Prepare for Python 3.13, fix issues with numpy>2 & matplotlib,

pylintrc

@@ -6,7 +6,7 @@
 #R0903 - Too Few public methods
 #W0511 - TODO in code
 #R0401 - cyclic-import
-disable=C0103,R0903,W0511,R0401,unspecified-encoding,consider-using-f-string
+disable=C0103,R0903,W0511,R0401,unspecified-encoding,consider-using-f-string, too-many-positional-arguments
 
 [FORMAT]
 # Maximum number of characters on a single line.

pyproject.toml

@@ -24,6 +24,7 @@ classifiers = [
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
     "Topic :: Scientific/Engineering :: Bio-Informatics",
 ]
 dependencies = [

tests/apps/test_morph_stats.py

@@ -212,10 +212,9 @@ def test_extract_stats_scalar_feature():
         # silence warning about approximating soma volume with a sphere
         warnings.simplefilter("ignore", category=UserWarning)
         res = ms.extract_stats(m, config)
-    assert res == {
-        'all': {'max_number_of_forking_points': 277},
-        'morphology': {'sum_soma_volume': 1424.4383771584492},
-    }
+
+    assert res["all"] == {'max_number_of_forking_points': 277}
+    assert_almost_equal(res["morphology"]["sum_soma_volume"], 1424.4383771584492, decimal=4)
 
 
 def test_extract_stats__kwarg_modes_multiple_features():
@@ -493,7 +492,8 @@ def test_extract_dataframe_multiproc():
         actual = ms.extract_dataframe(morphs, REF_CONFIG, n_workers=os.cpu_count() + 1)
         # drop raw features as they require too much test data to mock
         actual = actual.drop(columns='raw_section_branch_orders', level=1)
-        assert len(w) == 1, "Warning not emitted"
+        assert len(w) >= 1, "Warning not emitted"
+
     assert_frame_equal(actual, expected, check_dtype=False)
 
     with warnings.catch_warnings(record=True) as w:

tests/core/test_section.py

@@ -42,8 +42,8 @@ def test_section_base_func():
     assert section.id == 0
     assert_array_equal(section.points, [[0, 0, 0, 1], [0, 5, 0, 1]])
     assert_almost_equal(section.length, 5)
-    assert_almost_equal(section.area, 31.41592653589793)
-    assert_almost_equal(section.volume, 15.707963267948964)
+    assert_almost_equal(section.area, 31.4159, decimal=4)
+    assert_almost_equal(section.volume, 15.7079, decimal=4)
 
     # __nonzero__
     assert section

tests/core/test_soma.py

@@ -101,7 +101,7 @@ def test_Soma_ThreePointCylinder():
     assert 'SomaNeuromorphoThreePointCylinders' in str(sm)
     assert isinstance(sm, soma.SomaNeuromorphoThreePointCylinders)
     assert list(sm.center) == [0, 0, 0]
-    assert sm.radius == 44
+    assert_almost_equal(sm.radius, 44.0, decimal=5)
 
 
 def test_Soma_ThreePointCylinder_invalid_radius():

tests/features/test_get_features.py

@@ -147,7 +147,9 @@ def test_max_radial_distance():
 
 def test_section_tortuosity():
     assert_allclose(
-        _stats(features.get('section_tortuosity', POP)), (1.0, 4.657, 440.408, 1.342), rtol=1e-3
+        _stats(features.get('section_tortuosity', POP)),
+        (1.0, 4.657, 440.408, 1.342),
+        rtol=1e-3,
     )
     assert_allclose(
         _stats(features.get('section_tortuosity', POP, neurite_type=NeuriteType.all)),
@@ -326,6 +328,7 @@ def test_total_length():
     assert_allclose(
         features.get('total_length', POP, neurite_type=NeuriteType.axon),
         [207.8797736031714, 207.81088341560977, 11767.156115224638],
+        rtol=1e-6,
     )
     assert_allclose(
         features.get('total_length', POP, neurite_type=NeuriteType.apical_dendrite),
@@ -518,12 +521,14 @@ def test_neurite_volumes():
     assert_allclose(
         _stats(features.get('total_volume_per_neurite', POP, neurite_type=NeuriteType.axon)),
         (276.58135508666612, 277.5357232437392, 830.85568094763551, 276.95189364921185),
+        rtol=1e-3,
     )
     assert_allclose(
         _stats(
             features.get('total_volume_per_neurite', POP, neurite_type=NeuriteType.apical_dendrite)
         ),
         (271.94122143951864, 271.94122143951864, 271.94122143951864, 271.94122143951864),
+        rtol=1e-3,
     )
     assert_allclose(
         _stats(
@@ -567,52 +572,61 @@ def test_neurite_density():
     assert_allclose(
         _stats(features.get('neurite_volume_density', POP)),
         (6.1847539631150784e-06, 0.52464681266899216, 1.9767794901940539, 0.19767794901940539),
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(features.get('neurite_volume_density', POP, neurite_type=NeuriteType.all)),
         (6.1847539631150784e-06, 0.52464681266899216, 1.9767794901940539, 0.19767794901940539),
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(features.get('neurite_volume_density', POP, neurite_type=NeuriteType.axon)),
         (6.1847539631150784e-06, 0.26465213325053372, 0.5275513670655404, 0.1758504556885134),
-        1e-6,
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(
             features.get('neurite_volume_density', POP, neurite_type=NeuriteType.apical_dendrite)
         ),
         (0.43756606998299519, 0.43756606998299519, 0.43756606998299519, 0.43756606998299519),
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(
             features.get('neurite_volume_density', POP, neurite_type=NeuriteType.basal_dendrite)
         ),
         (0.00034968816544949771, 0.52464681266899216, 1.0116620531455183, 0.16861034219091972),
+        rtol=1e-6,
     )
 
     assert_allclose(
         _stats(features.get('neurite_volume_density', NRN)),
         (0.24068543213643726, 0.52464681266899216, 1.4657913638494682, 0.36644784096236704),
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(features.get('neurite_volume_density', NRN, neurite_type=NeuriteType.all)),
         (0.24068543213643726, 0.52464681266899216, 1.4657913638494682, 0.36644784096236704),
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(features.get('neurite_volume_density', NRN, neurite_type=NeuriteType.axon)),
         (0.26289304906104355, 0.26289304906104355, 0.26289304906104355, 0.26289304906104355),
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(
             features.get('neurite_volume_density', NRN, neurite_type=NeuriteType.apical_dendrite)
         ),
         (0.43756606998299519, 0.43756606998299519, 0.43756606998299519, 0.43756606998299519),
+        rtol=1e-6,
     )
     assert_allclose(
         _stats(
             features.get('neurite_volume_density', NRN, neurite_type=NeuriteType.basal_dendrite)
         ),
         (0.24068543213643726, 0.52464681266899216, 0.76533224480542938, 0.38266612240271469),
+        rtol=1e-6,
     )
 
 

tests/features/test_morphology.py

@@ -90,8 +90,8 @@ def test_soma_volume():
 
 
 def test_soma_surface_area():
-    assert_allclose(morphology.soma_surface_area(SIMPLE), 12.566370614359172)
-    assert_allclose(morphology.soma_surface_area(NRN), 0.1075095256160432)
+    assert_allclose(morphology.soma_surface_area(SIMPLE), 12.566370614359172, rtol=1e-6)
+    assert_allclose(morphology.soma_surface_area(NRN), 0.1075095256160432, rtol=1e-6)
 
 
 def test_soma_radius():
@@ -105,11 +105,11 @@ def surface(r0, r1, h):
 
     basal_area = surface(1, 1, 5) + surface(1, 0, 5) + surface(1, 0, 6)
     ret = morphology.total_area_per_neurite(SIMPLE, neurite_type=BASAL_DENDRITE)
-    assert_almost_equal(ret[0], basal_area)
+    assert_almost_equal(ret[0], basal_area, decimal=5)
 
     axon_area = surface(1, 1, 4) + surface(1, 0, 5) + surface(1, 0, 6)
     ret = morphology.total_area_per_neurite(SIMPLE, neurite_type=AXON)
-    assert_almost_equal(ret[0], axon_area)
+    assert_almost_equal(ret[0], axon_area, decimal=5)
 
     ret = morphology.total_area_per_neurite(SIMPLE)
     assert np.allclose(ret, [basal_area, axon_area])
@@ -143,6 +143,7 @@ def test_total_volume_per_neurite():
     assert_allclose(
         total_volumes,
         [271.94122143951864, 281.24754646913954, 274.98039928781355, 276.73860261723024],
+        rtol=1e-6,
     )
 
 

tests/features/test_neurite.py

@@ -77,7 +77,7 @@ def test_neurite_volume_density():
         0.24068543213643726,
         0.26289304906104355,
     ]
-    assert_allclose(vol_density, ref_density)
+    assert_allclose(vol_density, ref_density, rtol=1e-6)
 
 
 def test_neurite_volume_density_failed_convex_hull():
@@ -215,7 +215,7 @@ def test_segment_areas():
 def test_segment_volumes():
     expected = [[15.70796327, 5.23598776, 6.28318531], [12.56637061, 6.28318531, 5.23598776]]
     result = [neurite.segment_volumes(s) for s in SIMPLE.neurites]
-    assert_allclose(result, expected)
+    assert_allclose(result, expected, rtol=1e-6)
 
 
 def test_segment_midpoints():

tests/view/test_matplotlib_impl.py

@@ -28,8 +28,10 @@
 import warnings
 from io import StringIO
 from pathlib import Path
+from packaging.version import parse
 
 import numpy as np
+import matplotlib
 from neurom import load_morphology
 from neurom.core.types import NeuriteType
 from neurom.view import matplotlib_utils, matplotlib_impl
@@ -112,7 +114,14 @@ def test_tree3d(get_fig_3d):
     xy_bounds = ax.xy_dataLim.bounds
     np.testing.assert_allclose(xy_bounds, (-5.0, 0.0, 11.0, 5.0))
     zz_bounds = ax.zz_dataLim.bounds
-    np.testing.assert_allclose(zz_bounds, (0.0, 0.0, 1.0, 1.0))
+
+    # auto scaling of data limits was fixed for LineCollection3D
+    # in 3.9.1+ fixing the previously wrong bbox limits
+    # See: https://github.com/matplotlib/matplotlib/pull/28403
+    if parse(matplotlib.__version__) < parse("3.9.1"):
+        np.testing.assert_allclose(zz_bounds, (0.0, 0.0, 1.0, 1.0))
+    else:
+        np.testing.assert_allclose(zz_bounds, (0.0, 0.0, 0.0, 1.0))
 
 
 def test_morph3d(get_fig_3d):

tox.ini

@@ -10,7 +10,7 @@ envlist =
     coverage
     tutorial
     check-packaging
-    py{38,39,310,311,312}
+    py{38,39,310,311,312,313}
 
 [testenv]
 deps =
@@ -102,3 +102,4 @@ python =
   3.10: py310, tutorial
   3.11: py311, check-packaging
   3.12: py312
+  3.13: py313