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# to you under the Apache License, Version 2.0 (the
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#
# http://www.apache.org/licenses/LICENSE-2.0
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# -------------------------------------------------------------
import unittest
import numpy as np
from systemds.context import SystemDSContext
class TestFFT(unittest.TestCase):
def setUp(self):
self.sds = SystemDSContext(capture_stdout=True, logging_level=50)
def tearDown(self):
self.sds.close()
def test_fft_basic(self):
input_matrix = np.array(
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
)
sds_input = self.sds.from_numpy(input_matrix)
fft_result = sds_input.fft().compute()
real_part, imag_part = fft_result
np_fft_result = np.fft.fft2(input_matrix)
expected_real = np.real(np_fft_result)
expected_imag = np.imag(np_fft_result)
np.testing.assert_array_almost_equal(real_part, expected_real, decimal=5)
np.testing.assert_array_almost_equal(imag_part, expected_imag, decimal=5)
def test_fft_random_1d(self):
np.random.seed(123)
for _ in range(10):
input_matrix = np.random.rand(1, 16)
sds_input = self.sds.from_numpy(input_matrix)
fft_result = sds_input.fft().compute()
real_part, imag_part = fft_result
np_fft_result = np.fft.fft(input_matrix[0])
expected_real = np.real(np_fft_result)
expected_imag = np.imag(np_fft_result)
np.testing.assert_array_almost_equal(
real_part.flatten(), expected_real, decimal=5
)
np.testing.assert_array_almost_equal(
imag_part.flatten(), expected_imag, decimal=5
)
def test_fft_2d(self):
np.random.seed(123)
for _ in range(10):
input_matrix = np.random.rand(8, 8)
sds_input = self.sds.from_numpy(input_matrix)
fft_result = sds_input.fft().compute()
real_part, imag_part = fft_result
np_fft_result = np.fft.fft2(input_matrix)
expected_real = np.real(np_fft_result)
expected_imag = np.imag(np_fft_result)
np.testing.assert_array_almost_equal(real_part, expected_real, decimal=5)
np.testing.assert_array_almost_equal(imag_part, expected_imag, decimal=5)
def test_fft_non_power_of_two_matrix(self):
input_matrix = np.random.rand(3, 5)
sds_input = self.sds.from_numpy(input_matrix)
with self.assertRaisesRegex(
RuntimeError,
"This FFT implementation is only defined for matrices with dimensions that are powers of 2.",
):
_ = sds_input.fft().compute()
def test_ifft_basic(self):
real_input_matrix = np.array(
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
)
imag_input_matrix = np.array(
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
)
sds_real_input = self.sds.from_numpy(real_input_matrix)
sds_imag_input = self.sds.from_numpy(imag_input_matrix)
ifft_result = sds_real_input.ifft(sds_imag_input).compute()
real_part, imag_part = ifft_result
np_ifft_result = np.fft.ifft2(real_input_matrix + 1j * imag_input_matrix)
expected_real = np.real(np_ifft_result)
expected_imag = np.imag(np_ifft_result)
np.testing.assert_array_almost_equal(real_part, expected_real, decimal=5)
np.testing.assert_array_almost_equal(imag_part, expected_imag, decimal=5)
def test_ifft_only_zeros_imag(self):
real_input_matrix = np.array(
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
)
imag_input_matrix = np.array(
[[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
)
sds_real_input = self.sds.from_numpy(real_input_matrix)
sds_imag_input = self.sds.from_numpy(imag_input_matrix)
ifft_result = sds_real_input.ifft(sds_imag_input).compute()
real_part, imag_part = ifft_result
np_ifft_result = np.fft.ifft2(real_input_matrix + 1j * imag_input_matrix)
expected_real = np.real(np_ifft_result)
expected_imag = np.imag(np_ifft_result)
np.testing.assert_array_almost_equal(real_part, expected_real, decimal=5)
np.testing.assert_array_almost_equal(imag_part, expected_imag, decimal=5)
def test_ifft_empty_matrix_imag(self):
real_input_matrix = np.array(
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
)
imag_input_matrix = np.array([])
sds_real_input = self.sds.from_numpy(real_input_matrix)
sds_imag_input = self.sds.from_numpy(imag_input_matrix)
with self.assertRaisesRegex(
RuntimeError,
"The second argument to IFFT cannot be an empty matrix. Provide either only a real matrix or a filled real and imaginary one.",
):
sds_real_input.ifft(sds_imag_input).compute()
def test_ifft_empty_2dmatrix_imag(self):
real_input_matrix = np.array(
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
)
imag_input_matrix = np.array([[]])
sds_real_input = self.sds.from_numpy(real_input_matrix)
sds_imag_input = self.sds.from_numpy(imag_input_matrix)
with self.assertRaisesRegex(
RuntimeError,
"The second argument to IFFT cannot be an empty matrix. Provide either only a real matrix or a filled real and imaginary one.",
):
sds_real_input.ifft(sds_imag_input).compute()
def test_ifft_random_1d(self):
np.random.seed(123)
for _ in range(10):
real_part = np.random.rand(1, 16)
imag_part = np.random.rand(1, 16)
complex_input = real_part + 1j * imag_part
np_fft_result = np.fft.fft(complex_input[0])
sds_real_input = self.sds.from_numpy(np.real(np_fft_result).reshape(1, -1))
sds_imag_input = self.sds.from_numpy(np.imag(np_fft_result).reshape(1, -1))
ifft_result = sds_real_input.ifft(sds_imag_input).compute()
real_part_result, imag_part_result = ifft_result
real_part_result = real_part_result.flatten()
imag_part_result = imag_part_result.flatten()
expected_ifft = np.fft.ifft(np_fft_result)
expected_real = np.real(expected_ifft)
expected_imag = np.imag(expected_ifft)
np.testing.assert_array_almost_equal(
real_part_result, expected_real, decimal=5
)
np.testing.assert_array_almost_equal(
imag_part_result, expected_imag, decimal=5
)
def test_ifft_real_only_basic(self):
np.random.seed(123)
real = np.array([1, 2, 3, 4, 4, 3, 2, 1])
sds_real_input = self.sds.from_numpy(real)
ifft_result = sds_real_input.ifft().compute()
real_part_result, imag_part_result = ifft_result
real_part_result = real_part_result.flatten()
imag_part_result = imag_part_result.flatten()
expected_ifft = np.fft.ifft(real)
expected_real = np.real(expected_ifft)
expected_imag = np.imag(expected_ifft)
np.testing.assert_array_almost_equal(real_part_result, expected_real, decimal=5)
np.testing.assert_array_almost_equal(imag_part_result, expected_imag, decimal=5)
def test_ifft_real_only_random(self):
np.random.seed(123)
for _ in range(10):
input_matrix = np.random.rand(1, 16)
sds_input = self.sds.from_numpy(input_matrix)
ifft_result = sds_input.ifft().compute()
real_part, imag_part = ifft_result
np_ifft_result = np.fft.ifft(input_matrix[0])
expected_real = np.real(np_ifft_result)
expected_imag = np.imag(np_ifft_result)
np.testing.assert_array_almost_equal(
real_part.flatten(), expected_real, decimal=5
)
np.testing.assert_array_almost_equal(
imag_part.flatten(), expected_imag, decimal=5
)
def test_ifft_2d(self):
np.random.seed(123)
for _ in range(10):
input_matrix = np.random.rand(8, 8) + 1j * np.random.rand(8, 8)
fft_result = np.fft.fft2(input_matrix)
sds_real_input = self.sds.from_numpy(np.real(fft_result))
sds_imag_input = self.sds.from_numpy(np.imag(fft_result))
ifft_result = sds_real_input.ifft(sds_imag_input).compute()
real_part, imag_part = ifft_result
expected_ifft_result = np.fft.ifft2(fft_result)
expected_real = np.real(expected_ifft_result)
expected_imag = np.imag(expected_ifft_result)
np.testing.assert_array_almost_equal(real_part, expected_real, decimal=5)
np.testing.assert_array_almost_equal(imag_part, expected_imag, decimal=5)
def test_fft_empty_matrix(self):
input_matrix = np.array([])
sds_input = self.sds.from_numpy(input_matrix)
with self.assertRaisesRegex(
RuntimeError, "The first argument to FFT cannot be an empty matrix."
):
_ = sds_input.fft().compute()
def test_ifft_empty_matrix(self):
input_matrix = np.array([])
sds_input = self.sds.from_numpy(input_matrix)
with self.assertRaisesRegex(
RuntimeError, "The first argument to IFFT cannot be an empty matrix."
):
_ = sds_input.ifft().compute()
def test_fft_single_element(self):
input_matrix = np.array([[5]])
sds_input = self.sds.from_numpy(input_matrix)
fft_result = sds_input.fft().compute()
real_part, imag_part = fft_result
np.testing.assert_array_almost_equal(real_part, [[5]], decimal=5)
np.testing.assert_array_almost_equal(imag_part, [[0]], decimal=5)
def test_ifft_single_element(self):
input_matrix = np.array([[5]])
sds_input = self.sds.from_numpy(input_matrix)
ifft_result = sds_input.ifft().compute()
real_part, imag_part = ifft_result
np.testing.assert_array_almost_equal(real_part, [[5]], decimal=5)
np.testing.assert_array_almost_equal(imag_part, [[0]], decimal=5)
def test_fft_zeros_matrix(self):
input_matrix = np.zeros((4, 4))
sds_input = self.sds.from_numpy(input_matrix)
fft_result = sds_input.fft().compute()
real_part, imag_part = fft_result
np.testing.assert_array_almost_equal(real_part, np.zeros((4, 4)), decimal=5)
np.testing.assert_array_almost_equal(imag_part, np.zeros((4, 4)), decimal=5)
def test_ifft_zeros_matrix(self):
input_matrix = np.zeros((4, 4))
sds_input = self.sds.from_numpy(input_matrix)
ifft_result = sds_input.ifft().compute()
real_part, imag_part = ifft_result
np.testing.assert_array_almost_equal(real_part, np.zeros((4, 4)), decimal=5)
np.testing.assert_array_almost_equal(imag_part, np.zeros((4, 4)), decimal=5)
def test_ifft_real_and_imaginary_dimensions_check(self):
real_part = np.random.rand(1, 16)
imag_part = np.random.rand(1, 14)
sds_real_input = self.sds.from_numpy(real_part)
sds_imag_input = self.sds.from_numpy(imag_part)
with self.assertRaisesRegex(
RuntimeError,
"The real and imaginary part of the provided matrix are of different dimensions.",
):
sds_real_input.ifft(sds_imag_input).compute()
def test_ifft_non_power_of_two_matrix(self):
real_part = np.random.rand(3, 5)
imag_part = np.random.rand(3, 5)
sds_real_input = self.sds.from_numpy(real_part)
sds_imag_input = self.sds.from_numpy(imag_part)
with self.assertRaisesRegex(
RuntimeError,
"This IFFT implementation is only defined for matrices with dimensions that are powers of 2.",
):
_ = sds_real_input.ifft(sds_imag_input).compute()
if __name__ == "__main__":
unittest.main()