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test_funcs.py
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from __future__ import annotations
import contextlib
import warnings
# data-apis/array-api-strict#6
import array_api_strict as xp
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal, assert_equal
from array_api_extra import (
atleast_nd,
cov,
create_diagonal,
expand_dims,
kron,
setdiff1d,
sinc,
)
from array_api_extra._lib._typing import Array
class TestAtLeastND:
def test_0D(self):
x = xp.asarray(1)
y = atleast_nd(x, ndim=0)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=1)
assert_array_equal(y, xp.ones((1,)))
y = atleast_nd(x, ndim=5)
assert_array_equal(y, xp.ones((1, 1, 1, 1, 1)))
def test_1D(self):
x = xp.asarray([0, 1])
y = atleast_nd(x, ndim=0)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=1)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=2)
assert_array_equal(y, xp.asarray([[0, 1]]))
y = atleast_nd(x, ndim=5)
assert_array_equal(y, xp.reshape(xp.arange(2), (1, 1, 1, 1, 2)))
def test_2D(self):
x = xp.asarray([[3]])
y = atleast_nd(x, ndim=0)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=2)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=3)
assert_array_equal(y, 3 * xp.ones((1, 1, 1)))
y = atleast_nd(x, ndim=5)
assert_array_equal(y, 3 * xp.ones((1, 1, 1, 1, 1)))
def test_5D(self):
x = xp.ones((1, 1, 1, 1, 1))
y = atleast_nd(x, ndim=0)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=4)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=5)
assert_array_equal(y, x)
y = atleast_nd(x, ndim=6)
assert_array_equal(y, xp.ones((1, 1, 1, 1, 1, 1)))
y = atleast_nd(x, ndim=9)
assert_array_equal(y, xp.ones((1, 1, 1, 1, 1, 1, 1, 1, 1)))
def test_device(self):
device = xp.Device("device1")
x = xp.asarray([1, 2, 3], device=device)
assert atleast_nd(x, ndim=2).device == device
def test_xp(self):
x = xp.asarray(1)
y = atleast_nd(x, ndim=0, xp=xp)
assert_array_equal(y, x)
class TestCov:
def test_basic(self):
assert_allclose(
cov(xp.asarray([[0, 2], [1, 1], [2, 0]]).T),
xp.asarray([[1.0, -1.0], [-1.0, 1.0]]),
)
def test_complex(self):
x = xp.asarray([[1, 2, 3], [1j, 2j, 3j]])
res = xp.asarray([[1.0, -1.0j], [1.0j, 1.0]])
assert_allclose(cov(x), res)
def test_empty(self):
with warnings.catch_warnings(record=True):
warnings.simplefilter("always", RuntimeWarning)
assert_array_equal(cov(xp.asarray([])), xp.nan)
assert_array_equal(
cov(xp.reshape(xp.asarray([]), (0, 2))),
xp.reshape(xp.asarray([]), (0, 0)),
)
assert_array_equal(
cov(xp.reshape(xp.asarray([]), (2, 0))),
xp.asarray([[xp.nan, xp.nan], [xp.nan, xp.nan]]),
)
def test_combination(self):
x = xp.asarray([-2.1, -1, 4.3])
y = xp.asarray([3, 1.1, 0.12])
X = xp.stack((x, y), axis=0)
desired = xp.asarray([[11.71, -4.286], [-4.286, 2.144133]])
assert_allclose(cov(X), desired, rtol=1e-6)
assert_allclose(cov(x), xp.asarray(11.71))
assert_allclose(cov(y), xp.asarray(2.144133), rtol=1e-6)
def test_device(self):
device = xp.Device("device1")
x = xp.asarray([1, 2, 3], device=device)
assert cov(x).device == device
def test_xp(self):
assert_allclose(
cov(xp.asarray([[0, 2], [1, 1], [2, 0]]).T, xp=xp),
xp.asarray([[1.0, -1.0], [-1.0, 1.0]]),
)
class TestCreateDiagonal:
def test_1d(self):
# from np.diag tests
vals = 100 * xp.arange(5, dtype=xp.float64)
b = xp.zeros((5, 5))
for k in range(5):
b[k, k] = vals[k]
assert_array_equal(create_diagonal(vals), b)
b = xp.zeros((7, 7))
c = xp.asarray(b, copy=True)
for k in range(5):
b[k, k + 2] = vals[k]
c[k + 2, k] = vals[k]
assert_array_equal(create_diagonal(vals, offset=2), b)
assert_array_equal(create_diagonal(vals, offset=-2), c)
@pytest.mark.parametrize("n", range(1, 10))
@pytest.mark.parametrize("offset", range(1, 10))
def test_create_diagonal(self, n: int, offset: int):
# from scipy._lib tests
rng = np.random.default_rng(2347823)
one = xp.asarray(1.0)
x = rng.random(n)
A = create_diagonal(xp.asarray(x, dtype=one.dtype), offset=offset)
B = xp.asarray(np.diag(x, offset), dtype=one.dtype)
assert_array_equal(A, B)
def test_0d(self):
with pytest.raises(ValueError, match="1-dimensional"):
create_diagonal(xp.asarray(1))
def test_2d(self):
with pytest.raises(ValueError, match="1-dimensional"):
create_diagonal(xp.asarray([[1]]))
def test_device(self):
device = xp.Device("device1")
x = xp.asarray([1, 2, 3], device=device)
assert create_diagonal(x).device == device
def test_xp(self):
x = xp.asarray([1, 2])
y = create_diagonal(x, xp=xp)
assert_array_equal(y, xp.asarray([[1, 0], [0, 2]]))
class TestExpandDims:
def test_functionality(self):
def _squeeze_all(b: Array) -> Array:
"""Mimics `np.squeeze(b)`. `xpx.squeeze`?"""
for axis in range(b.ndim):
with contextlib.suppress(ValueError):
b = xp.squeeze(b, axis=axis)
return b
s = (2, 3, 4, 5)
a = xp.empty(s)
for axis in range(-5, 4):
b = expand_dims(a, axis=axis)
assert b.shape[axis] == 1
assert _squeeze_all(b).shape == s
def test_axis_tuple(self):
a = xp.empty((3, 3, 3))
assert expand_dims(a, axis=(0, 1, 2)).shape == (1, 1, 1, 3, 3, 3)
assert expand_dims(a, axis=(0, -1, -2)).shape == (1, 3, 3, 3, 1, 1)
assert expand_dims(a, axis=(0, 3, 5)).shape == (1, 3, 3, 1, 3, 1)
assert expand_dims(a, axis=(0, -3, -5)).shape == (1, 1, 3, 1, 3, 3)
def test_axis_out_of_range(self):
s = (2, 3, 4, 5)
a = xp.empty(s)
with pytest.raises(IndexError, match="out of bounds"):
expand_dims(a, axis=-6)
with pytest.raises(IndexError, match="out of bounds"):
expand_dims(a, axis=5)
a = xp.empty((3, 3, 3))
with pytest.raises(IndexError, match="out of bounds"):
expand_dims(a, axis=(0, -6))
with pytest.raises(IndexError, match="out of bounds"):
expand_dims(a, axis=(0, 5))
def test_repeated_axis(self):
a = xp.empty((3, 3, 3))
with pytest.raises(ValueError, match="Duplicate dimensions"):
expand_dims(a, axis=(1, 1))
def test_positive_negative_repeated(self):
# https://github.com/data-apis/array-api/issues/760#issuecomment-1989449817
a = xp.empty((2, 3, 4, 5))
with pytest.raises(ValueError, match="Duplicate dimensions"):
expand_dims(a, axis=(3, -3))
def test_device(self):
device = xp.Device("device1")
x = xp.asarray([1, 2, 3], device=device)
assert expand_dims(x, axis=0).device == device
def test_xp(self):
x = xp.asarray([1, 2, 3])
y = expand_dims(x, axis=(0, 1, 2), xp=xp)
assert y.shape == (1, 1, 1, 3)
class TestKron:
def test_basic(self):
# Using 0-dimensional array
a = xp.asarray(1)
b = xp.asarray([[1, 2], [3, 4]])
k = xp.asarray([[1, 2], [3, 4]])
assert_array_equal(kron(a, b), k)
a = xp.asarray([[1, 2], [3, 4]])
b = xp.asarray(1)
assert_array_equal(kron(a, b), k)
# Using 1-dimensional array
a = xp.asarray([3])
b = xp.asarray([[1, 2], [3, 4]])
k = xp.asarray([[3, 6], [9, 12]])
assert_array_equal(kron(a, b), k)
a = xp.asarray([[1, 2], [3, 4]])
b = xp.asarray([3])
assert_array_equal(kron(a, b), k)
# Using 3-dimensional array
a = xp.asarray([[[1]], [[2]]])
b = xp.asarray([[1, 2], [3, 4]])
k = xp.asarray([[[1, 2], [3, 4]], [[2, 4], [6, 8]]])
assert_array_equal(kron(a, b), k)
a = xp.asarray([[1, 2], [3, 4]])
b = xp.asarray([[[1]], [[2]]])
k = xp.asarray([[[1, 2], [3, 4]], [[2, 4], [6, 8]]])
assert_array_equal(kron(a, b), k)
def test_kron_smoke(self):
a = xp.ones((3, 3))
b = xp.ones((3, 3))
k = xp.ones((9, 9))
assert_array_equal(kron(a, b), k)
@pytest.mark.parametrize(
("shape_a", "shape_b"),
[
((1, 1), (1, 1)),
((1, 2, 3), (4, 5, 6)),
((2, 2), (2, 2, 2)),
((1, 0), (1, 1)),
((2, 0, 2), (2, 2)),
((2, 0, 0, 2), (2, 0, 2)),
],
)
def test_kron_shape(self, shape_a: tuple[int, ...], shape_b: tuple[int, ...]):
a = xp.ones(shape_a)
b = xp.ones(shape_b)
normalised_shape_a = xp.asarray(
(1,) * max(0, len(shape_b) - len(shape_a)) + shape_a
)
normalised_shape_b = xp.asarray(
(1,) * max(0, len(shape_a) - len(shape_b)) + shape_b
)
expected_shape = tuple(
int(dim) for dim in xp.multiply(normalised_shape_a, normalised_shape_b)
)
k = kron(a, b)
assert_equal(k.shape, expected_shape, err_msg="Unexpected shape from kron")
def test_device(self):
device = xp.Device("device1")
x1 = xp.asarray([1, 2, 3], device=device)
x2 = xp.asarray([4, 5], device=device)
assert kron(x1, x2).device == device
def test_xp(self):
a = xp.ones((3, 3))
b = xp.ones((3, 3))
k = xp.ones((9, 9))
assert_array_equal(kron(a, b, xp=xp), k)
class TestSetDiff1D:
def test_setdiff1d(self):
x1 = xp.asarray([6, 5, 4, 7, 1, 2, 7, 4])
x2 = xp.asarray([2, 4, 3, 3, 2, 1, 5])
expected = xp.asarray([6, 7])
actual = setdiff1d(x1, x2)
assert_array_equal(actual, expected)
x1 = xp.arange(21)
x2 = xp.arange(19)
expected = xp.asarray([19, 20])
actual = setdiff1d(x1, x2)
assert_array_equal(actual, expected)
assert_array_equal(setdiff1d(xp.empty(0), xp.empty(0)), xp.empty(0))
x1 = xp.empty(0, dtype=xp.uint32)
x2 = x1
assert_equal(setdiff1d(x1, x2).dtype, xp.uint32)
def test_assume_unique(self):
x1 = xp.asarray([3, 2, 1])
x2 = xp.asarray([7, 5, 2])
expected = xp.asarray([3, 1])
actual = setdiff1d(x1, x2, assume_unique=True)
assert_array_equal(actual, expected)
def test_device(self):
device = xp.Device("device1")
x1 = xp.asarray([3, 8, 20], device=device)
x2 = xp.asarray([2, 3, 4], device=device)
assert setdiff1d(x1, x2).device == device
def test_xp(self):
x1 = xp.asarray([3, 8, 20])
x2 = xp.asarray([2, 3, 4])
expected = xp.asarray([8, 20])
actual = setdiff1d(x1, x2, xp=xp)
assert_array_equal(actual, expected)
class TestSinc:
def test_simple(self):
assert_array_equal(sinc(xp.asarray(0.0)), xp.asarray(1.0))
w = sinc(xp.linspace(-1, 1, 100))
# check symmetry
assert_allclose(w, xp.flip(w, axis=0))
@pytest.mark.parametrize("x", [0, 1 + 3j])
def test_dtype(self, x: int | complex):
with pytest.raises(ValueError, match="real floating data type"):
sinc(xp.asarray(x))
def test_3d(self):
x = xp.reshape(xp.arange(18, dtype=xp.float64), (3, 3, 2))
expected = xp.zeros((3, 3, 2))
expected[0, 0, 0] = 1.0
assert_allclose(sinc(x), expected, atol=1e-15)
def test_device(self):
device = xp.Device("device1")
x = xp.asarray(0.0, device=device)
assert sinc(x).device == device
def test_xp(self):
assert_array_equal(sinc(xp.asarray(0.0), xp=xp), xp.asarray(1.0))