fmYZsb'' + 71. '/acquisition/timeseries/Zstack_Green_0015/data: dtype=uint16, shape=(512, 512) size (272429), compress=gzip val='[[138,136,123,125,135,122,122,133,132,119...lioiZt'' + 72. '/acquisition/timeseries/Zstack_Green_0016/data: dtype=uint16, shape=(512, 512) size (273589), compress=gzip val='[[146,135,125,125,121,129,120,133,131,121...cAimNd'' + 73. '/acquisition/timeseries/Zstack_Green_0017/data: dtype=uint16, shape=(512, 512) size (274125), compress=gzip val='[[134,123,123,116,132,132,130,126,131,122...dcIEtz'' + 74. '/acquisition/timeseries/Zstack_Green_0018/data: dtype=uint16, shape=(512, 512) size (273522), compress=gzip val='[[141,133,138,130,190,145,132,118,135,129...kFQjOb'' + 75. '/acquisition/timeseries/Zstack_Green_0019/data: dtype=uint16, shape=(512, 512) size (272134), compress=gzip val='[[145,135,113,125,145,126,114,135,130,125...PZxbn'' + 76. '/acquisition/timeseries/Zstack_Green_0020/data: dtype=uint16, shape=(512, 512) size (273234), compress=gzip val='[[150,133,128,122,131,124,140,136,123,128...bVDBNH'' + 77. '/acquisition/timeseries/Zstack_Green_0021/data: dtype=uint16, shape=(512, 512) size (272929), compress=gzip val='[[128,129,128,117,116,135,114,130,139,130...iuJYEF'' + 78. '/acquisition/timeseries/Zstack_Green_0022/data: dtype=uint16, shape=(512, 512) size (273457), compress=gzip val='[[135,119,128,134,132,118,129,127,129,141...hsjvIM'' + 79. '/acquisition/timeseries/Zstack_Green_0023/data: dtype=uint16, shape=(512, 512) size (273539), compress=gzip val='[[135,127,129,124,123,130,134,132,136,138...hHKtKK'' + 80. '/acquisition/timeseries/Zstack_Green_0024/data: dtype=uint16, shape=(512, 512) size (274014), compress=gzip val='[[146,119,136,130,137,126,119,127,138,125...gXlhMp'' + 81. '/acquisition/timeseries/Zstack_Green_0025/data: dtype=uint16, shape=(512, 512) size (273700), compress=gzip val='[[133,126,205,139,129,131,134,116,127,121...bIybLs'' + 82. '/acquisition/timeseries/Zstack_Green_0026/data: dtype=uint16, shape=(512, 512) size (273712), compress=gzip val='[[136,124,115,197,126,135,120,120,139,131...gZHzjH'' + 83. '/acquisition/timeseries/Zstack_Green_0027/data: dtype=uint16, shape=(512, 512) size (274294), compress=gzip val='[[148,133,137,131,134,131,126,120,116,124...bopzOa'' + 84. '/acquisition/timeseries/Zstack_Green_0028/data: dtype=uint16, shape=(512, 512) size (274517), compress=gzip val='[[140,139,130,120,130,141,135,148,139,136...HTkmx'' + 85. '/acquisition/timeseries/Zstack_Green_0029/data: dtype=uint16, shape=(512, 512) size (274970), compress=gzip val='[[150,130,127,150,141,125,125,118,132,122...gERFbR'' + 86. '/acquisition/timeseries/Zstack_Green_0030/data: dtype=uint16, shape=(512, 512) size (274319), compress=gzip val='[[141,122,130,128,123,120,134,131,132,131...JfnOI'' + 87. '/acquisition/timeseries/Zstack_Green_0031/data: dtype=uint16, shape=(512, 512) size (274827), compress=gzip val='[[130,145,126,117,124,125,121,128,125,128...dJAxse'' + 88. '/acquisition/timeseries/Zstack_Green_0032/data: dtype=uint16, shape=(512, 512) size (274258), compress=gzip val='[[136,125,134,134,129,110,138,115,126,129...fhAesa'' + 89. '/acquisition/timeseries/Zstack_Green_0033/data: dtype=uint16, shape=(512, 512) size (274708), compress=gzip val='[[132,143,124,124,131,127,123,107,138,122...jDHNNq'' + 90. '/acquisition/timeseries/Zstack_Green_0034/data: dtype=uint16, shape=(512, 512) size (274503), compress=gzip val='[[144,122,128,202,122,120,131,128,138,113...evEgoH'' + 91. '/acquisition/timeseries/Zstack_Green_0035/data: dtype=uint16, shape=(512, 512) size (274046), compress=gzip val='[[148,120,135,120,127,131,177,133,122,116...fGmZd'' + 92. '/acquisition/timeseries/Zstack_Green_0036/data: dtype=uint16, shape=(512, 512) size (274446), compress=gzip val='[[151,134,122,128,123,126,126,133,127,135...bdNXY'' + 93. '/acquisition/timeseries/Zstack_Green_0037/data: dtype=uint16, shape=(512, 512) size (275145), compress=gzip val='[[178,132,118,133,121,135,126,127,132,118...dmjTls'' + 94. '/acquisition/timeseries/Zstack_Green_0038/data: dtype=uint16, shape=(512, 512) size (275913), compress=gzip val='[[141,122,122,121,143,128,130,138,134,133...gHyynT'' + 95. '/acquisition/timeseries/Zstack_Green_0039/data: dtype=uint16, shape=(512, 512) size (275753), compress=gzip val='[[131,120,129,119,125,131,134,132,119,127...bgHmkV'' + 96. 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'/processing/Acquired_ROIs/ImageSegmentation/Zstack0037/ROI_003/roi_description: dtype=|S7, shape=() size (7) val='"ROI_003"'' +485. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0037/roi_list: dtype=|S7, shape=(1,) size (15), compress=gzip val='["ROI_003"]'' +486. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]'' +487. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/img_mask: dtype=float32, shape=(512, 512) size (2933), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...glcAwE'' +488. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/pix_mask: dtype=uint16, shape=(12120, 2) size (934), compress=gzip val='[[79,167],[80,167],[81,167],[82,167],[83,...hgPCCE'' +489. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/pix_mask_weight: dtype=float32, shape=(12120,) size (152), compress=gzip val='[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,...gZQoTY'' +490. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/pixel_time_offsets: dtype=float64, shape=(60, 202) size (70321), compress=gzip val='[[0.01916,0.01916,0.01916,0.01916,0.01916...gOENE'' +491. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/ROI_005/roi_description: dtype=|S7, shape=() size (7) val='"ROI_005"'' +492. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0047/roi_list: dtype=|S7, shape=(1,) size (15), compress=gzip val='["ROI_005"]'' +493. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]'' +494. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/img_mask: dtype=float32, shape=(512, 512) size (2913), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...ewVDBQ'' +495. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/pix_mask: dtype=uint16, shape=(12120, 2) size (963), compress=gzip val='[[94,404],[95,404],[96,404],[97,404],[98,...iBbMFI'' +496. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/pix_mask_weight: dtype=float32, shape=(12120,) size (152), compress=gzip val='[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,...gZQoTY'' +497. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/pixel_time_offsets: dtype=float64, shape=(60, 202) size (70311), compress=gzip val='[[0.02376,0.02376,0.02376,0.02376,0.02376...iOsyvm'' +498. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/ROI_006/roi_description: dtype=|S7, shape=() size (7) val='"ROI_006"'' +499. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0049/roi_list: dtype=|S7, shape=(1,) size (15), compress=gzip val='["ROI_006"]'' +500. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]'' +501. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/img_mask: dtype=float32, shape=(512, 512) size (2910), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...dEEoTY'' +502. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/pix_mask: dtype=uint16, shape=(12120, 2) size (963), compress=gzip val='[[219,263],[220,263],[221,263],[222,263],...nZrBU'' +503. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/pix_mask_weight: dtype=float32, shape=(12120,) size (152), compress=gzip val='[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,...gZQoTY'' +504. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/pixel_time_offsets: dtype=float64, shape=(60, 202) size (70346), compress=gzip val='[[0.02837,0.02837,0.02837,0.02837,0.02837...ilMrKU'' +505. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/ROI_007/roi_description: dtype=|S7, shape=() size (7) val='"ROI_007"'' +506. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0052/roi_list: dtype=|S7, shape=(1,) size (15), compress=gzip val='["ROI_007"]'' +507. '/processing/Acquired_ROIs/roi_spec: dtype=float16, shape=(7, 17) size (158), compress=gzip val='[[1,3,inf,12120,134,175,13,336,235,13,0,0...eGMRCH'' +508. '/session_description: dtype=|S68, shape=() size (68) val='"One or two sentences describing the expe...ezufjX'' +509. '/session_start_time: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +510. '/silverlab_api_version: dtype=|S3, shape=() size (3) val='"0.1"'' +511. '/stimulus/presentation/air_puff/data: dtype=|S4, shape=(18,) size (15), compress=gzip val='["puff","puff","puff","puff","puff","puff...dXbuSd'' +512. '/stimulus/presentation/air_puff/num_samples: dtype=int32, shape=() size (4) val='18'' +513. '/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(18,) size (155), compress=gzip val='[5,17.23,29.45,41.68,53.91,66.13,78.36,90...Pmgmy'' +-------------------- +** Summary +731 groups, 3498 datasets, 2315 attributes diff --git a/Python/test/data/Experiment Header.ini b/Python/test/data/Experiment Header.ini new file mode 100644 index 0000000..b8ece10 --- /dev/null +++ b/Python/test/data/Experiment Header.ini @@ -0,0 +1,20 @@ +[LOGIN] +User = "Mr Test" + +[GLOBAL PARAMETERS] +number of poi = 3.000000 +number of miniscans = 0.000000 +number of trials = 2.000000 +number of cycles = 5.000000 +# averaged frames = 16.000000 +laser power (%) = 60.000000 +pmt 1 = 650.000000 +pmt 2 = 720.000000 +frame size = 512.000000 +field of view = 175.000000 +x centre = 0.000000 +y centre = 0.000000 +aol z = 0.000000 + +[MOVEMENT CORRECTION] +MovCor Enabled? = TRUE diff --git a/Python/test/data/Speed_Data/Speed data 001.txt b/Python/test/data/Speed_Data/Speed data 001.txt new file mode 100644 index 0000000..039b044 --- /dev/null +++ b/Python/test/data/Speed_Data/Speed data 001.txt @@ -0,0 +1,26 @@ +08/11/2016 11:12:56.634109 966 0.00 291.312 +08/11/2016 11:12:56.636252 3109 -0.00 291.312 +08/11/2016 11:12:56.638396 5253 -0.00 291.312 +08/11/2016 11:12:56.998872 365729 -2.79 291.708 +08/11/2016 11:12:57.001019 367876 -2.79 291.744 +08/11/2016 11:12:57.003167 370024 -0.00 291.744 +08/11/2016 11:12:57.005312 372169 -2.79 291.780 +08/11/2016 11:12:57.007459 374316 -2.79 291.816 +08/11/2016 11:12:57.009607 376464 -2.79 291.852 +08/11/2016 11:12:57.011754 378611 -0.00 291.852 +08/11/2016 11:13:10.726144 14093001 -0.00 208.368 +08/11/2016 11:13:10.728288 14095145 -2.80 208.404 +08/11/2016 11:13:10.730435 14097292 -0.00 208.404 +08/11/2016 11:13:10.731570 1135 0.00 208.404 +08/11/2016 11:13:10.735861 5426 -2.79 208.440 +08/11/2016 11:13:10.738008 7573 -0.00 208.440 +08/11/2016 11:13:10.738439 431 0.00 208.440 +08/11/2016 11:13:10.740583 2575 -0.00 208.440 +08/11/2016 11:13:10.742727 4719 -2.80 208.476 +08/11/2016 11:13:10.744874 6866 -0.00 208.476 +08/11/2016 11:13:10.747019 9011 -0.00 208.476 +08/11/2016 11:13:24.833318 14095310 -0.00 281.772 +08/11/2016 11:13:24.835463 14097455 -0.00 281.772 +08/11/2016 11:13:24.836760 1297 0.00 281.772 +08/11/2016 11:13:24.841061 5598 -0.00 281.772 +08/11/2016 11:13:24.843205 7742 -0.00 281.772 diff --git a/Python/test/data/expected.yaml b/Python/test/data/expected.yaml new file mode 100644 index 0000000..67e22af --- /dev/null +++ b/Python/test/data/expected.yaml @@ -0,0 +1,85 @@ +# Expected HDF5 contents after parsing the raw data from this folder. +session_start_time: "2016-11-08T11:12:56.633143" +session_description: "Test epoch calculation" +general: + experimenter: Mr Test + institution: University College London + lab: Silver Lab (http://silverlab.org) + labview_header: [['LOGIN', 'User', '"Mr Test"'], + ['GLOBAL PARAMETERS', 'number of poi', '3.000000'], + ['GLOBAL PARAMETERS', 'number of miniscans', '0.000000'], + ['GLOBAL PARAMETERS', 'number of trials', '2.000000'], + ['GLOBAL PARAMETERS', 'number of cycles', '5.000000'], + ['GLOBAL PARAMETERS', '# averaged frames', '16.000000'], + ['GLOBAL PARAMETERS', 'laser power (%)', '60.000000'], + ['GLOBAL PARAMETERS', 'pmt 1', '650.000000'], + ['GLOBAL PARAMETERS', 'pmt 2', '720.000000'], + ['GLOBAL PARAMETERS', 'frame size', '512.000000'], + ['GLOBAL PARAMETERS', 'field of view', '175.000000'], + ['GLOBAL PARAMETERS', 'x centre', '0.000000'], + ['GLOBAL PARAMETERS', 'y centre', '0.000000'], + ['GLOBAL PARAMETERS', 'aol z', '0.000000'], + ['MOVEMENT CORRECTION', 'MovCor Enabled?', 'TRUE']] +acquisition: + timeseries: + speed_data: + num_samples: 26 + data: + _attrs: + unit: "cm/s" + resolution: 0.000833333333333333 + conversion: 0.83333333333333 + _value: [0.0, 0.0, 0.0, -2.79, -2.79, 0.0, -2.79, -2.79, -2.79, 0.0, 0.0, -2.8, 0.0, + 0.0, -2.79, 0.0, + 0.0, 0.0, -2.8, 0.0, 0.0, 0.0, 0.0, + 0.0, 0.0, 0.0] + timestamps: + _attrs: + unit: Seconds + _value: [0.000966, 0.003109, 0.005253, 0.365729, 0.367876, 0.370024, 0.372169, 0.374316, 0.376464, 0.378611, 14.093001, 14.095145, 14.097292, + 14.098427, 14.102718, 14.104865, + 14.105296, 14.107440, 14.109584, 14.111731, 14.113876, 28.200175, 28.202320, + 28.203617, 28.207918, 28.210062] + trial_times: + num_samples: 26 + data: + _attrs: + unit: second + resolution: 0.000001 + conversion: 1000000 + _value: [966, 3109, 5253, 365729, 367876, 370024, 372169, 374316, 376464, 378611, 14093001, 14095145, 14097292, + 1135, 5426, 7573, + 431, 2575, 4719, 6866, 9011, 14095310, 14097455, + 1297, 5598, 7742] + timestamps: + _attrs: + unit: Seconds + _value: [0.000966, 0.003109, 0.005253, 0.365729, 0.367876, 0.370024, 0.372169, 0.374316, 0.376464, 0.378611, 14.093001, 14.095145, 14.097292, + 14.098427, 14.102718, 14.104865, + 14.105296, 14.107440, 14.109584, 14.111731, 14.113876, 28.200175, 28.202320, + 28.203617, 28.207918, 28.210062] +epochs: + trial_0001: + start_time: 0.0 + stop_time: 14.097292 + _attrs: + links: ["'speed_data' is '/acquisition/timeseries/speed_data'"] + speed_data: + count: 13 + idx_start: 0 + timeseries: + _link: '/acquisition/timeseries/speed_data' + # trial_times: + # _link: '/acquisition/timeseries/trial_times' + trial_0002: + start_time: 14.104865 + stop_time: 28.202320 + _attrs: + links: ["'speed_data' is '/acquisition/timeseries/speed_data'"] + speed_data: + count: 7 + idx_start: 16 + timeseries: + _link: '/acquisition/timeseries/speed_data' + # trial_times: + # _link: '/acquisition/timeseries/trial_times' diff --git a/Python/test/data/metadata.yaml b/Python/test/data/metadata.yaml new file mode 100644 index 0000000..9be684c --- /dev/null +++ b/Python/test/data/metadata.yaml @@ -0,0 +1,10 @@ +people: + Mr Test: + name: Mr Test +experiments: + test: + description: Test experiment description. +sessions: + Mr Test: + description: Test epoch calculation + experiment: test diff --git a/Python/test/data/sample_miniscan_fred_170322_14_06_43.sig b/Python/test/data/sample_miniscan_fred_170322_14_06_43.sig new file mode 100644 index 0000000..a0c57f0 --- /dev/null +++ b/Python/test/data/sample_miniscan_fred_170322_14_06_43.sig @@ -0,0 +1,345 @@ +<% Generating signature for /Users/jonc/projects/OpenSourceBrain/Data/sample_miniscan_fred_170322_14_06_43.nwb %> + +** No datasets hard links. +** No groups hard links. +** 2 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0033/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/description' + 2. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' +** 4 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-2)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-2)' + 3. 'to: "/acquisition/timeseries/Zstack_Red_0033" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0033/reference_images/Zstack_image' + 4. 'to: "/acquisition/timeseries/speed_data" 2 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-2)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 267 attributes (sorted alphabetically) (111 combined): + 1. '/acquisition/timeseries/ROI_001_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]'' + 2. '/acquisition/timeseries/ROI_001_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ'' + 3. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 4. '/acquisition/timeseries/ROI_001_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"'' + 5. '/acquisition/timeseries/ROI_001_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 6. '/acquisition/timeseries/ROI_001_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' + 7. '/acquisition/timeseries/ROI_001_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 8. '/acquisition/timeseries/ROI_001_Green/data conversion: dtype=float64, shape=() size (8) val='1'' + 9. '/acquisition/timeseries/ROI_001_Green/data resolution: dtype=float64, shape=() size (8) val='nan'' + 10. '/acquisition/timeseries/ROI_001_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"'' + 11. '/acquisition/timeseries/ROI_001_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 12. '/acquisition/timeseries/ROI_001_Green/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 13. '/acquisition/timeseries/ROI_001_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 14. '/acquisition/timeseries/ROI_001_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]'' + 15. '/acquisition/timeseries/ROI_001_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ'' + 16. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 17. '/acquisition/timeseries/ROI_001_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"'' + 18. '/acquisition/timeseries/ROI_001_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 19. '/acquisition/timeseries/ROI_001_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' + 20. '/acquisition/timeseries/ROI_001_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 21. '/acquisition/timeseries/ROI_001_Red/data conversion: dtype=float64, shape=() size (8) val='1'' + 22. '/acquisition/timeseries/ROI_001_Red/data resolution: dtype=float64, shape=() size (8) val='nan'' + 23. '/acquisition/timeseries/ROI_001_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"'' + 24. '/acquisition/timeseries/ROI_001_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 25. '/acquisition/timeseries/ROI_001_Red/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 26. '/acquisition/timeseries/ROI_001_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 27. '/acquisition/timeseries/Zstack_Green_0033 ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]'' + 28. '/acquisition/timeseries/Zstack_Green_0033 comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"'' + 29. '/acquisition/timeseries/Zstack_Green_0033 description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"'' + 30. '/acquisition/timeseries/Zstack_Green_0033 help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"'' + 31. '/acquisition/timeseries/Zstack_Green_0033 neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 32. '/acquisition/timeseries/Zstack_Green_0033 source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' + 33. '/acquisition/timeseries/Zstack_Green_0033/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 34. '/acquisition/timeseries/Zstack_Green_0033/data conversion: dtype=float64, shape=() size (8) val='1'' + 35. '/acquisition/timeseries/Zstack_Green_0033/data resolution: dtype=float64, shape=() size (8) val='nan'' + 36. '/acquisition/timeseries/Zstack_Green_0033/data unit: dtype=|S9, shape=() size (9) val='"intensity"'' + 37. '/acquisition/timeseries/Zstack_Green_0033/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 38. '/acquisition/timeseries/Zstack_Green_0033/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 39. '/acquisition/timeseries/Zstack_Red_0033 ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]'' + 40. '/acquisition/timeseries/Zstack_Red_0033 comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"'' + 41. '/acquisition/timeseries/Zstack_Red_0033 description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"'' + 42. '/acquisition/timeseries/Zstack_Red_0033 help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"'' + 43. '/acquisition/timeseries/Zstack_Red_0033 neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 44. '/acquisition/timeseries/Zstack_Red_0033 source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' + 45. '/acquisition/timeseries/Zstack_Red_0033/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 46. '/acquisition/timeseries/Zstack_Red_0033/data conversion: dtype=float64, shape=() size (8) val='1'' + 47. '/acquisition/timeseries/Zstack_Red_0033/data resolution: dtype=float64, shape=() size (8) val='nan'' + 48. '/acquisition/timeseries/Zstack_Red_0033/data unit: dtype=|S9, shape=() size (9) val='"intensity"'' + 49. '/acquisition/timeseries/Zstack_Red_0033/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 50. '/acquisition/timeseries/Zstack_Red_0033/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 51. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 52. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' + 53. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' + 54. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' + 55. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 56. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' + 57. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' + 58. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' + 59. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' + 60. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 61. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 62. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 63. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' + 64. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' + 65. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' + 66. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 67. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' + 68. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' + 69. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' + 70. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' + 71. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 72. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 73. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' + 74. '/epochs/trial_# links: dtype=|S58, shape=(3,) size (174) val='["'ROI_001_Green' is '/acquisition/timese...gLZBmP' (#=1-2)' + 75. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-2)' + 76. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' + 77. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-78)' + 78. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-78)' + 79. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 80. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 81. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 82. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' + 83. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 84. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' + 85. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' + 86. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' + 87. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' + 88. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' + 89. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' + 90. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' + 91. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' + 92. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' + 93. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' + 94. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' + 95. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' + 96. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 97. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"'' + 98. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' + 99. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +100. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +101. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +102. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +103. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +104. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +105. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +106. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +107. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +108. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +109. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +110. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +111. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 1054 datasets (sorted alphabetically) (204 combined): + 1. '/acquisition/timeseries/ROI_001_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64'' + 2. '/acquisition/timeseries/ROI_001_Green/channel: dtype=|S5, shape=() size (5) val='"Green"'' + 3. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(734, 60, 202) size (12338021), compress=gzip val='[[[128,132,131,136,138,133,121,122,138,12...klCNdL'' + 4. '/acquisition/timeseries/ROI_001_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]'' + 5. '/acquisition/timeseries/ROI_001_Green/field_of_view: dtype=float32, shape=(2,) size (16), compress=gzip val='[6.904e-05,2.051e-05]'' + 6. '/acquisition/timeseries/ROI_001_Green/format: dtype=|S3, shape=() size (3) val='"raw"'' + 7. '/acquisition/timeseries/ROI_001_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"'' + 8. '/acquisition/timeseries/ROI_001_Green/num_samples: dtype=int32, shape=() size (4) val='734'' + 9. '/acquisition/timeseries/ROI_001_Green/pmt_gain: dtype=float32, shape=() size (4) val='700'' + 10. '/acquisition/timeseries/ROI_001_Green/roi_name: dtype=|S7, shape=() size (7) val='"ROI_001"'' + 11. '/acquisition/timeseries/ROI_001_Green/scan_line_rate: dtype=float32, shape=() size (4) val='30.03'' + 12. '/acquisition/timeseries/ROI_001_Green/timestamps: dtype=float64, shape=(734,) size (4774), compress=gzip val='[2.168e-19,0.0333,0.06661,0.09991,0.1332,...dwacaX'' + 13. '/acquisition/timeseries/ROI_001_Red/bits_per_pixel: dtype=int32, shape=() size (4) val='64'' + 14. '/acquisition/timeseries/ROI_001_Red/channel: dtype=|S3, shape=() size (3) val='"Red"'' + 15. '/acquisition/timeseries/ROI_001_Red/data: dtype=float32, shape=(734, 60, 202) size (11129235), compress=gzip val='[[[88,119,104,102,124,108,112,114,118,116...eZjdxc'' + 16. '/acquisition/timeseries/ROI_001_Red/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]'' + 17. '/acquisition/timeseries/ROI_001_Red/field_of_view: dtype=float32, shape=(2,) size (16), compress=gzip val='[6.904e-05,2.051e-05]'' + 18. '/acquisition/timeseries/ROI_001_Red/format: dtype=|S3, shape=() size (3) val='"raw"'' + 19. '/acquisition/timeseries/ROI_001_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"'' + 20. '/acquisition/timeseries/ROI_001_Red/num_samples: dtype=int32, shape=() size (4) val='734'' + 21. '/acquisition/timeseries/ROI_001_Red/pmt_gain: dtype=float32, shape=() size (4) val='650'' + 22. '/acquisition/timeseries/ROI_001_Red/roi_name: dtype=|S7, shape=() size (7) val='"ROI_001"'' + 23. '/acquisition/timeseries/ROI_001_Red/scan_line_rate: dtype=float32, shape=() size (4) val='30.03'' + 24. '/acquisition/timeseries/ROI_001_Red/timestamps: dtype=float64, shape=(734,) size (4774), compress=gzip val='[2.168e-19,0.0333,0.06661,0.09991,0.1332,...dwacaX'' + 25. '/acquisition/timeseries/Zstack_Green_0033/bits_per_pixel: dtype=int32, shape=() size (4) val='16'' + 26. '/acquisition/timeseries/Zstack_Green_0033/channel: dtype=|S5, shape=() size (5) val='"Green"'' + 27. '/acquisition/timeseries/Zstack_Green_0033/data: dtype=uint16, shape=(512, 512) size (274708), compress=gzip val='[[132,143,124,124,131,127,123,107,138,122...jDHNNq'' + 28. '/acquisition/timeseries/Zstack_Green_0033/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' + 29. '/acquisition/timeseries/Zstack_Green_0033/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[0.000175,0.000175]'' + 30. '/acquisition/timeseries/Zstack_Green_0033/format: dtype=|S4, shape=() size (4) val='"tiff"'' + 31. '/acquisition/timeseries/Zstack_Green_0033/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"'' + 32. '/acquisition/timeseries/Zstack_Green_0033/num_samples: dtype=int32, shape=() size (4) val='1'' + 33. '/acquisition/timeseries/Zstack_Green_0033/pmt_gain: dtype=float32, shape=() size (4) val='700'' + 34. '/acquisition/timeseries/Zstack_Green_0033/scan_line_rate: dtype=float32, shape=() size (4) val='30.03'' + 35. '/acquisition/timeseries/Zstack_Green_0033/timestamps: dtype=float64, shape=(1,) size (11), compress=gzip val='[0]'' + 36. '/acquisition/timeseries/Zstack_Red_0033/bits_per_pixel: dtype=int32, shape=() size (4) val='16'' + 37. '/acquisition/timeseries/Zstack_Red_0033/channel: dtype=|S3, shape=() size (3) val='"Red"'' + 38. '/acquisition/timeseries/Zstack_Red_0033/data: dtype=uint16, shape=(512, 512) size (231278), compress=gzip val='[[111,106,115,100,115,121,110,112,106,116...fiZJkQ'' + 39. '/acquisition/timeseries/Zstack_Red_0033/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' + 40. '/acquisition/timeseries/Zstack_Red_0033/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[0.000175,0.000175]'' + 41. '/acquisition/timeseries/Zstack_Red_0033/format: dtype=|S4, shape=() size (4) val='"tiff"'' + 42. '/acquisition/timeseries/Zstack_Red_0033/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0033"'' + 43. '/acquisition/timeseries/Zstack_Red_0033/num_samples: dtype=int32, shape=() size (4) val='1'' + 44. '/acquisition/timeseries/Zstack_Red_0033/pmt_gain: dtype=float32, shape=() size (4) val='650'' + 45. '/acquisition/timeseries/Zstack_Red_0033/scan_line_rate: dtype=float32, shape=() size (4) val='30.03'' + 46. '/acquisition/timeseries/Zstack_Red_0033/timestamps: dtype=float64, shape=(1,) size (11), compress=gzip val='[0]'' + 47. '/acquisition/timeseries/speed_data/data: dtype=float32, shape=(11396,) size (207), compress=gzip val='[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,...feEHBm'' + 48. '/acquisition/timeseries/speed_data/num_samples: dtype=int32, shape=() size (4) val='11396'' + 49. '/acquisition/timeseries/speed_data/timestamps: dtype=float64, shape=(11396,) size (80157), compress=gzip val='[0.001002,0.003146,0.005289,0.007433,0.00...dOpdek'' + 50. '/acquisition/timeseries/trial_times/data: dtype=int32, shape=(11396,) size (38429), compress=gzip val='[1002,3146,5289,7433,9581,11725,13869,160...gZDpHR'' + 51. '/acquisition/timeseries/trial_times/num_samples: dtype=int32, shape=() size (4) val='11396'' + 52. '/acquisition/timeseries/trial_times/timestamps: dtype=float64, shape=(11396,) size (80157), compress=gzip val='[0.001002,0.003146,0.005289,0.007433,0.00...dOpdek'' + 53. '/epochs/trial_#/ROI_001_Green/count: dtype=int32, shape=() size (4) val='367' (#=1-2)' + 54. '/epochs/trial_0001/ROI_001_Green/idx_start: dtype=int32, shape=() size (4) val='0'' + 55. '/epochs/trial_#/ROI_001_Red/count: dtype=int32, shape=() size (4) val='367' (#=1-2)' + 56. '/epochs/trial_0001/ROI_001_Red/idx_start: dtype=int32, shape=() size (4) val='0'' + 57. '/epochs/trial_#/speed_data/count: dtype=int32, shape=() size (4) val='5695' (#=1-2)' + 58. '/epochs/trial_0001/speed_data/idx_start: dtype=int32, shape=() size (4) val='0'' + 59. '/epochs/trial_0001/start_time: dtype=float64, shape=() size (8) val='2.168e-19'' + 60. '/epochs/trial_0001/stop_time: dtype=float64, shape=() size (8) val='12.22'' + 61. '/epochs/trial_0002/ROI_001_Green/idx_start: dtype=int32, shape=() size (4) val='367'' + 62. '/epochs/trial_0002/ROI_001_Red/idx_start: dtype=int32, shape=() size (4) val='367'' + 63. '/epochs/trial_0002/speed_data/idx_start: dtype=int32, shape=() size (4) val='5700'' + 64. '/epochs/trial_0002/start_time: dtype=float64, shape=() size (8) val='12.23'' + 65. '/epochs/trial_0002/stop_time: dtype=float64, shape=() size (8) val='24.44'' + 66. '/file_create_date: dtype=--, shape=(1,) size (--), compress=gzip val='"--value removed for NWB signature--"'' + 67. '/general/data_collection: dtype=|S80, shape=() size (80) val='"Text notes about data collection and ana...gWoCry'' + 68. '/general/devices/AOL_microscope: dtype=|S57, shape=() size (57) val='"Random access 3d acousto-optic lens two-...ekQKnw'' + 69. '/general/devices/air_puff_device: dtype=|S53, shape=() size (53) val='"Delivers an air puff stimulus to the mou...NXTbu'' + 70. '/general/devices/mouse_wheel_device: dtype=|S24, shape=() size (24) val='"Records mouse speed data"'' + 71. '/general/experiment_description: dtype=|S84, shape=() size (84) val='"A general description of the experiment ...LbatF'' + 72. '/general/experimenter: dtype=|S15, shape=() size (15) val='"Frederic Lanore"'' + 73. '/general/institution: dtype=|S25, shape=() size (25) val='"University College London"'' + 74. '/general/lab: dtype=|S33, shape=() size (33) val='"Silver Lab (http://silverlab.org)"'' + 75. '/general/labview_header: dtype=|S37, shape=(39, 3) size (760), compress=gzip val='[["LOGIN","User",""Fred""],["LOGIN","Prof...hcNvXH'' + 76. '/general/notes: dtype=|S62, shape=() size (62) val='"Notes about the experiment that don't fi...jyjZeD'' + 77. '/general/optophysiology/Zstack#/description: dtype=|S17, shape=() size (17) val='"Reference Z stack"' (#=1-78)' + 78. '/general/optophysiology/Zstack#/device: dtype=|S14, shape=() size (14) val='"AOL_microscope"' (#=1-78)' + 79. '/general/optophysiology/Zstack#/excitation_lambda: dtype=|S22, shape=() size (22) val='"Excitation wavelength."' (#=1-78)' + 80. '/general/optophysiology/Zstack#/green/description: dtype=|S48, shape=() size (48) val='"Green channel, typically used for active...hSPyys' (#=1-78)' + 81. '/general/optophysiology/Zstack#/green/emission_lambda: dtype=|S38, shape=() size (38) val='"Emission wavelength for green channel."' (#=1-78)' + 82. '/general/optophysiology/Zstack#/imaging_rate: dtype=|S72, shape=() size (72) val='"30.0264232524621661Hz (cycle time = 3330...fhIvKj' (#=1-78)' + 83. '/general/optophysiology/Zstack#/indicator: dtype=|S18, shape=() size (18) val='"Calcium indicator."' (#=1-78)' + 84. '/general/optophysiology/Zstack#/location: dtype=|S94, shape=() size (94) val='"Anatomy gross description of imaging loc...fuLdPY' (#=1-78)' + 85. '/general/optophysiology/Zstack0001/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,77],[0.3425,0,77],[0.6849,0,77],[1...ccvZnJ'' + 86. '/general/optophysiology/Zstack#/red/description: dtype=|S42, shape=() size (42) val='"Red channel, typically used for reference."' (#=1-78)' + 87. '/general/optophysiology/Zstack#/red/emission_lambda: dtype=|S36, shape=() size (36) val='"Emission wavelength for red channel."' (#=1-78)' + 88. '/general/optophysiology/Zstack#/reference_frame: dtype=|S27, shape=() size (27) val='"TODO: In lab book (partly?)"' (#=1-78)' + 89. '/general/optophysiology/Zstack0002/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,75],[0.3425,0,75],[0.6849,0,75],[1...jViGCx'' + 90. '/general/optophysiology/Zstack0003/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,73],[0.3425,0,73],[0.6849,0,73],[1...gyGDUV'' + 91. '/general/optophysiology/Zstack0004/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,71],[0.3425,0,71],[0.6849,0,71],[1...dceBnt'' + 92. '/general/optophysiology/Zstack0005/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,69],[0.3425,0,69],[0.6849,0,69],[1...kURiCh'' + 93. '/general/optophysiology/Zstack0006/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,67],[0.3425,0,67],[0.6849,0,67],[1...hypfUF'' + 94. '/general/optophysiology/Zstack0007/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,65],[0.3425,0,65],[0.6849,0,65],[1...ebNdnd'' + 95. '/general/optophysiology/Zstack0008/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,63],[0.3425,0,63],[0.6849,0,63],[1...eBErmV'' + 96. '/general/optophysiology/Zstack0009/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,61],[0.3425,0,61],[0.6849,0,61],[1...iXOVUh'' + 97. '/general/optophysiology/Zstack0010/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,59],[0.3425,0,59],[0.6849,0,59],[1...ceKQFd'' + 98. '/general/optophysiology/Zstack0011/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,57],[0.3425,0,57],[0.6849,0,57],[1...gAVvmp'' + 99. '/general/optophysiology/Zstack0012/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,55],[0.3425,0,55],[0.6849,0,55],[1...kXfZTB'' +100. '/general/optophysiology/Zstack0013/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,53],[0.3425,0,53],[0.6849,0,53],[1...eebUEx'' +101. '/general/optophysiology/Zstack0014/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,51],[0.3425,0,51],[0.6849,0,51],[1...iAmzlJ'' +102. '/general/optophysiology/Zstack0015/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,49],[0.3425,0,49],[0.6849,0,49],[1...bHitWF'' +103. '/general/optophysiology/Zstack0016/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,47],[0.3425,0,47],[0.6849,0,47],[1...gdsYDR'' +104. '/general/optophysiology/Zstack0017/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,45],[0.3425,0,45],[0.6849,0,45],[1...kzDDld'' +105. '/general/optophysiology/Zstack0018/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,43],[0.3425,0,43],[0.6849,0,43],[1...dGzxVZ'' +106. '/general/optophysiology/Zstack0019/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,41],[0.3425,0,41],[0.6849,0,41],[1...icKcDl'' +107. '/general/optophysiology/Zstack0020/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,39],[0.3425,0,39],[0.6849,0,39],[1...bjFXoh'' +108. '/general/optophysiology/Zstack0021/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,37],[0.3425,0,37],[0.6849,0,37],[1...fFQBVt'' +109. '/general/optophysiology/Zstack0022/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,35],[0.3425,0,35],[0.6849,0,35],[1...kcbgCF'' +110. '/general/optophysiology/Zstack0023/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,33],[0.3425,0,33],[0.6849,0,33],[1...diXbnB'' +111. '/general/optophysiology/Zstack0024/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,31],[0.3425,0,31],[0.6849,0,31],[1...fHRYwR'' +112. '/general/optophysiology/Zstack0025/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,29],[0.3425,0,29],[0.6849,0,29],[1...dkYxOZ'' +113. '/general/optophysiology/Zstack0026/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,27],[0.3425,0,27],[0.6849,0,27],[1...OeXhh'' +114. '/general/optophysiology/Zstack0027/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,25],[0.3425,0,25],[0.6849,0,25],[1...jGAgvF'' +115. '/general/optophysiology/Zstack0028/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,23],[0.3425,0,23],[0.6849,0,23],[1...hjGFNN'' +116. '/general/optophysiology/Zstack0029/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,21],[0.3425,0,21],[0.6849,0,21],[1...eMNffV'' +117. '/general/optophysiology/Zstack0030/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,19],[0.3425,0,19],[0.6849,0,19],[1...cpTEyd'' +118. '/general/optophysiology/Zstack0031/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,17],[0.3425,0,17],[0.6849,0,17],[1...lioNMB'' +119. '/general/optophysiology/Zstack0032/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,15],[0.3425,0,15],[0.6849,0,15],[1...bSrhPF'' +120. '/general/optophysiology/Zstack0033/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,13],[0.3425,0,13],[0.6849,0,13],[1...inSQwl'' +121. '/general/optophysiology/Zstack0034/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,11],[0.3425,0,11],[0.6849,0,11],[1...dufPgB'' +122. '/general/optophysiology/Zstack0035/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,9],[0.3425,0,9],[0.6849,0,9],[1.02...jPHxNh'' +123. '/general/optophysiology/Zstack0036/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,7],[0.3425,0,7],[0.6849,0,7],[1.02...dYnqZl'' +124. '/general/optophysiology/Zstack0037/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,5],[0.3425,0,5],[0.6849,0,5],[1.02...fAbYqh'' +125. '/general/optophysiology/Zstack0038/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,3],[0.3425,0,3],[0.6849,0,3],[1.02...cidErt'' +126. '/general/optophysiology/Zstack0039/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,1],[0.3425,0,1],[0.6849,0,1],[1.02...imHVzN'' +127. '/general/optophysiology/Zstack0040/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-1],[0.3425,0,-1],[0.6849,0,-1],[1...dSndeR'' +128. '/general/optophysiology/Zstack0041/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-3],[0.3425,0,-3],[0.6849,0,-3],[1...jcXvSN'' +129. '/general/optophysiology/Zstack0042/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-5],[0.3425,0,-5],[0.6849,0,-5],[1...bfHfVl'' +130. '/general/optophysiology/Zstack0043/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-7],[0.3425,0,-7],[0.6849,0,-7],[1...kThiAF'' +131. '/general/optophysiology/Zstack0044/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-9],[0.3425,0,-9],[0.6849,0,-9],[1...fvmFsl'' +132. '/general/optophysiology/Zstack0045/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-11],[0.3425,0,-11],[0.6849,0,-11]...koZGHV'' +133. '/general/optophysiology/Zstack0046/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-13],[0.3425,0,-13],[0.6849,0,-13]...dTxYbp'' +134. '/general/optophysiology/Zstack0047/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-15],[0.3425,0,-15],[0.6849,0,-15]...iNkZqZ'' +135. '/general/optophysiology/Zstack0048/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-17],[0.3425,0,-17],[0.6849,0,-17]...gNTVrF'' +136. '/general/optophysiology/Zstack0049/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-19],[0.3425,0,-19],[0.6849,0,-19]...jkNvZx'' +137. '/general/optophysiology/Zstack0050/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-21],[0.3425,0,-21],[0.6849,0,-21]...ssmKZ'' +138. '/general/optophysiology/Zstack0051/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-23],[0.3425,0,-23],[0.6849,0,-23]...cPlNsR'' +139. '/general/optophysiology/Zstack0052/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-25],[0.3425,0,-25],[0.6849,0,-25]...fmfoaJ'' +140. '/general/optophysiology/Zstack0053/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-27],[0.3425,0,-27],[0.6849,0,-27]...hIYOIB'' +141. '/general/optophysiology/Zstack0054/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-29],[0.3425,0,-29],[0.6849,0,-29]...kfSpqt'' +142. '/general/optophysiology/Zstack0055/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-31],[0.3425,0,-31],[0.6849,0,-31]...bnxgbV'' +143. '/general/optophysiology/Zstack0056/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-33],[0.3425,0,-33],[0.6849,0,-33]...kdQSOV'' +144. '/general/optophysiology/Zstack0057/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-35],[0.3425,0,-35],[0.6849,0,-35]...fHGohJ'' +145. '/general/optophysiology/Zstack0058/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-37],[0.3425,0,-37],[0.6849,0,-37]...blvJAx'' +146. '/general/optophysiology/Zstack0059/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-39],[0.3425,0,-39],[0.6849,0,-39]...iezOPB'' +147. '/general/optophysiology/Zstack0060/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-41],[0.3425,0,-41],[0.6849,0,-41]...dIpkip'' +148. '/general/optophysiology/Zstack0061/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-43],[0.3425,0,-43],[0.6849,0,-43]...kBtpxt'' +149. '/general/optophysiology/Zstack0062/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-45],[0.3425,0,-45],[0.6849,0,-45]...gfiKQh'' +150. '/general/optophysiology/Zstack0063/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-47],[0.3425,0,-47],[0.6849,0,-47]...bIYgiV'' +151. '/general/optophysiology/Zstack0064/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-49],[0.3425,0,-49],[0.6849,0,-49]...iCclxZ'' +152. '/general/optophysiology/Zstack0065/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-51],[0.3425,0,-51],[0.6849,0,-51]...efRGQN'' +153. '/general/optophysiology/Zstack0066/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-53],[0.3425,0,-53],[0.6849,0,-53]...kYVMfR'' +154. '/general/optophysiology/Zstack0067/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-55],[0.3425,0,-55],[0.6849,0,-55]...gCLhyF'' +155. '/general/optophysiology/Zstack0068/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-57],[0.3425,0,-57],[0.6849,0,-57]...cgACRt'' +156. '/general/optophysiology/Zstack0069/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-59],[0.3425,0,-59],[0.6849,0,-59]...iZEIgx'' +157. '/general/optophysiology/Zstack0070/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-61],[0.3425,0,-61],[0.6849,0,-61]...eDudzl'' +158. '/general/optophysiology/Zstack0071/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-63],[0.3425,0,-63],[0.6849,0,-63]...hjyRZ'' +159. '/general/optophysiology/Zstack0072/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-65],[0.3425,0,-65],[0.6849,0,-65]...kWGUOx'' +160. '/general/optophysiology/Zstack0073/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-67],[0.3425,0,-67],[0.6849,0,-67]...ddUnzJ'' +161. '/general/optophysiology/Zstack0074/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,-69],[0.3425,0,-69],[0.6849,0,-69]...gAwqhl'' +162. '/general/optophysiology/Zstack0075/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-71],[0.3425,0,-71],[0.6849,0,-71]...jWYsON'' +163. '/general/optophysiology/Zstack0076/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-73],[0.3425,0,-73],[0.6849,0,-73]...celLzZ'' +164. '/general/optophysiology/Zstack0077/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-75],[0.3425,0,-75],[0.6849,0,-75]...fANOhB'' +165. '/general/optophysiology/Zstack0078/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-77],[0.3425,0,-77],[0.6849,0,-77]...iXpQPd'' +166. '/general/optophysiology/cycle_time: dtype=float32, shape=() size (4) val='0.0333'' +167. '/general/optophysiology/frame_size: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' +168. '/general/optophysiology/imaging_mode: dtype=|S5, shape=() size (5) val='"patch"'' +169. '/general/optophysiology/zplane_pockels: dtype=float32, shape=(78, 4) size (682), compress=gzip val='[[77,77,70.35,65],[75,75,70.26,63],[73,73...fFYGau'' +170. '/general/pharmacology: dtype=|S152, shape=() size (152) val='"Description of drugs used, including how...goKGik'' +171. '/general/protocol: dtype=|S76, shape=() size (76) val='"Experimental protocol, if applicable, e....bWYeFo'' +172. '/general/related_publications: dtype=|S70, shape=() size (70) val='"Optional list of related publications, i...gGeOxQ'' +173. '/general/session_id: dtype=|S36, shape=() size (36) val='"sample_miniscan_fred_170322_14_06_43"'' +174. '/general/slices: dtype=|S127, shape=() size (127) val='"Description of slices, including informa...bwDbqR'' +175. '/general/specifications/e-labview.py: dtype=|S1534, shape=() size (1534) val='"# NWB extension to store LabView header ...fvMAMg'' +176. '/general/specifications/e-pixeltimes.py: dtype=|S2701, shape=() size (2701) val='"# NWB extension to store per-pixel time ...gVgtZh'' +177. '/general/specifications/nwb_core.py: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +178. '/general/stimulus: dtype=|S84, shape=() size (84) val='"Notes about stimuli, such as how and whe...DShaM'' +179. '/general/subject/age: dtype=|S25, shape=() size (25) val='"Age of subject. Optional."'' +180. '/general/subject/description: dtype=|S88, shape=() size (88) val='"Description of subject and where subject...fXgfBt'' +181. '/general/subject/genotype: dtype=|S59, shape=() size (59) val='"Genetic strain. If absent, assume Wild T...eOaNbr'' +182. '/general/subject/sex: dtype=|S28, shape=() size (28) val='"Gender of subject. Optional."'' +183. '/general/subject/species: dtype=|S29, shape=() size (29) val='"Species of subject. Optional."'' +184. '/general/subject/subject_id: dtype=|S80, shape=() size (80) val='"ID of animal/person used/participating i...hoSoPZ'' +185. '/general/subject/weight: dtype=|S88, shape=() size (88) val='"Weight at time of experiment, at time of...grFgyL'' +186. '/general/surgery: dtype=|S134, shape=() size (134) val='"Narrative description about surgery/surg...dKKeYq'' +187. '/general/virus: dtype=|S130, shape=() size (130) val='"Information about virus(es) used in expe...cMsZNh'' +188. '/identifier: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +189. '/nwb_version: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +190. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[202,60]'' +191. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/img_mask: dtype=float32, shape=(512, 512) size (2911), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...cPiXuw'' +192. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/pix_mask: dtype=uint16, shape=(12120, 2) size (972), compress=gzip val='[[134,175],[135,175],[136,175],[137,175],...dGaXxp'' +193. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/pix_mask_weight: dtype=float32, shape=(12120,) size (152), compress=gzip val='[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,...gZQoTY'' +194. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/pixel_time_offsets: dtype=float64, shape=(60, 202) size (74272), compress=gzip val='[[0.0003801,0.0003801,0.0003802,0.0003802...ievJCr'' +195. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/ROI_001/roi_description: dtype=|S7, shape=() size (7) val='"ROI_001"'' +196. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/imaging_plane_name: dtype=|S10, shape=() size (10) val='"Zstack0033"'' +197. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0033/roi_list: dtype=|S7, shape=(1,) size (15), compress=gzip val='["ROI_001"]'' +198. '/processing/Acquired_ROIs/roi_spec: dtype=float16, shape=(1, 17) size (40), compress=gzip val='[[1,3,inf,12120,134,175,13,336,235,13,0,0...hxiOAF'' +199. '/session_description: dtype=|S68, shape=() size (68) val='"One or two sentences describing the expe...ezufjX'' +200. '/session_start_time: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +201. '/silverlab_api_version: dtype=|S3, shape=() size (3) val='"0.1"'' +202. '/stimulus/presentation/air_puff/data: dtype=|S4, shape=(2,) size (14), compress=gzip val='["puff","puff"]'' +203. '/stimulus/presentation/air_puff/num_samples: dtype=int32, shape=() size (4) val='2'' +204. '/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(2,) size (21), compress=gzip val='[5,17.23]'' +-------------------- +** Summary +269 groups, 1054 datasets, 267 attributes diff --git a/Python/test/data/sample_pointing_fred_170317_10_11_01.sig b/Python/test/data/sample_pointing_fred_170317_10_11_01.sig new file mode 100644 index 0000000..eddb3d0 --- /dev/null +++ b/Python/test/data/sample_pointing_fred_170317_10_11_01.sig @@ -0,0 +1,475 @@ +<% Generating signature for /Users/jonc/projects/OpenSourceBrain/Data/sample_pointing_fred_170317_10_11_01.nwb %> + +** No datasets hard links. +** No groups hard links. +** 11 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0014/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0014/description' + 2. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' + 3. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_002/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_002_Green/pixel_time_offsets + /acquisition/timeseries/ROI_002_Red/pixel_time_offsets' + 4. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_003/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_003_Green/pixel_time_offsets + /acquisition/timeseries/ROI_003_Red/pixel_time_offsets' + 5. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_004/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_004_Green/pixel_time_offsets + /acquisition/timeseries/ROI_004_Red/pixel_time_offsets' + 6. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_005/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_005_Green/pixel_time_offsets + /acquisition/timeseries/ROI_005_Red/pixel_time_offsets' + 7. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_006/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_006_Green/pixel_time_offsets + /acquisition/timeseries/ROI_006_Red/pixel_time_offsets' + 8. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_007/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_007_Green/pixel_time_offsets + /acquisition/timeseries/ROI_007_Red/pixel_time_offsets' + 9. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_008/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_008_Green/pixel_time_offsets + /acquisition/timeseries/ROI_008_Red/pixel_time_offsets' + 10. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_009/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_009_Green/pixel_time_offsets + /acquisition/timeseries/ROI_009_Red/pixel_time_offsets' + 11. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_010/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_010_Green/pixel_time_offsets + /acquisition/timeseries/ROI_010_Red/pixel_time_offsets' +** 22 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-2)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-2)' + 3. 'to: "/acquisition/timeseries/ROI_002_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_002_Green/timeseries (#=1-2)' + 4. 'to: "/acquisition/timeseries/ROI_002_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_002_Red/timeseries (#=1-2)' + 5. 'to: "/acquisition/timeseries/ROI_003_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_003_Green/timeseries (#=1-2)' + 6. 'to: "/acquisition/timeseries/ROI_003_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_003_Red/timeseries (#=1-2)' + 7. 'to: "/acquisition/timeseries/ROI_004_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_004_Green/timeseries (#=1-2)' + 8. 'to: "/acquisition/timeseries/ROI_004_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_004_Red/timeseries (#=1-2)' + 9. 'to: "/acquisition/timeseries/ROI_005_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_005_Green/timeseries (#=1-2)' + 10. 'to: "/acquisition/timeseries/ROI_005_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_005_Red/timeseries (#=1-2)' + 11. 'to: "/acquisition/timeseries/ROI_006_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_006_Green/timeseries (#=1-2)' + 12. 'to: "/acquisition/timeseries/ROI_006_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_006_Red/timeseries (#=1-2)' + 13. 'to: "/acquisition/timeseries/ROI_007_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_007_Green/timeseries (#=1-2)' + 14. 'to: "/acquisition/timeseries/ROI_007_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_007_Red/timeseries (#=1-2)' + 15. 'to: "/acquisition/timeseries/ROI_008_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_008_Green/timeseries (#=1-2)' + 16. 'to: "/acquisition/timeseries/ROI_008_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_008_Red/timeseries (#=1-2)' + 17. 'to: "/acquisition/timeseries/ROI_009_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_009_Green/timeseries (#=1-2)' + 18. 'to: "/acquisition/timeseries/ROI_009_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_009_Red/timeseries (#=1-2)' + 19. 'to: "/acquisition/timeseries/ROI_010_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_010_Green/timeseries (#=1-2)' + 20. 'to: "/acquisition/timeseries/ROI_010_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_010_Red/timeseries (#=1-2)' + 21. 'to: "/acquisition/timeseries/Zstack_Red_0014" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0014/reference_images/Zstack_image' + 22. 'to: "/acquisition/timeseries/speed_data" 2 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-2)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 521 attributes (sorted alphabetically) (129 combined): + 1. '/acquisition/timeseries/ROI_#_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-10)' + 2. '/acquisition/timeseries/ROI_#_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-10)' + 3. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 4. '/acquisition/timeseries/ROI_#_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-10)' + 5. '/acquisition/timeseries/ROI_#_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-10)' + 6. '/acquisition/timeseries/ROI_#_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-10)' + 7. '/acquisition/timeseries/ROI_#_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 8. '/acquisition/timeseries/ROI_#_Green/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-10)' + 9. '/acquisition/timeseries/ROI_#_Green/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-10)' + 10. '/acquisition/timeseries/ROI_#_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-10)' + 11. '/acquisition/timeseries/ROI_#_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-10)' + 13. '/acquisition/timeseries/ROI_#_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-10)' + 14. '/acquisition/timeseries/ROI_#_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-10)' + 15. '/acquisition/timeseries/ROI_#_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-10)' + 16. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 17. '/acquisition/timeseries/ROI_#_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-10)' + 18. '/acquisition/timeseries/ROI_#_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-10)' + 19. '/acquisition/timeseries/ROI_#_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-10)' + 20. '/acquisition/timeseries/ROI_#_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 21. '/acquisition/timeseries/ROI_#_Red/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-10)' + 22. '/acquisition/timeseries/ROI_#_Red/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-10)' + 23. '/acquisition/timeseries/ROI_#_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-10)' + 24. '/acquisition/timeseries/ROI_#_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 25. '/acquisition/timeseries/ROI_#_Red/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-10)' + 26. '/acquisition/timeseries/ROI_#_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-10)' + 27. '/acquisition/timeseries/ROI_002_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPc'' + 28. '/acquisition/timeseries/ROI_002_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPC'' + 29. '/acquisition/timeseries/ROI_003_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnJ'' + 30. '/acquisition/timeseries/ROI_003_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroj'' + 31. '/acquisition/timeseries/ROI_004_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMq'' + 32. '/acquisition/timeseries/ROI_004_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMQ'' + 33. '/acquisition/timeseries/ROI_005_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkX'' + 34. '/acquisition/timeseries/ROI_005_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklx'' + 35. '/acquisition/timeseries/ROI_006_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJE'' + 36. '/acquisition/timeseries/ROI_006_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKe'' + 37. '/acquisition/timeseries/ROI_007_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcil'' + 38. '/acquisition/timeseries/ROI_007_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiL'' + 39. '/acquisition/timeseries/ROI_008_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGS'' + 40. '/acquisition/timeseries/ROI_008_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHs'' + 41. '/acquisition/timeseries/ROI_009_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfz'' + 42. '/acquisition/timeseries/ROI_009_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfZ'' + 43. '/acquisition/timeseries/ROI_010_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzVCL'' + 44. '/acquisition/timeseries/ROI_010_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytWDl'' + 45. '/acquisition/timeseries/Zstack_Green_0014 ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]'' + 46. '/acquisition/timeseries/Zstack_Green_0014 comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"'' + 47. '/acquisition/timeseries/Zstack_Green_0014 description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"'' + 48. '/acquisition/timeseries/Zstack_Green_0014 help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"'' + 49. '/acquisition/timeseries/Zstack_Green_0014 neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 50. '/acquisition/timeseries/Zstack_Green_0014 source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' + 51. '/acquisition/timeseries/Zstack_Green_0014/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 52. '/acquisition/timeseries/Zstack_Green_0014/data conversion: dtype=float64, shape=() size (8) val='1'' + 53. '/acquisition/timeseries/Zstack_Green_0014/data resolution: dtype=float64, shape=() size (8) val='nan'' + 54. '/acquisition/timeseries/Zstack_Green_0014/data unit: dtype=|S9, shape=() size (9) val='"intensity"'' + 55. '/acquisition/timeseries/Zstack_Green_0014/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 56. '/acquisition/timeseries/Zstack_Green_0014/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 57. '/acquisition/timeseries/Zstack_Red_0014 ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]'' + 58. '/acquisition/timeseries/Zstack_Red_0014 comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"'' + 59. '/acquisition/timeseries/Zstack_Red_0014 description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"'' + 60. '/acquisition/timeseries/Zstack_Red_0014 help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"'' + 61. '/acquisition/timeseries/Zstack_Red_0014 neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 62. '/acquisition/timeseries/Zstack_Red_0014 source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' + 63. '/acquisition/timeseries/Zstack_Red_0014/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 64. '/acquisition/timeseries/Zstack_Red_0014/data conversion: dtype=float64, shape=() size (8) val='1'' + 65. '/acquisition/timeseries/Zstack_Red_0014/data resolution: dtype=float64, shape=() size (8) val='nan'' + 66. '/acquisition/timeseries/Zstack_Red_0014/data unit: dtype=|S9, shape=() size (9) val='"intensity"'' + 67. '/acquisition/timeseries/Zstack_Red_0014/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 68. '/acquisition/timeseries/Zstack_Red_0014/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 69. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 70. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' + 71. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' + 72. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' + 73. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 74. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' + 75. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' + 76. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' + 77. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' + 78. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 79. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 80. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 81. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' + 82. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' + 83. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' + 84. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 85. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' + 86. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' + 87. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' + 88. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' + 89. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 90. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 91. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' + 92. '/epochs/trial_# links: dtype=|S58, shape=(21,) size (1218) val='["'ROI_001_Green' is '/acquisition/timese...bDhpwS' (#=1-2)' + 93. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-2)' + 94. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' + 95. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-79)' + 96. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-79)' + 97. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 98. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' + 99. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +100. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' +101. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +102. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +103. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' +104. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +105. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' +106. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +107. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' +108. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' +109. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' +110. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' +111. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' +112. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' +113. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' +114. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' +115. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=1-10)' +116. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' +117. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +118. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +119. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +120. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +121. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +122. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +123. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +124. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +125. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +126. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +127. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +128. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +129. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 1408 datasets (sorted alphabetically) (253 combined): + 1. '/acquisition/timeseries/ROI_#_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-10)' + 2. '/acquisition/timeseries/ROI_#_Green/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-10)' + 3. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(5858, 1, 1) size (5382), compress=gzip val='[[[119]],[[122]],[[116]],[[123]],[[122]],...ecmzXh'' + 4. '/acquisition/timeseries/ROI_#_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-10)' + 5. '/acquisition/timeseries/ROI_#_Green/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[3.418e-07,3.418e-07]' (#=1-10)' + 6. '/acquisition/timeseries/ROI_#_Green/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-10)' + 7. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0014"' (#=1-10)' + 8. '/acquisition/timeseries/ROI_#_Green/num_samples: dtype=int32, shape=() size (4) val='5858' (#=1-10)' + 9. '/acquisition/timeseries/ROI_#_Green/pmt_gain: dtype=float32, shape=() size (4) val='700' (#=1-10)' + 10. '/acquisition/timeseries/ROI_#_Green/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-10)' + 11. '/acquisition/timeseries/ROI_#_Green/scan_line_rate: dtype=float32, shape=() size (4) val='212.8' (#=1-10)' + 12. '/acquisition/timeseries/ROI_#_Green/timestamps: dtype=float64, shape=(5858,) size (40495), compress=gzip val='[2.168e-19,0.004699,0.009399,0.0141,0.018...bghVpW' (#=1-10)' + 13. '/acquisition/timeseries/ROI_#_Red/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-10)' + 14. '/acquisition/timeseries/ROI_#_Red/channel: dtype=|S3, shape=() size (3) val='"Red"' (#=1-10)' + 15. '/acquisition/timeseries/ROI_001_Red/data: dtype=float32, shape=(5858, 1, 1) size (4570), compress=gzip val='[[[109]],[[113]],[[108]],[[112]],[[110]],...iOChpm'' + 16. '/acquisition/timeseries/ROI_#_Red/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-10)' + 17. '/acquisition/timeseries/ROI_#_Red/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[3.418e-07,3.418e-07]' (#=1-10)' + 18. '/acquisition/timeseries/ROI_#_Red/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-10)' + 19. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0014"' (#=1-10)' + 20. '/acquisition/timeseries/ROI_#_Red/num_samples: dtype=int32, shape=() size (4) val='5858' (#=1-10)' + 21. '/acquisition/timeseries/ROI_#_Red/pmt_gain: dtype=float32, shape=() size (4) val='650' (#=1-10)' + 22. '/acquisition/timeseries/ROI_#_Red/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-10)' + 23. '/acquisition/timeseries/ROI_#_Red/scan_line_rate: dtype=float32, shape=() size (4) val='212.8' (#=1-10)' + 24. '/acquisition/timeseries/ROI_#_Red/timestamps: dtype=float64, shape=(5858,) size (40495), compress=gzip val='[2.168e-19,0.004699,0.009399,0.0141,0.018...bghVpW' (#=1-10)' + 25. '/acquisition/timeseries/ROI_002_Green/data: dtype=float32, shape=(5858, 1, 1) size (5464), compress=gzip val='[[[125]],[[126]],[[118]],[[126]],[[143]],...llEIHK'' + 26. '/acquisition/timeseries/ROI_002_Red/data: dtype=float32, shape=(5858, 1, 1) size (4679), compress=gzip val='[[[111]],[[106]],[[109]],[[109]],[[109]],...ngIrG'' + 27. '/acquisition/timeseries/ROI_003_Green/data: dtype=float32, shape=(5858, 1, 1) size (5348), compress=gzip val='[[[118]],[[119]],[[122]],[[124]],[[121]],...dVeDBV'' + 28. '/acquisition/timeseries/ROI_003_Red/data: dtype=float32, shape=(5858, 1, 1) size (4623), compress=gzip val='[[[107]],[[112]],[[104]],[[107]],[[109]],...pAGhU'' + 29. '/acquisition/timeseries/ROI_004_Green/data: dtype=float32, shape=(5858, 1, 1) size (5504), compress=gzip val='[[[119]],[[123]],[[120]],[[120]],[[126]],...bIozkg'' + 30. '/acquisition/timeseries/ROI_004_Red/data: dtype=float32, shape=(5858, 1, 1) size (4637), compress=gzip val='[[[109]],[[112]],[[109]],[[114]],[[115]],...RicBW'' + 31. '/acquisition/timeseries/ROI_005_Green/data: dtype=float32, shape=(5858, 1, 1) size (5412), compress=gzip val='[[[129]],[[120]],[[120]],[[120]],[[123]],...dtRcmr'' + 32. '/acquisition/timeseries/ROI_005_Red/data: dtype=float32, shape=(5858, 1, 1) size (4629), compress=gzip val='[[[109]],[[107]],[[112]],[[108]],[[106]],...iNTGRs'' + 33. '/acquisition/timeseries/ROI_006_Green/data: dtype=float32, shape=(5858, 1, 1) size (5659), compress=gzip val='[[[118]],[[120]],[[126]],[[123]],[[130]],...duMYgx'' + 34. '/acquisition/timeseries/ROI_006_Red/data: dtype=float32, shape=(5858, 1, 1) size (4658), compress=gzip val='[[[111]],[[110]],[[110]],[[113]],[[111]],...cSXLI'' + 35. '/acquisition/timeseries/ROI_007_Green/data: dtype=float32, shape=(5858, 1, 1) size (5497), compress=gzip val='[[[120]],[[127]],[[122]],[[121]],[[125]],...dOwDGC'' + 36. '/acquisition/timeseries/ROI_007_Red/data: dtype=float32, shape=(5858, 1, 1) size (4656), compress=gzip val='[[[108]],[[112]],[[108]],[[115]],[[108]],...iOwZhU'' + 37. '/acquisition/timeseries/ROI_008_Green/data: dtype=float32, shape=(5858, 1, 1) size (5566), compress=gzip val='[[[138]],[[126]],[[125]],[[120]],[[128]],...jNPqoW'' + 38. '/acquisition/timeseries/ROI_008_Red/data: dtype=float32, shape=(5858, 1, 1) size (4677), compress=gzip val='[[[116]],[[113]],[[109]],[[112]],[[110]],...eHTotM'' + 39. '/acquisition/timeseries/ROI_009_Green/data: dtype=float32, shape=(5858, 1, 1) size (5389), compress=gzip val='[[[122]],[[128]],[[123]],[[121]],[[123]],...hbLigF'' + 40. '/acquisition/timeseries/ROI_009_Red/data: dtype=float32, shape=(5858, 1, 1) size (4646), compress=gzip val='[[[107]],[[108]],[[109]],[[114]],[[115]],...bFXKIK'' + 41. '/acquisition/timeseries/ROI_010_Green/data: dtype=float32, shape=(5858, 1, 1) size (5274), compress=gzip val='[[[120]],[[124]],[[118]],[[123]],[[134]],...eeiTHu'' + 42. '/acquisition/timeseries/ROI_010_Red/data: dtype=float32, shape=(5858, 1, 1) size (4591), compress=gzip val='[[[108]],[[104]],[[108]],[[108]],[[107]],...fCZayg'' + 43. '/acquisition/timeseries/Zstack_Green_0014/bits_per_pixel: dtype=int32, shape=() size (4) val='16'' + 44. '/acquisition/timeseries/Zstack_Green_0014/channel: dtype=|S5, shape=() size (5) val='"Green"'' + 45. '/acquisition/timeseries/Zstack_Green_0014/data: dtype=uint16, shape=(512, 512) size (269214), compress=gzip val='[[141,124,119,111,125,133,132,121,132,120...htWJmm'' + 46. '/acquisition/timeseries/Zstack_Green_0014/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' + 47. '/acquisition/timeseries/Zstack_Green_0014/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[0.000175,0.000175]'' + 48. '/acquisition/timeseries/Zstack_Green_0014/format: dtype=|S4, shape=() size (4) val='"tiff"'' + 49. '/acquisition/timeseries/Zstack_Green_0014/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0014"'' + 50. '/acquisition/timeseries/Zstack_Green_0014/num_samples: dtype=int32, shape=() size (4) val='1'' + 51. '/acquisition/timeseries/Zstack_Green_0014/pmt_gain: dtype=float32, shape=() size (4) val='700'' + 52. '/acquisition/timeseries/Zstack_Green_0014/scan_line_rate: dtype=float32, shape=() size (4) val='212.8'' + 53. '/acquisition/timeseries/Zstack_Green_0014/timestamps: dtype=float64, shape=(1,) size (11), compress=gzip val='[0]'' + 54. '/acquisition/timeseries/Zstack_Red_0014/bits_per_pixel: dtype=int32, shape=() size (4) val='16'' + 55. '/acquisition/timeseries/Zstack_Red_0014/channel: dtype=|S3, shape=() size (3) val='"Red"'' + 56. '/acquisition/timeseries/Zstack_Red_0014/data: dtype=uint16, shape=(512, 512) size (233880), compress=gzip val='[[121,107,112,105,119,104,105,106,122,105...kZRVuh'' + 57. '/acquisition/timeseries/Zstack_Red_0014/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' + 58. '/acquisition/timeseries/Zstack_Red_0014/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[0.000175,0.000175]'' + 59. '/acquisition/timeseries/Zstack_Red_0014/format: dtype=|S4, shape=() size (4) val='"tiff"'' + 60. '/acquisition/timeseries/Zstack_Red_0014/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0014"'' + 61. '/acquisition/timeseries/Zstack_Red_0014/num_samples: dtype=int32, shape=() size (4) val='1'' + 62. '/acquisition/timeseries/Zstack_Red_0014/pmt_gain: dtype=float32, shape=() size (4) val='650'' + 63. '/acquisition/timeseries/Zstack_Red_0014/scan_line_rate: dtype=float32, shape=() size (4) val='212.8'' + 64. '/acquisition/timeseries/Zstack_Red_0014/timestamps: dtype=float64, shape=(1,) size (11), compress=gzip val='[0]'' + 65. '/acquisition/timeseries/speed_data/data: dtype=float32, shape=(12864,) size (1035), compress=gzip val='[0,0,0,0,0,0,0,0,0,0,0,0,2.79,0,0,0,0,0,0...kJYGpg'' + 66. '/acquisition/timeseries/speed_data/num_samples: dtype=int32, shape=() size (4) val='12864'' + 67. '/acquisition/timeseries/speed_data/timestamps: dtype=float64, shape=(12864,) size (90065), compress=gzip val='[0.001378,0.003522,0.005666,0.007809,0.00...cTJudR'' + 68. '/acquisition/timeseries/trial_times/data: dtype=int32, shape=(12864,) size (43059), compress=gzip val='[1378,3522,5666,7809,9953,12097,14244,163...bQKYvg'' + 69. '/acquisition/timeseries/trial_times/num_samples: dtype=int32, shape=() size (4) val='12864'' + 70. '/acquisition/timeseries/trial_times/timestamps: dtype=float64, shape=(12864,) size (90065), compress=gzip val='[0.001378,0.003522,0.005666,0.007809,0.00...cTJudR'' + 71. '/epochs/trial_0001/ROI_#_Green/count: dtype=int32, shape=() size (4) val='2929' (#=1-10)' + 72. '/epochs/trial_0001/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='0' (#=1-10)' + 73. '/epochs/trial_0001/ROI_#_Red/count: dtype=int32, shape=() size (4) val='2929' (#=1-10)' + 74. '/epochs/trial_0001/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='0' (#=1-10)' + 75. '/epochs/trial_0001/speed_data/count: dtype=int32, shape=() size (4) val='6429'' + 76. '/epochs/trial_0001/speed_data/idx_start: dtype=int32, shape=() size (4) val='0'' + 77. '/epochs/trial_0001/start_time: dtype=float64, shape=() size (8) val='2.168e-19'' + 78. '/epochs/trial_0001/stop_time: dtype=float64, shape=() size (8) val='13.8'' + 79. '/epochs/trial_0002/ROI_#_Green/count: dtype=int32, shape=() size (4) val='2929' (#=1-10)' + 80. '/epochs/trial_0002/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='2929' (#=1-10)' + 81. '/epochs/trial_0002/ROI_#_Red/count: dtype=int32, shape=() size (4) val='2929' (#=1-10)' + 82. '/epochs/trial_0002/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='2929' (#=1-10)' + 83. '/epochs/trial_0002/speed_data/count: dtype=int32, shape=() size (4) val='6430'' + 84. '/epochs/trial_0002/speed_data/idx_start: dtype=int32, shape=() size (4) val='6433'' + 85. '/epochs/trial_0002/start_time: dtype=float64, shape=() size (8) val='13.81'' + 86. '/epochs/trial_0002/stop_time: dtype=float64, shape=() size (8) val='27.6'' + 87. '/file_create_date: dtype=--, shape=(1,) size (--), compress=gzip val='"--value removed for NWB signature--"'' + 88. '/general/data_collection: dtype=|S80, shape=() size (80) val='"Text notes about data collection and ana...gWoCry'' + 89. '/general/devices/AOL_microscope: dtype=|S57, shape=() size (57) val='"Random access 3d acousto-optic lens two-...ekQKnw'' + 90. '/general/devices/air_puff_device: dtype=|S53, shape=() size (53) val='"Delivers an air puff stimulus to the mou...NXTbu'' + 91. '/general/devices/mouse_wheel_device: dtype=|S24, shape=() size (24) val='"Records mouse speed data"'' + 92. '/general/experiment_description: dtype=|S84, shape=() size (84) val='"A general description of the experiment ...LbatF'' + 93. '/general/experimenter: dtype=|S15, shape=() size (15) val='"Frederic Lanore"'' + 94. '/general/institution: dtype=|S25, shape=() size (25) val='"University College London"'' + 95. '/general/lab: dtype=|S33, shape=() size (33) val='"Silver Lab (http://silverlab.org)"'' + 96. '/general/labview_header: dtype=|S37, shape=(31, 3) size (651), compress=gzip val='[["LOGIN","User",""Fred""],["LOGIN","Prof...ilMcwG'' + 97. '/general/notes: dtype=|S62, shape=() size (62) val='"Notes about the experiment that don't fi...jyjZeD'' + 98. '/general/optophysiology/Zstack#/description: dtype=|S17, shape=() size (17) val='"Reference Z stack"' (#=1-79)' + 99. '/general/optophysiology/Zstack#/device: dtype=|S14, shape=() size (14) val='"AOL_microscope"' (#=1-79)' +100. '/general/optophysiology/Zstack#/excitation_lambda: dtype=|S22, shape=() size (22) val='"Excitation wavelength."' (#=1-79)' +101. '/general/optophysiology/Zstack#/green/description: dtype=|S48, shape=() size (48) val='"Green channel, typically used for active...hSPyys' (#=1-79)' +102. '/general/optophysiology/Zstack#/green/emission_lambda: dtype=|S38, shape=() size (38) val='"Emission wavelength for green channel."' (#=1-79)' +103. '/general/optophysiology/Zstack#/imaging_rate: dtype=|S72, shape=() size (72) val='"212.7976507139361217Hz (cycle time = 469...fynhQU' (#=1-79)' +104. '/general/optophysiology/Zstack#/indicator: dtype=|S18, shape=() size (18) val='"Calcium indicator."' (#=1-79)' +105. '/general/optophysiology/Zstack#/location: dtype=|S94, shape=() size (94) val='"Anatomy gross description of imaging loc...fuLdPY' (#=1-79)' +106. '/general/optophysiology/Zstack0001/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,78],[0.3425,0,78],[0.6849,0,78],[1...jvrsCF'' +107. '/general/optophysiology/Zstack#/red/description: dtype=|S42, shape=() size (42) val='"Red channel, typically used for reference."' (#=1-79)' +108. '/general/optophysiology/Zstack#/red/emission_lambda: dtype=|S36, shape=() size (36) val='"Emission wavelength for red channel."' (#=1-79)' +109. '/general/optophysiology/Zstack#/reference_frame: dtype=|S27, shape=() size (27) val='"TODO: In lab book (partly?)"' (#=1-79)' +110. '/general/optophysiology/Zstack0002/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,76],[0.3425,0,76],[0.6849,0,76],[1...fYPpVd'' +111. '/general/optophysiology/Zstack0003/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,74],[0.3425,0,74],[0.6849,0,74],[1...cCnnnB'' +112. '/general/optophysiology/Zstack0004/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,72],[0.3425,0,72],[0.6849,0,72],[1...kuZUCp'' +113. '/general/optophysiology/Zstack0005/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,70],[0.3425,0,70],[0.6849,0,70],[1...gYxRUN'' +114. '/general/optophysiology/Zstack0006/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,68],[0.3425,0,68],[0.6849,0,68],[1...dBVPnl'' +115. '/general/optophysiology/Zstack0007/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,66],[0.3425,0,66],[0.6849,0,66],[1...ftMFJ'' +116. '/general/optophysiology/Zstack0008/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,64],[0.3425,0,64],[0.6849,0,64],[1...hYgtUx'' +117. '/general/optophysiology/Zstack0009/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,62],[0.3425,0,62],[0.6849,0,62],[1...bfcoFt'' +118. '/general/optophysiology/Zstack0010/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,60],[0.3425,0,60],[0.6849,0,60],[1...fBmTmF'' +119. '/general/optophysiology/Zstack0011/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,58],[0.3425,0,58],[0.6849,0,58],[1...jXxxTR'' +120. '/general/optophysiology/Zstack0012/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,56],[0.3425,0,56],[0.6849,0,56],[1...detsEN'' +121. '/general/optophysiology/Zstack0013/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,54],[0.3425,0,54],[0.6849,0,54],[1...hADXlZ'' +122. '/general/optophysiology/Zstack0014/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,52],[0.3425,0,52],[0.6849,0,52],[1...HzRWV'' +123. '/general/optophysiology/Zstack0015/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,50],[0.3425,0,50],[0.6849,0,50],[1...fdKwEh'' +124. '/general/optophysiology/Zstack0016/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,48],[0.3425,0,48],[0.6849,0,48],[1...jzVblt'' +125. '/general/optophysiology/Zstack0017/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,46],[0.3425,0,46],[0.6849,0,46],[1...cGQVWp'' +126. '/general/optophysiology/Zstack0018/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,44],[0.3425,0,44],[0.6849,0,44],[1...hdbADB'' +127. '/general/optophysiology/Zstack0019/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,42],[0.3425,0,42],[0.6849,0,42],[1...jXvox'' +128. '/general/optophysiology/Zstack0020/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,40],[0.3425,0,40],[0.6849,0,40],[1...eGhZVJ'' +129. '/general/optophysiology/Zstack0021/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,38],[0.3425,0,38],[0.6849,0,38],[1...jcsECV'' +130. '/general/optophysiology/Zstack0022/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,36],[0.3425,0,36],[0.6849,0,36],[1...cjoznR'' +131. '/general/optophysiology/Zstack0023/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,34],[0.3425,0,34],[0.6849,0,34],[1...gFzdVd'' +132. '/general/optophysiology/Zstack0024/manifold: dtype=float32, shape=(512, 512, 3) size (33276), compress=gzip val='[[[0,0,32],[0.3425,0,32],[0.6849,0,32],[1...lbJICp'' +133. '/general/optophysiology/Zstack0025/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,30],[0.3425,0,30],[0.6849,0,30],[1...kecDed'' +134. '/general/optophysiology/Zstack0026/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,28],[0.3425,0,28],[0.6849,0,28],[1...hHjcwl'' +135. '/general/optophysiology/Zstack0027/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,26],[0.3425,0,26],[0.6849,0,26],[1...fkpBOt'' +136. '/general/optophysiology/Zstack0028/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,24],[0.3425,0,24],[0.6849,0,24],[1...cNwbgB'' +137. '/general/optophysiology/Zstack0029/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,22],[0.3425,0,22],[0.6849,0,22],[1...qCAyJ'' +138. '/general/optophysiology/Zstack0030/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,20],[0.3425,0,20],[0.6849,0,20],[1...jiXJNh'' +139. '/general/optophysiology/Zstack0031/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,18],[0.3425,0,18],[0.6849,0,18],[1...gMejfp'' +140. '/general/optophysiology/Zstack0032/manifold: dtype=float32, shape=(512, 512, 3) size (33308), compress=gzip val='[[[0,0,16],[0.3425,0,16],[0.6849,0,16],[1...epkIxx'' +141. '/general/optophysiology/Zstack0033/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,14],[0.3425,0,14],[0.6849,0,14],[1...kKMred'' +142. 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'/general/optophysiology/Zstack0079/manifold: dtype=float32, shape=(512, 512, 3) size (33340), compress=gzip val='[[[0,0,-78],[0.3425,0,-78],[0.6849,0,-78]...faWAhJ'' +188. '/general/optophysiology/cycle_time: dtype=float32, shape=() size (4) val='0.004699'' +189. '/general/optophysiology/frame_size: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' +190. '/general/optophysiology/imaging_mode: dtype=|S8, shape=() size (8) val='"pointing"'' +191. '/general/optophysiology/zplane_pockels: dtype=float32, shape=(79, 4) size (690), compress=gzip val='[[78,78,60.25,37],[76,76,60.32,35],[74,74...erpSPT'' +192. '/general/pharmacology: dtype=|S152, shape=() size (152) val='"Description of drugs used, including how...goKGik'' +193. '/general/protocol: dtype=|S76, shape=() size (76) val='"Experimental protocol, if applicable, e....bWYeFo'' +194. '/general/related_publications: dtype=|S70, shape=() size (70) val='"Optional list of related publications, i...gGeOxQ'' +195. '/general/session_id: dtype=|S36, shape=() size (36) val='"sample_pointing_fred_170317_10_11_01"'' +196. '/general/slices: dtype=|S127, shape=() size (127) val='"Description of slices, including informa...bwDbqR'' +197. '/general/specifications/e-labview.py: dtype=|S1534, shape=() size (1534) val='"# NWB extension to store LabView header ...fvMAMg'' +198. '/general/specifications/e-pixeltimes.py: dtype=|S2701, shape=() size (2701) val='"# NWB extension to store per-pixel time ...gVgtZh'' +199. '/general/specifications/nwb_core.py: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +200. '/general/stimulus: dtype=|S84, shape=() size (84) val='"Notes about stimuli, such as how and whe...DShaM'' +201. '/general/subject/age: dtype=|S25, shape=() size (25) val='"Age of subject. Optional."'' +202. '/general/subject/description: dtype=|S88, shape=() size (88) val='"Description of subject and where subject...fXgfBt'' +203. '/general/subject/genotype: dtype=|S59, shape=() size (59) val='"Genetic strain. If absent, assume Wild T...eOaNbr'' +204. '/general/subject/sex: dtype=|S28, shape=() size (28) val='"Gender of subject. Optional."'' +205. '/general/subject/species: dtype=|S29, shape=() size (29) val='"Species of subject. Optional."'' +206. '/general/subject/subject_id: dtype=|S80, shape=() size (80) val='"ID of animal/person used/participating i...hoSoPZ'' +207. '/general/subject/weight: dtype=|S88, shape=() size (88) val='"Weight at time of experiment, at time of...grFgyL'' +208. '/general/surgery: dtype=|S134, shape=() size (134) val='"Narrative description about surgery/surg...dKKeYq'' +209. '/general/virus: dtype=|S130, shape=() size (130) val='"Information about virus(es) used in expe...cMsZNh'' +210. '/identifier: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +211. '/nwb_version: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +212. 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'/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_007/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...idxicy'' +234. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_007/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[126,284]]'' +235. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_007/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.0006235]'' +236. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_008/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...dsluCq'' +237. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_008/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[191,195]]'' +238. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_008/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.000652]'' +239. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_009/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...fGrZRu'' +240. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_009/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[170,227]]'' +241. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_009/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.0006805]'' +242. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_010/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...jymMvC'' +243. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_010/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[169,238]]'' +244. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/ROI_010/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.0007089]'' +245. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/imaging_plane_name: dtype=|S10, shape=() size (10) val='"Zstack0014"'' +246. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0014/roi_list: dtype=|S7, shape=(10,) size (40), compress=gzip val='["ROI_001","ROI_002","ROI_003","ROI_004",...gURXAr'' +247. '/processing/Acquired_ROIs/roi_spec: dtype=float16, shape=(10, 17) size (142), compress=gzip val='[[1,0,4000,1,171,189,52,171,189,52,0,0,0,...daSnCC'' +248. '/session_description: dtype=|S68, shape=() size (68) val='"One or two sentences describing the expe...ezufjX'' +249. '/session_start_time: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +250. '/silverlab_api_version: dtype=|S3, shape=() size (3) val='"0.1"'' +251. '/stimulus/presentation/air_puff/data: dtype=|S4, shape=(2,) size (14), compress=gzip val='["puff","puff"]'' +252. '/stimulus/presentation/air_puff/num_samples: dtype=int32, shape=() size (4) val='2'' +253. '/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(2,) size (22), compress=gzip val='[5,18.81]'' +-------------------- +** Summary +335 groups, 1408 datasets, 521 attributes diff --git a/Python/test/data/sample_pointing_videos_161215_15_34_21.sig b/Python/test/data/sample_pointing_videos_161215_15_34_21.sig new file mode 100644 index 0000000..f6ffcc4 --- /dev/null +++ b/Python/test/data/sample_pointing_videos_161215_15_34_21.sig @@ -0,0 +1,505 @@ +<% Generating signature for /Users/jonc/projects/OpenSourceBrain/Data/sample_pointing_videos_161215_15_34_21.nwb %> + +** No datasets hard links. +** No groups hard links. +** 13 datasets soft links: + 1. 'to: "/general/optophysiology/Zstack0027/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0027/description' + 2. 'to: "/general/optophysiology/Zstack0029/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/description' + 3. 'to: "/general/optophysiology/Zstack0030/description" 1 datasets: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0030/description' + 4. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_001/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_001_Green/pixel_time_offsets + /acquisition/timeseries/ROI_001_Red/pixel_time_offsets' + 5. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_002/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_002_Green/pixel_time_offsets + /acquisition/timeseries/ROI_002_Red/pixel_time_offsets' + 6. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_003/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_003_Green/pixel_time_offsets + /acquisition/timeseries/ROI_003_Red/pixel_time_offsets' + 7. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_004/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_004_Green/pixel_time_offsets + /acquisition/timeseries/ROI_004_Red/pixel_time_offsets' + 8. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_005/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_005_Green/pixel_time_offsets + /acquisition/timeseries/ROI_005_Red/pixel_time_offsets' + 9. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_006/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_006_Green/pixel_time_offsets + /acquisition/timeseries/ROI_006_Red/pixel_time_offsets' + 10. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_007/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_007_Green/pixel_time_offsets + /acquisition/timeseries/ROI_007_Red/pixel_time_offsets' + 11. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_008/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_008_Green/pixel_time_offsets + /acquisition/timeseries/ROI_008_Red/pixel_time_offsets' + 12. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_009/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_009_Green/pixel_time_offsets + /acquisition/timeseries/ROI_009_Red/pixel_time_offsets' + 13. 'to: "/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_010/pixel_time_offsets" 2 datasets: + /acquisition/timeseries/ROI_010_Green/pixel_time_offsets + /acquisition/timeseries/ROI_010_Red/pixel_time_offsets' +** 24 groups soft links: + 1. 'to: "/acquisition/timeseries/ROI_001_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_001_Green/timeseries (#=1-2)' + 2. 'to: "/acquisition/timeseries/ROI_001_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_001_Red/timeseries (#=1-2)' + 3. 'to: "/acquisition/timeseries/ROI_002_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_002_Green/timeseries (#=1-2)' + 4. 'to: "/acquisition/timeseries/ROI_002_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_002_Red/timeseries (#=1-2)' + 5. 'to: "/acquisition/timeseries/ROI_003_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_003_Green/timeseries (#=1-2)' + 6. 'to: "/acquisition/timeseries/ROI_003_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_003_Red/timeseries (#=1-2)' + 7. 'to: "/acquisition/timeseries/ROI_004_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_004_Green/timeseries (#=1-2)' + 8. 'to: "/acquisition/timeseries/ROI_004_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_004_Red/timeseries (#=1-2)' + 9. 'to: "/acquisition/timeseries/ROI_005_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_005_Green/timeseries (#=1-2)' + 10. 'to: "/acquisition/timeseries/ROI_005_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_005_Red/timeseries (#=1-2)' + 11. 'to: "/acquisition/timeseries/ROI_006_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_006_Green/timeseries (#=1-2)' + 12. 'to: "/acquisition/timeseries/ROI_006_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_006_Red/timeseries (#=1-2)' + 13. 'to: "/acquisition/timeseries/ROI_007_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_007_Green/timeseries (#=1-2)' + 14. 'to: "/acquisition/timeseries/ROI_007_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_007_Red/timeseries (#=1-2)' + 15. 'to: "/acquisition/timeseries/ROI_008_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_008_Green/timeseries (#=1-2)' + 16. 'to: "/acquisition/timeseries/ROI_008_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_008_Red/timeseries (#=1-2)' + 17. 'to: "/acquisition/timeseries/ROI_009_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_009_Green/timeseries (#=1-2)' + 18. 'to: "/acquisition/timeseries/ROI_009_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_009_Red/timeseries (#=1-2)' + 19. 'to: "/acquisition/timeseries/ROI_010_Green" 2 groups (1 combined): + /epochs/trial_#/ROI_010_Green/timeseries (#=1-2)' + 20. 'to: "/acquisition/timeseries/ROI_010_Red" 2 groups (1 combined): + /epochs/trial_#/ROI_010_Red/timeseries (#=1-2)' + 21. 'to: "/acquisition/timeseries/Zstack_Red_0027" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0027/reference_images/Zstack_image' + 22. 'to: "/acquisition/timeseries/Zstack_Red_0029" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0029/reference_images/Zstack_image' + 23. 'to: "/acquisition/timeseries/Zstack_Red_0030" 1 groups: + /processing/Acquired_ROIs/ImageSegmentation/Zstack0030/reference_images/Zstack_image' + 24. 'to: "/acquisition/timeseries/speed_data" 2 groups (1 combined): + /epochs/trial_#/speed_data/timeseries (#=1-2)' +** No ext_links. +** No unknown node types. -- Good +** 3 empty groups (no members or attributes): + 1. /acquisition/images + 2. /analysis + 3. /stimulus/templates +** 527 attributes (sorted alphabetically) (151 combined): + 1. '/acquisition/timeseries/EyeCam ancestry: dtype=|S11, shape=(2,) size (22) val='["TimeSeries","ImageSeries"]'' + 2. '/acquisition/timeseries/EyeCam comments: dtype=|S17, shape=() size (17) val='"Frame rate 1/30 s"'' + 3. '/acquisition/timeseries/EyeCam description: dtype=|S35, shape=() size (35) val='"Video recording of mouse behaviour."'' + 4. '/acquisition/timeseries/EyeCam help: dtype=|S45, shape=() size (45) val='"Storage object for time-series 2-D image data"'' + 5. '/acquisition/timeseries/EyeCam neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 6. '/acquisition/timeseries/EyeCam source: dtype=|S23, shape=() size (23) val='"/general/devices/EyeCam"'' + 7. '/acquisition/timeseries/EyeCam/external_file starting_frame: dtype=int64, shape=(1,) size (8) val='[0]'' + 8. '/acquisition/timeseries/EyeCam/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 9. '/acquisition/timeseries/EyeCam/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 10. '/acquisition/timeseries/ROI_#_Green ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-10)' + 11. '/acquisition/timeseries/ROI_#_Green comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-10)' + 12. '/acquisition/timeseries/ROI_001_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzxqv'' + 13. '/acquisition/timeseries/ROI_#_Green help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-10)' + 14. '/acquisition/timeseries/ROI_#_Green neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-10)' + 15. '/acquisition/timeseries/ROI_#_Green source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-10)' + 16. '/acquisition/timeseries/ROI_#_Green/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 17. '/acquisition/timeseries/ROI_#_Green/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-10)' + 18. '/acquisition/timeseries/ROI_#_Green/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-10)' + 19. '/acquisition/timeseries/ROI_#_Green/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-10)' + 20. '/acquisition/timeseries/ROI_#_Green/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 21. '/acquisition/timeseries/ROI_#_Green/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-10)' + 22. '/acquisition/timeseries/ROI_#_Green/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-10)' + 23. '/acquisition/timeseries/ROI_#_Red ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=1-10)' + 24. '/acquisition/timeseries/ROI_#_Red comments: dtype=|S146, shape=() size (146) val='"The AOL microscope can acquire just the ...cNUmzZ' (#=1-10)' + 25. '/acquisition/timeseries/ROI_001_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytyqV'' + 26. '/acquisition/timeseries/ROI_#_Red help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=1-10)' + 27. '/acquisition/timeseries/ROI_#_Red neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=1-10)' + 28. '/acquisition/timeseries/ROI_#_Red source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=1-10)' + 29. '/acquisition/timeseries/ROI_#_Red/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 30. '/acquisition/timeseries/ROI_#_Red/data conversion: dtype=float64, shape=() size (8) val='1' (#=1-10)' + 31. '/acquisition/timeseries/ROI_#_Red/data resolution: dtype=float64, shape=() size (8) val='nan' (#=1-10)' + 32. '/acquisition/timeseries/ROI_#_Red/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=1-10)' + 33. '/acquisition/timeseries/ROI_#_Red/roi_name neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-10)' + 34. '/acquisition/timeseries/ROI_#_Red/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=1-10)' + 35. '/acquisition/timeseries/ROI_#_Red/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=1-10)' + 36. '/acquisition/timeseries/ROI_002_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCAtPc'' + 37. '/acquisition/timeseries/ROI_002_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyuuPC'' + 38. '/acquisition/timeseries/ROI_003_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCBqnJ'' + 39. '/acquisition/timeseries/ROI_003_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyvroj'' + 40. '/acquisition/timeseries/ROI_004_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCCmMq'' + 41. '/acquisition/timeseries/ROI_004_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gywnMQ'' + 42. '/acquisition/timeseries/ROI_005_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCDjkX'' + 43. '/acquisition/timeseries/ROI_005_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyxklx'' + 44. '/acquisition/timeseries/ROI_006_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCEfJE'' + 45. '/acquisition/timeseries/ROI_006_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyygKe'' + 46. '/acquisition/timeseries/ROI_007_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFcil'' + 47. '/acquisition/timeseries/ROI_007_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzdiL'' + 48. '/acquisition/timeseries/ROI_008_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCFYGS'' + 49. '/acquisition/timeseries/ROI_008_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyzZHs'' + 50. '/acquisition/timeseries/ROI_009_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCGVfz'' + 51. '/acquisition/timeseries/ROI_009_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gyAWfZ'' + 52. '/acquisition/timeseries/ROI_010_Green description: dtype=|S61, shape=() size (61) val='"Fluorescence data acquired from the gree...iCzVCL'' + 53. '/acquisition/timeseries/ROI_010_Red description: dtype=|S59, shape=() size (59) val='"Fluorescence data acquired from the red ...gytWDl'' + 54. '/acquisition/timeseries/WhiskersCam ancestry: dtype=|S11, shape=(2,) size (22) val='["TimeSeries","ImageSeries"]'' + 55. '/acquisition/timeseries/WhiskersCam comments: dtype=|S18, shape=() size (18) val='"Frame rate 1/300 s"'' + 56. '/acquisition/timeseries/WhiskersCam description: dtype=|S35, shape=() size (35) val='"Video recording of mouse behaviour."'' + 57. '/acquisition/timeseries/WhiskersCam help: dtype=|S45, shape=() size (45) val='"Storage object for time-series 2-D image data"'' + 58. '/acquisition/timeseries/WhiskersCam neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 59. '/acquisition/timeseries/WhiskersCam source: dtype=|S28, shape=() size (28) val='"/general/devices/WhiskersCam"'' + 60. '/acquisition/timeseries/WhiskersCam/external_file starting_frame: dtype=int64, shape=(1,) size (8) val='[0]'' + 61. '/acquisition/timeseries/WhiskersCam/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 62. '/acquisition/timeseries/WhiskersCam/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 63. '/acquisition/timeseries/Zstack_Green_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=27,29-30)' + 64. '/acquisition/timeseries/Zstack_Green_# comments: dtype=|S40, shape=() size (40) val='"Contains single slice from green channel"' (#=27,29-30)' + 65. '/acquisition/timeseries/Zstack_Green_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=27,29-30)' + 66. '/acquisition/timeseries/Zstack_Green_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=27,29-30)' + 67. '/acquisition/timeseries/Zstack_Green_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=27,29-30)' + 68. '/acquisition/timeseries/Zstack_Green_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=27,29-30)' + 69. '/acquisition/timeseries/Zstack_Green_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=27,29-30)' + 70. '/acquisition/timeseries/Zstack_Green_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=27,29-30)' + 71. '/acquisition/timeseries/Zstack_Green_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=27,29-30)' + 72. '/acquisition/timeseries/Zstack_Green_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=27,29-30)' + 73. '/acquisition/timeseries/Zstack_Green_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=27,29-30)' + 74. '/acquisition/timeseries/Zstack_Green_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=27,29-30)' + 75. '/acquisition/timeseries/Zstack_Red_# ancestry: dtype=|S15, shape=(3,) size (45) val='["TimeSeries","ImageSeries","TwoPhotonSeries"]' (#=27,29-30)' + 76. '/acquisition/timeseries/Zstack_Red_# comments: dtype=|S38, shape=() size (38) val='"Contains single slice from red channel"' (#=27,29-30)' + 77. '/acquisition/timeseries/Zstack_Red_# description: dtype=|S31, shape=() size (31) val='"Initial reference Z stack plane"' (#=27,29-30)' + 78. '/acquisition/timeseries/Zstack_Red_# help: dtype=|S45, shape=() size (45) val='"Image stack recorded from 2-photon microscope"' (#=27,29-30)' + 79. '/acquisition/timeseries/Zstack_Red_# neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"' (#=27,29-30)' + 80. '/acquisition/timeseries/Zstack_Red_# source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"' (#=27,29-30)' + 81. '/acquisition/timeseries/Zstack_Red_#/channel neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=27,29-30)' + 82. '/acquisition/timeseries/Zstack_Red_#/data conversion: dtype=float64, shape=() size (8) val='1' (#=27,29-30)' + 83. '/acquisition/timeseries/Zstack_Red_#/data resolution: dtype=float64, shape=() size (8) val='nan' (#=27,29-30)' + 84. '/acquisition/timeseries/Zstack_Red_#/data unit: dtype=|S9, shape=() size (9) val='"intensity"' (#=27,29-30)' + 85. '/acquisition/timeseries/Zstack_Red_#/timestamps interval: dtype=int32, shape=() size (4) val='1' (#=27,29-30)' + 86. '/acquisition/timeseries/Zstack_Red_#/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"' (#=27,29-30)' + 87. '/acquisition/timeseries/speed_data ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 88. '/acquisition/timeseries/speed_data comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' + 89. '/acquisition/timeseries/speed_data description: dtype=|S21, shape=() size (21) val='"Raw mouse speed data."'' + 90. '/acquisition/timeseries/speed_data help: dtype=|S26, shape=() size (26) val='"General time series object"'' + 91. '/acquisition/timeseries/speed_data neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' + 92. '/acquisition/timeseries/speed_data source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' + 93. '/acquisition/timeseries/speed_data/data conversion: dtype=float64, shape=() size (8) val='0.8333'' + 94. '/acquisition/timeseries/speed_data/data resolution: dtype=float64, shape=() size (8) val='0.0008333'' + 95. '/acquisition/timeseries/speed_data/data unit: dtype=|S4, shape=() size (4) val='"cm/s"'' + 96. '/acquisition/timeseries/speed_data/timestamps interval: dtype=int32, shape=() size (4) val='1'' + 97. '/acquisition/timeseries/speed_data/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' + 98. '/acquisition/timeseries/trial_times ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' + 99. '/acquisition/timeseries/trial_times comments: dtype=|S58, shape=() size (58) val='"Speed is in rpm, with conversion factor ...eBaxIy'' +100. '/acquisition/timeseries/trial_times description: dtype=|S37, shape=() size (37) val='"Per-trial times for mouse speed data."'' +101. '/acquisition/timeseries/trial_times help: dtype=|S26, shape=() size (26) val='"General time series object"'' +102. '/acquisition/timeseries/trial_times neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +103. '/acquisition/timeseries/trial_times source: dtype=|S35, shape=() size (35) val='"/general/devices/mouse_wheel_device"'' +104. '/acquisition/timeseries/trial_times/data conversion: dtype=float64, shape=() size (8) val='1000000'' +105. '/acquisition/timeseries/trial_times/data resolution: dtype=float64, shape=() size (8) val='1e-06'' +106. '/acquisition/timeseries/trial_times/data unit: dtype=|S6, shape=() size (6) val='"second"'' +107. '/acquisition/timeseries/trial_times/timestamps interval: dtype=int32, shape=() size (4) val='1'' +108. '/acquisition/timeseries/trial_times/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +109. '/epochs tags: dtype=|S1, shape=(0,) size (0) val='[]'' +110. '/epochs/trial_# links: dtype=|S58, shape=(21,) size (1218) val='["'ROI_001_Green' is '/acquisition/timese...bDhpwS' (#=1-2)' +111. '/epochs/trial_# neurodata_type: dtype=|S5, shape=() size (5) val='"Epoch"' (#=1-2)' +112. '/general/labview_header schema_id: dtype=|S22, shape=() size (22) val='"labview:labview_header"'' +113. '/general/optophysiology/Zstack#/manifold conversion: dtype=float64, shape=() size (8) val='1000000' (#=1-49)' +114. '/general/optophysiology/Zstack#/manifold unit: dtype=|S5, shape=() size (5) val='"metre"' (#=1-49)' +115. '/general/optophysiology/cycle_time neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +116. '/general/optophysiology/frame_size neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +117. '/general/optophysiology/imaging_mode neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +118. '/general/optophysiology/zplane_pockels columns: dtype=|S11, shape=(4,) size (44) val='["z","z_norm","laser_power","z_motor"]'' +119. '/general/optophysiology/zplane_pockels neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +120. '/general/specifications/e-labview.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +121. '/general/specifications/e-labview.py namespaces: dtype=|S7, shape=(1,) size (7) val='["labview"]'' +122. '/general/specifications/e-pixeltimes.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +123. '/general/specifications/e-pixeltimes.py namespaces: dtype=|S10, shape=(1,) size (10) val='["pixeltimes"]'' +124. '/general/specifications/nwb_core.py help: dtype=|S38, shape=() size (38) val='"Contents of format specification file."'' +125. '/general/specifications/nwb_core.py namespaces: dtype=|S4, shape=(1,) size (4) val='["core"]'' +126. '/processing/Acquired_ROIs description: dtype=|S85, shape=() size (85) val='"ROI locations and acquired fluorescence ...dciJBi'' +127. '/processing/Acquired_ROIs interfaces: dtype=|S17, shape=(1,) size (17) val='["ImageSegmentation"]'' +128. '/processing/Acquired_ROIs neurodata_type: dtype=|S6, shape=() size (6) val='"Module"'' +129. '/processing/Acquired_ROIs/ImageSegmentation help: dtype=|S87, shape=() size (87) val='"Stores groups of pixels that define regi...gWLuoY'' +130. '/processing/Acquired_ROIs/ImageSegmentation neurodata_type: dtype=|S9, shape=() size (9) val='"Interface"'' +131. '/processing/Acquired_ROIs/ImageSegmentation source: dtype=|S31, shape=() size (31) val='"/general/devices/AOL_microscope"'' +132. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=1-2)' +133. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=1-2)' +134. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=3-7)' +135. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=3-7)' +136. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_#/dimension neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"' (#=8-10)' +137. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0030/ROI_#/pixel_time_offsets schema_id: dtype=|S29, shape=() size (29) val='"pixeltimes:pixel_time_offsets"' (#=8-10)' +138. '/processing/Acquired_ROIs/roi_spec columns: dtype=|S15, shape=(17,) size (255) val='["ROI index","ROI ID","ROI Time (ns)","Pi...eGJCLZ'' +139. '/processing/Acquired_ROIs/roi_spec neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +140. '/silverlab_api_version neurodata_type: dtype=|S6, shape=() size (6) val='"Custom"'' +141. '/stimulus/presentation/air_puff ancestry: dtype=|S10, shape=(1,) size (10) val='["TimeSeries"]'' +142. '/stimulus/presentation/air_puff comments: dtype=|S50, shape=() size (50) val='"Delivered 'instantaneously' at the speci...jVqzsG'' +143. '/stimulus/presentation/air_puff description: dtype=|S17, shape=() size (17) val='"Air puff stimulus"'' +144. '/stimulus/presentation/air_puff help: dtype=|S26, shape=() size (26) val='"General time series object"'' +145. '/stimulus/presentation/air_puff neurodata_type: dtype=|S10, shape=() size (10) val='"TimeSeries"'' +146. '/stimulus/presentation/air_puff source: dtype=|S15, shape=() size (15) val='"air_puff_device"'' +147. '/stimulus/presentation/air_puff/data conversion: dtype=float64, shape=() size (8) val='nan'' +148. '/stimulus/presentation/air_puff/data resolution: dtype=float64, shape=() size (8) val='nan'' +149. '/stimulus/presentation/air_puff/data unit: dtype=|S3, shape=() size (3) val='"n/a"'' +150. '/stimulus/presentation/air_puff/timestamps interval: dtype=int32, shape=() size (4) val='1'' +151. '/stimulus/presentation/air_puff/timestamps unit: dtype=|S7, shape=() size (7) val='"Seconds"'' +** 1110 datasets (sorted alphabetically) (253 combined): + 1. '/acquisition/timeseries/EyeCam/bits_per_pixel: dtype=int32, shape=() size (4) val='8'' + 2. '/acquisition/timeseries/EyeCam/dimension: dtype=int32, shape=(2,) size (16), compress=gzip val='[300,226]'' + 3. '/acquisition/timeseries/EyeCam/external_file: dtype=|S58, shape=(1,) size (64), compress=gzip val='["sample_pointing_videos_161215_15_34_21 ...eBOBUt'' + 4. '/acquisition/timeseries/EyeCam/format: dtype=|S8, shape=() size (8) val='"external"'' + 5. '/acquisition/timeseries/EyeCam/num_samples: dtype=int32, shape=() size (4) val='630'' + 6. '/acquisition/timeseries/EyeCam/timestamps: dtype=float64, shape=(630,) size (1668), compress=gzip val='[0,0.08,0.16,0.24,0.32,0.4,0.48,0.56,0.64...egWzRG'' + 7. '/acquisition/timeseries/ROI_#_Green/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-10)' + 8. '/acquisition/timeseries/ROI_#_Green/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=1-10)' + 9. '/acquisition/timeseries/ROI_001_Green/data: dtype=float32, shape=(17544, 1, 1) size (19969), compress=gzip val='[[[112]],[[113]],[[110]],[[159]],[[120]],...bQXTHJ'' + 10. '/acquisition/timeseries/ROI_#_Green/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-10)' + 11. '/acquisition/timeseries/ROI_#_Green/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-10)' + 12. '/acquisition/timeseries/ROI_#_Green/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-10)' + 13. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0027"' (#=1-2)' + 14. '/acquisition/timeseries/ROI_#_Green/num_samples: dtype=int32, shape=() size (4) val='17544' (#=1-10)' + 15. '/acquisition/timeseries/ROI_#_Green/pmt_gain: dtype=float32, shape=() size (4) val='715' (#=1-10)' + 16. '/acquisition/timeseries/ROI_#_Green/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-10)' + 17. '/acquisition/timeseries/ROI_#_Green/scan_line_rate: dtype=float32, shape=() size (4) val='348.7' (#=1-10)' + 18. '/acquisition/timeseries/ROI_#_Green/timestamps: dtype=float64, shape=(17544,) size (119075), compress=gzip val='[0,0.002867,0.005735,0.008602,0.01147,0.0...lRgWP' (#=1-10)' + 19. '/acquisition/timeseries/ROI_#_Red/bits_per_pixel: dtype=int32, shape=() size (4) val='64' (#=1-10)' + 20. '/acquisition/timeseries/ROI_#_Red/channel: dtype=|S3, shape=() size (3) val='"Red"' (#=1-10)' + 21. '/acquisition/timeseries/ROI_001_Red/data: dtype=float32, shape=(17544, 1, 1) size (13212), compress=gzip val='[[[111]],[[112]],[[109]],[[113]],[[110]],...jzbMJV'' + 22. '/acquisition/timeseries/ROI_#_Red/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-10)' + 23. '/acquisition/timeseries/ROI_#_Red/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[4.883e-07,4.883e-07]' (#=1-10)' + 24. '/acquisition/timeseries/ROI_#_Red/format: dtype=|S3, shape=() size (3) val='"raw"' (#=1-10)' + 25. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0027"' (#=1-2)' + 26. '/acquisition/timeseries/ROI_#_Red/num_samples: dtype=int32, shape=() size (4) val='17544' (#=1-10)' + 27. '/acquisition/timeseries/ROI_#_Red/pmt_gain: dtype=float32, shape=() size (4) val='505' (#=1-10)' + 28. '/acquisition/timeseries/ROI_#_Red/roi_name: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-10)' + 29. '/acquisition/timeseries/ROI_#_Red/scan_line_rate: dtype=float32, shape=() size (4) val='348.7' (#=1-10)' + 30. '/acquisition/timeseries/ROI_#_Red/timestamps: dtype=float64, shape=(17544,) size (119075), compress=gzip val='[0,0.002867,0.005735,0.008602,0.01147,0.0...lRgWP' (#=1-10)' + 31. '/acquisition/timeseries/ROI_002_Green/data: dtype=float32, shape=(17544, 1, 1) size (19777), compress=gzip val='[[[139]],[[117]],[[118]],[[128]],[[113]],...izEgYa'' + 32. '/acquisition/timeseries/ROI_002_Red/data: dtype=float32, shape=(17544, 1, 1) size (13183), compress=gzip val='[[[112]],[[107]],[[108]],[[111]],[[112]],...kFMfAD'' + 33. '/acquisition/timeseries/ROI_003_Green/data: dtype=float32, shape=(17544, 1, 1) size (29724), compress=gzip val='[[[165]],[[154]],[[202]],[[170]],[[205]],...gtNfNf'' + 34. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0029"' (#=3-7)' + 35. '/acquisition/timeseries/ROI_003_Red/data: dtype=float32, shape=(17544, 1, 1) size (13268), compress=gzip val='[[[113]],[[113]],[[110]],[[112]],[[114]],...eSCmqk'' + 36. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0029"' (#=3-7)' + 37. '/acquisition/timeseries/ROI_004_Green/data: dtype=float32, shape=(17544, 1, 1) size (28550), compress=gzip val='[[[115]],[[153]],[[194]],[[142]],[[156]],...fwFKNC'' + 38. '/acquisition/timeseries/ROI_004_Red/data: dtype=float32, shape=(17544, 1, 1) size (13262), compress=gzip val='[[[109]],[[110]],[[110]],[[110]],[[111]],...NYcNy'' + 39. '/acquisition/timeseries/ROI_005_Green/data: dtype=float32, shape=(17544, 1, 1) size (30202), compress=gzip val='[[[178]],[[120]],[[157]],[[165]],[[191]],...crBtVu'' + 40. '/acquisition/timeseries/ROI_005_Red/data: dtype=float32, shape=(17544, 1, 1) size (13201), compress=gzip val='[[[111]],[[112]],[[108]],[[114]],[[111]],...bQLkLK'' + 41. '/acquisition/timeseries/ROI_006_Green/data: dtype=float32, shape=(17544, 1, 1) size (30088), compress=gzip val='[[[191]],[[212]],[[190]],[[197]],[[191]],...glSadN'' + 42. '/acquisition/timeseries/ROI_006_Red/data: dtype=float32, shape=(17544, 1, 1) size (13262), compress=gzip val='[[[110]],[[114]],[[105]],[[110]],[[108]],...jSAGnm'' + 43. '/acquisition/timeseries/ROI_007_Green/data: dtype=float32, shape=(17544, 1, 1) size (29108), compress=gzip val='[[[138]],[[147]],[[159]],[[144]],[[122]],...cPBaGM'' + 44. '/acquisition/timeseries/ROI_007_Red/data: dtype=float32, shape=(17544, 1, 1) size (13310), compress=gzip val='[[[117]],[[115]],[[113]],[[110]],[[108]],...izHSMM'' + 45. '/acquisition/timeseries/ROI_008_Green/data: dtype=float32, shape=(17544, 1, 1) size (27548), compress=gzip val='[[[150]],[[128]],[[163]],[[141]],[[175]],...cvwluM'' + 46. '/acquisition/timeseries/ROI_#_Green/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0030"' (#=8-10)' + 47. '/acquisition/timeseries/ROI_008_Red/data: dtype=float32, shape=(17544, 1, 1) size (13326), compress=gzip val='[[[109]],[[115]],[[110]],[[111]],[[109]],...jrdDOY'' + 48. '/acquisition/timeseries/ROI_#_Red/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack0030"' (#=8-10)' + 49. '/acquisition/timeseries/ROI_009_Green/data: dtype=float32, shape=(17544, 1, 1) size (27379), compress=gzip val='[[[127]],[[123]],[[127]],[[163]],[[165]],...cygYpN'' + 50. '/acquisition/timeseries/ROI_009_Red/data: dtype=float32, shape=(17544, 1, 1) size (13224), compress=gzip val='[[[111]],[[113]],[[112]],[[110]],[[112]],...fwmaxu'' + 51. '/acquisition/timeseries/ROI_010_Green/data: dtype=float32, shape=(17544, 1, 1) size (28212), compress=gzip val='[[[144]],[[118]],[[141]],[[138]],[[165]],...gSffGs'' + 52. '/acquisition/timeseries/ROI_010_Red/data: dtype=float32, shape=(17544, 1, 1) size (13254), compress=gzip val='[[[110]],[[111]],[[112]],[[112]],[[108]],...lQAhQ'' + 53. '/acquisition/timeseries/WhiskersCam/bits_per_pixel: dtype=int32, shape=() size (4) val='8'' + 54. '/acquisition/timeseries/WhiskersCam/dimension: dtype=int32, shape=(2,) size (16), compress=gzip val='[300,226]'' + 55. '/acquisition/timeseries/WhiskersCam/external_file: dtype=|S63, shape=(1,) size (69), compress=gzip val='["sample_pointing_videos_161215_15_34_21 ...juaOJS'' + 56. '/acquisition/timeseries/WhiskersCam/format: dtype=|S8, shape=() size (8) val='"external"'' + 57. '/acquisition/timeseries/WhiskersCam/num_samples: dtype=int32, shape=() size (4) val='7550'' + 58. '/acquisition/timeseries/WhiskersCam/timestamps: dtype=float64, shape=(7550,) size (22646), compress=gzip val='[0,0.006,0.013,0.02,0.026,0.033,0.04,0.04...hOPrrM'' + 59. '/acquisition/timeseries/Zstack_Green_#/bits_per_pixel: dtype=int32, shape=() size (4) val='16' (#=27,29-30)' + 60. '/acquisition/timeseries/Zstack_Green_#/channel: dtype=|S5, shape=() size (5) val='"Green"' (#=27,29-30)' + 61. '/acquisition/timeseries/Zstack_Green_0027/data: dtype=uint16, shape=(512, 512) size (257406), compress=gzip val='[[120,112,156,111,108,118,111,116,114,119...bPkWwE'' + 62. '/acquisition/timeseries/Zstack_Green_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]' (#=27,29-30)' + 63. '/acquisition/timeseries/Zstack_Green_#/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[0.00025,0.00025]' (#=27,29-30)' + 64. '/acquisition/timeseries/Zstack_Green_#/format: dtype=|S4, shape=() size (4) val='"tiff"' (#=27,29-30)' + 65. '/acquisition/timeseries/Zstack_Green_#/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack#"' (#=27,29-30)' + 66. '/acquisition/timeseries/Zstack_Green_#/num_samples: dtype=int32, shape=() size (4) val='1' (#=27,29-30)' + 67. '/acquisition/timeseries/Zstack_Green_#/pmt_gain: dtype=float32, shape=() size (4) val='715' (#=27,29-30)' + 68. '/acquisition/timeseries/Zstack_Green_#/scan_line_rate: dtype=float32, shape=() size (4) val='348.7' (#=27,29-30)' + 69. '/acquisition/timeseries/Zstack_Green_#/timestamps: dtype=float64, shape=(1,) size (11), compress=gzip val='[0]' (#=27,29-30)' + 70. '/acquisition/timeseries/Zstack_Green_0029/data: dtype=uint16, shape=(512, 512) size (260018), compress=gzip val='[[165,132,118,112,155,162,117,123,135,134...NMccT'' + 71. '/acquisition/timeseries/Zstack_Green_0030/data: dtype=uint16, shape=(512, 512) size (258562), compress=gzip val='[[160,116,114,113,130,110,107,117,113,152...bUnapG'' + 72. '/acquisition/timeseries/Zstack_Red_#/bits_per_pixel: dtype=int32, shape=() size (4) val='16' (#=27,29-30)' + 73. '/acquisition/timeseries/Zstack_Red_#/channel: dtype=|S3, shape=() size (3) val='"Red"' (#=27,29-30)' + 74. '/acquisition/timeseries/Zstack_Red_0027/data: dtype=uint16, shape=(512, 512) size (178897), compress=gzip val='[[118,110,117,119,111,112,110,116,115,110...idJksK'' + 75. '/acquisition/timeseries/Zstack_Red_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]' (#=27,29-30)' + 76. '/acquisition/timeseries/Zstack_Red_#/field_of_view: dtype=float32, shape=(2,) size (14), compress=gzip val='[0.00025,0.00025]' (#=27,29-30)' + 77. '/acquisition/timeseries/Zstack_Red_#/format: dtype=|S4, shape=() size (4) val='"tiff"' (#=27,29-30)' + 78. '/acquisition/timeseries/Zstack_Red_#/imaging_plane: dtype=|S10, shape=() size (10) val='"Zstack#"' (#=27,29-30)' + 79. '/acquisition/timeseries/Zstack_Red_#/num_samples: dtype=int32, shape=() size (4) val='1' (#=27,29-30)' + 80. '/acquisition/timeseries/Zstack_Red_#/pmt_gain: dtype=float32, shape=() size (4) val='505' (#=27,29-30)' + 81. '/acquisition/timeseries/Zstack_Red_#/scan_line_rate: dtype=float32, shape=() size (4) val='348.7' (#=27,29-30)' + 82. '/acquisition/timeseries/Zstack_Red_#/timestamps: dtype=float64, shape=(1,) size (11), compress=gzip val='[0]' (#=27,29-30)' + 83. '/acquisition/timeseries/Zstack_Red_0029/data: dtype=uint16, shape=(512, 512) size (181102), compress=gzip val='[[116,112,114,113,110,117,113,116,112,111...hnBKMu'' + 84. '/acquisition/timeseries/Zstack_Red_0030/data: dtype=uint16, shape=(512, 512) size (181620), compress=gzip val='[[111,116,111,113,113,107,113,111,108,105...jKUxSe'' + 85. '/acquisition/timeseries/speed_data/data: dtype=float32, shape=(23448,) size (6578), compress=gzip val='[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,...hrTeCd'' + 86. '/acquisition/timeseries/speed_data/num_samples: dtype=int32, shape=() size (4) val='23448'' + 87. '/acquisition/timeseries/speed_data/timestamps: dtype=float64, shape=(23448,) size (155183), compress=gzip val='[0.002107,0.004252,0.006397,0.008541,0.01...csbqku'' + 88. '/acquisition/timeseries/trial_times/data: dtype=int32, shape=(23448,) size (79535), compress=gzip val='[2107,4252,6397,8541,10685,12832,14976,17...cMpki'' + 89. '/acquisition/timeseries/trial_times/num_samples: dtype=int32, shape=() size (4) val='23448'' + 90. '/acquisition/timeseries/trial_times/timestamps: dtype=float64, shape=(23448,) size (155183), compress=gzip val='[0.002107,0.004252,0.006397,0.008541,0.01...csbqku'' + 91. '/epochs/trial_0001/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-10)' + 92. '/epochs/trial_0001/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='0' (#=1-10)' + 93. '/epochs/trial_0001/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-10)' + 94. '/epochs/trial_0001/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='0' (#=1-10)' + 95. '/epochs/trial_0001/speed_data/count: dtype=int32, shape=() size (4) val='11721'' + 96. '/epochs/trial_0001/speed_data/idx_start: dtype=int32, shape=() size (4) val='0'' + 97. '/epochs/trial_0001/start_time: dtype=float64, shape=() size (8) val='0'' + 98. '/epochs/trial_0001/stop_time: dtype=float64, shape=() size (8) val='25.16'' + 99. '/epochs/trial_0002/ROI_#_Green/count: dtype=int32, shape=() size (4) val='8772' (#=1-10)' +100. '/epochs/trial_0002/ROI_#_Green/idx_start: dtype=int32, shape=() size (4) val='8772' (#=1-10)' +101. '/epochs/trial_0002/ROI_#_Red/count: dtype=int32, shape=() size (4) val='8772' (#=1-10)' +102. '/epochs/trial_0002/ROI_#_Red/idx_start: dtype=int32, shape=() size (4) val='8772' (#=1-10)' +103. '/epochs/trial_0002/speed_data/count: dtype=int32, shape=() size (4) val='11722'' +104. '/epochs/trial_0002/speed_data/idx_start: dtype=int32, shape=() size (4) val='11725'' +105. '/epochs/trial_0002/start_time: dtype=float64, shape=() size (8) val='25.17'' +106. '/epochs/trial_0002/stop_time: dtype=float64, shape=() size (8) val='50.33'' +107. '/file_create_date: dtype=--, shape=(1,) size (--), compress=gzip val='"--value removed for NWB signature--"'' +108. '/general/data_collection: dtype=|S80, shape=() size (80) val='"Text notes about data collection and ana...gWoCry'' +109. '/general/devices/AOL_microscope: dtype=|S57, shape=() size (57) val='"Random access 3d acousto-optic lens two-...ekQKnw'' +110. '/general/devices/EyeCam: dtype=|S40, shape=() size (40) val='"30Hz video camera viewing the mouse face"'' +111. '/general/devices/WhiskersCam: dtype=|S47, shape=() size (47) val='"300Hz video camera viewing the mouse's whiskers"'' +112. '/general/devices/air_puff_device: dtype=|S53, shape=() size (53) val='"Delivers an air puff stimulus to the mou...NXTbu'' +113. '/general/devices/mouse_wheel_device: dtype=|S24, shape=() size (24) val='"Records mouse speed data"'' +114. '/general/experiment_description: dtype=|S84, shape=() size (84) val='"A general description of the experiment ...LbatF'' +115. '/general/experimenter: dtype=|S8, shape=() size (8) val='"Hana Ros"'' +116. '/general/institution: dtype=|S25, shape=() size (25) val='"University College London"'' +117. '/general/lab: dtype=|S33, shape=() size (33) val='"Silver Lab (http://silverlab.org)"'' +118. '/general/labview_header: dtype=|S37, shape=(31, 3) size (641), compress=gzip val='[["LOGIN","User",""Hana""],["LOGIN","Prof...kgtRrn'' +119. '/general/notes: dtype=|S62, shape=() size (62) val='"Notes about the experiment that don't fi...jyjZeD'' +120. '/general/optophysiology/Zstack#/description: dtype=|S17, shape=() size (17) val='"Reference Z stack"' (#=1-49)' +121. '/general/optophysiology/Zstack#/device: dtype=|S14, shape=() size (14) val='"AOL_microscope"' (#=1-49)' +122. '/general/optophysiology/Zstack#/excitation_lambda: dtype=|S22, shape=() size (22) val='"Excitation wavelength."' (#=1-49)' +123. '/general/optophysiology/Zstack#/green/description: dtype=|S48, shape=() size (48) val='"Green channel, typically used for active...hSPyys' (#=1-49)' +124. '/general/optophysiology/Zstack#/green/emission_lambda: dtype=|S38, shape=() size (38) val='"Emission wavelength for green channel."' (#=1-49)' +125. '/general/optophysiology/Zstack#/imaging_rate: dtype=|S72, shape=() size (72) val='"348.7419135468796867Hz (cycle time = 286...gfdcho' (#=1-49)' +126. '/general/optophysiology/Zstack#/indicator: dtype=|S18, shape=() size (18) val='"Calcium indicator."' (#=1-49)' +127. '/general/optophysiology/Zstack#/location: dtype=|S94, shape=() size (94) val='"Anatomy gross description of imaging loc...fuLdPY' (#=1-49)' +128. '/general/optophysiology/Zstack0001/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-120],[0.4892,0,-120],[0.9785,0,-1...Wllpt'' +129. '/general/optophysiology/Zstack#/red/description: dtype=|S42, shape=() size (42) val='"Red channel, typically used for reference."' (#=1-49)' +130. '/general/optophysiology/Zstack#/red/emission_lambda: dtype=|S36, shape=() size (36) val='"Emission wavelength for red channel."' (#=1-49)' +131. '/general/optophysiology/Zstack#/reference_frame: dtype=|S27, shape=() size (27) val='"TODO: In lab book (partly?)"' 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'/general/optophysiology/Zstack0007/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-90],[0.4892,0,-90],[0.9785,0,-90]...fUBVnR'' +138. '/general/optophysiology/Zstack0008/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-85],[0.4892,0,-85],[0.9785,0,-85]...cXRgGh'' +139. '/general/optophysiology/Zstack0009/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-80],[0.4892,0,-80],[0.9785,0,-80]...bgrYx'' +140. '/general/optophysiology/Zstack0010/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-75],[0.4892,0,-75],[0.9785,0,-75]...itKnnd'' +141. '/general/optophysiology/Zstack0011/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-70],[0.4892,0,-70],[0.9785,0,-70]...fwZyFt'' +142. '/general/optophysiology/Zstack0012/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-65],[0.4892,0,-65],[0.9785,0,-65]...cAoJXJ'' +143. '/general/optophysiology/Zstack0013/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-60],[0.4892,0,-60],[0.9785,0,-60]...dZOzXl'' +144. '/general/optophysiology/Zstack0014/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-55],[0.4892,0,-55],[0.9785,0,-55]...jvHGEh'' +145. '/general/optophysiology/Zstack0015/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-50],[0.4892,0,-50],[0.9785,0,-50]...dCmdoN'' +146. '/general/optophysiology/Zstack0016/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-45],[0.4892,0,-45],[0.9785,0,-45]...iYfjVJ'' +147. '/general/optophysiology/Zstack0017/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-40],[0.4892,0,-40],[0.9785,0,-40]...deJGGp'' +148. '/general/optophysiology/Zstack0018/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-35],[0.4892,0,-35],[0.9785,0,-35]...iACNnl'' +149. '/general/optophysiology/Zstack0019/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-30],[0.4892,0,-30],[0.9785,0,-30]...iCEjOJ'' +150. '/general/optophysiology/Zstack0020/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-25],[0.4892,0,-25],[0.9785,0,-25]...ifbNgl'' +151. '/general/optophysiology/Zstack0021/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-20],[0.4892,0,-20],[0.9785,0,-20]...hHzqxN'' +152. '/general/optophysiology/Zstack0022/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,-15],[0.4892,0,-15],[0.9785,0,-15]...qSOAl'' +153. '/general/optophysiology/Zstack0023/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-10],[0.4892,0,-10],[0.9785,0,-10]...kLcFfF'' +154. '/general/optophysiology/Zstack0024/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,-5],[0.4892,0,-5],[0.9785,0,-5],[1...dYDFaN'' +155. '/general/optophysiology/Zstack0025/manifold: dtype=float32, shape=(512, 512, 3) size (34372), compress=gzip val='[[[0,0,0],[0.4892,0,0],[0.9785,0,0],[1.46...iMZFkq'' +156. '/general/optophysiology/Zstack0026/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,5],[0.4892,0,5],[0.9785,0,5],[1.46...isYxvJ'' +157. '/general/optophysiology/Zstack0027/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,10],[0.4892,0,10],[0.9785,0,10],[1...dQjlQm'' +158. '/general/optophysiology/Zstack0028/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,15],[0.4892,0,15],[0.9785,0,15],[1...eLnGVh'' +159. '/general/optophysiology/Zstack0029/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,20],[0.4892,0,20],[0.9785,0,20],[1...MFyWt'' +160. '/general/optophysiology/Zstack0030/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,25],[0.4892,0,25],[0.9785,0,25],[1...bkhVER'' +161. '/general/optophysiology/Zstack0031/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,30],[0.4892,0,30],[0.9785,0,30],[1...bHKsnp'' +162. '/general/optophysiology/Zstack0032/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,35],[0.4892,0,35],[0.9785,0,35],[1...bFJtXS'' +163. '/general/optophysiology/Zstack0033/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,40],[0.4892,0,40],[0.9785,0,40],[1...hzeXnm'' +164. '/general/optophysiology/Zstack0034/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,45],[0.4892,0,45],[0.9785,0,45],[1...cdlQGq'' +165. '/general/optophysiology/Zstack0035/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,50],[0.4892,0,50],[0.9785,0,50],[1...hWHtVK'' +166. '/general/optophysiology/Zstack0036/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,55],[0.4892,0,55],[0.9785,0,55],[1...cANPcN'' +167. '/general/optophysiology/Zstack0037/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,60],[0.4892,0,60],[0.9785,0,60],[1...iujssh'' +168. '/general/optophysiology/Zstack0038/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,65],[0.4892,0,65],[0.9785,0,65],[1...gUJCsF'' +169. '/general/optophysiology/Zstack0039/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,70],[0.4892,0,70],[0.9785,0,70],[1...jRurap'' +170. '/general/optophysiology/Zstack0040/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,75],[0.4892,0,75],[0.9785,0,75],[1...byQvLJ'' +171. '/general/optophysiology/Zstack0041/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,80],[0.4892,0,80],[0.9785,0,80],[1...evBktt'' +172. '/general/optophysiology/Zstack0042/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,85],[0.4892,0,85],[0.9785,0,85],[1...hslZbd'' +173. '/general/optophysiology/Zstack0043/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,90],[0.4892,0,90],[0.9785,0,90],[1...koWNIN'' +174. '/general/optophysiology/Zstack0044/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,95],[0.4892,0,95],[0.9785,0,95],[1...bWsSuh'' +175. '/general/optophysiology/Zstack0045/manifold: dtype=float32, shape=(512, 512, 3) size (34564), compress=gzip val='[[[0,0,100],[0.4892,0,100],[0.9785,0,100]...eTdHbR'' +176. '/general/optophysiology/Zstack0046/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,105],[0.4892,0,105],[0.9785,0,105]...hPOvJB'' +177. '/general/optophysiology/Zstack0047/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,110],[0.4892,0,110],[0.9785,0,110]...kMzkrl'' +178. '/general/optophysiology/Zstack0048/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,115],[0.4892,0,115],[0.9785,0,115]...ctVpcF'' +179. '/general/optophysiology/Zstack0049/manifold: dtype=float32, shape=(512, 512, 3) size (34596), compress=gzip val='[[[0,0,120],[0.4892,0,120],[0.9785,0,120]...fqGdKp'' +180. '/general/optophysiology/cycle_time: dtype=float32, shape=() size (4) val='0.002867'' +181. '/general/optophysiology/frame_size: dtype=int32, shape=(2,) size (14), compress=gzip val='[512,512]'' +182. '/general/optophysiology/imaging_mode: dtype=|S8, shape=() size (8) val='"pointing"'' +183. '/general/optophysiology/zplane_pockels: dtype=float32, shape=(49, 4) size (579), compress=gzip val='[[-120,0.4994,100,-120],[-115,0.4797,100,...iUevau'' +184. '/general/pharmacology: dtype=|S152, shape=() size (152) val='"Description of drugs used, including how...goKGik'' +185. '/general/protocol: dtype=|S76, shape=() size (76) val='"Experimental protocol, if applicable, e....bWYeFo'' +186. '/general/related_publications: dtype=|S70, shape=() size (70) val='"Optional list of related publications, i...gGeOxQ'' +187. '/general/session_id: dtype=|S38, shape=() size (38) val='"sample_pointing_videos_161215_15_34_21"'' +188. '/general/slices: dtype=|S127, shape=() size (127) val='"Description of slices, including informa...bwDbqR'' +189. '/general/specifications/e-labview.py: dtype=|S1534, shape=() size (1534) val='"# NWB extension to store LabView header ...fvMAMg'' +190. '/general/specifications/e-pixeltimes.py: dtype=|S2701, shape=() size (2701) val='"# NWB extension to store per-pixel time ...gVgtZh'' +191. '/general/specifications/nwb_core.py: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +192. '/general/stimulus: dtype=|S84, shape=() size (84) val='"Notes about stimuli, such as how and whe...DShaM'' +193. '/general/subject/age: dtype=|S25, shape=() size (25) val='"Age of subject. Optional."'' +194. '/general/subject/description: dtype=|S88, shape=() size (88) val='"Description of subject and where subject...fXgfBt'' +195. '/general/subject/genotype: dtype=|S59, shape=() size (59) val='"Genetic strain. If absent, assume Wild T...eOaNbr'' +196. '/general/subject/sex: dtype=|S28, shape=() size (28) val='"Gender of subject. Optional."'' +197. '/general/subject/species: dtype=|S29, shape=() size (29) val='"Species of subject. Optional."'' +198. '/general/subject/subject_id: dtype=|S80, shape=() size (80) val='"ID of animal/person used/participating i...hoSoPZ'' +199. '/general/subject/weight: dtype=|S88, shape=() size (88) val='"Weight at time of experiment, at time of...grFgyL'' +200. '/general/surgery: dtype=|S134, shape=() size (134) val='"Narrative description about surgery/surg...dKKeYq'' +201. '/general/virus: dtype=|S130, shape=() size (130) val='"Information about virus(es) used in expe...cMsZNh'' +202. '/identifier: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +203. '/nwb_version: dtype=--, shape=() size (--) val='"--value removed for NWB signature--"'' +204. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=1-2)' +205. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_001/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...cORCJK'' +206. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_001/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[382,134]]'' +207. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_#/pix_mask_weight: dtype=float32, shape=(1,) size (12), compress=gzip val='[1]' (#=1-2)' +208. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_001/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.0003182]'' +209. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_#/roi_description: dtype=|S7, shape=() size (7) val='"ROI_#"' (#=1-2)' +210. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_002/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...kOcKXm'' +211. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_002/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[388,160]]'' +212. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/ROI_002/pixel_time_offsets: dtype=float64, shape=(1,) size (16), compress=gzip val='[0.0003467]'' +213. '/processing/Acquired_ROIs/ImageSegmentation/Zstack#/imaging_plane_name: dtype=|S10, shape=() size (10) val='"Zstack#"' (#=27,29-30)' +214. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0027/roi_list: dtype=|S7, shape=(2,) size (18), compress=gzip val='["ROI_001","ROI_002"]'' +215. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/dimension: dtype=int32, shape=(2,) size (14), compress=gzip val='[1,1]' (#=3-7)' +216. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_003/img_mask: dtype=float32, shape=(512, 512) size (2503), compress=gzip val='[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0...gZRdvm'' +217. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_003/pix_mask: dtype=uint16, shape=(1, 2) size (12), compress=gzip val='[[186,70]]'' +218. '/processing/Acquired_ROIs/ImageSegmentation/Zstack0029/ROI_#/pix_mask_weight: dtype=float32, shape=(1,) size (12), compress=gzip val='[1]' (#=3-7)' +219. 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'/stimulus/presentation/air_puff/timestamps: dtype=float64, shape=(2,) size (21), compress=gzip val='[5,30.17]'' +-------------------- +** Summary +255 groups, 1110 datasets, 527 attributes diff --git a/Python/test/test_epochs.py b/Python/test/test_epochs.py new file mode 100644 index 0000000..054cc88 --- /dev/null +++ b/Python/test/test_epochs.py @@ -0,0 +1,96 @@ +"""Testing that epochs are calculated and added correctly.""" + +import os + +import h5py +import numpy as np +import yaml + +from silverlabnwb import NwbFile + + +def compare_hdf5(nwb_path, expected_yaml_path): + """Test utility method comparing a generated NWB file against expected contents. + + As a side-effect, checks that we can open files for reading with our API. + """ + with open(expected_yaml_path, 'r') as f: + expected = yaml.load(f) + with NwbFile(nwb_path, mode='r') as nwb: + compare_group(nwb.hdf_file, expected, '') + + +def compare_group(nwb_group, expected_group, path): + """Check that an HDF5 group has the expected contents.""" + for key in expected_group: + expected_value = expected_group[key] + if key == '_attrs': + # Check attributes of the node + compare_attributes(nwb_group, expected_value, path) + elif key == '_value': + # nwb_group should actually be a dataset + assert isinstance(nwb_group, h5py.Dataset) + compare_dataset(nwb_group, expected_value, path) + elif key == '_link': + # This group should be a soft link to another + link = nwb_group.get(nwb_group.name, getlink=True) + assert isinstance(link, h5py.SoftLink) + assert link.path == expected_value + else: + assert key in nwb_group + if isinstance(expected_value, dict): + compare_group(nwb_group[key], expected_value, path + '/' + key) + else: + compare_dataset(nwb_group[key], expected_value, path + '/' + key) + + +def compare_attributes(nwb_node, expected_attrs, path): + """Check that an HDF5 node has the expected attributes.""" + for attr_name, attr_value in expected_attrs.items(): + assert attr_name in nwb_node.attrs + compare_dataset(nwb_node.attrs[attr_name], attr_value, path + '/@' + attr_name) + + +def compare_dataset(nwb_dataset, expected_value, path): + """Check that an HDF5 dataset has the expected contents. + + Note that this gets used for both 'normal' datasets and attribute values. + In the former case we must access the numpy value with .value; in the latter + nwb_dataset is already the numpy value. + """ + if hasattr(nwb_dataset, 'value'): + # Extract the actual data from the dataset + nwb_dataset = nwb_dataset.value + if isinstance(expected_value, str): + if isinstance(nwb_dataset, np.bytes_): + # Convert to string so we can compare naturally + nwb_dataset = nwb_dataset.decode('UTF-8') + assert nwb_dataset == expected_value, 'Mismatch at {}'.format(path) + elif isinstance(expected_value, (int, float)): + assert abs(nwb_dataset - expected_value) < 1e-6, 'Mismatch at {}'.format(path) + elif isinstance(expected_value, list): + expected_value = np.array(expected_value) + assert nwb_dataset.shape == expected_value.shape, 'Mismatch at {}'.format(path) + if expected_value.dtype.kind == 'U': + expected_value = expected_value.astype('S') + if nwb_dataset.dtype.kind in ['O', 'U']: + nwb_dataset = nwb_dataset.astype('S') + if expected_value.dtype.kind == 'S': + np.testing.assert_array_equal(nwb_dataset, expected_value) + else: + np.testing.assert_allclose(nwb_dataset, expected_value, atol=1e-6) + else: + assert 0, 'Unexpected expected_value {!r}'.format(expected_value) + + +def test_epochs(tmpdir, capfd): + data_path = os.path.join(os.path.dirname(__file__), 'data') + import silverlabnwb + silverlabnwb.metadata.set_conf_dir(data_path) + fname = "test_epochs.nwb" + with NwbFile(os.path.join(str(tmpdir), fname), mode='w') as nwb: + speed_data, start_time = nwb.create_nwb_file(data_path, 'test_epochs') + nwb.add_core_metadata() + nwb.add_speed_data(speed_data, start_time) + nwb.determine_trial_times() + compare_hdf5(str(tmpdir.join(fname)), os.path.join(data_path, 'expected.yaml')) diff --git a/Python/test/test_labview_import.py b/Python/test/test_labview_import.py new file mode 100644 index 0000000..02b8d10 --- /dev/null +++ b/Python/test/test_labview_import.py @@ -0,0 +1,90 @@ + +import os +import subprocess + +import pytest + +from silverlabnwb import NwbFile +from silverlabnwb.nwb_util import compare_to_signature + + +# Where to look for large raw data files +DATA_PATH = os.environ.get('SILVERLAB_DATA_DIR', '') +# Where reference data is kept +REF_PATH = os.path.join(os.path.dirname(__file__), 'data') + + +@pytest.mark.skipif( + os.environ.get('SILVERLAB_GEN_REF', '0') == '0', + reason="SILVERLAB_GEN_REF not set or set to 0") +def test_generate_signatures(): + """A 'test' to generate reference data for the tests below.""" + def generate(expt): + cmd = [ + 'python', '-m', 'nwb.h5diffsig', + os.path.join(DATA_PATH, expt + '.nwb'), + '-Na' + ] + output_path = os.path.join(REF_PATH, expt + '.sig') + with open(output_path, 'wt') as output: + subprocess.check_call(cmd, stdout=output) + # Cut-down samples + generate('sample_pointing_videos_161215_15_34_21') + generate('sample_pointing_fred_170317_10_11_01') + generate('sample_miniscan_fred_170322_14_06_43') + # Full datasets + generate('161215_15_58_52') + generate('161215_15_34_21') + generate('170317_10_11_01') + generate('170322_14_06_43') + + +def do_import_test(tmpdir, expt, add_suffix=False): + """Helper method for tests below.""" + nwb_path = os.path.join(str(tmpdir), expt + '.nwb') + labview_path = os.path.join(DATA_PATH, expt + ' FunctAcq' if add_suffix else expt) + sig_path = os.path.join(REF_PATH, expt + '.sig') + + with NwbFile(nwb_path, mode='w') as nwb: + nwb.import_labview_folder(labview_path) + assert compare_to_signature(nwb_path, sig_path, ignore_external_file=True) + + +@pytest.mark.skipif( + not os.path.isdir(DATA_PATH), + reason="raw data folder '{}' not present".format(DATA_PATH)) +class TestSampleImports(object): + + def test_hana_video(self, tmpdir): + do_import_test(tmpdir, 'sample_pointing_videos_161215_15_34_21') + + def test_fred_pointing(self, tmpdir): + do_import_test(tmpdir, 'sample_pointing_fred_170317_10_11_01') + + def test_fred_miniscan(self, tmpdir): + do_import_test(tmpdir, 'sample_miniscan_fred_170322_14_06_43') + + +@pytest.mark.skipif( + not os.path.isdir(DATA_PATH), + reason="raw data folder '{}' not present".format(DATA_PATH)) +@pytest.mark.skipif( + os.environ.get('SILVERLAB_SKIP_IMPORTS', '0') == '1', + reason="SILVERLAB_SKIP_IMPORTS set to 1") +class TestFullImporting(object): + + def test_hana(self, tmpdir): + """A sample dataset from Hana with no videos.""" + do_import_test(tmpdir, '161215_15_58_52', True) + + def test_hana_video(self, tmpdir): + """A sample dataset from Hana with videos.""" + do_import_test(tmpdir, '161215_15_34_21', True) + + def test_fred_pointing(self, tmpdir): + """A sample dataset from Fred with pointing mode data.""" + do_import_test(tmpdir, '170317_10_11_01', True) + + def test_fred_patch(self, tmpdir): + """A sample dataset from Fred with miniscans.""" + do_import_test(tmpdir, '170322_14_06_43', True) diff --git a/Python/test/test_local_files.sh b/Python/test/test_local_files.sh new file mode 100755 index 0000000..8fa0f57 --- /dev/null +++ b/Python/test/test_local_files.sh @@ -0,0 +1,43 @@ +#!/usr/bin/env bash + +mydir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" + +# Pointing mode + +# Hana, 80 ROIs, 20 trials, 8772 cycles, some TDMS missing, video +labview2nwb --no-gui "$SILVERLAB_DATA_DIR/161215_15_34_21.nwb" "$SILVERLAB_DATA_DIR/161215_15_34_21 FunctAcq" +nwb_check_signature "$SILVERLAB_DATA_DIR/161215_15_34_21.nwb" "$mydir/data/161215_15_34_21.sig" + +# Hana, 80 ROIs, 20 trials, 8772 cycles +# Reading TDMS: 5m47.735s; 10:35:48 - 10:41:25 = 5m37 +# Reading .dat: 1m45.357s; 10:50:35 - 10:52:10 = 1m35 +labview2nwb --no-gui "$SILVERLAB_DATA_DIR/161215_15_58_52.nwb" "$SILVERLAB_DATA_DIR/161215_15_58_52 FunctAcq" +nwb_check_signature "$SILVERLAB_DATA_DIR/161215_15_58_52.nwb" "$mydir/data/161215_15_58_52.sig" + +# Fred, 120 ROIs, 18 trials, 2929 cycles +# Reading TDMS: 2m49.831s; 09:15:14 - 09:17:47 = 2m33 +# Reading .dat: 1m20.015s; 09:12:13 - 09:13:17 = 1m05 +labview2nwb --no-gui "$SILVERLAB_DATA_DIR/170317_10_11_01.nwb" "$SILVERLAB_DATA_DIR/170317_10_11_01 FunctAcq" +nwb_check_signature "$SILVERLAB_DATA_DIR/170317_10_11_01.nwb" "$mydir/data/170317_10_11_01.sig" + +# Miniscans + +# Fred, 4 ROIs, 96 miniscans, 6 trials, 2611 cycles +# Note: this first example seems to have some corrupt data in the TDMS (trial 4) - not enough data points +# It wasn't mentioned in Fred's email, so may not be a good sample to use. +labview2nwb --no-gui "$SILVERLAB_DATA_DIR/170209_11_26_03.nwb" "$SILVERLAB_DATA_DIR/170209_11_26_03 FunctAcq" +nwb_check_signature "$SILVERLAB_DATA_DIR/170209_11_26_03.nwb" "$mydir/data/170209_11_26_03.sig" + +# Fred, 7 ROIs, 420 miniscans, 18 trials, 367 cycles +labview2nwb --no-gui "$SILVERLAB_DATA_DIR/170322_14_06_43.nwb" "$SILVERLAB_DATA_DIR/170322_14_06_43 FunctAcq" +nwb_check_signature "$SILVERLAB_DATA_DIR/170322_14_06_43.nwb" "$mydir/data/170322_14_06_43.sig" + +exit 0 + +# To regenerate sigs use the commands below + +python -m nwb.h5diffsig "$SILVERLAB_DATA_DIR/161215_15_34_21.nwb" -Na > "$mydir/data/161215_15_34_21.sig" +python -m nwb.h5diffsig "$SILVERLAB_DATA_DIR/161215_15_58_52.nwb" -Na > "$mydir/data/161215_15_58_52.sig" +python -m nwb.h5diffsig "$SILVERLAB_DATA_DIR/170317_10_11_01.nwb" -Na > "$mydir/data/170317_10_11_01.sig" +# python -m nwb.h5diffsig "$SILVERLAB_DATA_DIR/170209_11_26_03.nwb" -Na > "$mydir/data/170209_11_26_03.sig" +python -m nwb.h5diffsig "$SILVERLAB_DATA_DIR/170322_14_06_43.nwb" -Na > "$mydir/data/170322_14_06_43.sig" diff --git a/README.md b/README.md new file mode 100644 index 0000000..43f0712 --- /dev/null +++ b/README.md @@ -0,0 +1,116 @@ +# Silver Lab analysis pipeline + +Data -> NWB 1.0.x -> Analysis + +This is not yet 'production software', but there are working tools for converting Labview data to NWB and viewing/processing this in Matlab. + +## Quick installation + +An installation script is provided, but it requires some software to be installed on your machine first: +1. The [git](https://git-scm.com/) version control system +2. The [Anaconda](https://conda.io/docs/) Python distribution + +In both cases the command-line tools are needed. +Software Carpentry provide some [installation instructions](https://swcarpentry.github.io/workshop-template/#setup) for Windows, Mac OS and Linux. +Follow the sections for "The Bash Shell", "Git" and "Python". + +You can then open a bash shell, download this software to your machine, and run our installer script. +For instance: +``` sh +cd $HOME +git clone https://github.com/SilverLabUCL/SilverLab_NWBv1 +cd SilverLab_NWBv1 +./install.sh +``` + +The tools should now be ready to use from both Python and Matlab. +For more details on each component, see: +- [our Python library for working with NWB files](Python/README.md) +- [Matlab wrappers for this with a graphical interface](MATLAB/README.md) + +### Installation notes & variations + +1. You can install the software in any folder; `$HOME` was just used above as an example that exists on all systems. +2. Rather than installing the full Anaconda suite, you can install the cut-down 'Miniconda' version; + see the [Miniconda quick install instructions](https://conda.io/docs/install/quick.html) for details. + It doesn't matter whether you choose Python 2 or Python 3, but we do recommend using the 64-bit version. +3. When the Anaconda/Miniconda installer asks if you want to have conda added to your path, + or be made the default Python version, say yes so that the conda tools can be found by our installation script. + (The script will try to guess if you don't, but this isn't as reliable.) +4. It's worth while learning how to use git to version control your own analysis scripts. + Look out for the next [Software Carpentry workshop](http://www.ucl.ac.uk/isd/services/research-it/training) + being run by Research IT Services. +5. You may also want to install a graphical interface to git such as [Git Kraken](https://www.gitkraken.com/). + + +## Links + +Neurodata Without Borders: http://nwb.org/ + +Python & MATLAB APIs: https://github.com/NeurodataWithoutBorders/api-python + +HDFView: https://support.hdfgroup.org/products/java/hdfview, to view hdf5 files: + +![HDFview](/HDFView.png) + + + +# Other tools for data analysis + +## Whisker Tracking – Janelia + +https://openwiki.janelia.org/wiki/display/MyersLab/Whisker+Tracking+Downloads + +Clack NG, O'Connor DH, Huber D, Petreanu L, Hires A., Peron, S., Svoboda, K., and Myers, E.W. (2012)  +Automated Tracking of Whiskers in Videos of Head Fixed Rodents. +PLoS Comput Biol 8(7):e1002591. doi:10.1371/journal.pcbi.1002591 + +## Locomotion Videography – Hausser Lab + +Synaptic representation of locomotion in single cerebellar granule cells +https://elifesciences.org/content/4/e07290/supp-material1 +https://elifesciences.org/content/4/e07290/article-data + + +## July 2016 Nature Communications Paper + +Accurate spike estimation from noisy calcium signals for ultrafast three-dimensional imaging of large neuronal populations in vivo +http://www.nature.com/articles/ncomms12190 + + +## Losonczy Lab + +http://www.losonczylab.org/software + +We strive to share our software with the scientific community. The most recent versions of our software are made available on this page. + +#### SIMA (Documentation, Downloads, Example Dataset, GitHub) +The SIMA package is an open source Python package for analysis of fluorescence imaging data. We use this software for motion correction, segmentation, and extraction of fluorescence signals from 2-photon calcium imaging experiments. + +#### ROI Buddy (Documentation, Downloads) +ROI Buddy is a graphical user interface for editing ROIs. It is designed to be used in conjunction with the SIMA package. See the documentation for installation details. + +**References:** +Kaifosh P, Zaremba J, Danielson N, and Losonczy A. SIMA: Python software for analysis of dynamic fluorescence imaging data. Frontiers in Neuroinformatics. 2014 Aug 27; 8:77. doi: 10.3389/fninf.2014.00077. +Kaifosh P, Lovett-Barron M, Turi GF, Reardon TR, Losonczy A. Septo-hippocampal GABAergic signaling across multiple modalities in awake mice. Nat Neurosci. 2013 Sep;16(9):1182-4. doi: 10.1038/nn.3482. + + +## VAA3D +https://www.janelia.org/open-science/vaa3d + +## Schultz Lab +http://www.schultzlab.org/software/index.html + +## Svoboda Lab +Janelia Automatic Animal Behavior Annotator (JAABA®) +https://www.janelia.org/open-science/jaaba%C2%AE + +## Yuste Lab +Lots of software and cluster analysis +http://www.columbia.edu/cu/biology/faculty/yuste/methods.html + +## Hausser Lab +http://michael-hausser.squarespace.com/software/ + +http://www.treestoolbox.org/ + diff --git a/install.bat b/install.bat new file mode 100644 index 0000000..55417a9 --- /dev/null +++ b/install.bat @@ -0,0 +1,50 @@ +REM Installer script for the SilverLab AnalysisPipeline software + dependencies + +REM Settings +SET conda_env_name=nwb +SET python_version=2.7 +SET nwb_api_folder=nwb_api_python +SET nwb_api_uri="https://github.com/SilverLabUCL/api-python" +SET our_folder=%cd% + +REM Set up our conda environment +echo "Setting up conda environment..." +conda env remove -q -y -n %conda_env_name% +conda create --yes -n %conda_env_name% python=%python_version% +conda install --yes -n %conda_env_name% numpy=1.13.0 +conda install --yes -n %conda_env_name% hdf5=1.8.12 h5py=2.7.0 -c jonc +conda install --yes -n %conda_env_name% av=0.3.3 tifffile=0.12.1 -c conda-forge +call activate %conda_env_name% + +REM Install the NWB API +REM Note that we can't just pip install direct from GitHub as we also need the Matlab bridge +echo "Installing NeurodataWithoutBorders API..." +IF EXIST %nwb_api_folder% ( + git -C %nwb_api_folder% pull --ff-only +) ELSE ( + git clone %nwb_api_uri% %nwb_api_folder% +) +cd %nwb_api_folder% +pip install -e . + +REM Install the analysis pipeline +echo "Installing Silver Lab analysis pipeline..." +cd %our_folder%/Python +pip install -r "requirements/main.in" +pip install -e . + +REM Set up Matlab to use the pipeline & NWB +echo "Setting up Matlab..." +FOR /F "delims=" %%i IN ('python -c "import sys; print(sys.executable)"') DO SET python=%%i +SET cmds=pyversion '%python%'; +SET cmds=%cmds% addpath('%our_folder%/%nwb_api_folder%/matlab_bridge/matlab_bridge_api'); +SET cmds=%cmds% addpath(genpath('%our_folder%/MATLAB/source')); +SET cmds=%cmds% success = savepath(); +SET cmds=%cmds% if success == 1; error('Failed to save Matlab path - set manually'); end; +matlab -nosplash -nodesktop -r "%cmds% quit" + +echo "To activate the conda environment, in order to convert Labview to NWB, run:" +echo " On Linux, Mac OS, Windows with Git Bash:" +echo "source activate %conda_env_name%" +echo " On Windows with PowerShell or Cmd:" +echo "activate.bat %conda_env_name%" diff --git a/install.sh b/install.sh new file mode 100755 index 0000000..5903460 --- /dev/null +++ b/install.sh @@ -0,0 +1,105 @@ +#!/usr/bin/env bash + +# Installer script for the SilverLab AnalysisPipeline software + dependencies + +# Are we running on Windows? +case "$(uname -s)" in + MINGW*|CYGWIN*|Windows*) WINDOWS=1 ;; + *) WINDOWS=0 ;; +esac + + +# Settings +conda_env_name=nwb +if [ $WINDOWS == 1 ]; then + python_version=2.7 +else + # Python 3.5 is still crashing Matlab on Windows + python_version=3.5 +fi +nwb_api_folder=nwb_api_python +nwb_api_uri="https://github.com/SilverLabUCL/api-python" +our_folder="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" + +# Define helper functions +function error () { + echo "Error: $1" + exit 1 +} + +# Try to find required tools +echo 'Checking for presence of required tools...' +which git || error 'No git found' +conda=`which conda` +if [ ! $conda ]; then + for name in anaconda2 anaconda3 miniconda2 miniconda3; do + conda=$HOME/$name/bin/conda + [ -x $conda ] && break + # Try Windows style instead + conda=$HOME/$name/Scripts/conda.exe + [ -x $conda ] && break + done +fi +[ -x $conda ] || error 'Unable to find conda' + +conda_envs_dir="`$conda info | grep 'envs directories' | awk -F' : ' '{print $2}'`" +conda_root="`$conda info --root`" +conda_bin_dir=`dirname $conda` + +echo "Found conda install at $conda_root" + +# Set up our conda environment +function setup_env () { + echo 'Setting up conda environment...' + [ -d "$conda_envs_dir/$conda_env_name" ] || $conda create --yes -n $conda_env_name python=$python_version + source $conda_bin_dir/activate $conda_env_name + $conda install --yes -n $conda_env_name numpy=1.13.0 + if [ $WINDOWS == 1 ]; then + # Use h5py compiled to match Matlab's HDF5 version + $conda install --yes -n $conda_env_name hdf5=1.8.12 h5py=2.7.0 -c jonc + else + $conda install --yes -n $conda_env_name h5py=2.7.0 + fi + $conda install --yes -n $conda_env_name av=0.3.3 tifffile=0.12.1 -c conda-forge +} + +# Install the NWB API +# Note that we can't just pip install direct from GitHub as we also need the Matlab bridge +function install_nwb () { + echo 'Installing NeurodataWithoutBorders API...' + cd "$our_folder" + if [ -d "$nwb_api_folder" ]; then + git -C "$nwb_api_folder" pull --ff-only + else + git clone "$nwb_api_uri" "$nwb_api_folder" + fi + cd "$nwb_api_folder" + pip install -e . +} + +# Install the analysis pipeline +function install_pipeline () { + echo 'Installing Silver Lab analysis pipeline...' + cd "$our_folder/Python" + pip install -r "requirements/main.in" + pip install -e . +} + +# Set up Matlab to use the pipeline & NWB +function setup_matlab () { + echo 'Setting up Matlab...' + python "$our_folder/MATLAB/setup.py" "$our_folder/$nwb_api_folder" +} + +# Run everything +setup_env +install_nwb +install_pipeline +# source $conda_bin_dir/activate $conda_env_name +setup_matlab + +echo "To activate the conda environment, in order to convert Labview to NWB, run:" +echo " On Linux, Mac OS, Windows with Git Bash:" +echo "source $conda_bin_dir/activate $conda_env_name" +echo " On Windows with PowerShell:" +echo "$conda_bin_dir/activate.bat $conda_env_name" From c529fdf14ac6ccb32419b23036728f4aec94cb4d Mon Sep 17 00:00:00 2001 From: Jonathan Cooper Date: Mon, 26 Mar 2018 15:12:11 +0100 Subject: [PATCH 2/3] Add MIT licence --- LICENSE | 21 +++++++++++++++++++++ 1 file changed, 21 insertions(+) create mode 100644 LICENSE diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..a059ea6 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2017-2018 University College London + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. From 0f3dd10208ccf925d58ea14de1ebbe5358bd6ce4 Mon Sep 17 00:00:00 2001 From: Jonathan Cooper Date: Mon, 26 Mar 2018 15:35:51 +0100 Subject: [PATCH 3/3] Updates from double-checking local install works --- .gitignore | 4 ++++ Python/test/test_labview_import.py | 2 +- install.sh | 2 +- 3 files changed, 6 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index 7bbc71c..3a064a3 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,6 @@ +# Project-specific ignore patterns +nwb_api_python/ + # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] @@ -45,6 +48,7 @@ nosetests.xml coverage.xml *.cover .hypothesis/ +.pytest_cache/ # Translations *.mo diff --git a/Python/test/test_labview_import.py b/Python/test/test_labview_import.py index 02b8d10..cfa9954 100644 --- a/Python/test/test_labview_import.py +++ b/Python/test/test_labview_import.py @@ -69,7 +69,7 @@ def test_fred_miniscan(self, tmpdir): not os.path.isdir(DATA_PATH), reason="raw data folder '{}' not present".format(DATA_PATH)) @pytest.mark.skipif( - os.environ.get('SILVERLAB_SKIP_IMPORTS', '0') == '1', + os.environ.get('SILVERLAB_SKIP_IMPORTS', '1') == '1', reason="SILVERLAB_SKIP_IMPORTS set to 1") class TestFullImporting(object): diff --git a/install.sh b/install.sh index 5903460..9e8b9d1 100755 --- a/install.sh +++ b/install.sh @@ -10,7 +10,7 @@ esac # Settings -conda_env_name=nwb +conda_env_name=nwb_v1 if [ $WINDOWS == 1 ]; then python_version=2.7 else