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MAINT: Adapt sklearn for NumPy default integer change #27041

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Merged
merged 4 commits into from
Nov 16, 2023
Merged

MAINT: Adapt sklearn for NumPy default integer change #27041

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73b7749
MAINT: Adapt sklearn for NumPy default integer change
seberg Aug 9, 2023
4e3d417
MAINT: Fix two NumPy deprecation warnings
seberg Nov 3, 2023
cf53a99
DOC: Tweak code comments explaining the branching/logic
seberg Nov 8, 2023
c4c167e
Update sklearn/utils/_random.pyx
seberg Nov 13, 2023
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2 changes: 1 addition & 1 deletion sklearn/cluster/_hdbscan/hdbscan.py
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Expand Up @@ -124,7 +124,7 @@ def _brute_mst(mutual_reachability, min_samples):
# Compute the minimum spanning tree for the sparse graph
sparse_min_spanning_tree = csgraph.minimum_spanning_tree(mutual_reachability)
rows, cols = sparse_min_spanning_tree.nonzero()
mst = np.core.records.fromarrays(
mst = np.rec.fromarrays(
[rows, cols, sparse_min_spanning_tree.data],
dtype=MST_edge_dtype,
)
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4 changes: 0 additions & 4 deletions sklearn/utils/_random.pxd
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Expand Up @@ -16,10 +16,6 @@ cdef enum:
# 32-bit signed integers (i.e. 2^31 - 1).
RAND_R_MAX = 2147483647

cpdef sample_without_replacement(cnp.int_t n_population,
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This would make sample_without_replacement not cimportable by other modules. Given that _random is a private module, I am okay with it's removal.

cnp.int_t n_samples,
method=*,
random_state=*)

# rand_r replacement using a 32bit XorShift generator
# See http://www.jstatsoft.org/v08/i14/paper for details
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75 changes: 55 additions & 20 deletions sklearn/utils/_random.pyx
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Expand Up @@ -19,8 +19,17 @@ from . import check_random_state
cdef UINT32_t DEFAULT_SEED = 1


cpdef _sample_without_replacement_check_input(cnp.int_t n_population,
cnp.int_t n_samples):
# Compatibility type to always accept the default int type used by NumPy, both
# before and after NumPy 2. On Windows, `long` does not always match `cnp.inp_t`.
# See the comments in the `sample_without_replacement` Python function for more
# details.
ctypedef fused default_int:
cnp.intp_t
long


cpdef _sample_without_replacement_check_input(default_int n_population,
default_int n_samples):
""" Check that input are consistent for sample_without_replacement"""
if n_population < 0:
raise ValueError('n_population should be greater than 0, got %s.'
Expand All @@ -33,8 +42,8 @@ cpdef _sample_without_replacement_check_input(cnp.int_t n_population,


cpdef _sample_without_replacement_with_tracking_selection(
cnp.int_t n_population,
cnp.int_t n_samples,
default_int n_population,
default_int n_samples,
random_state=None):
r"""Sample integers without replacement.

Expand Down Expand Up @@ -76,9 +85,9 @@ cpdef _sample_without_replacement_with_tracking_selection(
"""
_sample_without_replacement_check_input(n_population, n_samples)

cdef cnp.int_t i
cdef cnp.int_t j
cdef cnp.int_t[::1] out = np.empty((n_samples, ), dtype=int)
cdef default_int i
cdef default_int j
cdef default_int[::1] out = np.empty((n_samples, ), dtype=int)

rng = check_random_state(random_state)
rng_randint = rng.randint
Expand All @@ -97,8 +106,8 @@ cpdef _sample_without_replacement_with_tracking_selection(
return np.asarray(out)


cpdef _sample_without_replacement_with_pool(cnp.int_t n_population,
cnp.int_t n_samples,
cpdef _sample_without_replacement_with_pool(default_int n_population,
default_int n_samples,
random_state=None):
"""Sample integers without replacement.

Expand Down Expand Up @@ -131,10 +140,10 @@ cpdef _sample_without_replacement_with_pool(cnp.int_t n_population,
"""
_sample_without_replacement_check_input(n_population, n_samples)

cdef cnp.int_t i
cdef cnp.int_t j
cdef cnp.int_t[::1] out = np.empty((n_samples,), dtype=int)
cdef cnp.int_t[::1] pool = np.empty((n_population,), dtype=int)
cdef default_int i
cdef default_int j
cdef default_int[::1] out = np.empty((n_samples,), dtype=int)
cdef default_int[::1] pool = np.empty((n_population,), dtype=int)

rng = check_random_state(random_state)
rng_randint = rng.randint
Expand All @@ -154,8 +163,8 @@ cpdef _sample_without_replacement_with_pool(cnp.int_t n_population,


cpdef _sample_without_replacement_with_reservoir_sampling(
cnp.int_t n_population,
cnp.int_t n_samples,
default_int n_population,
default_int n_samples,
random_state=None
):
"""Sample integers without replacement.
Expand Down Expand Up @@ -191,9 +200,9 @@ cpdef _sample_without_replacement_with_reservoir_sampling(
"""
_sample_without_replacement_check_input(n_population, n_samples)

cdef cnp.int_t i
cdef cnp.int_t j
cdef cnp.int_t[::1] out = np.empty((n_samples, ), dtype=int)
cdef default_int i
cdef default_int j
cdef default_int[::1] out = np.empty((n_samples, ), dtype=int)

rng = check_random_state(random_state)
rng_randint = rng.randint
Expand All @@ -213,8 +222,8 @@ cpdef _sample_without_replacement_with_reservoir_sampling(
return np.asarray(out)


cpdef sample_without_replacement(cnp.int_t n_population,
cnp.int_t n_samples,
cdef _sample_without_replacement(default_int n_population,
default_int n_samples,
method="auto",
random_state=None):
"""Sample integers without replacement.
Expand Down Expand Up @@ -303,6 +312,32 @@ cpdef sample_without_replacement(cnp.int_t n_population,
% (all_methods, method))


def sample_without_replacement(
object n_population, object n_samples, method="auto", random_state=None):
cdef:
cnp.intp_t n_pop_intp, n_samples_intp
long n_pop_long, n_samples_long

# On most platforms `np.int_ is np.intp`. However, before NumPy 2 the
# default integer `np.int_` was a long which is 32bit on 64bit windows
# while `intp` is 64bit on 64bit platforms and 32bit on 32bit ones.
if np.int_ is np.intp:
# Branch always taken on NumPy >=2 (or when not on 64bit windows).
# Cython has different rules for conversion of values to integers.
# For NumPy <1.26.2 AND Cython 3, this first branch requires `int()`
# called explicitly to allow e.g. floats.
n_pop_intp = int(n_population)
n_samples_intp = int(n_samples)
return _sample_without_replacement(
n_pop_intp, n_samples_intp, method, random_state)
else:
# Branch taken on 64bit windows with Numpy<2.0 where `long` is 32bit
n_pop_long = n_population
n_samples_long = n_samples
return _sample_without_replacement(
n_pop_long, n_samples_long, method, random_state)


def _our_rand_r_py(seed):
"""Python utils to test the our_rand_r function"""
cdef UINT32_t my_seed = seed
Expand Down
2 changes: 1 addition & 1 deletion sklearn/utils/estimator_checks.py
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Expand Up @@ -3470,7 +3470,7 @@ def param_filter(p):
type,
}
# Any numpy numeric such as np.int32.
allowed_types.update(np.core.numerictypes.allTypes.values())
allowed_types.update(np.sctypeDict.values())

allowed_value = (
type(init_param.default) in allowed_types
Expand Down