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- """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)
- 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]])
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