Merge pull request #11888 from mreineck/add_pocketfft

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

1 files changed, 0 insertions, 79 deletions

diff --git a/numpy/fft/tests/test_helper.py b/numpy/fft/tests/test_helper.py
index 8d315fa02..6613c8002 100644
--- a/numpy/fft/tests/test_helper.py
+++ b/numpy/fft/tests/test_helper.py
@@ -7,7 +7,6 @@ from __future__ import division, absolute_import, print_function
 import numpy as np
 from numpy.testing import assert_array_almost_equal, assert_equal
 from numpy import fft, pi
-from numpy.fft.helper import _FFTCache
 
 
 class TestFFTShift(object):
@@ -168,81 +167,3 @@ class TestIRFFTN(object):
 
         # Should not raise error
         fft.irfftn(a, axes=axes)
-
-
-class TestFFTCache(object):
-
-    def test_basic_behaviour(self):
-        c = _FFTCache(max_size_in_mb=1, max_item_count=4)
-
-        # Put
-        c.put_twiddle_factors(1, np.ones(2, dtype=np.float32))
-        c.put_twiddle_factors(2, np.zeros(2, dtype=np.float32))
-
-        # Get
-        assert_array_almost_equal(c.pop_twiddle_factors(1),
-                                  np.ones(2, dtype=np.float32))
-        assert_array_almost_equal(c.pop_twiddle_factors(2),
-                                  np.zeros(2, dtype=np.float32))
-
-        # Nothing should be left.
-        assert_equal(len(c._dict), 0)
-
-        # Now put everything in twice so it can be retrieved once and each will
-        # still have one item left.
-        for _ in range(2):
-            c.put_twiddle_factors(1, np.ones(2, dtype=np.float32))
-            c.put_twiddle_factors(2, np.zeros(2, dtype=np.float32))
-        assert_array_almost_equal(c.pop_twiddle_factors(1),
-                                  np.ones(2, dtype=np.float32))
-        assert_array_almost_equal(c.pop_twiddle_factors(2),
-                                  np.zeros(2, dtype=np.float32))
-        assert_equal(len(c._dict), 2)
-
-    def test_automatic_pruning(self):
-        # That's around 2600 single precision samples.
-        c = _FFTCache(max_size_in_mb=0.01, max_item_count=4)
-
-        c.put_twiddle_factors(1, np.ones(200, dtype=np.float32))
-        c.put_twiddle_factors(2, np.ones(200, dtype=np.float32))
-        assert_equal(list(c._dict.keys()), [1, 2])
-
-        # This is larger than the limit but should still be kept.
-        c.put_twiddle_factors(3, np.ones(3000, dtype=np.float32))
-        assert_equal(list(c._dict.keys()), [1, 2, 3])
-        # Add one more.
-        c.put_twiddle_factors(4, np.ones(3000, dtype=np.float32))
-        # The other three should no longer exist.
-        assert_equal(list(c._dict.keys()), [4])
-
-        # Now test the max item count pruning.
-        c = _FFTCache(max_size_in_mb=0.01, max_item_count=2)
-        c.put_twiddle_factors(2, np.empty(2))
-        c.put_twiddle_factors(1, np.empty(2))
-        # Can still be accessed.
-        assert_equal(list(c._dict.keys()), [2, 1])
-
-        c.put_twiddle_factors(3, np.empty(2))
-        # 1 and 3 can still be accessed - c[2] has been touched least recently
-        # and is thus evicted.
-        assert_equal(list(c._dict.keys()), [1, 3])
-
-        # One last test. We will add a single large item that is slightly
-        # bigger then the cache size. Some small items can still be added.
-        c = _FFTCache(max_size_in_mb=0.01, max_item_count=5)
-        c.put_twiddle_factors(1, np.ones(3000, dtype=np.float32))
-        c.put_twiddle_factors(2, np.ones(2, dtype=np.float32))
-        c.put_twiddle_factors(3, np.ones(2, dtype=np.float32))
-        c.put_twiddle_factors(4, np.ones(2, dtype=np.float32))
-        assert_equal(list(c._dict.keys()), [1, 2, 3, 4])
-
-        # One more big item. This time it is 6 smaller ones but they are
-        # counted as one big item.
-        for _ in range(6):
-            c.put_twiddle_factors(5, np.ones(500, dtype=np.float32))
-        # '1' no longer in the cache. Rest still in the cache.
-        assert_equal(list(c._dict.keys()), [2, 3, 4, 5])
-
-        # Another big item - should now be the only item in the cache.
-        c.put_twiddle_factors(6, np.ones(4000, dtype=np.float32))
-        assert_equal(list(c._dict.keys()), [6])