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[MRG] Fixing wrapping in named_test.test_common #8558

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[MRG] Fixing wrapping in named_test.test_common #8558

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4911e73
Fix improper wrapping
kahnchana Mar 8, 2017
c550ab8
Fix wrapping of test_sample_weight_invariance function
kahnchana Mar 8, 2017
451a30c
wrapping improved
kahnchana Mar 9, 2017
5874a08
wrapping
kahnchana Mar 9, 2017
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25 changes: 16 additions & 9 deletions sklearn/metrics/tests/test_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -369,11 +369,11 @@

# No Sample weight support
METRICS_WITHOUT_SAMPLE_WEIGHT = [
"confusion_matrix", # Left this one here because the tests in this file do
# not work for confusion_matrix, as its output is a
# matrix instead of a number. Testing of
# confusion_matrix with sample_weight is in
# test_classification.py
"confusion_matrix", # Left this one here because the tests in this file do
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This is fine for now but from next time kindly avoid unrelated changes :)

# not work for confusion_matrix, as its output is a
# matrix instead of a number. Testing of
# confusion_matrix with sample_weight is in
# test_classification.py
"median_absolute_error",
]

Expand Down Expand Up @@ -619,9 +619,9 @@ def test_invariance_string_vs_numbers_labels():


def test_inf_nan_input():
invalids =[([0, 1], [np.inf, np.inf]),
([0, 1], [np.nan, np.nan]),
([0, 1], [np.nan, np.inf])]
invalids = [([0, 1], [np.inf, np.inf]),
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same comment as above

([0, 1], [np.nan, np.nan]),
([0, 1], [np.nan, np.inf])]

METRICS = dict()
METRICS.update(THRESHOLDED_METRICS)
Expand Down Expand Up @@ -1011,7 +1011,8 @@ def check_sample_weight_invariance(name, metric, y1, y2):
sample_weight=np.hstack([sample_weight, sample_weight]))


def test_sample_weight_invariance(n_samples=50):
def generate_sample_weight_invariance(n_samples=50):
# create generative function to iterate through each relevant metric
random_state = check_random_state(0)
# regression
y_true = random_state.random_sample(size=(n_samples,))
Expand Down Expand Up @@ -1088,6 +1089,12 @@ def test_sample_weight_invariance(n_samples=50):
metric, y_true, y_pred)


def test_sample_weight_invariance(n_samples=50):
# iterate through each metric testing each case
for metrics in generate_sample_weight_invariance(n_samples):
pass
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I don't understand the original issue as I commented there and I don't think you need this since nose supports yield in test functions ...



@ignore_warnings
def test_no_averaging_labels():
# test labels argument when not using averaging
Expand Down