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- import pytest
- import numpy as np
- from numpy.random import seed
- from numpy.testing import assert_allclose
- from scipy.linalg.lapack import _compute_lwork
- from scipy.stats import ortho_group, unitary_group
- from scipy.linalg import cossin, get_lapack_funcs
- REAL_DTYPES = (np.float32, np.float64)
- COMPLEX_DTYPES = (np.complex64, np.complex128)
- DTYPES = REAL_DTYPES + COMPLEX_DTYPES
- @pytest.mark.parametrize('dtype_', DTYPES)
- @pytest.mark.parametrize('m, p, q',
- [
- (2, 1, 1),
- (3, 2, 1),
- (3, 1, 2),
- (4, 2, 2),
- (4, 1, 2),
- (40, 12, 20),
- (40, 30, 1),
- (40, 1, 30),
- (100, 50, 1),
- (100, 50, 50),
- ])
- @pytest.mark.parametrize('swap_sign', [True, False])
- def test_cossin(dtype_, m, p, q, swap_sign):
- seed(1234)
- if dtype_ in COMPLEX_DTYPES:
- x = np.array(unitary_group.rvs(m), dtype=dtype_)
- else:
- x = np.array(ortho_group.rvs(m), dtype=dtype_)
- u, cs, vh = cossin(x, p, q,
- swap_sign=swap_sign)
- assert_allclose(x, u @ cs @ vh, rtol=0., atol=m*1e3*np.finfo(dtype_).eps)
- assert u.dtype == dtype_
- # Test for float32 or float 64
- assert cs.dtype == np.real(u).dtype
- assert vh.dtype == dtype_
- u, cs, vh = cossin([x[:p, :q], x[:p, q:], x[p:, :q], x[p:, q:]],
- swap_sign=swap_sign)
- assert_allclose(x, u @ cs @ vh, rtol=0., atol=m*1e3*np.finfo(dtype_).eps)
- assert u.dtype == dtype_
- assert cs.dtype == np.real(u).dtype
- assert vh.dtype == dtype_
- _, cs2, vh2 = cossin(x, p, q,
- compute_u=False,
- swap_sign=swap_sign)
- assert_allclose(cs, cs2, rtol=0., atol=10*np.finfo(dtype_).eps)
- assert_allclose(vh, vh2, rtol=0., atol=10*np.finfo(dtype_).eps)
- u2, cs2, _ = cossin(x, p, q,
- compute_vh=False,
- swap_sign=swap_sign)
- assert_allclose(u, u2, rtol=0., atol=10*np.finfo(dtype_).eps)
- assert_allclose(cs, cs2, rtol=0., atol=10*np.finfo(dtype_).eps)
- _, cs2, _ = cossin(x, p, q,
- compute_u=False,
- compute_vh=False,
- swap_sign=swap_sign)
- assert_allclose(cs, cs2, rtol=0., atol=10*np.finfo(dtype_).eps)
- def test_cossin_mixed_types():
- seed(1234)
- x = np.array(ortho_group.rvs(4), dtype=np.float64)
- u, cs, vh = cossin([x[:2, :2],
- np.array(x[:2, 2:], dtype=np.complex128),
- x[2:, :2],
- x[2:, 2:]])
- assert u.dtype == np.complex128
- assert cs.dtype == np.float64
- assert vh.dtype == np.complex128
- assert_allclose(x, u @ cs @ vh, rtol=0.,
- atol=1e4 * np.finfo(np.complex128).eps)
- def test_cossin_error_incorrect_subblocks():
- with pytest.raises(ValueError, match="be due to missing p, q arguments."):
- cossin(([1, 2], [3, 4, 5], [6, 7], [8, 9, 10]))
- def test_cossin_error_empty_subblocks():
- with pytest.raises(ValueError, match="x11.*empty"):
- cossin(([], [], [], []))
- with pytest.raises(ValueError, match="x12.*empty"):
- cossin(([1, 2], [], [6, 7], [8, 9, 10]))
- with pytest.raises(ValueError, match="x21.*empty"):
- cossin(([1, 2], [3, 4, 5], [], [8, 9, 10]))
- with pytest.raises(ValueError, match="x22.*empty"):
- cossin(([1, 2], [3, 4, 5], [2], []))
- def test_cossin_error_missing_partitioning():
- with pytest.raises(ValueError, match=".*exactly four arrays.* got 2"):
- cossin(unitary_group.rvs(2))
- with pytest.raises(ValueError, match=".*might be due to missing p, q"):
- cossin(unitary_group.rvs(4))
- def test_cossin_error_non_iterable():
- with pytest.raises(ValueError, match="containing the subblocks of X"):
- cossin(12j)
- def test_cossin_error_non_square():
- with pytest.raises(ValueError, match="only supports square"):
- cossin(np.array([[1, 2]]), 1, 1)
- def test_cossin_error_partitioning():
- x = np.array(ortho_group.rvs(4), dtype=np.float64)
- with pytest.raises(ValueError, match="invalid p=0.*0<p<4.*"):
- cossin(x, 0, 1)
- with pytest.raises(ValueError, match="invalid p=4.*0<p<4.*"):
- cossin(x, 4, 1)
- with pytest.raises(ValueError, match="invalid q=-2.*0<q<4.*"):
- cossin(x, 1, -2)
- with pytest.raises(ValueError, match="invalid q=5.*0<q<4.*"):
- cossin(x, 1, 5)
- @pytest.mark.parametrize("dtype_", DTYPES)
- def test_cossin_separate(dtype_):
- seed(1234)
- m, p, q = 250, 80, 170
- pfx = 'or' if dtype_ in REAL_DTYPES else 'un'
- X = ortho_group.rvs(m) if pfx == 'or' else unitary_group.rvs(m)
- X = np.array(X, dtype=dtype_)
- drv, dlw = get_lapack_funcs((pfx + 'csd', pfx + 'csd_lwork'),[X])
- lwval = _compute_lwork(dlw, m, p, q)
- lwvals = {'lwork': lwval} if pfx == 'or' else dict(zip(['lwork',
- 'lrwork'],
- lwval))
- *_, theta, u1, u2, v1t, v2t, _ = \
- drv(X[:p, :q], X[:p, q:], X[p:, :q], X[p:, q:], **lwvals)
- (u1_2, u2_2), theta2, (v1t_2, v2t_2) = cossin(X, p, q, separate=True)
- assert_allclose(u1_2, u1, rtol=0., atol=10*np.finfo(dtype_).eps)
- assert_allclose(u2_2, u2, rtol=0., atol=10*np.finfo(dtype_).eps)
- assert_allclose(v1t_2, v1t, rtol=0., atol=10*np.finfo(dtype_).eps)
- assert_allclose(v2t_2, v2t, rtol=0., atol=10*np.finfo(dtype_).eps)
- assert_allclose(theta2, theta, rtol=0., atol=10*np.finfo(dtype_).eps)
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