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Use LHS seed parameter instead of deprecated random_state #38

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Merged
merged 2 commits into from
Oct 24, 2025
Merged

Use LHS seed parameter instead of deprecated random_state #38

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ad9e0e1
Add seed parameter to LHS, deprecate random_state
relf Oct 19, 2025
70a3fcb
Test LHS seed parameter and random_state deprecation
relf Oct 19, 2025
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41 changes: 38 additions & 3 deletions pyDOE3/doe_lhs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@
from scipy import linalg
from numpy import ma

from warnings import warn

__all__ = ["lhs"]


Expand All @@ -29,6 +31,7 @@ def lhs(
iterations=None,
random_state=None,
correlation_matrix=None,
seed=None,
):
"""
Generate a latin-hypercube design
Expand All @@ -50,9 +53,12 @@ def lhs(
The number of iterations in the maximin and correlations algorithms
(Default: 5).
randomstate : np.random.RandomState, int
DEPRECATED! It will be removed in a future release. Use seed parameter instead.
Random state (or seed-number) which controls the seed and random draws
correlation_matrix : ndarray
Enforce correlation between factors (only used in lhsmu)
seed : int or np.random.Generator
Seed or np.random.Generator which controls random draws

Returns
-------
Expand Down Expand Up @@ -111,10 +117,31 @@ def lhs(
H = None

if random_state is None:
random_state = np.random.RandomState()
random_state = np.random.default_rng()
elif isinstance(random_state, np.random.RandomState):
warn(
"Using random_state is deprecated "
"and will raise an error in a future version. Please "
"use seed parameter and pass a np.random.Generator",
DeprecationWarning,
stacklevel=2,
)
elif not isinstance(random_state, np.random.RandomState):
warn(
"Passing a seed or integer to random_state is deprecated "
"and will raise an error in a future version. Please "
"use seed parameter",
DeprecationWarning,
stacklevel=2,
)
random_state = np.random.RandomState(random_state)

if seed is not None:
if isinstance(seed, np.random.Generator):
random_state = seed
else:
random_state = np.random.default_rng(seed)

if samples is None:
samples = n

Expand Down Expand Up @@ -164,7 +191,11 @@ def _lhsclassic(n, samples, randomstate):
cut = np.linspace(0, 1, samples + 1)

# Fill points uniformly in each interval
u = randomstate.rand(samples, n)
u = (
randomstate.rand(samples, n)
if isinstance(randomstate, np.random.RandomState)
else randomstate.random((samples, n))
)
a = cut[:samples]
b = cut[1 : samples + 1]
rdpoints = np.zeros_like(u)
Expand All @@ -188,7 +219,11 @@ def _lhscentered(n, samples, randomstate):
cut = np.linspace(0, 1, samples + 1)

# Fill points uniformly in each interval
u = randomstate.rand(samples, n)
u = (
randomstate.rand(samples, n)
if isinstance(randomstate, np.random.RandomState)
else randomstate.random((samples, n))
)
a = cut[:samples]
b = cut[1 : samples + 1]
_center = (a + b) / 2
Expand Down
86 changes: 70 additions & 16 deletions tests/test_lhs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,16 +4,17 @@


class TestLhs(unittest.TestCase):
def test_lhs1(self):
def test_lhs1_deprecated(self):
expected = [
[0.12484671, 0.95539205, 0.24399798],
[0.53288616, 0.38533955, 0.86703834],
[0.68602787, 0.31690477, 0.38533151],
]
actual = lhs(3, random_state=42)
np.testing.assert_allclose(actual, expected)
with self.assertWarns(DeprecationWarning):
actual = lhs(3, random_state=42)
np.testing.assert_allclose(actual, expected)

def test_lhs2(self):
def test_lhs2_deprecated(self):
expected = [
[0.06242335, 0.19266575, 0.88202411, 0.89439364],
[0.19266977, 0.53538985, 0.53030416, 0.49498498],
Expand All @@ -22,33 +23,86 @@ def test_lhs2(self):
[0.43351917, 0.45134543, 0.12199899, 0.53056742],
[0.93530882, 0.15845238, 0.7386575, 0.09977641],
]
actual = lhs(4, samples=6, random_state=42)
np.testing.assert_allclose(actual, expected)
with self.assertWarns(DeprecationWarning):
actual = lhs(4, samples=6, random_state=42)
np.testing.assert_allclose(actual, expected)

def test_lhs3(self):
def test_lhs3_deprecated(self):
expected = [[0.1, 0.9], [0.5, 0.5], [0.7, 0.1], [0.3, 0.7], [0.9, 0.3]]
actual = lhs(2, samples=5, criterion="center", random_state=42)
np.testing.assert_allclose(actual, expected)
with self.assertWarns(DeprecationWarning):
actual = lhs(2, samples=5, criterion="center", random_state=42)
np.testing.assert_allclose(actual, expected)

def test_lhs4(self):
def test_lhs4_deprecated(self):
expected = [
[0.69754389, 0.2997106, 0.96250964],
[0.10585037, 0.09872038, 0.73157522],
[0.25351996, 0.65148999, 0.07337204],
[0.91276926, 0.97873992, 0.42783549],
]
actual = lhs(3, samples=4, criterion="maximin", random_state=42)
np.testing.assert_allclose(actual, expected)
with self.assertWarns(DeprecationWarning):
actual = lhs(3, samples=4, criterion="maximin", random_state=42)
np.testing.assert_allclose(actual, expected)

def test_lhs5(self):
def test_lhs5_deprecated(self):
expected = [
[0.4846803, 0.74226839, 0.23305339, 0.97000772],
[0.98526018, 0.11735023, 0.75803511, 0.20312728],
[0.10793843, 0.2592547, 0.98299194, 0.72119199],
[0.25519984, 0.4789763, 0.19305106, 0.12140685],
[0.63976848, 0.93021541, 0.45869763, 0.40281596],
]
actual = lhs(
4, samples=5, criterion="correlation", iterations=10, random_state=42
)
with self.assertWarns(DeprecationWarning):
actual = lhs(
4, samples=5, criterion="correlation", iterations=10, random_state=42
)
np.testing.assert_allclose(actual, expected)

def test_lhs1(self):
expected = [
[0.25798535, 0.14629281, 0.65854078],
[0.56578934, 0.9286881, 0.28619931],
[0.9203799, 0.36472578, 0.70937121],
]
actual = lhs(3, seed=42)
np.testing.assert_allclose(actual, expected, atol=1e-6)

def test_lhs2(self):
expected = [
[0.60731085, 0.32927039, 0.8046052, 0.98218685],
[0.35468561, 0.67730288, 0.14309965, 0.77194407],
[0.18236289, 0.89242099, 0.29352328, 0.53787312],
[0.75909746, 0.63712694, 0.395133, 0.48779416],
[0.95968129, 0.40839766, 0.99511634, 0.116228],
[0.12899267, 0.07314641, 0.57390237, 0.29767738],
]
actual = lhs(4, samples=6, seed=42)
np.testing.assert_allclose(actual, expected, atol=1e-6)

def test_lhs3(self):
expected = [[0.9, 0.1], [0.1, 0.7], [0.5, 0.9], [0.7, 0.5], [0.3, 0.3]]
actual = lhs(2, samples=5, criterion="center", seed=42)
print(actual)
np.testing.assert_allclose(actual, expected)

def test_lhs4(self):
expected = [
[0.91547913, 0.46335077, 0.05364617],
[0.51457569, 0.10917935, 0.94597455],
[0.35213216, 0.57034597, 0.30848487],
[0.00770446, 0.88925804, 0.57339844],
]
actual = lhs(3, samples=4, criterion="maximin", seed=42)
print(actual)
np.testing.assert_allclose(actual, expected, atol=1e-6)

def test_lhs5(self):
expected = [
[0.15479121, 0.49007719, 0.68868284, 0.35721286],
[0.21883547, 0.39512447, 0.4741596, 0.64544774],
[0.42562273, 0.08777569, 0.35222794, 0.92633288],
[0.91091696, 0.76455232, 0.96552623, 0.585353],
[0.72877302, 0.81276345, 0.17171958, 0.13947361],
]
actual = lhs(4, samples=5, criterion="correlation", iterations=10, seed=42)
np.testing.assert_allclose(actual, expected)