[pre-commit.ci] auto fixes from pre-commit.com hooks

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hitsz-ids · Nov 27, 2024 · c4805f1 · c4805f1
1 parent 1ee0b35
commit c4805f1
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Showing 4 changed files with 11 additions and 8 deletions.
diff --git a/sdgx/data_models/inspectors/numeric.py b/sdgx/data_models/inspectors/numeric.py
@@ -171,8 +171,9 @@ def fit(self, raw_data: pd.DataFrame, *args, **kwargs):
 
         # Iterate all columns and determain the final data type
         for col in raw_data.columns:
-            if (pd.api.types.is_integer_dtype(raw_data[col].dtype)
-                    or pd.api.types.is_float_dtype(raw_data[col].dtype)):
+            if pd.api.types.is_integer_dtype(raw_data[col].dtype) or pd.api.types.is_float_dtype(
+                raw_data[col].dtype
+            ):
                 # series type may be 32/64bit.
                 # float or int
                 if self._is_int_column(raw_data[col]):

diff --git a/sdgx/data_models/metadata.py b/sdgx/data_models/metadata.py
@@ -98,10 +98,7 @@ def check_categorical_threshold(self, num_categories):
 
     def get_column_encoder(self, column_name):
         encoder_type = None
-        if (
-                self.categorical_encoder
-                and column_name in self.categorical_encoder
-        ):
+        if self.categorical_encoder and column_name in self.categorical_encoder:
             encoder_type = self.categorical_encoder[column_name]
         return encoder_type
 

diff --git a/sdgx/models/components/optimize/sdv_ctgan/data_transformer.py b/sdgx/models/components/optimize/sdv_ctgan/data_transformer.py
@@ -90,7 +90,9 @@ def _fit_discrete(self, data, encoder_type: CategoricalEncoderType = None):
         num_categories = len(encoder.dummies)
         activate_fn = "softmax"
 
-        checked = self.metadata.check_categorical_threshold(num_categories) if self.metadata else False
+        checked = (
+            self.metadata.check_categorical_threshold(num_categories) if self.metadata else False
+        )
         if encoder_type == "onehot" or not checked:
             pass
         elif encoder_type == "label":
@@ -127,7 +129,9 @@ def fit(self, data_loader: DataLoader, discrete_columns=()):
             if column_name in discrete_columns:
                 #  or column_name in self.metadata.label_columns
                 logger.debug(f"Fitting discrete column {column_name}...")
-                encoder_type = self.metadata.get_column_encoder(column_name) if self.metadata else None
+                encoder_type = (
+                    self.metadata.get_column_encoder(column_name) if self.metadata else None
+                )
                 column_transform_info = self._fit_discrete(data_loader[[column_name]], encoder_type)
             else:
                 logger.debug(f"Fitting continuous column {column_name}...")

diff --git a/tests/data_models/test_metadata.py b/tests/data_models/test_metadata.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from pathlib import Path
+
 import pytest
 
 from sdgx.data_connectors.csv_connector import CsvConnector