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[MRG] Deprecate use_pca parameter of LMNN #231

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Merged
merged 2 commits into from
Jul 4, 2019
Merged

[MRG] Deprecate use_pca parameter of LMNN #231

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fbb6f13
deprecate use_pca
bellet Jul 3, 2019
f77ddd9
fix failing test
bellet Jul 3, 2019
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13 changes: 12 additions & 1 deletion metric_learn/lmnn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,6 +87,12 @@ class LMNN(MahalanobisMixin, TransformerMixin):
Tolerance of the optimization procedure. If the objective value varies
less than `tol`, we consider the algorithm has converged and stop it.

use_pca : Not used

.. deprecated:: 0.5.0
`use_pca` was deprecated in version 0.5.0 and will
be removed in 0.6.0.

verbose : bool, optional (default=False)
Whether to print the progress of the optimization procedure.

Expand Down Expand Up @@ -151,7 +157,7 @@ class LMNN(MahalanobisMixin, TransformerMixin):

def __init__(self, init=None, k=3, min_iter=50, max_iter=1000,
learn_rate=1e-7, regularization=0.5, convergence_tol=0.001,
use_pca=True, verbose=False, preprocessor=None,
use_pca='deprecated', verbose=False, preprocessor=None,
n_components=None, num_dims='deprecated', random_state=None):
self.init = init
self.k = k
Expand All @@ -173,6 +179,11 @@ def fit(self, X, y):
' It has been deprecated in version 0.5.0 and will be'
' removed in 0.6.0. Use "n_components" instead',
DeprecationWarning)
if self.use_pca != 'deprecated':
warnings.warn('"use_pca" parameter is not used.'
' It has been deprecated in version 0.5.0 and will be'
' removed in 0.6.0.',
DeprecationWarning)
k = self.k
reg = self.regularization
learn_rate = self.learn_rate
Expand Down
12 changes: 12 additions & 0 deletions test/metric_learn_test.py
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Expand Up @@ -291,6 +291,18 @@ def test_changed_behaviour_warning(self):
lmnn.fit(X, y)
assert any(msg == str(wrn.message) for wrn in raised_warning)

def test_deprecation_use_pca(self):
# test that a DeprecationWarning is thrown about use_pca, if the
# default parameters are used.
# TODO: remove in v.0.6
X = np.array([[0, 0], [0, 1], [2, 0], [2, 1]])
y = np.array([1, 0, 1, 0])
lmnn = LMNN(k=2, use_pca=True)
msg = ('"use_pca" parameter is not used.'
' It has been deprecated in version 0.5.0 and will be'
' removed in 0.6.0.')
assert_warns_message(DeprecationWarning, msg, lmnn.fit, X, y)


@pytest.mark.parametrize('X, y, loss', [(np.array([[0], [1], [2], [3]]),
[1, 1, 0, 0], 3.0),
Expand Down
2 changes: 1 addition & 1 deletion test/test_base_metric.py
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Expand Up @@ -26,7 +26,7 @@ def test_lmnn(self):
"learn_rate=1e-07, "
"max_iter=1000, min_iter=50, n_components=None, "
"num_dims='deprecated', preprocessor=None, random_state=None, "
"regularization=0.5, use_pca=True, verbose=False)"))
"regularization=0.5, use_pca='deprecated', verbose=False)"))

def test_nca(self):
self.assertEqual(remove_spaces(str(metric_learn.NCA())),
Expand Down