Vehicle-Anti-Theft-Face-Rec.../venv/Lib/site-packages/scipy/fft/tests/test_helper.py

297 lines
9.5 KiB
Python

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)
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)