Merge pull request #73 from kaklise/main

Update to custom static and streaming methods to use a specific column

documentation/whatsnew/v0.2.1.rst

@@ -3,6 +3,7 @@
 v0.2.1 (main)
 --------------------------
 
+* Bug fix in custom static and streaming quality control tests to use a specific column
 * Minor updates for testing and documentation
 * Added GitHub Actions and Python 3.9 tests
 

pecos/monitoring.py

@@ -788,7 +788,7 @@ def check_custom_static(self, quality_control_func, key=None, min_failures=1,
 
         # Function that operates on the entire dataset and returns a mask and
         # metadata for the entire dataset
-        mask, metadata = quality_control_func(self.df) 
+        mask, metadata = quality_control_func(df) 
         assert isinstance(mask, pd.DataFrame), 'mask returned by quality_control_func must be of type pd.DataFrame'
         assert isinstance(metadata, pd.DataFrame), 'metadata returned by quality_control_func must be of type pd.DataFrame'
 
@@ -852,7 +852,7 @@ def check_custom_streaming(self, quality_control_func, window, key=None,
         # The streaming framework uses numpy arrays to improve performance but
         # still expects pandas DataFrames and Series in the user defined quality 
         # control function to keep data types consitent on the user side.
-        np_mask = pd.DataFrame(True, index=self.df.index, columns=self.df.columns).values
+        np_mask = pd.DataFrame(True, index=df.index, columns=df.columns).values
         np_data = df.values.astype('float64')
 
         ti = df.index.get_loc(df.index[0]+history_window)
@@ -881,7 +881,7 @@ def check_custom_streaming(self, quality_control_func, window, key=None,
                     np_data[t][check_rebase] = df.iloc[t][check_rebase]
                     rebase_count = rebase_count + sum(check_rebase)
 
-        mask = pd.DataFrame(np_mask, index=self.df.index, columns=self.df.columns)
+        mask = pd.DataFrame(np_mask, index=df.index, columns=df.columns)
         self._append_test_results(mask, error_message, min_failures)
 
         # Convert metadata to a dataframe

pecos/tests/test_monitoring.py

@@ -590,11 +590,15 @@ def custom_func(data):
         percent = 1-self.pm.test_results['Timesteps'].sum()/N
         assert_almost_equal(percent, 0.95, 2) # 95% within 2 std
 
+        # using a specific key
+        metadata_A = self.pm.check_custom_static(custom_func, key='A', error_message='Static')
+        assert_frame_equal(metadata[['A']], metadata_A)
+
         # Functional tests
         results = pecos.monitoring.check_custom_static(self.pm.data, custom_func, error_message='Static')
         percent = 1-results['test_results']['Timesteps'].sum()/N
         assert_almost_equal(percent, 0.95, 2) # 95% within 2 std
-        
+
     def test_custom_streaming(self):
 
         def custom_func(data_pt, history):
@@ -607,6 +611,10 @@ def custom_func(data_pt, history):
         percent = 1-self.pm.test_results['Timesteps'].sum()/N
         assert_almost_equal(percent, 0.95, 2) # 95% within 2 std
 
+        # using a specific key
+        metadata_A = self.pm.check_custom_streaming(custom_func, 50, key='A', error_message='Streaming')
+        assert_frame_equal(metadata[['A']], metadata_A)
+
         # Functional tests
         results = pecos.monitoring.check_custom_streaming(self.pm.data, custom_func, 50, error_message='Streaming')
         percent = 1-results['test_results']['Timesteps'].sum()/N