| # ------------------------------------------------------------- |
| # |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| # |
| # ------------------------------------------------------------- |
| |
| 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() |