/usr/lib/python2.7/dist-packages/numpy/fft/tests/test_fftpack.py is in python-numpy 1:1.13.3-2ubuntu1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 | from __future__ import division, absolute_import, print_function
import numpy as np
from numpy.random import random
from numpy.testing import TestCase, run_module_suite, assert_array_almost_equal
from numpy.testing import assert_array_equal
import threading
import sys
if sys.version_info[0] >= 3:
import queue
else:
import Queue as queue
def fft1(x):
L = len(x)
phase = -2j*np.pi*(np.arange(L)/float(L))
phase = np.arange(L).reshape(-1, 1) * phase
return np.sum(x*np.exp(phase), axis=1)
class TestFFTShift(TestCase):
def test_fft_n(self):
self.assertRaises(ValueError, np.fft.fft, [1, 2, 3], 0)
class TestFFT1D(TestCase):
def test_fft(self):
x = random(30) + 1j*random(30)
assert_array_almost_equal(fft1(x), np.fft.fft(x))
assert_array_almost_equal(fft1(x) / np.sqrt(30),
np.fft.fft(x, norm="ortho"))
def test_ifft(self):
x = random(30) + 1j*random(30)
assert_array_almost_equal(x, np.fft.ifft(np.fft.fft(x)))
assert_array_almost_equal(
x, np.fft.ifft(np.fft.fft(x, norm="ortho"), norm="ortho"))
def test_fft2(self):
x = random((30, 20)) + 1j*random((30, 20))
assert_array_almost_equal(np.fft.fft(np.fft.fft(x, axis=1), axis=0),
np.fft.fft2(x))
assert_array_almost_equal(np.fft.fft2(x) / np.sqrt(30 * 20),
np.fft.fft2(x, norm="ortho"))
def test_ifft2(self):
x = random((30, 20)) + 1j*random((30, 20))
assert_array_almost_equal(np.fft.ifft(np.fft.ifft(x, axis=1), axis=0),
np.fft.ifft2(x))
assert_array_almost_equal(np.fft.ifft2(x) * np.sqrt(30 * 20),
np.fft.ifft2(x, norm="ortho"))
def test_fftn(self):
x = random((30, 20, 10)) + 1j*random((30, 20, 10))
assert_array_almost_equal(
np.fft.fft(np.fft.fft(np.fft.fft(x, axis=2), axis=1), axis=0),
np.fft.fftn(x))
assert_array_almost_equal(np.fft.fftn(x) / np.sqrt(30 * 20 * 10),
np.fft.fftn(x, norm="ortho"))
def test_ifftn(self):
x = random((30, 20, 10)) + 1j*random((30, 20, 10))
assert_array_almost_equal(
np.fft.ifft(np.fft.ifft(np.fft.ifft(x, axis=2), axis=1), axis=0),
np.fft.ifftn(x))
assert_array_almost_equal(np.fft.ifftn(x) * np.sqrt(30 * 20 * 10),
np.fft.ifftn(x, norm="ortho"))
def test_rfft(self):
x = random(30)
for n in [x.size, 2*x.size]:
for norm in [None, 'ortho']:
assert_array_almost_equal(
np.fft.fft(x, n=n, norm=norm)[:(n//2 + 1)],
np.fft.rfft(x, n=n, norm=norm))
assert_array_almost_equal(np.fft.rfft(x, n=n) / np.sqrt(n),
np.fft.rfft(x, n=n, norm="ortho"))
def test_irfft(self):
x = random(30)
assert_array_almost_equal(x, np.fft.irfft(np.fft.rfft(x)))
assert_array_almost_equal(
x, np.fft.irfft(np.fft.rfft(x, norm="ortho"), norm="ortho"))
def test_rfft2(self):
x = random((30, 20))
assert_array_almost_equal(np.fft.fft2(x)[:, :11], np.fft.rfft2(x))
assert_array_almost_equal(np.fft.rfft2(x) / np.sqrt(30 * 20),
np.fft.rfft2(x, norm="ortho"))
def test_irfft2(self):
x = random((30, 20))
assert_array_almost_equal(x, np.fft.irfft2(np.fft.rfft2(x)))
assert_array_almost_equal(
x, np.fft.irfft2(np.fft.rfft2(x, norm="ortho"), norm="ortho"))
def test_rfftn(self):
x = random((30, 20, 10))
assert_array_almost_equal(np.fft.fftn(x)[:, :, :6], np.fft.rfftn(x))
assert_array_almost_equal(np.fft.rfftn(x) / np.sqrt(30 * 20 * 10),
np.fft.rfftn(x, norm="ortho"))
def test_irfftn(self):
x = random((30, 20, 10))
assert_array_almost_equal(x, np.fft.irfftn(np.fft.rfftn(x)))
assert_array_almost_equal(
x, np.fft.irfftn(np.fft.rfftn(x, norm="ortho"), norm="ortho"))
def test_hfft(self):
x = random(14) + 1j*random(14)
x_herm = np.concatenate((random(1), x, random(1)))
x = np.concatenate((x_herm, x[::-1].conj()))
assert_array_almost_equal(np.fft.fft(x), np.fft.hfft(x_herm))
assert_array_almost_equal(np.fft.hfft(x_herm) / np.sqrt(30),
np.fft.hfft(x_herm, norm="ortho"))
def test_ihttf(self):
x = random(14) + 1j*random(14)
x_herm = np.concatenate((random(1), x, random(1)))
x = np.concatenate((x_herm, x[::-1].conj()))
assert_array_almost_equal(x_herm, np.fft.ihfft(np.fft.hfft(x_herm)))
assert_array_almost_equal(
x_herm, np.fft.ihfft(np.fft.hfft(x_herm, norm="ortho"),
norm="ortho"))
def test_all_1d_norm_preserving(self):
# verify that round-trip transforms are norm-preserving
x = random(30)
x_norm = np.linalg.norm(x)
n = x.size * 2
func_pairs = [(np.fft.fft, np.fft.ifft),
(np.fft.rfft, np.fft.irfft),
# hfft: order so the first function takes x.size samples
# (necessary for comparison to x_norm above)
(np.fft.ihfft, np.fft.hfft),
]
for forw, back in func_pairs:
for n in [x.size, 2*x.size]:
for norm in [None, 'ortho']:
tmp = forw(x, n=n, norm=norm)
tmp = back(tmp, n=n, norm=norm)
assert_array_almost_equal(x_norm,
np.linalg.norm(tmp))
class TestFFTThreadSafe(TestCase):
threads = 16
input_shape = (800, 200)
def _test_mtsame(self, func, *args):
def worker(args, q):
q.put(func(*args))
q = queue.Queue()
expected = func(*args)
# Spin off a bunch of threads to call the same function simultaneously
t = [threading.Thread(target=worker, args=(args, q))
for i in range(self.threads)]
[x.start() for x in t]
[x.join() for x in t]
# Make sure all threads returned the correct value
for i in range(self.threads):
assert_array_equal(q.get(timeout=5), expected,
'Function returned wrong value in multithreaded context')
def test_fft(self):
a = np.ones(self.input_shape) * 1+0j
self._test_mtsame(np.fft.fft, a)
def test_ifft(self):
a = np.ones(self.input_shape) * 1+0j
self._test_mtsame(np.fft.ifft, a)
def test_rfft(self):
a = np.ones(self.input_shape)
self._test_mtsame(np.fft.rfft, a)
def test_irfft(self):
a = np.ones(self.input_shape) * 1+0j
self._test_mtsame(np.fft.irfft, a)
if __name__ == "__main__":
run_module_suite()
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