Merge pull request #11888 from mreineck/add_pocketfft

WIP: Add pocketfft sources to numpy for testing, benchmarks, etc.

1 files changed, 195 insertions, 0 deletions

diff --git a/numpy/fft/tests/test_pocketfft.py b/numpy/fft/tests/test_pocketfft.py
new file mode 100644
index 000000000..0552f6afd
--- /dev/null
+++ b/numpy/fft/tests/test_pocketfft.py
@@ -0,0 +1,195 @@
+from __future__ import division, absolute_import, print_function
+
+import numpy as np
+from numpy.random import random
+from numpy.testing import (
+        assert_array_almost_equal, assert_array_equal, assert_raises,
+        )
+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(object):
+
+    def test_fft_n(self):
+        assert_raises(ValueError, np.fft.fft, [1, 2, 3], 0)
+
+
+class TestFFT1D(object):
+
+    def test_identity(self):
+        maxlen = 512
+        x = random(maxlen) + 1j*random(maxlen)
+        xr = random(maxlen)
+        for i in range(1,maxlen):
+            assert_array_almost_equal(np.fft.ifft(np.fft.fft(x[0:i])), x[0:i],
+                                      decimal=12)
+            assert_array_almost_equal(np.fft.irfft(np.fft.rfft(xr[0:i]),i),
+                                      xr[0:i], decimal=12)
+
+    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(object):
+    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)