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[MRG + 1]Deprecating 1D inputs in fast_mcd #5234

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Merged
merged 1 commit into from
Oct 12, 2015
Merged

[MRG + 1]Deprecating 1D inputs in fast_mcd #5234

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8 changes: 2 additions & 6 deletions sklearn/covariance/robust_covariance.py
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Original file line number Diff line number Diff line change
Expand Up @@ -361,11 +361,7 @@ def fast_mcd(X, support_fraction=None,
"""
random_state = check_random_state(random_state)

X = np.asarray(X)
if X.ndim == 1:
X = np.reshape(X, (1, -1))
warnings.warn("Only one sample available. "
"You may want to reshape your data array")
X = check_array(X, ensure_min_samples=2, estimator='fast_mcd')
n_samples, n_features = X.shape

# minimum breakdown value
Expand Down Expand Up @@ -609,7 +605,7 @@ def fit(self, X, y=None):
Returns self.

"""
X = check_array(X)
X = check_array(X, ensure_min_samples=2, estimator='MinCovDet')
random_state = check_random_state(self.random_state)
n_samples, n_features = X.shape
# check that the empirical covariance is full rank
Expand Down
17 changes: 16 additions & 1 deletion sklearn/covariance/tests/test_robust_covariance.py
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Expand Up @@ -8,12 +8,14 @@

from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_raises, assert_warns
from sklearn.utils.testing import assert_raise_message
from sklearn.utils.validation import NotFittedError

from sklearn import datasets
from sklearn.covariance import empirical_covariance, MinCovDet, \
EllipticEnvelope
from sklearn.covariance import fast_mcd

X = datasets.load_iris().data
X_1d = X[:, 0]
Expand All @@ -40,6 +42,19 @@ def test_mcd():
launch_mcd_on_dataset(500, 1, 100, 0.001, 0.001, 350)


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To be consistent with the style of the other functions in this file and the project in general, please remove this blank line.

def test_fast_mcd_on_invalid_input():
X = np.arange(100)
assert_raise_message(ValueError, 'fast_mcd expects at least 2 samples',
fast_mcd, X)


def test_mcd_class_on_invalid_input():
X = np.arange(100)
mcd = MinCovDet()
assert_raise_message(ValueError, 'MinCovDet expects at least 2 samples',
mcd.fit, X)


def launch_mcd_on_dataset(n_samples, n_features, n_outliers, tol_loc, tol_cov,
tol_support):

Expand Down
4 changes: 4 additions & 0 deletions sklearn/utils/validation.py
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Expand Up @@ -374,6 +374,10 @@ def check_array(array, accept_sparse=None, dtype="numeric", order=None,

if ensure_2d:
if array.ndim == 1:
if ensure_min_samples >= 2:
raise ValueError("%s expects at least 2 samples provided "
"in a 2 dimensional array-like input"
% estimator_name)
warnings.warn(
"Passing 1d arrays as data is deprecated in 0.17 and will"
"raise ValueError in 0.19. Reshape your data either using "
Expand Down