pyGPGO/surrogates/RandomForest.py
Killed 11 out of 33 mutantsSurvived
Survived mutation testing. These mutants show holes in your test suite.Mutant 125
--- pyGPGO/surrogates/RandomForest.py
+++ pyGPGO/surrogates/RandomForest.py
@@ -30,7 +30,7 @@
"""
self.X = X
self.y = y
- self.n = self.X.shape[0]
+ self.n = self.X.shape[1]
self.model = RandomForestRegressor(**self.params)
self.model.fit(X, y)
Mutant 126
--- pyGPGO/surrogates/RandomForest.py
+++ pyGPGO/surrogates/RandomForest.py
@@ -30,7 +30,7 @@
"""
self.X = X
self.y = y
- self.n = self.X.shape[0]
+ self.n = None
self.model = RandomForestRegressor(**self.params)
self.model.fit(X, y)
Mutant 128
--- pyGPGO/surrogates/RandomForest.py
+++ pyGPGO/surrogates/RandomForest.py
@@ -34,7 +34,7 @@
self.model = RandomForestRegressor(**self.params)
self.model.fit(X, y)
- def predict(self, Xstar, return_std = True, eps = 1e-6):
+ def predict(self, Xstar, return_std = False, eps = 1e-6):
"""
Predicts 'posterior' mean and variance for the RF model.
Mutant 129
--- pyGPGO/surrogates/RandomForest.py
+++ pyGPGO/surrogates/RandomForest.py
@@ -34,7 +34,7 @@
self.model = RandomForestRegressor(**self.params)
self.model.fit(X, y)
- def predict(self, Xstar, return_std = True, eps = 1e-6):
+ def predict(self, Xstar, return_std = True, eps = 1.000001):
"""
Predicts 'posterior' mean and variance for the RF model.
Mutant 137
--- pyGPGO/surrogates/RandomForest.py
+++ pyGPGO/surrogates/RandomForest.py
@@ -66,7 +66,7 @@
var_tree = tree.tree_.impurity[tree.apply(Xstar)]
var_tree = np.clip(var_tree, eps, np.inf)
mean_tree = tree.predict(Xstar)
- std += var_tree + mean_tree ** 2
+ std = var_tree + mean_tree ** 2
std /= len(trees)
std -= ymean ** 2
Mutant 138
--- pyGPGO/surrogates/RandomForest.py
+++ pyGPGO/surrogates/RandomForest.py
@@ -66,7 +66,7 @@
var_tree = tree.tree_.impurity[tree.apply(Xstar)]
var_tree = np.clip(var_tree, eps, np.inf)
mean_tree = tree.predict(Xstar)
- std += var_tree + mean_tree ** 2
+ std -= var_tree + mean_tree ** 2
std /= len(trees)
std -= ymean ** 2
Mutant 139
--- pyGPGO/surrogates/RandomForest.py
+++ pyGPGO/surrogates/RandomForest.py
@@ -66,7 +66,7 @@
var_tree = tree.tree_.impurity[tree.apply(Xstar)]
var_tree = np.clip(var_tree, eps, np.inf)
mean_tree = tree.predict(Xstar)
- std += var_tree + mean_tree ** 2
+ std += var_tree - mean_tree ** 2
std /= len(trees)
std -= ymean ** 2