Change "nid" Casted Value in caliper_native_reader to np.int64 (#118)

* Change cast value to np.int64

* Update test

* Use existing datastructure to cast

* Change type to float so we can support NaN nid values

hatchet/readers/caliper_native_reader.py

@@ -527,7 +527,9 @@ def read(self):
             with self.timer.phase("data frame"):
                 # merge the metrics and node dataframes on the nid column
                 dataframe = pd.merge(df_metrics, self.df_nodes, on="nid")
-                dataframe["nid"] = dataframe["nid"].astype(pd.Int64Dtype())
+                dataframe["nid"] = dataframe["nid"].astype(
+                    self.__cali_type_dict["double"]
+                )
 
                 # set the index to be a MultiIndex
                 indices = ["node"]

hatchet/tests/caliper.py

@@ -5,7 +5,6 @@
 
 import subprocess
 import numpy as np
-import pandas as pd
 
 import pytest
 import sys
@@ -196,7 +195,7 @@ def test_graphframe_native_lulesh_from_file(lulesh_caliper_cali):
         if col in ("time (inc)", "time"):
             assert gf.dataframe[col].dtype == np.float64
         elif col in ("nid", "rank"):
-            assert gf.dataframe[col].dtype == pd.Int64Dtype()
+            assert gf.dataframe[col].dtype == np.float64
         elif col in ("name", "node"):
             assert gf.dataframe[col].dtype == object
 
@@ -222,7 +221,7 @@ def test_graphframe_native_lulesh_from_caliperreader(lulesh_caliper_cali):
         if col in ("time (inc)", "time"):
             assert gf.dataframe[col].dtype == np.float64
         elif col in ("nid", "rank"):
-            assert gf.dataframe[col].dtype == pd.Int64Dtype()
+            assert gf.dataframe[col].dtype == np.float64
         elif col in ("name", "node"):
             assert gf.dataframe[col].dtype == object
 
@@ -882,7 +881,7 @@ def test_graphframe_timeseries_lulesh_from_file(caliper_timeseries_cali):
         if col in ("time (inc)", "time"):
             assert gf.dataframe[col].dtype == np.float64
         elif col in ("nid", "rank"):
-            assert gf.dataframe[col].dtype == pd.Int64Dtype()
+            assert gf.dataframe[col].dtype == np.float64
         elif col in ("name", "node"):
             assert gf.dataframe[col].dtype == object