bug fix

CHANGES.txt

@@ -177,3 +177,4 @@ v<1.0.8>, <03/08/2023> -- Improve clone compatibility (#471).
 v<1.0.8>, <03/08/2023> -- Add QMCD detector (#452).
 v<1.0.8>, <03/08/2023> -- Optimized ECDF and drop Statsmodels dependency (#467).
 v<1.0.9>, <03/19/2023> -- Hot fix for errors in ECOD and COPOD due to the issue of scipy.
+v<1.0.9>, <06/19/2023> -- Further integration of PyThresh.

examples/cd_example.py

@@ -15,7 +15,6 @@
 sys.path.append(
  os.path.abspath(os.path.join(os.path.dirname("__file__"), '..')))
 
-import numpy as np
 from pyod.models.cd import CD
 from pyod.utils.data import generate_data
 from pyod.utils.data import evaluate_print

pyod/models/cd.py

@@ -15,6 +15,7 @@
 
 from .base import BaseDetector
 
+
 def _Cooks_dist(X, y, model):
  """Calculated the Cook's distance
 
@@ -45,20 +46,22 @@ def _Cooks_dist(X, y, model):
  # Compute the MSE from the residuals
  residuals = y - model.predict(X)
  mse = np.dot(residuals, residuals) / df
- 
+
  # Compute Cook's distance
- if (mse!=0) or (mse!=np.nan):
- residuals_studentized = residuals / np.sqrt(mse) / np.sqrt(1 - leverage)
+ if (mse != 0) or (mse != np.nan):
+ residuals_studentized = residuals / np.sqrt(mse) / np.sqrt(
+ 1 - leverage)
  distance_ = residuals_studentized ** 2 / X.shape[1]
  distance_ *= leverage / (1 - leverage)
  distance_ = ((distance_ - distance_.min())
- / (distance_.max() - distance_.min()))
+  / (distance_.max() - distance_.min()))
 
  else:
- distance_ = np.ones(len(y))*np.nan
+ distance_ = np.ones(len(y)) * np.nan
 
  return distance_
 
+
 def _process_distances(X, model):
  """Calculated the mean Cook's distances for
  each feature
@@ -79,15 +82,14 @@ def _process_distances(X, model):
 
  distances_ = []
  for i in range(X.shape[1]):
-
  mod = model
 
  # Extract new X and y inputs
  exp = np.delete(X.copy(), i, axis=1)
- resp = X[:,i]
+ resp = X[:, i]
+
+ exp = exp.reshape(-1, 1) if exp.ndim == 1 else exp
 
- exp = exp.reshape(-1,1) if exp.ndim == 1 else exp
-
  # Fit the model
  mod.fit(exp, resp)
 
@@ -168,7 +170,7 @@ def fit(self, X, y=None):
 
  # Get Cook's distance
  distances_ = _process_distances(X, self.model)
- 
+
  self.decision_scores_ = distances_
 
  self._process_decision_scores()

pyod/test/test_cd.py

@@ -6,7 +6,6 @@
 import sys
 import unittest
 
-import numpy as np
 # noinspection PyProtectedMember
 from numpy.testing import assert_equal
 from numpy.testing import assert_raises