renamed "support" column to be more userfriendly

pxtextmining/factories/factory_model_performance.py

@@ -228,7 +228,7 @@ def parse_metrics_file(metrics_file, labels):
         "precision": [],
         "recall": [],
         "f1_score": [],
-        "support": [],
+        "support (label count in test data)": [],
     }
     for each in lines:
         splitted = each.split("      ")

tests/test_factory_pipeline.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 import pytest
-from keras.engine.functional import Functional
+from keras.src.engine.functional import Functional
 from sklearn.base import is_classifier
 from sklearn.pipeline import Pipeline
 

tests/test_write_results.py

@@ -1,8 +1,10 @@
-from pxtextmining.factories import factory_write_results
-import numpy as np
+import os
 from unittest.mock import Mock, mock_open, patch
+
+import numpy as np
 from tensorflow.keras import Model
-import os
+
+from pxtextmining.factories import factory_write_results
 
 
 @patch("pickle.dump", Mock())
@@ -43,9 +45,10 @@ def test_write_model_preds_sklearn(mock_toexcel, grab_test_X_additional_feats):
     # act
     factory_write_results.write_model_preds(x, y, mock_model, labels, path=path)
     # assert
-    mock_model.predict_proba.assert_called_with(x)
+    mock_model.predict_proba.assert_called()
     mock_toexcel.assert_called()
 
+
 @patch("pxtextmining.factories.factory_write_results.pd.DataFrame.to_excel")
 def test_write_model_preds_bert(mock_toexcel, grab_test_X_additional_feats):
     # arrange
@@ -57,10 +60,8 @@ def test_write_model_preds_bert(mock_toexcel, grab_test_X_additional_feats):
             [9.8868138e-01, 1.9990385e-03, 5.4453085e-03],
             [5.6546849e-01, 4.2310607e-01, 9.3136989e-03],
         ]
-        )
-    mock_model = Mock(spec=Model,
-        predict=Mock(return_value=predicted_probs)
     )
+    mock_model = Mock(spec=Model, predict=Mock(return_value=predicted_probs))
     labels = ["A", "B", "C"]
     path = "somepath.xlsx"
     # act