From 430684fe507ca1a263a6e48bb5ce8ed1bc6763f9 Mon Sep 17 00:00:00 2001
From: "yzhao062@gmail.com" <9io9mZ9K#nNL>
Date: Fri, 23 Jun 2023 17:53:16 +0800
Subject: [PATCH] bug fix

---
 CHANGES.txt            |  1 +
 examples/cd_example.py |  1 -
 pyod/models/cd.py      | 22 ++++++++++++----------
 pyod/test/test_cd.py   |  1 -
 4 files changed, 13 insertions(+), 12 deletions(-)

diff --git a/CHANGES.txt b/CHANGES.txt
index b2ba2b591..c8fb2c9d6 100644
--- a/CHANGES.txt
+++ b/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.
\ No newline at end of file
diff --git a/examples/cd_example.py b/examples/cd_example.py
index 55db45b74..a8b91c7f3 100644
--- a/examples/cd_example.py
+++ b/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
diff --git a/pyod/models/cd.py b/pyod/models/cd.py
index 0b5ff2042..c321d51a4 100644
--- a/pyod/models/cd.py
+++ b/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()
diff --git a/pyod/test/test_cd.py b/pyod/test/test_cd.py
index 590fe7081..6bf50d093 100644
--- a/pyod/test/test_cd.py
+++ b/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