imblearn/pipeline.py
Killed 8 out of 37 mutantsSurvived
Survived mutation testing. These mutants show holes in your test suite.Mutant 24
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -119,7 +119,7 @@
self._validate_names(names)
# validate estimators
- transformers = estimators[:-1]
+ transformers = estimators[:+1]
estimator = estimators[-1]
for t in transformers:
Mutant 25
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -119,7 +119,7 @@
self._validate_names(names)
# validate estimators
- transformers = estimators[:-1]
+ transformers = estimators[:-2]
estimator = estimators[-1]
for t in transformers:
Mutant 27
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -120,7 +120,7 @@
# validate estimators
transformers = estimators[:-1]
- estimator = estimators[-1]
+ estimator = estimators[+1]
for t in transformers:
if t is None or t == "passthrough":
Mutant 28
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -120,7 +120,7 @@
# validate estimators
transformers = estimators[:-1]
- estimator = estimators[-1]
+ estimator = estimators[-2]
for t in transformers:
if t is None or t == "passthrough":
Mutant 29
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -120,7 +120,7 @@
# validate estimators
transformers = estimators[:-1]
- estimator = estimators[-1]
+ estimator = None
for t in transformers:
if t is None or t == "passthrough":
Mutant 30
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -123,7 +123,7 @@
estimator = estimators[-1]
for t in transformers:
- if t is None or t == "passthrough":
+ if t is not None or t == "passthrough":
continue
if not (
hasattr(t, "fit")
Mutant 31
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -123,7 +123,7 @@
estimator = estimators[-1]
for t in transformers:
- if t is None or t == "passthrough":
+ if t is None or t != "passthrough":
continue
if not (
hasattr(t, "fit")
Mutant 32
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -123,7 +123,7 @@
estimator = estimators[-1]
for t in transformers:
- if t is None or t == "passthrough":
+ if t is None or t == "XXpassthroughXX":
continue
if not (
hasattr(t, "fit")
Mutant 33
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -123,7 +123,7 @@
estimator = estimators[-1]
for t in transformers:
- if t is None or t == "passthrough":
+ if t is None and t == "passthrough":
continue
if not (
hasattr(t, "fit")
Mutant 34
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -126,7 +126,7 @@
if t is None or t == "passthrough":
continue
if not (
- hasattr(t, "fit")
+ hasattr(t, "XXfitXX")
or hasattr(t, "fit_transform")
or hasattr(t, "fit_resample")
) or not (hasattr(t, "transform") or hasattr(t, "fit_resample")):
Mutant 36
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -129,7 +129,7 @@
hasattr(t, "fit")
or hasattr(t, "fit_transform")
or hasattr(t, "fit_resample")
- ) or not (hasattr(t, "transform") or hasattr(t, "fit_resample")):
+ ) or not (hasattr(t, "XXtransformXX") or hasattr(t, "fit_resample")):
raise TypeError(
"All intermediate steps of the chain should "
"be estimators that implement fit and transform or "
Mutant 39
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -129,7 +129,7 @@
hasattr(t, "fit")
or hasattr(t, "fit_transform")
or hasattr(t, "fit_resample")
- ) or not (hasattr(t, "transform") or hasattr(t, "fit_resample")):
+ ) and not (hasattr(t, "transform") or hasattr(t, "fit_resample")):
raise TypeError(
"All intermediate steps of the chain should "
"be estimators that implement fit and transform or "
Mutant 40
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -137,7 +137,7 @@
"'%s' (type %s) doesn't)" % (t, type(t))
)
- if hasattr(t, "fit_resample") and (
+ if hasattr(t, "XXfit_resampleXX") and (
hasattr(t, "fit_transform") or hasattr(t, "transform")
):
raise TypeError(
Mutant 41
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -138,7 +138,7 @@
)
if hasattr(t, "fit_resample") and (
- hasattr(t, "fit_transform") or hasattr(t, "transform")
+ hasattr(t, "XXfit_transformXX") or hasattr(t, "transform")
):
raise TypeError(
"All intermediate steps of the chain should "
Mutant 42
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -138,7 +138,7 @@
)
if hasattr(t, "fit_resample") and (
- hasattr(t, "fit_transform") or hasattr(t, "transform")
+ hasattr(t, "fit_transform") or hasattr(t, "XXtransformXX")
):
raise TypeError(
"All intermediate steps of the chain should "
Mutant 43
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -138,7 +138,7 @@
)
if hasattr(t, "fit_resample") and (
- hasattr(t, "fit_transform") or hasattr(t, "transform")
+ hasattr(t, "fit_transform") and hasattr(t, "transform")
):
raise TypeError(
"All intermediate steps of the chain should "
Mutant 44
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -155,7 +155,7 @@
# We allow last estimator to be None as an identity transformation
if (
- estimator is not None
+ estimator is None
and estimator != "passthrough"
and not hasattr(estimator, "fit")
):
Mutant 45
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -156,7 +156,7 @@
# We allow last estimator to be None as an identity transformation
if (
estimator is not None
- and estimator != "passthrough"
+ and estimator == "passthrough"
and not hasattr(estimator, "fit")
):
raise TypeError(
Mutant 46
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -156,7 +156,7 @@
# We allow last estimator to be None as an identity transformation
if (
estimator is not None
- and estimator != "passthrough"
+ and estimator != "XXpassthroughXX"
and not hasattr(estimator, "fit")
):
raise TypeError(
Mutant 50
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -166,7 +166,7 @@
)
def _iter(
- self, with_final=True, filter_passthrough=True, filter_resample=True
+ self, with_final=False, filter_passthrough=True, filter_resample=True
):
"""Generate (idx, (name, trans)) tuples from self.steps.
Mutant 51
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -166,7 +166,7 @@
)
def _iter(
- self, with_final=True, filter_passthrough=True, filter_resample=True
+ self, with_final=True, filter_passthrough=False, filter_resample=True
):
"""Generate (idx, (name, trans)) tuples from self.steps.
Mutant 52
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -166,7 +166,7 @@
)
def _iter(
- self, with_final=True, filter_passthrough=True, filter_resample=True
+ self, with_final=True, filter_passthrough=True, filter_resample=False
):
"""Generate (idx, (name, trans)) tuples from self.steps.
Mutant 53
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -358,7 +358,7 @@
elif hasattr(last_step, "fit_resample"):
return last_step.fit_resample(Xt, yt, **fit_params)
- @if_delegate_has_method(delegate="_final_estimator")
+ @if_delegate_has_method(delegate="XX_final_estimatorXX")
def fit_predict(self, X, y=None, **fit_params):
"""Apply `fit_predict` of last step in pipeline after transforms.
Mutant 54
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -358,7 +358,6 @@
elif hasattr(last_step, "fit_resample"):
return last_step.fit_resample(Xt, yt, **fit_params)
- @if_delegate_has_method(delegate="_final_estimator")
def fit_predict(self, X, y=None, **fit_params):
"""Apply `fit_predict` of last step in pipeline after transforms.
Mutant 55
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -449,7 +449,7 @@
Pipeline(steps=[('standardscaler', StandardScaler()),
('gaussiannb', GaussianNB())])
"""
- memory = kwargs.pop("memory", None)
+ memory = kwargs.pop("XXmemoryXX", None)
verbose = kwargs.pop('verbose', False)
if kwargs:
raise TypeError(
Mutant 56
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -449,7 +449,7 @@
Pipeline(steps=[('standardscaler', StandardScaler()),
('gaussiannb', GaussianNB())])
"""
- memory = kwargs.pop("memory", None)
+ memory = None
verbose = kwargs.pop('verbose', False)
if kwargs:
raise TypeError(
Mutant 57
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -450,7 +450,7 @@
('gaussiannb', GaussianNB())])
"""
memory = kwargs.pop("memory", None)
- verbose = kwargs.pop('verbose', False)
+ verbose = kwargs.pop('XXverboseXX', False)
if kwargs:
raise TypeError(
'Unknown keyword arguments: "{}"'.format(list(kwargs.keys())[0])
Mutant 58
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -450,7 +450,7 @@
('gaussiannb', GaussianNB())])
"""
memory = kwargs.pop("memory", None)
- verbose = kwargs.pop('verbose', False)
+ verbose = kwargs.pop('verbose', True)
if kwargs:
raise TypeError(
'Unknown keyword arguments: "{}"'.format(list(kwargs.keys())[0])
Mutant 59
--- imblearn/pipeline.py
+++ imblearn/pipeline.py
@@ -450,7 +450,7 @@
('gaussiannb', GaussianNB())])
"""
memory = kwargs.pop("memory", None)
- verbose = kwargs.pop('verbose', False)
+ verbose = None
if kwargs:
raise TypeError(
'Unknown keyword arguments: "{}"'.format(list(kwargs.keys())[0])