def test_float_range_2():
"""Assert that the TPOT CLI interface's float range throws an exception when input it out of range"""
try:
float_range('2.0')
assert False # Should be unreachable
except Exception:
pass
def test_float_range_3():
"""Assert that the TPOT CLI interface's float range throws an exception when input is not a float"""
try:
float_range('foobar')
assert False # Should be unreachable
except Exception:
pass
def test_predict_proba2():
"""Assert that the TPOT predict_proba function returns a numpy matrix filled with probabilities (float)"""
tpot_obj = TPOTClassifier()
pipeline_string = (
'DecisionTreeClassifier(input_matrix, DecisionTreeClassifier__criterion=gini'
', DecisionTreeClassifier__max_depth=8,DecisionTreeClassifier__min_samples_leaf=5,'
'DecisionTreeClassifier__min_samples_split=5)')
tpot_obj._optimized_pipeline = creator.Individual.from_string(
pipeline_string, tpot_obj._pset)
tpot_obj._fitted_pipeline = tpot_obj._toolbox.compile(
expr=tpot_obj._optimized_pipeline)
tpot_obj._fitted_pipeline.fit(training_features, training_classes)
result = tpot_obj.predict_proba(testing_features)
rows = result.shape[0]
columns = result.shape[1]
try:
for i in range(rows):
for j in range(columns):
float_range(result[i][j])
assert True
except Exception:
assert False
def test_float_range_3():
"""Assert that the TPOT CLI interface's float range throws an exception when input is not a float"""
try:
float_range('foobar')
assert False # Should be unreachable
except Exception:
pass
def test_float_range_2():
"""Assert that the TPOT CLI interface's float range throws an exception when input it out of range"""
try:
float_range('2.0')
assert False # Should be unreachable
except Exception:
pass
def test_predict_proba2():
"""Assert that the TPOT predict_proba function returns a numpy matrix filled with probabilities (float)"""
tpot_obj = TPOTClassifier()
pipeline_string= ('DecisionTreeClassifier(input_matrix, DecisionTreeClassifier__criterion=gini'
', DecisionTreeClassifier__max_depth=8,DecisionTreeClassifier__min_samples_leaf=5,'
'DecisionTreeClassifier__min_samples_split=5)')
tpot_obj._optimized_pipeline = creator.Individual.from_string(pipeline_string, tpot_obj._pset)
tpot_obj._fitted_pipeline = tpot_obj._toolbox.compile(expr=tpot_obj._optimized_pipeline)
tpot_obj._fitted_pipeline.fit(training_features, training_classes)
result = tpot_obj.predict_proba(testing_features)
rows = result.shape[0]
columns = result.shape[1]
try:
for i in range(rows):
for j in range(columns):
float_range(result[i][j])
assert True
except Exception:
assert False
def test_float_range():
"""Assert that the TPOT CLI interface's float range returns a float with input is in 0. - 1.0."""
assert 0.5 == float_range('0.5')
def test_float_range():
"""Assert that the TPOT CLI interface's float range returns a float with input is in 0. - 1.0."""
assert 0.5 == float_range('0.5')
