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MAINT Clean up deprecations for 1.6: in make_sparse_spd_matrix #30214

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Nov 5, 2024
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MAINT Clean up deprecations for 1.6: in make_sparse_spd_matrix #30214

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0c2cfa5
cln deprecations
jeremiedbb Nov 4, 2024
85da6e9
Merge branch 'main' into cln-deprecations-1.6-make_sparse_spd_matrix
jeremiedbb Nov 4, 2024
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48 changes: 7 additions & 41 deletions sklearn/datasets/_samples_generator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,6 @@

import array
import numbers
import warnings
from collections.abc import Iterable
from numbers import Integral, Real

Expand All @@ -18,7 +17,7 @@
from ..preprocessing import MultiLabelBinarizer
from ..utils import check_array, check_random_state
from ..utils import shuffle as util_shuffle
from ..utils._param_validation import Hidden, Interval, StrOptions, validate_params
from ..utils._param_validation import Interval, StrOptions, validate_params
from ..utils.random import sample_without_replacement


Expand Down Expand Up @@ -1667,7 +1666,7 @@ def make_spd_matrix(n_dim, *, random_state=None):

@validate_params(
{
"n_dim": [Hidden(None), Interval(Integral, 1, None, closed="left")],
"n_dim": [Interval(Integral, 1, None, closed="left")],
"alpha": [Interval(Real, 0, 1, closed="both")],
"norm_diag": ["boolean"],
"smallest_coef": [Interval(Real, 0, 1, closed="both")],
Expand All @@ -1677,23 +1676,18 @@ def make_spd_matrix(n_dim, *, random_state=None):
None,
],
"random_state": ["random_state"],
"dim": [
Interval(Integral, 1, None, closed="left"),
Hidden(StrOptions({"deprecated"})),
],
},
prefer_skip_nested_validation=True,
)
def make_sparse_spd_matrix(
n_dim=None,
n_dim=1,
*,
alpha=0.95,
norm_diag=False,
smallest_coef=0.1,
largest_coef=0.9,
sparse_format=None,
random_state=None,
dim="deprecated",
):
"""Generate a sparse symmetric definite positive matrix.

Expand Down Expand Up @@ -1732,12 +1726,6 @@ def make_sparse_spd_matrix(
for reproducible output across multiple function calls.
See :term:`Glossary <random_state>`.

dim : int, default=1
The size of the random matrix to generate.

.. deprecated:: 1.4
`dim` is deprecated and will be removed in 1.6.

Returns
-------
prec : ndarray or sparse matrix of shape (dim, dim)
Expand Down Expand Up @@ -1765,32 +1753,10 @@ def make_sparse_spd_matrix(
"""
random_state = check_random_state(random_state)

# TODO(1.6): remove in 1.6
# Also make sure to change `n_dim` default back to 1 and deprecate None
if n_dim is not None and dim != "deprecated":
raise ValueError(
"`dim` and `n_dim` cannot be both specified. Please use `n_dim` only "
"as `dim` is deprecated in v1.4 and will be removed in v1.6."
)

if dim != "deprecated":
warnings.warn(
(
"dim was deprecated in version 1.4 and will be removed in 1.6."
"Please use ``n_dim`` instead."
),
FutureWarning,
)
_n_dim = dim
elif n_dim is None:
_n_dim = 1
else:
_n_dim = n_dim

chol = -sp.eye(_n_dim)
chol = -sp.eye(n_dim)
aux = sp.random(
m=_n_dim,
n=_n_dim,
m=n_dim,
n=n_dim,
density=1 - alpha,
data_rvs=lambda x: random_state.uniform(
low=smallest_coef, high=largest_coef, size=x
Expand All @@ -1802,7 +1768,7 @@ def make_sparse_spd_matrix(

# Permute the lines: we don't want to have asymmetries in the final
# SPD matrix
permutation = random_state.permutation(_n_dim)
permutation = random_state.permutation(n_dim)
aux = aux[permutation].T[permutation]
chol += aux
prec = chol.T @ chol
Expand Down
20 changes: 0 additions & 20 deletions sklearn/datasets/tests/test_samples_generator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -552,26 +552,6 @@ def test_make_sparse_spd_matrix(norm_diag, sparse_format, global_random_seed):
assert_array_almost_equal(Xarr.diagonal(), np.ones(n_dim))


# TODO(1.6): remove
def test_make_sparse_spd_matrix_deprecation_warning():
"""Check the message for future deprecation."""
warn_msg = "dim was deprecated in version 1.4"
with pytest.warns(FutureWarning, match=warn_msg):
make_sparse_spd_matrix(
dim=1,
)

error_msg = "`dim` and `n_dim` cannot be both specified"
with pytest.raises(ValueError, match=error_msg):
make_sparse_spd_matrix(
dim=1,
n_dim=1,
)

X = make_sparse_spd_matrix()
assert X.shape[1] == 1


@pytest.mark.parametrize("hole", [False, True])
def test_make_swiss_roll(hole):
X, t = make_swiss_roll(n_samples=5, noise=0.0, random_state=0, hole=hole)
Expand Down