peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/scipy
/sparse
/tests
/test_sputils.py
"""unit tests for sparse utility functions""" | |
import numpy as np | |
from numpy.testing import assert_equal | |
from pytest import raises as assert_raises | |
from scipy.sparse import _sputils as sputils | |
from scipy.sparse._sputils import matrix | |
class TestSparseUtils: | |
def test_upcast(self): | |
assert_equal(sputils.upcast('intc'), np.intc) | |
assert_equal(sputils.upcast('int32', 'float32'), np.float64) | |
assert_equal(sputils.upcast('bool', complex, float), np.complex128) | |
assert_equal(sputils.upcast('i', 'd'), np.float64) | |
def test_getdtype(self): | |
A = np.array([1], dtype='int8') | |
assert_equal(sputils.getdtype(None, default=float), float) | |
assert_equal(sputils.getdtype(None, a=A), np.int8) | |
with assert_raises( | |
ValueError, | |
match="object dtype is not supported by sparse matrices", | |
): | |
sputils.getdtype("O") | |
def test_isscalarlike(self): | |
assert_equal(sputils.isscalarlike(3.0), True) | |
assert_equal(sputils.isscalarlike(-4), True) | |
assert_equal(sputils.isscalarlike(2.5), True) | |
assert_equal(sputils.isscalarlike(1 + 3j), True) | |
assert_equal(sputils.isscalarlike(np.array(3)), True) | |
assert_equal(sputils.isscalarlike("16"), True) | |
assert_equal(sputils.isscalarlike(np.array([3])), False) | |
assert_equal(sputils.isscalarlike([[3]]), False) | |
assert_equal(sputils.isscalarlike((1,)), False) | |
assert_equal(sputils.isscalarlike((1, 2)), False) | |
def test_isintlike(self): | |
assert_equal(sputils.isintlike(-4), True) | |
assert_equal(sputils.isintlike(np.array(3)), True) | |
assert_equal(sputils.isintlike(np.array([3])), False) | |
with assert_raises( | |
ValueError, | |
match="Inexact indices into sparse matrices are not allowed" | |
): | |
sputils.isintlike(3.0) | |
assert_equal(sputils.isintlike(2.5), False) | |
assert_equal(sputils.isintlike(1 + 3j), False) | |
assert_equal(sputils.isintlike((1,)), False) | |
assert_equal(sputils.isintlike((1, 2)), False) | |
def test_isshape(self): | |
assert_equal(sputils.isshape((1, 2)), True) | |
assert_equal(sputils.isshape((5, 2)), True) | |
assert_equal(sputils.isshape((1.5, 2)), False) | |
assert_equal(sputils.isshape((2, 2, 2)), False) | |
assert_equal(sputils.isshape(([2], 2)), False) | |
assert_equal(sputils.isshape((-1, 2), nonneg=False),True) | |
assert_equal(sputils.isshape((2, -1), nonneg=False),True) | |
assert_equal(sputils.isshape((-1, 2), nonneg=True),False) | |
assert_equal(sputils.isshape((2, -1), nonneg=True),False) | |
assert_equal(sputils.isshape((1.5, 2), allow_1d=True), False) | |
assert_equal(sputils.isshape(([2], 2), allow_1d=True), False) | |
assert_equal(sputils.isshape((2, 2, -2), nonneg=True, allow_1d=True), | |
False) | |
assert_equal(sputils.isshape((2,), allow_1d=True), True) | |
assert_equal(sputils.isshape((2, 2,), allow_1d=True), True) | |
assert_equal(sputils.isshape((2, 2, 2), allow_1d=True), False) | |
def test_issequence(self): | |
assert_equal(sputils.issequence((1,)), True) | |
assert_equal(sputils.issequence((1, 2, 3)), True) | |
assert_equal(sputils.issequence([1]), True) | |
assert_equal(sputils.issequence([1, 2, 3]), True) | |
assert_equal(sputils.issequence(np.array([1, 2, 3])), True) | |
assert_equal(sputils.issequence(np.array([[1], [2], [3]])), False) | |
assert_equal(sputils.issequence(3), False) | |
def test_ismatrix(self): | |
assert_equal(sputils.ismatrix(((),)), True) | |
assert_equal(sputils.ismatrix([[1], [2]]), True) | |
assert_equal(sputils.ismatrix(np.arange(3)[None]), True) | |
assert_equal(sputils.ismatrix([1, 2]), False) | |
assert_equal(sputils.ismatrix(np.arange(3)), False) | |
assert_equal(sputils.ismatrix([[[1]]]), False) | |
assert_equal(sputils.ismatrix(3), False) | |
def test_isdense(self): | |
assert_equal(sputils.isdense(np.array([1])), True) | |
assert_equal(sputils.isdense(matrix([1])), True) | |
def test_validateaxis(self): | |
assert_raises(TypeError, sputils.validateaxis, (0, 1)) | |
assert_raises(TypeError, sputils.validateaxis, 1.5) | |
assert_raises(ValueError, sputils.validateaxis, 3) | |
# These function calls should not raise errors | |
for axis in (-2, -1, 0, 1, None): | |
sputils.validateaxis(axis) | |
def test_get_index_dtype(self): | |
imax = np.int64(np.iinfo(np.int32).max) | |
too_big = imax + 1 | |
# Check that uint32's with no values too large doesn't return | |
# int64 | |
a1 = np.ones(90, dtype='uint32') | |
a2 = np.ones(90, dtype='uint32') | |
assert_equal( | |
np.dtype(sputils.get_index_dtype((a1, a2), check_contents=True)), | |
np.dtype('int32') | |
) | |
# Check that if we can not convert but all values are less than or | |
# equal to max that we can just convert to int32 | |
a1[-1] = imax | |
assert_equal( | |
np.dtype(sputils.get_index_dtype((a1, a2), check_contents=True)), | |
np.dtype('int32') | |
) | |
# Check that if it can not convert directly and the contents are | |
# too large that we return int64 | |
a1[-1] = too_big | |
assert_equal( | |
np.dtype(sputils.get_index_dtype((a1, a2), check_contents=True)), | |
np.dtype('int64') | |
) | |
# test that if can not convert and didn't specify to check_contents | |
# we return int64 | |
a1 = np.ones(89, dtype='uint32') | |
a2 = np.ones(89, dtype='uint32') | |
assert_equal( | |
np.dtype(sputils.get_index_dtype((a1, a2))), | |
np.dtype('int64') | |
) | |
# Check that even if we have arrays that can be converted directly | |
# that if we specify a maxval directly it takes precedence | |
a1 = np.ones(12, dtype='uint32') | |
a2 = np.ones(12, dtype='uint32') | |
assert_equal( | |
np.dtype(sputils.get_index_dtype( | |
(a1, a2), maxval=too_big, check_contents=True | |
)), | |
np.dtype('int64') | |
) | |
# Check that an array with a too max size and maxval set | |
# still returns int64 | |
a1[-1] = too_big | |
assert_equal( | |
np.dtype(sputils.get_index_dtype((a1, a2), maxval=too_big)), | |
np.dtype('int64') | |
) | |
def test_check_shape_overflow(self): | |
new_shape = sputils.check_shape([(10, -1)], (65535, 131070)) | |
assert_equal(new_shape, (10, 858967245)) | |
def test_matrix(self): | |
a = [[1, 2, 3]] | |
b = np.array(a) | |
assert isinstance(sputils.matrix(a), np.matrix) | |
assert isinstance(sputils.matrix(b), np.matrix) | |
c = sputils.matrix(b) | |
c[:, :] = 123 | |
assert_equal(b, a) | |
c = sputils.matrix(b, copy=False) | |
c[:, :] = 123 | |
assert_equal(b, [[123, 123, 123]]) | |
def test_asmatrix(self): | |
a = [[1, 2, 3]] | |
b = np.array(a) | |
assert isinstance(sputils.asmatrix(a), np.matrix) | |
assert isinstance(sputils.asmatrix(b), np.matrix) | |
c = sputils.asmatrix(b) | |
c[:, :] = 123 | |
assert_equal(b, [[123, 123, 123]]) | |