220 lines
7.7 KiB
Python
220 lines
7.7 KiB
Python
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import pytest
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from numpy.testing import assert_array_almost_equal, assert_array_equal
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from pytest import raises as assert_raises
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import numpy as np
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from numpy import array, transpose, dot, conjugate, zeros_like, empty
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from numpy.random import random
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from scipy.linalg import cholesky, cholesky_banded, cho_solve_banded, \
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cho_factor, cho_solve
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from scipy.linalg._testutils import assert_no_overwrite
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class TestCholesky:
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def test_simple(self):
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a = [[8, 2, 3], [2, 9, 3], [3, 3, 6]]
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c = cholesky(a)
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assert_array_almost_equal(dot(transpose(c), c), a)
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c = transpose(c)
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a = dot(c, transpose(c))
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assert_array_almost_equal(cholesky(a, lower=1), c)
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def test_check_finite(self):
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a = [[8, 2, 3], [2, 9, 3], [3, 3, 6]]
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c = cholesky(a, check_finite=False)
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assert_array_almost_equal(dot(transpose(c), c), a)
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c = transpose(c)
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a = dot(c, transpose(c))
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assert_array_almost_equal(cholesky(a, lower=1, check_finite=False), c)
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def test_simple_complex(self):
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m = array([[3+1j, 3+4j, 5], [0, 2+2j, 2+7j], [0, 0, 7+4j]])
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a = dot(transpose(conjugate(m)), m)
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c = cholesky(a)
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a1 = dot(transpose(conjugate(c)), c)
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assert_array_almost_equal(a, a1)
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c = transpose(c)
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a = dot(c, transpose(conjugate(c)))
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assert_array_almost_equal(cholesky(a, lower=1), c)
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def test_random(self):
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n = 20
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for k in range(2):
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m = random([n, n])
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for i in range(n):
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m[i, i] = 20*(.1+m[i, i])
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a = dot(transpose(m), m)
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c = cholesky(a)
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a1 = dot(transpose(c), c)
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assert_array_almost_equal(a, a1)
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c = transpose(c)
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a = dot(c, transpose(c))
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assert_array_almost_equal(cholesky(a, lower=1), c)
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def test_random_complex(self):
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n = 20
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for k in range(2):
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m = random([n, n])+1j*random([n, n])
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for i in range(n):
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m[i, i] = 20*(.1+abs(m[i, i]))
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a = dot(transpose(conjugate(m)), m)
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c = cholesky(a)
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a1 = dot(transpose(conjugate(c)), c)
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assert_array_almost_equal(a, a1)
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c = transpose(c)
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a = dot(c, transpose(conjugate(c)))
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assert_array_almost_equal(cholesky(a, lower=1), c)
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@pytest.mark.xslow
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def test_int_overflow(self):
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# regression test for
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# https://github.com/scipy/scipy/issues/17436
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# the problem was an int overflow in zeroing out
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# the unused triangular part
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n = 47_000
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x = np.eye(n, dtype=np.float64, order='F')
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x[:4, :4] = np.array([[4, -2, 3, -1],
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[-2, 4, -3, 1],
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[3, -3, 5, 0],
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[-1, 1, 0, 5]])
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cholesky(x, check_finite=False, overwrite_a=True) # should not segfault
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class TestCholeskyBanded:
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"""Tests for cholesky_banded() and cho_solve_banded."""
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def test_check_finite(self):
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# Symmetric positive definite banded matrix `a`
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a = array([[4.0, 1.0, 0.0, 0.0],
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[1.0, 4.0, 0.5, 0.0],
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[0.0, 0.5, 4.0, 0.2],
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[0.0, 0.0, 0.2, 4.0]])
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# Banded storage form of `a`.
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ab = array([[-1.0, 1.0, 0.5, 0.2],
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[4.0, 4.0, 4.0, 4.0]])
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c = cholesky_banded(ab, lower=False, check_finite=False)
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ufac = zeros_like(a)
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ufac[list(range(4)), list(range(4))] = c[-1]
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ufac[(0, 1, 2), (1, 2, 3)] = c[0, 1:]
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assert_array_almost_equal(a, dot(ufac.T, ufac))
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b = array([0.0, 0.5, 4.2, 4.2])
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x = cho_solve_banded((c, False), b, check_finite=False)
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assert_array_almost_equal(x, [0.0, 0.0, 1.0, 1.0])
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def test_upper_real(self):
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# Symmetric positive definite banded matrix `a`
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a = array([[4.0, 1.0, 0.0, 0.0],
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[1.0, 4.0, 0.5, 0.0],
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[0.0, 0.5, 4.0, 0.2],
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[0.0, 0.0, 0.2, 4.0]])
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# Banded storage form of `a`.
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ab = array([[-1.0, 1.0, 0.5, 0.2],
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[4.0, 4.0, 4.0, 4.0]])
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c = cholesky_banded(ab, lower=False)
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ufac = zeros_like(a)
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ufac[list(range(4)), list(range(4))] = c[-1]
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ufac[(0, 1, 2), (1, 2, 3)] = c[0, 1:]
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assert_array_almost_equal(a, dot(ufac.T, ufac))
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b = array([0.0, 0.5, 4.2, 4.2])
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x = cho_solve_banded((c, False), b)
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assert_array_almost_equal(x, [0.0, 0.0, 1.0, 1.0])
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def test_upper_complex(self):
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# Hermitian positive definite banded matrix `a`
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a = array([[4.0, 1.0, 0.0, 0.0],
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[1.0, 4.0, 0.5, 0.0],
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[0.0, 0.5, 4.0, -0.2j],
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[0.0, 0.0, 0.2j, 4.0]])
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# Banded storage form of `a`.
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ab = array([[-1.0, 1.0, 0.5, -0.2j],
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[4.0, 4.0, 4.0, 4.0]])
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c = cholesky_banded(ab, lower=False)
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ufac = zeros_like(a)
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ufac[list(range(4)), list(range(4))] = c[-1]
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ufac[(0, 1, 2), (1, 2, 3)] = c[0, 1:]
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assert_array_almost_equal(a, dot(ufac.conj().T, ufac))
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b = array([0.0, 0.5, 4.0-0.2j, 0.2j + 4.0])
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x = cho_solve_banded((c, False), b)
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assert_array_almost_equal(x, [0.0, 0.0, 1.0, 1.0])
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def test_lower_real(self):
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# Symmetric positive definite banded matrix `a`
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a = array([[4.0, 1.0, 0.0, 0.0],
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[1.0, 4.0, 0.5, 0.0],
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[0.0, 0.5, 4.0, 0.2],
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[0.0, 0.0, 0.2, 4.0]])
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# Banded storage form of `a`.
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ab = array([[4.0, 4.0, 4.0, 4.0],
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[1.0, 0.5, 0.2, -1.0]])
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c = cholesky_banded(ab, lower=True)
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lfac = zeros_like(a)
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lfac[list(range(4)), list(range(4))] = c[0]
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lfac[(1, 2, 3), (0, 1, 2)] = c[1, :3]
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assert_array_almost_equal(a, dot(lfac, lfac.T))
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b = array([0.0, 0.5, 4.2, 4.2])
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x = cho_solve_banded((c, True), b)
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assert_array_almost_equal(x, [0.0, 0.0, 1.0, 1.0])
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def test_lower_complex(self):
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# Hermitian positive definite banded matrix `a`
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a = array([[4.0, 1.0, 0.0, 0.0],
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[1.0, 4.0, 0.5, 0.0],
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[0.0, 0.5, 4.0, -0.2j],
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[0.0, 0.0, 0.2j, 4.0]])
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# Banded storage form of `a`.
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ab = array([[4.0, 4.0, 4.0, 4.0],
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[1.0, 0.5, 0.2j, -1.0]])
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c = cholesky_banded(ab, lower=True)
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lfac = zeros_like(a)
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lfac[list(range(4)), list(range(4))] = c[0]
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lfac[(1, 2, 3), (0, 1, 2)] = c[1, :3]
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assert_array_almost_equal(a, dot(lfac, lfac.conj().T))
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b = array([0.0, 0.5j, 3.8j, 3.8])
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x = cho_solve_banded((c, True), b)
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assert_array_almost_equal(x, [0.0, 0.0, 1.0j, 1.0])
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class TestOverwrite:
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def test_cholesky(self):
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assert_no_overwrite(cholesky, [(3, 3)])
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def test_cho_factor(self):
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assert_no_overwrite(cho_factor, [(3, 3)])
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def test_cho_solve(self):
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x = array([[2, -1, 0], [-1, 2, -1], [0, -1, 2]])
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xcho = cho_factor(x)
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assert_no_overwrite(lambda b: cho_solve(xcho, b), [(3,)])
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def test_cholesky_banded(self):
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assert_no_overwrite(cholesky_banded, [(2, 3)])
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def test_cho_solve_banded(self):
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x = array([[0, -1, -1], [2, 2, 2]])
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xcho = cholesky_banded(x)
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assert_no_overwrite(lambda b: cho_solve_banded((xcho, False), b),
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[(3,)])
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class TestEmptyArray:
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def test_cho_factor_empty_square(self):
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a = empty((0, 0))
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b = array([])
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c = array([[]])
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d = []
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e = [[]]
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x, _ = cho_factor(a)
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assert_array_equal(x, a)
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for x in ([b, c, d, e]):
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assert_raises(ValueError, cho_factor, x)
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