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344 lines
11 KiB
344 lines
11 KiB
# |
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# This file is part of Magnum. |
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# |
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# Copyright © 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, |
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# 2020, 2021, 2022 Vladimír Vondruš <mosra@centrum.cz> |
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# |
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# Permission is hereby granted, free of charge, to any person obtaining a |
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# copy of this software and associated documentation files (the "Software"), |
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# to deal in the Software without restriction, including without limitation |
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# the rights to use, copy, modify, merge, publish, distribute, sublicense, |
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# and/or sell copies of the Software, and to permit persons to whom the |
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# Software is furnished to do so, subject to the following conditions: |
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# |
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# The above copyright notice and this permission notice shall be included |
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# in all copies or substantial portions of the Software. |
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# |
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL |
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# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING |
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# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER |
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# DEALINGS IN THE SOFTWARE. |
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# |
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import unittest |
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from magnum import * |
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from magnum import math |
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try: |
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import numpy as np |
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except ModuleNotFoundError: |
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raise unittest.SkipTest("numpy not installed") |
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class Vector(unittest.TestCase): |
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def test_from_numpy(self): |
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a = Vector3(np.array([1.0, 2.0, 3.0])) |
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self.assertEqual(a, Vector3(1.0, 2.0, 3.0)) |
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def test_to_numpy(self): |
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a = np.array(Vector3(1.0, 2.0, 3.0)) |
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np.testing.assert_array_equal(a, np.array([1.0, 2.0, 3.0])) |
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def test_from_numpy_implicit(self): |
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# This works even w/o buffer protocol |
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a = Vector4() |
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a.xyz = np.array([1.0, 2.0, 3.0]) |
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b = Matrix4.translation(np.array([1.0, 2.0, 3.0])) |
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self.assertEqual(b.translation, Vector3(1.0, 2.0, 3.0)) |
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def test_from_numpy_implicit_typed(self): |
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# But this doesn't, works only if buffer protocol is defined |
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a = Vector4() |
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a.xyz = np.array([1.0, 2.0, 3.0], dtype='float32') |
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a = Matrix4.translation(np.array([1.0, 2.0, 3.0], dtype='float32')) |
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self.assertEqual(a.translation, Vector3(1.0, 2.0, 3.0)) |
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def test_from_numpy_invalid_dimensions(self): |
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a = np.array([[1, 2], [3, 4]]) |
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self.assertEqual(a.ndim, 2) |
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with self.assertRaisesRegex(BufferError, "expected 1 dimension but got 2"): |
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b = Vector3i(a) |
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def test_from_numpy_invalid_size(self): |
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a = np.array([1.0, 2.0, 3.0]) |
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self.assertEqual(a.shape[0], 3) |
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with self.assertRaisesRegex(BufferError, "expected 2 elements but got 3"): |
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b = Vector2(a) |
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def test_type_from_numpy(self): |
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a = Vector3i(np.array([1, 2, -3], dtype='int32')) |
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self.assertEqual(a, Vector3i(1, 2, -3)) |
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a = Vector2ui(np.array([1, 2], dtype='uint32')) |
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self.assertEqual(a, Vector2ui(1, 2)) |
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a = Vector4i(np.array([1, 2, -3, 0], dtype='int64')) |
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self.assertEqual(a, Vector4i(1, 2, -3, 0)) |
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a = Vector3ui(np.array([1, 2, 3333], dtype='uint64')) |
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self.assertEqual(a, Vector3i(1, 2, 3333)) |
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a = Vector2d(np.array([1.0, 2.0], dtype='float32')) |
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self.assertEqual(a, Vector2d(1.0, 2.0)) |
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a = Vector2(np.array([1.0, 2.0], dtype='float64')) |
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self.assertEqual(a, Vector2(1.0, 2.0)) |
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def test_type_from_numpy_invalid_float(self): |
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a = np.array([1, 2, 3]) |
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self.assertEqual(a.dtype, 'int64') |
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with self.assertRaisesRegex(BufferError, "unexpected format l for a f vector"): |
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b = Vector3(a) |
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def test_type_from_numpy_invalid_signed(self): |
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a = np.array([1.0, 2.0, 3.0]) |
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self.assertEqual(a.dtype, 'float64') |
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with self.assertRaisesRegex(BufferError, "unexpected format d for a i vector"): |
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b = Vector3i(a) |
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class Matrix(unittest.TestCase): |
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def test_from_numpy(self): |
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a = Matrix2x3(np.array( |
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[[1.0, 2.0], |
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[4.0, 5.0], |
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[7.0, 8.0]])) |
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self.assertEqual(a, Matrix2x3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0))) |
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a = Matrix3x3d(np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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self.assertEqual(a, Matrix3x3d( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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a = Matrix4x2(np.array( |
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[[1.0, 2.0, 3.0, 4.0], |
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[5.0, 6.0, 7.0, 8.0]])) |
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self.assertEqual(a, Matrix4x2( |
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(1.0, 5.0), |
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(2.0, 6.0), |
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(3.0, 7.0), |
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(4.0, 8.0))) |
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def test_to_numpy(self): |
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a = np.array(Matrix2x3d( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0))) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0], |
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[4.0, 5.0], |
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[7.0, 8.0]])) |
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a = np.array(Matrix3x3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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a = np.array(Matrix4x2( |
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(1.0, 5.0), |
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(2.0, 6.0), |
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(3.0, 7.0), |
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(4.0, 8.0))) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0, 4.0], |
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[5.0, 6.0, 7.0, 8.0]])) |
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def test_from_numpy_invalid_dimensions(self): |
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a = np.array([1, 2, 3, 4]) |
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self.assertEqual(a.ndim, 1) |
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with self.assertRaisesRegex(BufferError, "expected 2 dimensions but got 1"): |
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b = Matrix2x2(a) |
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def test_from_numpy_invalid_size(self): |
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a = np.array([[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0]]) |
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self.assertEqual(a.shape[0], 2) |
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self.assertEqual(a.shape[1], 3) |
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with self.assertRaisesRegex(BufferError, "expected 2x3 elements but got 3x2"): |
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b = Matrix2x3(a) |
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def test_order_from_numpy(self): |
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a = np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]]) |
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self.assertEqual(a.strides[0], 24) |
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self.assertEqual(a.strides[1], 8) |
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self.assertEqual(Matrix3x3d(a), Matrix3x3d( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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a = np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]], order='C') |
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self.assertEqual(a.strides[0], 24) |
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self.assertEqual(a.strides[1], 8) |
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self.assertEqual(Matrix3x3d(a), Matrix3x3d( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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a = np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]], order='F') |
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self.assertEqual(a.strides[0], 8) |
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self.assertEqual(a.strides[1], 24) |
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self.assertEqual(Matrix3x3d(a), Matrix3x3d( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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def test_order_to_numpy(self): |
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a = np.array(Matrix3x3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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self.assertEqual(a.strides[0], 4) |
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self.assertEqual(a.strides[1], 12) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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a = np.array(Matrix3x3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0)), order='C') |
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self.assertEqual(a.strides[0], 12) |
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self.assertEqual(a.strides[1], 4) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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a = np.array(Matrix3x3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0)), order='F') |
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self.assertEqual(a.strides[0], 4) |
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self.assertEqual(a.strides[1], 12) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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def test_type_from_numpy(self): |
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a = np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]], dtype='f') |
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self.assertEqual(a.dtype, 'f') |
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self.assertEqual(a.itemsize, 4) |
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self.assertEqual(Matrix3x3d(a), Matrix3x3d( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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a = np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]], dtype='d') |
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self.assertEqual(a.dtype, 'd') |
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self.assertEqual(a.itemsize, 8) |
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self.assertEqual(Matrix3x3(a), Matrix3x3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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def test_type_from_numpy_invalid(self): |
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a = np.array([[1, 2], [3, 4]]) |
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self.assertEqual(a.dtype, 'int64') |
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with self.assertRaisesRegex(BufferError, "expected format f or d but got l"): |
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b = Matrix2x2(a) |
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def test_type_to_numpy(self): |
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a = np.array(Matrix3x3d( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0)), dtype='f') |
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self.assertEqual(a.dtype, 'f') |
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self.assertEqual(a.itemsize, 4) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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a = np.array(Matrix3x3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0)), dtype='d') |
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self.assertEqual(a.dtype, 'd') |
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self.assertEqual(a.itemsize, 8) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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class Matrix3_(unittest.TestCase): |
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def test_from_numpy(self): |
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a = Matrix3(np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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self.assertEqual(a, Matrix3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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def test_to_numpy(self): |
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a = np.array(Matrix3( |
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(1.0, 4.0, 7.0), |
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(2.0, 5.0, 8.0), |
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(3.0, 6.0, 9.0))) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0], |
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[4.0, 5.0, 6.0], |
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[7.0, 8.0, 9.0]])) |
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class Matrix4_(unittest.TestCase): |
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def test_from_numpy(self): |
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a = Matrix4(np.array( |
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[[1.0, 2.0, 3.0, 4.0], |
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[5.0, 6.0, 7.0, 8.0], |
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[9.0, 10.0, 11.0, 12.0], |
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[13.0, 14.0, 15.0, 16.0]])) |
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self.assertEqual(a, Matrix4( |
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(1.0, 5.0, 9.0, 13.0), |
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(2.0, 6.0, 10.0, 14.0), |
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(3.0, 7.0, 11.0, 15.0), |
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(4.0, 8.0, 12.0, 16.0))) |
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def test_to_numpy(self): |
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a = np.array(Matrix4( |
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(1.0, 5.0, 9.0, 13.0), |
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(2.0, 6.0, 10.0, 14.0), |
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(3.0, 7.0, 11.0, 15.0), |
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(4.0, 8.0, 12.0, 16.0))) |
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np.testing.assert_array_equal(a, np.array( |
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[[1.0, 2.0, 3.0, 4.0], |
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[5.0, 6.0, 7.0, 8.0], |
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[9.0, 10.0, 11.0, 12.0], |
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[13.0, 14.0, 15.0, 16.0]]))
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