fix: never parse index_col from node data

spras/dataset.py

@@ -136,7 +136,7 @@ def __init__(self, dataset_params: DatasetSchema):
         # Load generic node tables
         self.node_table = pd.DataFrame(node_set, columns=[self.NODE_ID])
         for node_file in node_data_files:
-            single_node_table = pd.read_table(os.path.join(data_loc, node_file))
+            single_node_table = pd.read_table(os.path.join(data_loc, node_file), index_col=False)
             # If we have only 1 column, assume this is an indicator variable
             if len(single_node_table.columns) == 1:
                 single_node_table = pd.read_table(

test/dataset/fixtures/toy-372/input-interactome.txt

@@ -0,0 +1,2 @@
+C	D	0.77	U
+N	O	0.66	U

test/dataset/fixtures/toy-372/input-nodes.txt

@@ -0,0 +1,3 @@
+NODEID	prize	active	dummy	sources	targets
+N											
+C	5.7	True			True

test/dataset/test_dataset.py

@@ -2,6 +2,7 @@
 
 import pandas
 import pytest
+import numpy as np
 
 from spras.config.dataset import DatasetSchema
 from spras.dataset import Dataset
@@ -59,3 +60,24 @@ def test_standard(self):
         ))
 
         assert len(dataset.get_interactome()) == 2
+
+    # 372 is a PR, but for the relevant comment, see
+    # https://github.com/Reed-CompBio/spras/pull/372/files#r2291953612.
+    # Note that the input-nodes file has more tabs than the original fixture.
+    def test_372(self):
+        dataset = Dataset({
+            'label': 'toy-372',
+            'edge_files': ['input-interactome.txt'],
+            'node_files': ['input-nodes.txt'],
+            'data_dir': FIXTURES_PATH / 'toy-372',
+            'other_files': []
+        })
+
+        node_table = dataset.node_table
+        assert node_table is not None
+
+        assert node_table[node_table[Dataset.NODE_ID] == 'C'].iloc[0]['prize'] == 5.7
+        assert node_table[node_table[Dataset.NODE_ID] == 'C'].iloc[0]['active'] == True
+
+        assert np.isnan(node_table[node_table[Dataset.NODE_ID] == 'C'].iloc[0]['sources'])
+        assert node_table[node_table[Dataset.NODE_ID] == 'C'].iloc[0]['targets'] == True