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#
# This file is part of Magnum.
#
# Copyright © 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019,
# 2020, 2021, 2022, 2023 Vladimír Vondruš <mosra@centrum.cz>
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
#
import unittest
from magnum import *
from magnum import math
try:
import numpy as np
except ModuleNotFoundError:
raise unittest.SkipTest("numpy not installed")
class Vector(unittest.TestCase):
def test_from_numpy(self):
a = Vector3(np.array([1.0, 2.0, 3.0]))
self.assertEqual(a, Vector3(1.0, 2.0, 3.0))
def test_to_numpy(self):
a = np.array(Vector3(1.0, 2.0, 3.0))
np.testing.assert_array_equal(a, np.array([1.0, 2.0, 3.0]))
def test_from_numpy_implicit(self):
# This works even w/o buffer protocol
a = Vector4()
a.xyz = np.array([1.0, 2.0, 3.0])
b = Matrix4.translation(np.array([1.0, 2.0, 3.0]))
self.assertEqual(b.translation, Vector3(1.0, 2.0, 3.0))
def test_from_numpy_implicit_typed(self):
# But this doesn't, works only if buffer protocol is defined
a = Vector4()
a.xyz = np.array([1.0, 2.0, 3.0], dtype='float32')
a = Matrix4.translation(np.array([1.0, 2.0, 3.0], dtype='float32'))
self.assertEqual(a.translation, Vector3(1.0, 2.0, 3.0))
def test_from_numpy_invalid_dimensions(self):
a = np.array([[1, 2], [3, 4]])
self.assertEqual(a.ndim, 2)
with self.assertRaisesRegex(BufferError, "expected 1 dimension but got 2"):
b = Vector3i(a)
def test_from_numpy_invalid_size(self):
a = np.array([1.0, 2.0, 3.0])
self.assertEqual(a.shape[0], 3)
with self.assertRaisesRegex(BufferError, "expected 2 elements but got 3"):
b = Vector2(a)
def test_type_from_numpy(self):
a = Vector3i(np.array([1, 2, -3], dtype='int32'))
self.assertEqual(a, Vector3i(1, 2, -3))
a = Vector2ui(np.array([1, 2], dtype='uint32'))
self.assertEqual(a, Vector2ui(1, 2))
a = Vector4i(np.array([1, 2, -3, 0], dtype='int64'))
self.assertEqual(a, Vector4i(1, 2, -3, 0))
a = Vector3ui(np.array([1, 2, 3333], dtype='uint64'))
self.assertEqual(a, Vector3i(1, 2, 3333))
a = Vector2d(np.array([1.0, 2.0], dtype='float32'))
self.assertEqual(a, Vector2d(1.0, 2.0))
a = Vector2(np.array([1.0, 2.0], dtype='float64'))
self.assertEqual(a, Vector2(1.0, 2.0))
def test_type_from_numpy_invalid_float(self):
a = np.array([1, 2, 3])
self.assertEqual(a.dtype, 'int64')
with self.assertRaisesRegex(BufferError, "unexpected format l for a f vector"):
b = Vector3(a)
def test_type_from_numpy_invalid_signed(self):
a = np.array([1.0, 2.0, 3.0])
self.assertEqual(a.dtype, 'float64')
with self.assertRaisesRegex(BufferError, "unexpected format d for a i vector"):
b = Vector3i(a)
class Matrix(unittest.TestCase):
def test_from_numpy(self):
a = Matrix2x3(np.array(
[[1.0, 2.0],
[4.0, 5.0],
[7.0, 8.0]]))
self.assertEqual(a, Matrix2x3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0)))
a = Matrix3x3d(np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
self.assertEqual(a, Matrix3x3d(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
a = Matrix4x2(np.array(
[[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0]]))
self.assertEqual(a, Matrix4x2(
(1.0, 5.0),
(2.0, 6.0),
(3.0, 7.0),
(4.0, 8.0)))
def test_to_numpy(self):
a = np.array(Matrix2x3d(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0)))
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0],
[4.0, 5.0],
[7.0, 8.0]]))
a = np.array(Matrix3x3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
a = np.array(Matrix4x2(
(1.0, 5.0),
(2.0, 6.0),
(3.0, 7.0),
(4.0, 8.0)))
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0]]))
def test_from_numpy_invalid_dimensions(self):
a = np.array([1, 2, 3, 4])
self.assertEqual(a.ndim, 1)
with self.assertRaisesRegex(BufferError, "expected 2 dimensions but got 1"):
b = Matrix2x2(a)
def test_from_numpy_invalid_size(self):
a = np.array([[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0]])
self.assertEqual(a.shape[0], 2)
self.assertEqual(a.shape[1], 3)
with self.assertRaisesRegex(BufferError, "expected 2x3 elements but got 3x2"):
b = Matrix2x3(a)
def test_order_from_numpy(self):
a = np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]])
self.assertEqual(a.strides[0], 24)
self.assertEqual(a.strides[1], 8)
self.assertEqual(Matrix3x3d(a), Matrix3x3d(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
a = np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]], order='C')
self.assertEqual(a.strides[0], 24)
self.assertEqual(a.strides[1], 8)
self.assertEqual(Matrix3x3d(a), Matrix3x3d(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
a = np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]], order='F')
self.assertEqual(a.strides[0], 8)
self.assertEqual(a.strides[1], 24)
self.assertEqual(Matrix3x3d(a), Matrix3x3d(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
def test_order_to_numpy(self):
a = np.array(Matrix3x3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
self.assertEqual(a.strides[0], 4)
self.assertEqual(a.strides[1], 12)
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
a = np.array(Matrix3x3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)), order='C')
self.assertEqual(a.strides[0], 12)
self.assertEqual(a.strides[1], 4)
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
a = np.array(Matrix3x3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)), order='F')
self.assertEqual(a.strides[0], 4)
self.assertEqual(a.strides[1], 12)
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
def test_type_from_numpy(self):
a = np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]], dtype='f')
self.assertEqual(a.dtype, 'f')
self.assertEqual(a.itemsize, 4)
self.assertEqual(Matrix3x3d(a), Matrix3x3d(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
a = np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]], dtype='d')
self.assertEqual(a.dtype, 'd')
self.assertEqual(a.itemsize, 8)
self.assertEqual(Matrix3x3(a), Matrix3x3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
def test_type_from_numpy_invalid(self):
a = np.array([[1, 2], [3, 4]])
self.assertEqual(a.dtype, 'int64')
with self.assertRaisesRegex(BufferError, "expected format f or d but got l"):
b = Matrix2x2(a)
def test_type_to_numpy(self):
a = np.array(Matrix3x3d(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)), dtype='f')
self.assertEqual(a.dtype, 'f')
self.assertEqual(a.itemsize, 4)
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
a = np.array(Matrix3x3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)), dtype='d')
self.assertEqual(a.dtype, 'd')
self.assertEqual(a.itemsize, 8)
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
class Matrix3_(unittest.TestCase):
def test_from_numpy(self):
a = Matrix3(np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
self.assertEqual(a, Matrix3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
def test_to_numpy(self):
a = np.array(Matrix3(
(1.0, 4.0, 7.0),
(2.0, 5.0, 8.0),
(3.0, 6.0, 9.0)))
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
class Matrix4_(unittest.TestCase):
def test_from_numpy(self):
a = Matrix4(np.array(
[[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0],
[13.0, 14.0, 15.0, 16.0]]))
self.assertEqual(a, Matrix4(
(1.0, 5.0, 9.0, 13.0),
(2.0, 6.0, 10.0, 14.0),
(3.0, 7.0, 11.0, 15.0),
(4.0, 8.0, 12.0, 16.0)))
def test_to_numpy(self):
a = np.array(Matrix4(
(1.0, 5.0, 9.0, 13.0),
(2.0, 6.0, 10.0, 14.0),
(3.0, 7.0, 11.0, 15.0),
(4.0, 8.0, 12.0, 16.0)))
np.testing.assert_array_equal(a, np.array(
[[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0],
[13.0, 14.0, 15.0, 16.0]]))