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| import unittest | |
| import numpy as np | |
| from training.np_tools import pad_1D, pad_2D, pad_3D | |
| class TestPad(unittest.TestCase): | |
| def test_pad_1D(self): | |
| # Test case 1: Pad a list of 1D numpy arrays with different lengths | |
| inputs = [np.array([1, 2, 3]), np.array([4, 5]), np.array([6])] | |
| expected_output = np.array([[1, 2, 3], [4, 5, 0], [6, 0, 0]]) | |
| self.assertTrue(np.array_equal(pad_1D(inputs), expected_output)) | |
| # Test case 2: Pad a list of 1D numpy arrays with the same length | |
| inputs = [np.array([1, 2, 3]), np.array([4, 5, 6]), np.array([7, 8, 9])] | |
| expected_output = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) | |
| self.assertTrue(np.array_equal(pad_1D(inputs), expected_output)) | |
| # Test case 3: Pad a list of 1D numpy arrays with a non-zero pad value | |
| inputs = [np.array([1, 2]), np.array([3, 4, 5]), np.array([6, 7, 8, 9])] | |
| expected_output = np.array([[1, 2, 0, 0], [3, 4, 5, 0], [6, 7, 8, 9]]) | |
| self.assertTrue(np.array_equal(pad_1D(inputs, pad_value=0.0), expected_output)) | |
| # Test case 4: Pad a list of 1D numpy arrays with a non-zero pad value | |
| inputs = [np.array([1, 2]), np.array([3, 4, 5]), np.array([6, 7, 8, 9])] | |
| expected_output = np.array([[1, 2, 1, 1], [3, 4, 5, 1], [6, 7, 8, 9]]) | |
| self.assertTrue(np.array_equal(pad_1D(inputs, pad_value=1.0), expected_output)) | |
| # Test case 5: Pad a list of 1D numpy arrays with a single non-empty array | |
| inputs = [np.array([1, 2, 3])] | |
| expected_output = np.array([[1, 2, 3]]) | |
| self.assertTrue(np.array_equal(pad_1D(inputs), expected_output)) | |
| def test_pad_2D(self): | |
| # Test case 1: Pad a list of 2D numpy arrays with different shapes | |
| inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6, 7], [8, 9, 10]])] | |
| expected_output = np.array([[[1, 2, 0], [3, 4, 0]], [[5, 6, 7], [8, 9, 10]]]) | |
| self.assertTrue(np.array_equal(pad_2D(inputs), expected_output)) | |
| # Test case 2: Pad a list of 2D numpy arrays with the same shape | |
| inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6], [7, 8]])] | |
| expected_output = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]) | |
| self.assertTrue(np.array_equal(pad_2D(inputs), expected_output)) | |
| # Test case 3: Pad a list of 2D numpy arrays with a non-zero pad value | |
| inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6, 7], [8, 9, 10]])] | |
| expected_output = np.array([[[1, 2, 1], [3, 4, 1]], [[5, 6, 7], [8, 9, 10]]]) | |
| self.assertTrue(np.array_equal(pad_2D(inputs, pad_value=1.0), expected_output)) | |
| # Test case 4: Pad a list of 2D numpy arrays with a maximum length | |
| inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6, 7], [8, 9, 10]])] | |
| expected_output = np.array([[[1, 2, 0], [3, 4, 0]], [[5, 6, 7], [8, 9, 10]]]) | |
| self.assertTrue(np.array_equal(pad_2D(inputs, maxlen=3), expected_output)) | |
| # Test case 5: Pad a list of 2D numpy arrays with a single non-empty array | |
| inputs = [np.array([[1, 2], [3, 4]])] | |
| expected_output = np.array([[[1, 2], [3, 4]]]) | |
| self.assertTrue(np.array_equal(pad_2D(inputs), expected_output)) | |
| def test_pad_3D(self): | |
| # Test case 1: Pad a 3D numpy array with different dimensions | |
| inputs = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]]) | |
| expected_output = np.array( | |
| [ | |
| [[1, 2, 0], [3, 4, 0], [0, 0, 0]], | |
| [[5, 6, 0], [7, 8, 0], [0, 0, 0]], | |
| [[9, 10, 0], [11, 12, 0], [0, 0, 0]], | |
| ], | |
| ) | |
| self.assertTrue(np.array_equal(pad_3D(inputs, B=3, T=3, L=3), expected_output)) | |
| # Test case 2: Pad a 3D numpy array with the same dimensions | |
| inputs = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]]) | |
| expected_output = np.array( | |
| [ | |
| [[1, 2], [3, 4]], | |
| [[5, 6], [7, 8]], | |
| [[9, 10], [11, 12]], | |
| ], | |
| ) | |
| self.assertTrue(np.array_equal(pad_3D(inputs, B=3, T=2, L=2), expected_output)) | |
| # Test case 3: Pad a 3D numpy array with a single element | |
| inputs = np.array([[[1, 2], [3, 4]]]) | |
| expected_output = np.array([[[1, 2, 0], [3, 4, 0]]]) | |
| self.assertTrue(np.array_equal(pad_3D(inputs, B=1, T=2, L=3), expected_output)) | |
| if __name__ == "__main__": | |
| unittest.main() | |