675 lines
24 KiB
Python
675 lines
24 KiB
Python
# ----------------------------------------------------------------------------
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# pyglet
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# Copyright (c) 2006-2008 Alex Holkner
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# Copyright (c) 2008-2021 pyglet contributors
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions
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# are met:
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#
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# * Redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in
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# the documentation and/or other materials provided with the
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# distribution.
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# * Neither the name of pyglet nor the names of its
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# contributors may be used to endorse or promote products
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# derived from this software without specific prior written
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# permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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# ----------------------------------------------------------------------------
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"""Matrix and Vector math.
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This module provides Vector and Matrix objects, include Vec2, Vec3, Vec4,
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Mat3 and Mat4. Most common operations are supported, and many helper
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methods are included for rotating, scaling, and transforming.
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The :py:class:`~pyglet.matrix.Mat4` includes class methods
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for creating orthographic and perspective projection matrixes.
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"""
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import math as _math
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import warnings as _warnings
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from operator import mul as _mul
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def clamp(num, min_val, max_val):
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return max(min(num, max_val), min_val)
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class Vec2(tuple):
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def __new__(cls, *args):
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assert len(args) in (0, 2), "0 or 2 values are required for Vec2 types."
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return super().__new__(Vec2, args or (0, 0))
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@property
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def x(self):
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return self[0]
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@property
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def y(self):
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return self[1]
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def __add__(self, other):
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return Vec2(self[0] + other[0], self[1] + other[1])
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def __sub__(self, other):
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return Vec2(self[0] - other[0], self[1] - other[1])
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def __mul__(self, other):
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return Vec2(self[0] * other[0], self[1] * other[1])
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def __truediv__(self, other):
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return Vec2(self[0] / other[0], self[1] / other[1])
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def __abs__(self):
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return _math.sqrt(self[0] ** 2 + self[1] ** 2)
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def __neg__(self):
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return Vec2(-self[0], -self[1])
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def __round__(self, ndigits=None):
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return Vec2(*(round(v, ndigits) for v in self))
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def lerp(self, other, alpha):
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return Vec2(self[0] + (alpha * (other[0] - self[0])),
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self[1] + (alpha * (other[1] - self[1])))
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def scale(self, value):
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return Vec2(self[0] * value, self[1] * value)
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def distance(self, other):
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return _math.sqrt(((other[0] - self[0]) ** 2) + ((other[1] - self[1]) ** 2))
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def normalize(self):
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d = self.__abs__()
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if d:
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return Vec2(self[0] / d, self[1] / d)
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return self
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def clamp(self, min_val, max_val):
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return Vec2(clamp(self[0], min_val, max_val), clamp(self[1], min_val, max_val))
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def dot(self, other):
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return self[0] * other[0] + self[1] * other[1]
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def __getattr__(self, attrs):
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try:
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# Allow swizzed getting of attrs
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vec_class = {2: Vec2, 3: Vec3, 4: Vec4}.get(len(attrs))
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return vec_class(*(self['xy'.index(c)] for c in attrs))
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except Exception:
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raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{attrs}'")
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def __repr__(self):
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return f"Vec2({self[0]}, {self[1]})"
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class Vec3(tuple):
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def __new__(cls, *args):
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assert len(args) in (0, 3), "0 or 3 values are required for Vec3 types."
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return super().__new__(Vec3, args or (0, 0, 0))
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@property
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def x(self):
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return self[0]
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@property
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def y(self):
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return self[1]
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@property
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def z(self):
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return self[2]
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def __add__(self, other):
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return Vec3(self[0] + other[0], self[1] + other[1], self[2] + other[2])
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def __sub__(self, other):
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return Vec3(self[0] - other[0], self[1] - other[1], self[2] - other[2])
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def __mul__(self, other):
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return Vec3(self[0] * other[0], self[1] * other[1], self[2] * other[2])
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def __truediv__(self, other):
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return Vec3(self[0] / other[0], self[1] / other[1], self[2] / other[2])
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def __abs__(self):
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return _math.sqrt(self[0] ** 2 + self[1] ** 2 + self[2] ** 2)
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def __neg__(self):
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return Vec3(-self[0], -self[1], -self[2])
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def __round__(self, ndigits=None):
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return Vec3(*(round(v, ndigits) for v in self))
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def cross(self, other):
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return Vec3((self[1] * other[2]) - (self[2] * other[1]),
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(self[2] * other[0]) - (self[0] * other[2]),
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(self[0] * other[1]) - (self[1] * other[0]))
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def dot(self, other):
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return self[0] * other[0] + self[1] * other[1] + self[2] * other[2]
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def lerp(self, other, alpha):
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return Vec3(self[0] + (alpha * (other[0] - self[0])),
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self[1] + (alpha * (other[1] - self[1])),
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self[2] + (alpha * (other[2] - self[2])))
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def scale(self, value):
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return Vec3(self[0] * value, self[1] * value, self[2] * value)
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def distance(self, other):
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return _math.sqrt(((other[0] - self[0]) ** 2) +
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((other[1] - self[1]) ** 2) +
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((other[2] - self[2]) ** 2))
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def normalize(self):
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d = self.__abs__()
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if d:
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return Vec3(self[0] / d, self[1] / d, self[2] / d)
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return self
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def clamp(self, min_val, max_val):
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return Vec3(clamp(self[0], min_val, max_val),
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clamp(self[1], min_val, max_val),
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clamp(self[2], min_val, max_val))
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def __getattr__(self, attrs):
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try:
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# Allow swizzed getting of attrs
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vec_class = {2: Vec2, 3: Vec3, 4: Vec4}.get(len(attrs))
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return vec_class(*(self['xyz'.index(c)] for c in attrs))
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except Exception:
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raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{attrs}'")
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def __repr__(self):
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return f"Vec3({self[0]}, {self[1]}, {self[2]})"
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class Vec4(tuple):
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def __new__(cls, *args):
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assert len(args) in (0, 4), "0 or 4 values are required for Vec4 types."
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return super().__new__(Vec4, args or (0, 0, 0, 0))
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@property
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def x(self):
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return self[0]
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@property
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def y(self):
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return self[1]
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@property
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def z(self):
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return self[2]
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@property
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def w(self):
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return self[3]
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def __add__(self, other):
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return Vec4(self[0] + other[0], self[1] + other[1], self[2] + other[2], self[3] + other[3])
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def __sub__(self, other):
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return Vec4(self[0] - other[0], self[1] - other[1], self[2] - other[2], self[3] - other[3])
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def __mul__(self, other):
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return Vec4(self[0] * other[0], self[1] * other[1], self[2] * other[2], self[3] * other[3])
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def __truediv__(self, other):
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return Vec4(self[0] / other[0], self[1] / other[1], self[2] / other[2], self[3] / other[3])
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def __abs__(self):
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return _math.sqrt(self[0] ** 2 + self[1] ** 2 + self[2] ** 2 + self[3] ** 2)
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def __neg__(self):
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return Vec4(-self[0], -self[1], -self[2], -self[3])
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def __round__(self, ndigits=None):
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return Vec4(*(round(v, ndigits) for v in self))
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def lerp(self, other, alpha):
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return Vec4(self[0] + (alpha * (other[0] - self[0])),
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self[1] + (alpha * (other[1] - self[1])),
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self[2] + (alpha * (other[2] - self[2])),
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self[3] + (alpha * (other[3] - self[3])))
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def scale(self, value):
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return Vec4(self[0] * value, self[1] * value, self[2] * value, self[3] * value)
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def distance(self, other):
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return _math.sqrt(((other[0] - self[0]) ** 2) +
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((other[1] - self[1]) ** 2) +
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((other[2] - self[2]) ** 2) +
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((other[3] - self[3]) ** 2))
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def normalize(self):
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d = self.__abs__()
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if d:
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return Vec4(self[0] / d, self[1] / d, self[2] / d, self[3] / d)
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return self
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def clamp(self, min_val, max_val):
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return Vec3(clamp(self[0], min_val, max_val),
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clamp(self[1], min_val, max_val),
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clamp(self[2], min_val, max_val),
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clamp(self[3], min_val, max_val))
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def dot(self, other):
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return self[0] * other[0] + self[1] * other[1] + self[2] * other[2] + self[3] * other[3]
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def __getattr__(self, attrs):
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try:
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# Allow swizzed getting of attrs
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vec_class = {2: Vec2, 3: Vec3, 4: Vec4}.get(len(attrs))
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return vec_class(*(self['xyzw'.index(c)] for c in attrs))
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except Exception:
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raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{attrs}'")
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def __repr__(self):
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return f"Vec4({self[0]}, {self[1]}, {self[2]}, {self[3]})"
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class Mat3(tuple):
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"""A 3x3 Matrix class
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`Mat3` is an immutable 3x3 Matrix, including most common
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operators. Matrix multiplication must be performed using
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the "@" operator.
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"""
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def __new__(cls, values=None) -> 'Mat3':
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"""Create a 3x3 Matrix
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A Mat3 can be created with a list or tuple of 9 values.
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If no values are provided, an "identity matrix" will be created
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(1.0 on the main diagonal). Matrix objects are immutable, so
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all operations return a new Mat3 object.
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:Parameters:
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`values` : tuple of float or int
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A tuple or list containing 9 floats or ints.
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"""
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assert values is None or len(values) == 9, "A 3x3 Matrix requires 9 values"
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return super().__new__(Mat3, values or (1.0, 0.0, 0.0,
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0.0, 1.0, 0.0,
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0.0, 0.0, 1.0))
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def scale(self, sx: float, sy: float):
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return self @ (1.0 / sx, 0.0, 0.0, 0.0, 1.0 / sy, 0.0, 0.0, 0.0, 1.0)
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def translate(self, tx: float, ty: float):
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return self @ (1.0, 0.0, 0.0, 0.0, 1.0, 0.0, -tx, ty, 1.0)
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def rotate(self, phi: float):
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s = _math.sin(_math.radians(phi))
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c = _math.cos(_math.radians(phi))
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return self @ (c, s, 0.0, -s, c, 0.0, 0.0, 0.0, 1.0)
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def shear(self, sx: float, sy: float):
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return self @ (1.0, sy, 0.0, sx, 1.0, 0.0, 0.0, 0.0, 1.0)
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def __add__(self, other) -> 'Mat3':
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assert len(other) == 9, "Can only add to other Mat3 types"
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return Mat3(tuple(s + o for s, o in zip(self, other)))
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def __sub__(self, other) -> 'Mat3':
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assert len(other) == 9, "Can only subtract from other Mat3 types"
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return Mat3(tuple(s - o for s, o in zip(self, other)))
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def __pos__(self):
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return self
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def __neg__(self) -> 'Mat3':
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return Mat3(tuple(-v for v in self))
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def __round__(self, ndigits=None) -> 'Mat3':
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return Mat3(tuple(round(v, ndigits) for v in self))
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def __mul__(self, other):
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raise NotImplementedError("Please use the @ operator for Matrix multiplication.")
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def __matmul__(self, other) -> 'Mat3':
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assert len(other) in (3, 9), "Can only multiply with Mat3 or Vec3 types"
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if type(other) is Vec3:
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# Columns:
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c0 = self[0::3]
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c1 = self[1::3]
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c2 = self[2::3]
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return Vec3(sum(map(_mul, c0, other)),
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sum(map(_mul, c1, other)),
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sum(map(_mul, c2, other)))
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# Rows:
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r0 = self[0:3]
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r1 = self[3:6]
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r2 = self[6:9]
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# Columns:
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c0 = other[0::3]
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c1 = other[1::3]
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c2 = other[2::3]
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# Multiply and sum rows * colums:
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return Mat3((sum(map(_mul, r0, c0)),
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sum(map(_mul, r0, c1)),
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sum(map(_mul, r0, c2)),
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sum(map(_mul, r1, c0)),
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sum(map(_mul, r1, c1)),
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sum(map(_mul, r1, c2)),
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sum(map(_mul, r2, c0)),
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sum(map(_mul, r2, c1)),
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sum(map(_mul, r2, c2))))
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def __repr__(self) -> str:
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return f"{self.__class__.__name__}{self[0:3]}\n {self[3:6]}\n {self[6:9]}"
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class Mat4(tuple):
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"""A 4x4 Matrix class
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`Mat4` is an immutable 4x4 Matrix, including most common
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operators. Matrix multiplication must be performed using
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the "@" operator.
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Class methods are available for creating orthogonal
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and perspective projections matrixes.
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"""
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def __new__(cls, values=None) -> 'Mat4':
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"""Create a 4x4 Matrix
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A Matrix can be created with a list or tuple of 16 values.
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If no values are provided, an "identity matrix" will be created
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(1.0 on the main diagonal). Matrix objects are immutable, so
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all operations return a new Mat4 object.
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:Parameters:
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`values` : tuple of float or int
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A tuple or list containing 16 floats or ints.
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"""
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assert values is None or len(values) == 16, "A 4x4 Matrix requires 16 values"
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return super().__new__(Mat4, values or (1.0, 0.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0,
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0.0, 0.0, 1.0, 0.0,
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0.0, 0.0, 0.0, 1.0))
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@classmethod
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def orthogonal_projection(cls, left, right, bottom, top, z_near, z_far) -> 'Mat4':
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"""Create a Mat4 orthographic projection matrix."""
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width = right - left
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height = top - bottom
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depth = z_far - z_near
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sx = 2.0 / width
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sy = 2.0 / height
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sz = 2.0 / -depth
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tx = -(right + left) / width
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ty = -(top + bottom) / height
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tz = -(z_far + z_near) / depth
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return cls((sx, 0.0, 0.0, 0.0,
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0.0, sy, 0.0, 0.0,
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0.0, 0.0, sz, 0.0,
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tx, ty, tz, 1.0))
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@classmethod
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def perspective_projection(cls, left, right, bottom, top, z_near, z_far, fov=60) -> 'Mat4':
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"""Create a Mat4 perspective projection matrix."""
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width = right - left
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height = top - bottom
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aspect = width / height
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xy_max = z_near * _math.tan(fov * _math.pi / 360)
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y_min = -xy_max
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x_min = -xy_max
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width = xy_max - x_min
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height = xy_max - y_min
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depth = z_far - z_near
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q = -(z_far + z_near) / depth
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qn = -2 * z_far * z_near / depth
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w = 2 * z_near / width
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w = w / aspect
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h = 2 * z_near / height
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return cls((w, 0, 0, 0,
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0, h, 0, 0,
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0, 0, q, -1,
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0, 0, qn, 0))
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@classmethod
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def from_translation(cls, vector: Vec3) -> 'Mat4':
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"""Create a translaton matrix from a Vec3.
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:Parameters:
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`vector` : A `Vec3`, or 3 component tuple of float or int
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Vec3 or tuple with x, y and z translaton values
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"""
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return cls((1.0, 0.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0,
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0.0, 0.0, 1.0, 0.0,
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vector[0], vector[1], vector[2], 1.0))
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@classmethod
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def from_rotation(cls, angle: float, vector: Vec3) -> 'Mat4':
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"""Create a rotation matrix from an angle and Vec3.
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:Parameters:
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`angle` : A `float`
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`vector` : A `Vec3`, or 3 component tuple of float or int
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Vec3 or tuple with x, y and z translaton values
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"""
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return cls().rotate(angle, vector)
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@classmethod
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def look_at_direction(cls, direction: Vec3, up: Vec3) -> 'Mat4':
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vec_z = direction.normalize()
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vec_x = direction.cross_product(up).normalize()
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vec_y = direction.cross_product(vec_z).normalize()
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return cls((vec_x.x, vec_y.x, vec_z.x, 0.0,
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vec_x.y, vec_y.y, vec_z.y, 0.0,
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vec_x.z, vec_z.z, vec_z.z, 0.0,
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0.0, 0.0, 0.0, 1.0))
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@classmethod
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def look_at(cls, position: Vec3, target: Vec3, up: Vec3) -> 'Mat4':
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direction = target - position
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direction_mat4 = cls.look_at_direction(direction, up)
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position_mat4 = cls.from_translation(position.negate())
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return direction_mat4 @ position_mat4
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def row(self, index: int):
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"""Get a specific row as a tuple."""
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return self[index*4:index*4+4]
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def column(self, index: int):
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"""Get a specific column as a tuple."""
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return self[index::4]
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def scale(self, vector: Vec3) -> 'Mat4':
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"""Get a scale Matrix on x, y, or z axis."""
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temp = list(self)
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temp[0] *= vector[0]
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temp[5] *= vector[1]
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temp[10] *= vector[2]
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return Mat4(temp)
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def translate(self, vector: Vec3) -> 'Mat4':
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"""Get a translate Matrix along x, y, and z axis."""
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return Mat4(self) @ Mat4((1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, *vector, 1))
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def rotate(self, angle: float, vector: Vec3) -> 'Mat4':
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"""Get a rotation Matrix on x, y, or z axis."""
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assert all(abs(n) <= 1 for n in vector), "vector must be normalized (<=1)"
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x, y, z = vector
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c = _math.cos(angle)
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s = _math.sin(angle)
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t = 1 - c
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temp_x, temp_y, temp_z = t * x, t * y, t * z
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ra = c + temp_x * x
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rb = 0 + temp_x * y + s * z
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rc = 0 + temp_x * z - s * y
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re = 0 + temp_y * x - s * z
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rf = c + temp_y * y
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rg = 0 + temp_y * z + s * x
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ri = 0 + temp_z * x + s * y
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rj = 0 + temp_z * y - s * x
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rk = c + temp_z * z
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# ra, rb, rc, --
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# re, rf, rg, --
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# ri, rj, rk, --
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# --, --, --, --
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return Mat4(self) @ Mat4((ra, rb, rc, 0, re, rf, rg, 0, ri, rj, rk, 0, 0, 0, 0, 1))
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def transpose(self) -> 'Mat4':
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|
"""Get a tranpose of this Matrix."""
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|
return Mat4(self[0::4] + self[1::4] + self[2::4] + self[3::4])
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|
|
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def __add__(self, other) -> 'Mat4':
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assert len(other) == 16, "Can only add to other Mat4 types"
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return Mat4(tuple(s + o for s, o in zip(self, other)))
|
|
|
|
def __sub__(self, other) -> 'Mat4':
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assert len(other) == 16, "Can only subtract from other Mat4 types"
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|
return Mat4(tuple(s - o for s, o in zip(self, other)))
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|
|
|
def __pos__(self):
|
|
return self
|
|
|
|
def __neg__(self) -> 'Mat4':
|
|
return Mat4(tuple(-v for v in self))
|
|
|
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def __invert__(self) -> 'Mat4':
|
|
a = self[10] * self[15] - self[11] * self[14]
|
|
b = self[9] * self[15] - self[11] * self[13]
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|
c = self[9] * self[14] - self[10] * self[13]
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d = self[8] * self[15] - self[11] * self[12]
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e = self[8] * self[14] - self[10] * self[12]
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|
f = self[8] * self[13] - self[9] * self[12]
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g = self[6] * self[15] - self[7] * self[14]
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|
h = self[5] * self[15] - self[7] * self[13]
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|
i = self[5] * self[14] - self[6] * self[13]
|
|
j = self[6] * self[11] - self[7] * self[10]
|
|
k = self[5] * self[11] - self[7] * self[9]
|
|
l = self[5] * self[10] - self[6] * self[9]
|
|
m = self[4] * self[15] - self[7] * self[12]
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|
n = self[4] * self[14] - self[6] * self[12]
|
|
o = self[4] * self[11] - self[7] * self[8]
|
|
p = self[4] * self[10] - self[6] * self[8]
|
|
q = self[4] * self[13] - self[5] * self[12]
|
|
r = self[4] * self[9] - self[5] * self[8]
|
|
|
|
det = (self[0] * (self[5] * a - self[6] * b + self[7] * c)
|
|
- self[1] * (self[4] * a - self[6] * d + self[7] * e)
|
|
+ self[2] * (self[4] * b - self[5] * d + self[7] * f)
|
|
- self[3] * (self[4] * c - self[5] * e + self[6] * f))
|
|
|
|
if det == 0:
|
|
_warnings.warn("Unable to calculate inverse of singular Matrix")
|
|
return self
|
|
|
|
pdet = 1 / det
|
|
ndet = -pdet
|
|
|
|
return Mat4((pdet * (self[5] * a - self[6] * b + self[7] * c),
|
|
ndet * (self[1] * a - self[2] * b + self[3] * c),
|
|
pdet * (self[1] * g - self[2] * h + self[3] * i),
|
|
ndet * (self[1] * j - self[2] * k + self[3] * l),
|
|
ndet * (self[4] * a - self[6] * d + self[7] * e),
|
|
pdet * (self[0] * a - self[2] * d + self[3] * e),
|
|
ndet * (self[0] * g - self[2] * m + self[3] * n),
|
|
pdet * (self[0] * j - self[2] * o + self[3] * p),
|
|
pdet * (self[4] * b - self[5] * d + self[7] * f),
|
|
ndet * (self[0] * b - self[1] * d + self[3] * f),
|
|
pdet * (self[0] * h - self[1] * m + self[3] * q),
|
|
ndet * (self[0] * k - self[1] * o + self[3] * r),
|
|
ndet * (self[4] * c - self[5] * e + self[6] * f),
|
|
pdet * (self[0] * c - self[1] * e + self[2] * f),
|
|
ndet * (self[0] * i - self[1] * n + self[2] * q),
|
|
pdet * (self[0] * l - self[1] * p + self[2] * r)))
|
|
|
|
def __round__(self, ndigits=None) -> 'Mat4':
|
|
return Mat4(tuple(round(v, ndigits) for v in self))
|
|
|
|
def __mul__(self, other):
|
|
raise NotImplementedError("Please use the @ operator for Matrix multiplication.")
|
|
|
|
def __matmul__(self, other) -> 'Mat4':
|
|
assert len(other) in (4, 16), "Can only multiply with Mat4 or Vec4 types"
|
|
|
|
if type(other) is Vec4:
|
|
# Columns:
|
|
c0 = self[0::4]
|
|
c1 = self[1::4]
|
|
c2 = self[2::4]
|
|
c3 = self[3::4]
|
|
return Vec4(sum(map(_mul, c0, other)),
|
|
sum(map(_mul, c1, other)),
|
|
sum(map(_mul, c2, other)),
|
|
sum(map(_mul, c3, other)))
|
|
|
|
# Rows:
|
|
r0 = self[0:4]
|
|
r1 = self[4:8]
|
|
r2 = self[8:12]
|
|
r3 = self[12:16]
|
|
# Columns:
|
|
c0 = other[0::4]
|
|
c1 = other[1::4]
|
|
c2 = other[2::4]
|
|
c3 = other[3::4]
|
|
|
|
# Multiply and sum rows * colums:
|
|
return Mat4((sum(map(_mul, r0, c0)),
|
|
sum(map(_mul, r0, c1)),
|
|
sum(map(_mul, r0, c2)),
|
|
sum(map(_mul, r0, c3)),
|
|
|
|
sum(map(_mul, r1, c0)),
|
|
sum(map(_mul, r1, c1)),
|
|
sum(map(_mul, r1, c2)),
|
|
sum(map(_mul, r1, c3)),
|
|
|
|
sum(map(_mul, r2, c0)),
|
|
sum(map(_mul, r2, c1)),
|
|
sum(map(_mul, r2, c2)),
|
|
sum(map(_mul, r2, c3)),
|
|
|
|
sum(map(_mul, r3, c0)),
|
|
sum(map(_mul, r3, c1)),
|
|
sum(map(_mul, r3, c2)),
|
|
sum(map(_mul, r3, c3))))
|
|
|
|
# def __getitem__(self, item):
|
|
# row = [slice(0, 4), slice(4, 8), slice(8, 12), slice(12, 16)][item]
|
|
# return super().__getitem__(row)
|
|
|
|
def __repr__(self) -> str:
|
|
return f"{self.__class__.__name__}{self[0:4]}\n {self[4:8]}\n {self[8:12]}\n {self[12:16]}"
|