imports, more systematically

benchmarks/analyse_rankings.py

@@ -6,6 +6,7 @@
 
 import matplotlib.pyplot as plt
 
+
 def extract_just_ranking(dfile):
     """Extract ranking from an output file."""
     ranks = []

outrank/__main__.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 import argparse
-import json
 import logging
 
 from outrank.task_generators import outrank_task_generate_data_set

outrank/algorithms/importance_estimator.py

@@ -11,15 +11,15 @@
 import pandas as pd
 from scipy.stats import pearsonr
 from sklearn.feature_selection import mutual_info_classif
-from sklearn.linear_model import LogisticRegression, SGDClassifier
+from sklearn.linear_model import LogisticRegression
+from sklearn.linear_model import SGDClassifier
 from sklearn.metrics import adjusted_mutual_info_score
 from sklearn.model_selection import cross_val_score
 from sklearn.preprocessing import OneHotEncoder
 from sklearn.svm import SVC
 
 from outrank.core_utils import is_prior_heuristic
 
-
 logger = logging.getLogger('syn-logger')
 logger.setLevel(logging.DEBUG)
 
@@ -43,11 +43,11 @@ def sklearn_MI(vector_first: Any, vector_second: Any) -> float:
 
 
 def sklearn_surrogate(
-    vector_first: Any, vector_second: Any, X: Any, surrogate_model: str
+    vector_first: Any, vector_second: Any, X: Any, surrogate_model: str,
 ) -> float:
-    
+
     clf = initialize_classifier(surrogate_model)
-    
+
     transf = OneHotEncoder()
 
     # They do not commute, swap if needed
@@ -67,7 +67,7 @@ def sklearn_surrogate(
         clf, X, vector_second, scoring='neg_log_loss', cv=num_folds,
     )
     estimate_feature_importance = 1 + \
-        np.median(estimate_feature_importance_list)        
+        np.median(estimate_feature_importance_list)
 
     return estimate_feature_importance
 
@@ -127,7 +127,7 @@ def get_importances_estimate_pairwise(combination, reference_model_features, arg
             X = tmp_df[reference_model_features].values
 
         estimate_feature_importance = sklearn_surrogate(
-            vector_first, vector_second, X, args.heuristic
+            vector_first, vector_second, X, args.heuristic,
         )
 
     elif 'MI-numba' in args.heuristic:

outrank/core_ranking.py

@@ -21,11 +21,12 @@
 import pandas as pd
 import tqdm
 
-from outrank.algorithms.importance_estimator import get_importances_estimate_pairwise
-from outrank.algorithms.sketches.counting_counters_ordinary import PrimitiveConstrainedCounter
-from outrank.algorithms.sketches.counting_ultiloglog import (
-    HyperLogLogWCache as HyperLogLog,
-)
+from outrank.algorithms.importance_estimator import \
+    get_importances_estimate_pairwise
+from outrank.algorithms.sketches.counting_counters_ordinary import \
+    PrimitiveConstrainedCounter
+from outrank.algorithms.sketches.counting_ultiloglog import \
+    HyperLogLogWCache as HyperLogLog
 from outrank.core_utils import BatchRankingSummary
 from outrank.core_utils import extract_features_from_reference_JSON
 from outrank.core_utils import generic_line_parser

outrank/feature_transformations/feature_transformer_vault/__init__.py

@@ -2,9 +2,8 @@
 
 from outrank.feature_transformations.feature_transformer_vault.default_transformers import DEFAULT_TRANSFORMERS
 from outrank.feature_transformations.feature_transformer_vault.default_transformers import MINIMAL_TRANSFORMERS
-from outrank.feature_transformations.feature_transformer_vault.fw_transformers import (
-    FW_TRANSFORMERS,
-)
+from outrank.feature_transformations.feature_transformer_vault.fw_transformers import \
+    FW_TRANSFORMERS
 
 _tr_global_namespace = {
     'default': DEFAULT_TRANSFORMERS,

outrank/feature_transformations/feature_transformer_vault/default_transformers.py

@@ -1,5 +1,6 @@
 # Some boilerplate transformations people tend to use
 from __future__ import annotations
+
 MINIMAL_TRANSFORMERS = {
     '_tr_sqrt': 'np.sqrt(X)',
     '_tr_log(x+1)': 'np.log(X + 1)',

outrank/feature_transformations/feature_transformer_vault/fw_transformers.py

@@ -2,9 +2,8 @@
 
 import numpy as np
 
-from outrank.feature_transformations.feature_transformer_vault.default_transformers import (
-    DEFAULT_TRANSFORMERS,
-)
+from outrank.feature_transformations.feature_transformer_vault.default_transformers import \
+    DEFAULT_TRANSFORMERS
 
 FW_TRANSFORMERS = DEFAULT_TRANSFORMERS.copy()
 resolution_range = [1, 10, 50, 100]

outrank/task_selftest.py

@@ -1,5 +1,6 @@
 # helper set of methods that enable anywhere verification of core functions
 from __future__ import annotations
+
 import logging
 import os
 import shutil

tests/fw_transformers_test.py

@@ -5,9 +5,8 @@
 
 import numpy as np
 
-from outrank.feature_transformations.feature_transformer_vault.fw_transformers import (
-    FW_TRANSFORMERS,
-)
+from outrank.feature_transformations.feature_transformer_vault.fw_transformers import \
+    FW_TRANSFORMERS
 
 sys.path.append('./outrank')
 

tests/hll_test.py

@@ -3,9 +3,8 @@
 import sys
 import unittest
 
-from outrank.algorithms.sketches.counting_ultiloglog import (
-    HyperLogLogWCache as HyperLogLog,
-)
+from outrank.algorithms.sketches.counting_ultiloglog import \
+    HyperLogLogWCache as HyperLogLog
 
 sys.path.append('./outrank')
 

tests/mi_numba_test.py

@@ -5,9 +5,8 @@
 
 import numpy as np
 
-from outrank.algorithms.feature_ranking.ranking_mi_numba import (
-    mutual_info_estimator_numba,
-)
+from outrank.algorithms.feature_ranking.ranking_mi_numba import \
+    mutual_info_estimator_numba
 
 np.random.seed(123)
 sys.path.append('./outrank')

tests/ranking_module_test.py

@@ -12,12 +12,10 @@
 from outrank.core_ranking import compute_combined_features
 from outrank.core_ranking import get_combinations_from_columns
 from outrank.core_ranking import mixed_rank_graph
-from outrank.feature_transformations.feature_transformer_vault import (
-    default_transformers,
-)
-from outrank.feature_transformations.ranking_transformers import (
-    FeatureTransformerGeneric,
-)
+from outrank.feature_transformations.feature_transformer_vault import \
+    default_transformers
+from outrank.feature_transformations.ranking_transformers import \
+    FeatureTransformerGeneric
 
 sys.path.append('./outrank')