utils_encoding.py

4 F401: 'sklearn.preprocessing.KBinsDiscretizer' imported but unused (and 3 similar)
- 'sklearn.preprocessing.KBinsDiscretizer' imported but unused:
  3 from sklearn.preprocessing import KBinsDiscretizer, OneHotEncoder, MinMaxScaler, StandardScaler
- 'sklearn.preprocessing.MinMaxScaler' imported but unused:
  3 from sklearn.preprocessing import KBinsDiscretizer, OneHotEncoder, MinMaxScaler, StandardScaler
- 'sklearn.preprocessing.OneHotEncoder' imported but unused:
  3 from sklearn.preprocessing import KBinsDiscretizer, OneHotEncoder, MinMaxScaler, StandardScaler
- 'sklearn.preprocessing.StandardScaler' imported but unused:
  3 from sklearn.preprocessing import KBinsDiscretizer, OneHotEncoder, MinMaxScaler, StandardScaler
1 F821: undefined name 'encoded'
- 56 encoded = torch.cat((encoded, translated), 1) if col > 0 else translated
24 W293: blank line contains whitespace
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11 E501: line too long (95 > 79 characters) (and 7 similar)
- Line too long (95 > 79 characters):
  3 from sklearn.preprocessing import KBinsDiscretizer, OneHotEncoder, MinMaxScaler, StandardScaler
- Line too long (89 > 79 characters):
  10 Encodes categorical variables such as structural identifiers and degree features.
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  44 uniques, corrs = np.unique(tensor_list[:, col], return_inverse=True, axis=0)
- Line too long (94 > 79 characters):
  55 translated = torch.LongTensor(self.corrs[col][pointer:pointer+n]).unsqueeze(1)
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  56 encoded = torch.cat((encoded, translated), 1) if col > 0 else translated
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  66 self.d = [int(tensor_list[:,i].max()+1) for i in range(tensor_list.shape[1])]
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  72 # NB: this encoding scheme has been implemented, but never tested in experiments: use at your own risk.
- Line too long (81 > 79 characters):
  78 range_scaler = [0.0, 1.0] if kwargs['range'] is None else kwargs['range']
- Line too long (103 > 79 characters):
  100 # NB: this encoding scheme has been implemented, but never tested in experiments: use at your own risk.
- Line too long (94 > 79 characters):
  124 encoder = KBinsDiscretizer(n_bins=B, encode='ordinal', strategy=self.strategy)
- Line too long (83 > 79 characters):
  129 translated = result if col == 0 else torch.cat((translated, result), 1)
2 E231: missing whitespace after ','
- 65 tensor_list = torch.cat(tensor_list,0)
- 66 self.d = [int(tensor_list[:,i].max()+1) for i in range(tensor_list.shape[1])]
2 W291: trailing whitespace
- 47 return
- 72 # NB: this encoding scheme has been implemented, but never tested in experiments: use at your own risk.
1 W391: blank line at end of file
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