from scipy.fft._helper import next_fast_len, _init_nd_shape_and_axes from numpy.testing import assert_equal, assert_array_equal from pytest import raises as assert_raises import pytest import numpy as np import sys _5_smooth_numbers = [ 2, 3, 4, 5, 6, 8, 9, 10, 2 * 3 * 5, 2**3 * 3**5, 2**3 * 3**3 * 5**2, ] def test_next_fast_len(): for n in _5_smooth_numbers: assert_equal(next_fast_len(n), n) def _assert_n_smooth(x, n): x_orig = x if n < 2: assert False while True: q, r = divmod(x, 2) if r != 0: break x = q for d in range(3, n+1, 2): while True: q, r = divmod(x, d) if r != 0: break x = q assert x == 1, \ 'x={} is not {}-smooth, remainder={}'.format(x_orig, n, x) class TestNextFastLen(object): def test_next_fast_len(self): np.random.seed(1234) def nums(): for j in range(1, 1000): yield j yield 2**5 * 3**5 * 4**5 + 1 for n in nums(): m = next_fast_len(n) _assert_n_smooth(m, 11) assert m == next_fast_len(n, False) m = next_fast_len(n, True) _assert_n_smooth(m, 5) def test_np_integers(self): ITYPES = [np.int16, np.int32, np.int64, np.uint16, np.uint32, np.uint64] for ityp in ITYPES: x = ityp(12345) testN = next_fast_len(x) assert_equal(testN, next_fast_len(int(x))) def testnext_fast_len_small(self): hams = { 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 8, 8: 8, 14: 15, 15: 15, 16: 16, 17: 18, 1021: 1024, 1536: 1536, 51200000: 51200000 } for x, y in hams.items(): assert_equal(next_fast_len(x, True), y) @pytest.mark.xfail(sys.maxsize < 2**32, reason="Hamming Numbers too large for 32-bit", raises=ValueError, strict=True) def testnext_fast_len_big(self): hams = { 510183360: 510183360, 510183360 + 1: 512000000, 511000000: 512000000, 854296875: 854296875, 854296875 + 1: 859963392, 196608000000: 196608000000, 196608000000 + 1: 196830000000, 8789062500000: 8789062500000, 8789062500000 + 1: 8796093022208, 206391214080000: 206391214080000, 206391214080000 + 1: 206624260800000, 470184984576000: 470184984576000, 470184984576000 + 1: 470715894135000, 7222041363087360: 7222041363087360, 7222041363087360 + 1: 7230196133913600, # power of 5 5**23 11920928955078125: 11920928955078125, 11920928955078125 - 1: 11920928955078125, # power of 3 3**34 16677181699666569: 16677181699666569, 16677181699666569 - 1: 16677181699666569, # power of 2 2**54 18014398509481984: 18014398509481984, 18014398509481984 - 1: 18014398509481984, # above this, int(ceil(n)) == int(ceil(n+1)) 19200000000000000: 19200000000000000, 19200000000000000 + 1: 19221679687500000, 288230376151711744: 288230376151711744, 288230376151711744 + 1: 288325195312500000, 288325195312500000 - 1: 288325195312500000, 288325195312500000: 288325195312500000, 288325195312500000 + 1: 288555831593533440, } for x, y in hams.items(): assert_equal(next_fast_len(x, True), y) def test_keyword_args(self): assert next_fast_len(11, real=True) == 12 assert next_fast_len(target=7, real=False) == 7 class Test_init_nd_shape_and_axes(object): def test_py_0d_defaults(self): x = np.array(4) shape = None axes = None shape_expected = np.array([]) axes_expected = np.array([]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_np_0d_defaults(self): x = np.array(7.) shape = None axes = None shape_expected = np.array([]) axes_expected = np.array([]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_py_1d_defaults(self): x = np.array([1, 2, 3]) shape = None axes = None shape_expected = np.array([3]) axes_expected = np.array([0]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_np_1d_defaults(self): x = np.arange(0, 1, .1) shape = None axes = None shape_expected = np.array([10]) axes_expected = np.array([0]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_py_2d_defaults(self): x = np.array([[1, 2, 3, 4], [5, 6, 7, 8]]) shape = None axes = None shape_expected = np.array([2, 4]) axes_expected = np.array([0, 1]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_np_2d_defaults(self): x = np.arange(0, 1, .1).reshape(5, 2) shape = None axes = None shape_expected = np.array([5, 2]) axes_expected = np.array([0, 1]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_np_5d_defaults(self): x = np.zeros([6, 2, 5, 3, 4]) shape = None axes = None shape_expected = np.array([6, 2, 5, 3, 4]) axes_expected = np.array([0, 1, 2, 3, 4]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_np_5d_set_shape(self): x = np.zeros([6, 2, 5, 3, 4]) shape = [10, -1, -1, 1, 4] axes = None shape_expected = np.array([10, 2, 5, 1, 4]) axes_expected = np.array([0, 1, 2, 3, 4]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_np_5d_set_axes(self): x = np.zeros([6, 2, 5, 3, 4]) shape = None axes = [4, 1, 2] shape_expected = np.array([4, 2, 5]) axes_expected = np.array([4, 1, 2]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_np_5d_set_shape_axes(self): x = np.zeros([6, 2, 5, 3, 4]) shape = [10, -1, 2] axes = [1, 0, 3] shape_expected = np.array([10, 6, 2]) axes_expected = np.array([1, 0, 3]) shape_res, axes_res = _init_nd_shape_and_axes(x, shape, axes) assert_equal(shape_res, shape_expected) assert_equal(axes_res, axes_expected) def test_shape_axes_subset(self): x = np.zeros((2, 3, 4, 5)) shape, axes = _init_nd_shape_and_axes(x, shape=(5, 5, 5), axes=None) assert_array_equal(shape, [5, 5, 5]) assert_array_equal(axes, [1, 2, 3]) def test_errors(self): x = np.zeros(1) with assert_raises(ValueError, match="axes must be a scalar or " "iterable of integers"): _init_nd_shape_and_axes(x, shape=None, axes=[[1, 2], [3, 4]]) with assert_raises(ValueError, match="axes must be a scalar or " "iterable of integers"): _init_nd_shape_and_axes(x, shape=None, axes=[1., 2., 3., 4.]) with assert_raises(ValueError, match="axes exceeds dimensionality of input"): _init_nd_shape_and_axes(x, shape=None, axes=[1]) with assert_raises(ValueError, match="axes exceeds dimensionality of input"): _init_nd_shape_and_axes(x, shape=None, axes=[-2]) with assert_raises(ValueError, match="all axes must be unique"): _init_nd_shape_and_axes(x, shape=None, axes=[0, 0]) with assert_raises(ValueError, match="shape must be a scalar or " "iterable of integers"): _init_nd_shape_and_axes(x, shape=[[1, 2], [3, 4]], axes=None) with assert_raises(ValueError, match="shape must be a scalar or " "iterable of integers"): _init_nd_shape_and_axes(x, shape=[1., 2., 3., 4.], axes=None) with assert_raises(ValueError, match="when given, axes and shape arguments" " have to be of the same length"): _init_nd_shape_and_axes(np.zeros([1, 1, 1, 1]), shape=[1, 2, 3], axes=[1]) with assert_raises(ValueError, match="invalid number of data points" r" \(\[0\]\) specified"): _init_nd_shape_and_axes(x, shape=[0], axes=None) with assert_raises(ValueError, match="invalid number of data points" r" \(\[-2\]\) specified"): _init_nd_shape_and_axes(x, shape=-2, axes=None)