Update black formatting

MindSetLib · May 7, 2024 · e99e729 · e99e729
1 parent b65751a
commit e99e729
Show file tree

Hide file tree

Showing 6 changed files with 40 additions and 19 deletions.
diff --git a/insolver/interpretation/shap.py b/insolver/interpretation/shap.py
@@ -22,8 +22,10 @@ def __init__(self, estimator, estimator_type='tree', data=None):
         self.estimator_type = estimator_type
 
         if self.estimator_type not in ['tree', 'linear']:
-            raise NotImplementedError(f'''
-            estimator_type {estimator_type} is not supported. Supported values are "tree" and "linear".''')
+            raise NotImplementedError(
+                f'''
+            estimator_type {estimator_type} is not supported. Supported values are "tree" and "linear".'''
+            )
 
         self.explainer = (
             TreeExplainer(self.estimator)
@@ -75,8 +77,10 @@ def logit(x):
 
         # check type of instance
         if not isinstance(instance, np.ndarray) and not isinstance(instance, pd.Series):
-            raise TypeError(f'''
-            Type {type(instance)} is not supported. Supported types are numpy.ndarray and pandas.Series.''')
+            raise TypeError(
+                f'''
+            Type {type(instance)} is not supported. Supported types are numpy.ndarray and pandas.Series.'''
+            )
         # get feature_names OR check shape and create features names
         if isinstance(instance, pd.Series):
             feature_names = list(instance.index)

diff --git a/insolver/report/metrics.py b/insolver/report/metrics.py
@@ -148,8 +148,10 @@ def _calc_metrics(y_true, y_pred, task, metrics_to_calc, x, exposure=None):
         elif isinstance(metrics_to_calc, list):
             functions_names = metrics_to_calc
         else:
-            raise TypeError(f'''{type(metrics_to_calc)} type of metrics_to_calc is not supported.
-                            Must be "all", "main" or list.''')
+            raise TypeError(
+                f'''{type(metrics_to_calc)} type of metrics_to_calc is not supported.
+                            Must be "all", "main" or list.'''
+            )
 
         result['root_mean_square_error'] = np.sqrt(functions['mean_squared_error'](y_true, y_pred))
 
@@ -167,8 +169,10 @@ def _calc_metrics(y_true, y_pred, task, metrics_to_calc, x, exposure=None):
             elif isinstance(metrics_to_calc, list):
                 functions_names = metrics_to_calc
             else:
-                raise TypeError(f'''{type(metrics_to_calc)} type of metrics_to_calc is not supported.
-                                Must be "all", "main" or list.''')
+                raise TypeError(
+                    f'''{type(metrics_to_calc)} type of metrics_to_calc is not supported.
+                                Must be "all", "main" or list.'''
+                )
 
         elif type_of_true == 'binary' and type_of_pred == 'continuous':
             functions_names = (
@@ -180,8 +184,10 @@ def _calc_metrics(y_true, y_pred, task, metrics_to_calc, x, exposure=None):
 
     for name in functions_names:
         if name not in functions.keys():
-            raise NotImplementedError(f'''{name} metric name is not supported. Supported names for {task} task:
-                                      {functions.keys()}.''')
+            raise NotImplementedError(
+                f'''{name} metric name is not supported. Supported names for {task} task:
+                                      {functions.keys()}.'''
+            )
         try:
             if name == 'gini_coef' and exposure:
                 result[name] = functions[name](y_true, y_pred, x[exposure])[2]

diff --git a/insolver/report/report.py b/insolver/report/report.py
@@ -186,20 +186,24 @@ def __init__(
             self.y_test = y_test
             self.original_dataset = original_dataset
         else:
-            raise TypeError(f"""Wrong types of input data.
+            raise TypeError(
+                f"""Wrong types of input data.
               \rX_train {type(X_train)} must be pandas.DataFrame
               \ry_train {type(y_train)} must be pandas.Series
               \rX_test {type(X_test)} must be pandas.DataFrame
               \ry_test {type(y_test)} should be pandas.Series
               \rpredicted_train {type(self.predicted_train)} must be pandas.Series
               \rpredicted_test {type(self.predicted_test)} must be pandas.Series
-              \rpredicted_test {type(original_dataset)} must be pandas.DataFrame""")
+              \rpredicted_test {type(original_dataset)} must be pandas.DataFrame"""
+            )
         self._directory = ntpath.dirname(inspect.getfile(Report))
 
         # check columns
         if not sorted(X_train.columns.to_list()) == sorted(X_test.columns.to_list()):
-            raise KeyError(f'''Columns in X_train {sorted(X_train.columns.to_list())}
-            and X_test {sorted(X_test.columns.to_list())} are not the same.''')
+            raise KeyError(
+                f'''Columns in X_train {sorted(X_train.columns.to_list())}
+            and X_test {sorted(X_test.columns.to_list())} are not the same.'''
+            )
         elif len(set(X_train.columns.to_list()).difference(original_dataset.columns.to_list())) > 0:
             s = set(X_train.columns.to_list()).difference(original_dataset.columns.to_list())
             raise KeyError(f'''Columns from X_train {s} are missing from original_dataset.''')
@@ -324,9 +328,11 @@ def _save_model_section(self, path, report_name):
                 'articles': [
                     {
                         'name': 'Coefficients',
-                        'parts': [f'''
+                        'parts': [
+                            f'''
                         <div class="p-3 m-3 bg-light border rounded-3 fw-light">
-                            {features_importance}{_create_importance_charts()}</div>'''],
+                            {features_importance}{_create_importance_charts()}</div>'''
+                        ],
                         'header': '',
                         'footer': features_importance_footer,
                         'icon': '<i class="bi bi-bar-chart-line"></i>',
@@ -347,9 +353,11 @@ def _save_model_section(self, path, report_name):
                     },
                     {
                         'name': 'Partial Dependence',
-                        'parts': [f'''
+                        'parts': [
+                            f'''
                         <div class="p-3 m-3 bg-light border rounded-3 text-center fw-light">
-                            {pdp_part}</div>'''],
+                            {pdp_part}</div>'''
+                        ],
                         'header': '',
                         'footer': pdp_footer,
                         'icon': '<i class="bi bi-graph-up"></i>',

diff --git a/requirements-dev.txt b/requirements-dev.txt
@@ -1,4 +1,4 @@
-black>=22.6.0
+black[jupyter]==24.4.2
 mypy>=0.971
 pre-commit>=2.19.0
 pytest>=6.2.5

diff --git a/tutorials/Binary Classification Example - Rain in Australia Prediction.ipynb b/tutorials/Binary Classification Example - Rain in Australia Prediction.ipynb
@@ -1834,6 +1834,7 @@
    ],
    "source": [
     "%%time\n",
+    "\n",
     "igbm = show_results(InsolverGBMWrapper(backend='lightgbm', task='class', n_estimators=100), x, y)"
    ]
   },
@@ -1980,6 +1981,7 @@
    ],
    "source": [
     "%%time\n",
+    "\n",
     "igbm3 = show_results(InsolverGBMWrapper(backend='xgboost', task='class', n_estimators=100), x, y)"
    ]
   },

diff --git a/tutorials/Regression Example - US Accidents.ipynb b/tutorials/Regression Example - US Accidents.ipynb
@@ -16,6 +16,7 @@
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
+    "\n",
     "import numpy as np\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",