def testStandardFFT(self):
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft.fft(t)
self.assertEqual(t1.shape, (10, 20, 30))
self.assertEqual(calc_shape(t1), t1.shape)
t1.tiles()
self.assertEqual(t1.shape, tuple(sum(ns) for ns in t1.nsplits))
self.assertEqual(calc_shape(t1.chunks[0]), t1.chunks[0].shape)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft.ifft(t)
self.assertEqual(t1.shape, (10, 20, 30))
self.assertEqual(calc_shape(t1), t1.shape)
t1.tiles()
self.assertEqual(t1.shape, tuple(sum(ns) for ns in t1.nsplits))
self.assertEqual(calc_shape(t1.chunks[0]), t1.chunks[0].shape)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft.fft2(t, s=(23, 21))
self.assertEqual(calc_shape(t1), t1.shape)
self.assertEqual(t1.shape, (10, 23, 21))
t1.tiles()
self.assertEqual(t1.shape, tuple(sum(ns) for ns in t1.nsplits))
self.assertEqual(calc_shape(t1.chunks[0]), t1.chunks[0].shape)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft.ifft2(t, s=(11, 9), axes=(1, 2))
self.assertEqual(calc_shape(t1), t1.shape)
self.assertEqual(t1.shape, (10, 11, 9))
t1.tiles()
self.assertEqual(t1.shape, tuple(sum(ns) for ns in t1.nsplits))
self.assertEqual(calc_shape(t1.chunks[0]), t1.chunks[0].shape)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft.fftn(t, s=(11, 9), axes=(1, 2))
self.assertEqual(calc_shape(t1), t1.shape)
self.assertEqual(t1.shape, (10, 11, 9))
t1.tiles()
self.assertEqual(t1.shape, tuple(sum(ns) for ns in t1.nsplits))
self.assertEqual(calc_shape(t1.chunks[0]), t1.chunks[0].shape)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft.ifftn(t, s=(11, 9), axes=(1, 2))
self.assertEqual(calc_shape(t1), t1.shape)
self.assertEqual(t1.shape, (10, 11, 9))
t1.tiles()
self.assertEqual(t1.shape, tuple(sum(ns) for ns in t1.nsplits))
self.assertEqual(calc_shape(t1.chunks[0]), t1.chunks[0].shape)
def test_ifftn_execution(setup):
raw = np.random.rand(10, 20, 30)
t = tensor(raw, chunk_size=(10, 20, 30))
r = ifftn(t)
res = r.execute().fetch()
expected = np.fft.ifftn(raw)
np.testing.assert_allclose(res, expected)
r = ifftn(t, norm='ortho')
res = r.execute().fetch()
expected = np.fft.ifftn(raw, norm='ortho')
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5))
res = r.execute().fetch()
expected = np.fft.ifftn(raw, s=(11, 12, 5))
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5), axes=(-1, -2, -3))
res = r.execute().fetch()
expected = np.fft.ifftn(raw, s=(11, 12, 5), axes=(-1, -2, -3))
np.testing.assert_allclose(res, expected)
raw = np.random.rand(10, 20, 30)
t = tensor(raw, chunk_size=(6, 8, 14))
r = ifftn(t)
res = r.execute().fetch()
expected = np.fft.ifftn(raw)
np.testing.assert_allclose(res, expected)
r = ifftn(t, norm='ortho')
res = r.execute().fetch()
expected = np.fft.ifftn(raw, norm='ortho')
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5))
res = r.execute().fetch()
expected = np.fft.ifftn(raw, s=(11, 12, 5))
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5), axes=(-1, -2, -3))
res = r.execute().fetch()
expected = np.fft.ifftn(raw, s=(11, 12, 5), axes=(-1, -2, -3))
np.testing.assert_allclose(res, expected)
def testIFFTNExecution(self):
raw = np.random.rand(10, 20, 30)
t = tensor(raw, chunk_size=(10, 20, 30))
r = ifftn(t)
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw)
np.testing.assert_allclose(res, expected)
r = ifftn(t, norm='ortho')
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw, norm='ortho')
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5))
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw, s=(11, 12, 5))
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5), axes=(-1, -2, -3))
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw, s=(11, 12, 5), axes=(-1, -2, -3))
np.testing.assert_allclose(res, expected)
raw = np.random.rand(10, 20, 30)
t = tensor(raw, chunk_size=(3, 4, 7))
r = ifftn(t)
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw)
np.testing.assert_allclose(res, expected)
r = ifftn(t, norm='ortho')
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw, norm='ortho')
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5))
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw, s=(11, 12, 5))
np.testing.assert_allclose(res, expected)
r = ifftn(t, s=(11, 12, 5), axes=(-1, -2, -3))
res = self.executor.execute_tensor(r, concat=True)[0]
expected = np.fft.ifftn(raw, s=(11, 12, 5), axes=(-1, -2, -3))
np.testing.assert_allclose(res, expected)
def test_standard_fft():
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft(t)
assert t1.shape == (10, 20, 30)
t1 = tile(t1)
assert t1.shape == tuple(sum(ns) for ns in t1.nsplits)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = ifft(t)
assert t1.shape == (10, 20, 30)
t1 = tile(t1)
assert t1.shape == tuple(sum(ns) for ns in t1.nsplits)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fft2(t, s=(23, 21))
assert t1.shape == (10, 23, 21)
t1 = tile(t1)
assert t1.shape == tuple(sum(ns) for ns in t1.nsplits)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = ifft2(t, s=(11, 9), axes=(1, 2))
assert t1.shape == (10, 11, 9)
t1 = tile(t1)
assert t1.shape == tuple(sum(ns) for ns in t1.nsplits)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = fftn(t, s=(11, 9), axes=(1, 2))
assert t1.shape == (10, 11, 9)
t1 = tile(t1)
assert t1.shape == tuple(sum(ns) for ns in t1.nsplits)
t = ones((10, 20, 30), chunk_size=(3, 20, 30))
t1 = ifftn(t, s=(11, 9), axes=(1, 2))
assert t1.shape == (10, 11, 9)
t1 = tile(t1)
assert t1.shape == tuple(sum(ns) for ns in t1.nsplits)
