437 lines
12 KiB
C++
437 lines
12 KiB
C++
/*
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* Copyright 2013 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MATH_MAT2_H_
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#define MATH_MAT2_H_
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#include <math/TMatHelpers.h>
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#include <math/vec2.h>
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#include <stdint.h>
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#include <sys/types.h>
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#define PURE __attribute__((pure))
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namespace math {
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// -------------------------------------------------------------------------------------
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namespace details {
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/**
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* A 2x2 column-major matrix class.
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*
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* Conceptually a 2x2 matrix is a an array of 2 column vec2:
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*
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* mat2 m =
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* \f$
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* \left(
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* \begin{array}{cc}
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* m[0] & m[1] \\
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* \end{array}
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* \right)
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* \f$
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* =
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* \f$
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* \left(
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* \begin{array}{cc}
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* m[0][0] & m[1][0] \\
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* m[0][1] & m[1][1] \\
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* \end{array}
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* \right)
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* \f$
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* =
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* \f$
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* \left(
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* \begin{array}{cc}
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* m(0,0) & m(0,1) \\
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* m(1,0) & m(1,1) \\
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* \end{array}
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* \right)
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* \f$
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*
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* m[n] is the \f$ n^{th} \f$ column of the matrix and is a vec2.
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*
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*/
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template <typename T>
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class MATH_EMPTY_BASES TMat22 :
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public TVecUnaryOperators<TMat22, T>,
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public TVecComparisonOperators<TMat22, T>,
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public TVecAddOperators<TMat22, T>,
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public TMatProductOperators<TMat22, T>,
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public TMatSquareFunctions<TMat22, T>,
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public TMatHelpers<TMat22, T>,
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public TMatDebug<TMat22, T> {
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public:
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enum no_init { NO_INIT };
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typedef T value_type;
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typedef T& reference;
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typedef T const& const_reference;
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typedef size_t size_type;
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typedef TVec2<T> col_type;
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typedef TVec2<T> row_type;
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static constexpr size_t COL_SIZE = col_type::SIZE; // size of a column (i.e.: number of rows)
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static constexpr size_t ROW_SIZE = row_type::SIZE; // size of a row (i.e.: number of columns)
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static constexpr size_t NUM_ROWS = COL_SIZE;
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static constexpr size_t NUM_COLS = ROW_SIZE;
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private:
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/*
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* <-- N columns -->
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*
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* a[0][0] a[1][0] a[2][0] ... a[N][0] ^
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* a[0][1] a[1][1] a[2][1] ... a[N][1] |
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* a[0][2] a[1][2] a[2][2] ... a[N][2] M rows
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* ... |
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* a[0][M] a[1][M] a[2][M] ... a[N][M] v
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*
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* COL_SIZE = M
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* ROW_SIZE = N
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* m[0] = [ a[0][0] a[0][1] a[0][2] ... a[0][M] ]
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*/
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col_type m_value[NUM_COLS];
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public:
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// array access
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inline constexpr col_type const& operator[](size_t column) const {
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#if __cplusplus >= 201402L
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// only possible in C++0x14 with constexpr
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assert(column < NUM_COLS);
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#endif
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return m_value[column];
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}
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inline col_type& operator[](size_t column) {
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assert(column < NUM_COLS);
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return m_value[column];
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}
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/**
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* constructors
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*/
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/**
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* leaves object uninitialized. use with caution.
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*/
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constexpr explicit TMat22(no_init) {}
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/**
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* initialize to identity.
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*
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* \f$
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* \left(
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* \begin{array}{cc}
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* 1 & 0 \\
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* 0 & 1 \\
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* \end{array}
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* \right)
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* \f$
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*/
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constexpr TMat22();
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/**
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* initialize to Identity*scalar.
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*
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* \f$
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* \left(
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* \begin{array}{cc}
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* v & 0 \\
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* 0 & v \\
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* \end{array}
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* \right)
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* \f$
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*/
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template<typename U>
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constexpr explicit TMat22(U v);
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/**
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* sets the diagonal to a vector.
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*
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* \f$
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* \left(
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* \begin{array}{cc}
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* v[0] & 0 \\
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* 0 & v[1] \\
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* \end{array}
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* \right)
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* \f$
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*/
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template <typename U>
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constexpr explicit TMat22(const TVec2<U>& v);
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/**
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* construct from another matrix of the same size
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*/
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template <typename U>
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constexpr explicit TMat22(const TMat22<U>& rhs);
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/**
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* construct from 2 column vectors.
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*
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* \f$
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* \left(
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* \begin{array}{cc}
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* v0 & v1 \\
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* \end{array}
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* \right)
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* \f$
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*/
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template <typename A, typename B>
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constexpr TMat22(const TVec2<A>& v0, const TVec2<B>& v1);
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/** construct from 4 elements in column-major form.
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*
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* \f$
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* \left(
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* \begin{array}{cc}
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* m[0][0] & m[1][0] \\
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* m[0][1] & m[1][1] \\
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* \end{array}
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* \right)
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* \f$
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*/
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template <
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typename A, typename B,
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typename C, typename D>
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constexpr explicit TMat22(A m00, B m01,
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C m10, D m11);
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struct row_major_init {
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template<
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typename A, typename B,
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typename C, typename D>
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constexpr explicit row_major_init(A m00, B m01,
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C m10, D m11) noexcept
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: m(m00, m10,
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m01, m11) {}
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private:
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friend TMat22;
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TMat22 m;
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};
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constexpr explicit TMat22(row_major_init c) : TMat22(std::move(c.m)) { }
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/**
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* Rotate by radians in the 2D plane
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*/
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static TMat22<T> rotate(T radian) {
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TMat22<T> r(TMat22<T>::NO_INIT);
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T c = std::cos(radian);
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T s = std::sin(radian);
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r[0][0] = c; r[1][1] = c;
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r[0][1] = s; r[1][0] = -s;
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return r;
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}
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// returns false if the two matrices are different. May return false if they're the
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// same, with some elements only differing by +0 or -0. Behaviour is undefined with NaNs.
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static constexpr bool fuzzyEqual(TMat22 l, TMat22 r) noexcept {
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uint64_t const* const li = reinterpret_cast<uint64_t const*>(&l);
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uint64_t const* const ri = reinterpret_cast<uint64_t const*>(&r);
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uint64_t result = 0;
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// For some reason clang is not able to vectoize this loop when the number of iteration
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// is known and constant (!?!?!). Still this is better than operator==.
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#pragma clang loop vectorize_width(2)
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for (size_t i = 0; i < sizeof(TMat22) / sizeof(uint64_t); i++) {
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result |= li[i] ^ ri[i];
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}
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return result != 0;
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}
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template <typename A>
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static constexpr TMat22 translate(const TVec2<A>& t) {
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TMat22 r;
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r[2] = t;
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return r;
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}
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template <typename A>
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static constexpr TMat22 translate(A t) {
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TMat22 r;
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r[1] = TVec2<T>{ t };
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return r;
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}
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template <typename A>
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static constexpr TMat22 scale(const TVec2<A>& s) {
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return TMat22{ s };
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}
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template <typename A>
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static constexpr TMat22 scale(A s) {
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return TMat22{ TVec2<T>{ s, s } };
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}
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};
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// ----------------------------------------------------------------------------------------
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// Constructors
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// ----------------------------------------------------------------------------------------
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// Since the matrix code could become pretty big quickly, we don't inline most
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// operations.
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template <typename T>
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constexpr TMat22<T>::TMat22() {
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m_value[0] = col_type(1, 0);
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m_value[1] = col_type(0, 1);
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}
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template <typename T>
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template <typename U>
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constexpr TMat22<T>::TMat22(U v) {
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m_value[0] = col_type(v, 0);
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m_value[1] = col_type(0, v);
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}
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template<typename T>
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template<typename U>
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constexpr TMat22<T>::TMat22(const TVec2<U>& v) {
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m_value[0] = col_type(v.x, 0);
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m_value[1] = col_type(0, v.y);
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}
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// construct from 4 scalars. Note that the arrangement
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// of values in the constructor is the transpose of the matrix
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// notation.
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template<typename T>
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template <
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typename A, typename B,
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typename C, typename D>
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constexpr TMat22<T>::TMat22(A m00, B m01,
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C m10, D m11) {
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m_value[0] = col_type(m00, m01);
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m_value[1] = col_type(m10, m11);
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}
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template <typename T>
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template <typename U>
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constexpr TMat22<T>::TMat22(const TMat22<U>& rhs) {
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for (size_t col = 0; col < NUM_COLS; ++col) {
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m_value[col] = col_type(rhs[col]);
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}
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}
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// Construct from 2 column vectors.
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template <typename T>
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template <typename A, typename B>
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constexpr TMat22<T>::TMat22(const TVec2<A>& v0, const TVec2<B>& v1) {
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m_value[0] = v0;
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m_value[1] = v1;
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}
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// ----------------------------------------------------------------------------------------
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// Arithmetic operators outside of class
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// ----------------------------------------------------------------------------------------
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/* We use non-friend functions here to prevent the compiler from using
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* implicit conversions, for instance of a scalar to a vector. The result would
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* not be what the caller expects.
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*
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* Also note that the order of the arguments in the inner loop is important since
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* it determines the output type (only relevant when T != U).
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*/
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// matrix * column-vector, result is a vector of the same type than the input vector
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template <typename T, typename U>
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constexpr typename TMat22<U>::col_type PURE operator *(const TMat22<T>& lhs, const TVec2<U>& rhs) {
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// Result is initialized to zero.
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typename TMat22<U>::col_type result = {};
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for (size_t col = 0; col < TMat22<T>::NUM_COLS; ++col) {
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result += lhs[col] * rhs[col];
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}
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return result;
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}
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// row-vector * matrix, result is a vector of the same type than the input vector
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template <typename T, typename U>
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constexpr typename TMat22<U>::row_type PURE operator *(const TVec2<U>& lhs, const TMat22<T>& rhs) {
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typename TMat22<U>::row_type result;
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for (size_t col = 0; col < TMat22<T>::NUM_COLS; ++col) {
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result[col] = dot(lhs, rhs[col]);
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}
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return result;
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}
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// matrix * scalar, result is a matrix of the same type than the input matrix
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template<typename T, typename U>
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constexpr typename std::enable_if<std::is_arithmetic<U>::value, TMat22<T>>::type PURE
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operator*(TMat22<T> lhs, U rhs) {
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return lhs *= rhs;
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}
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// scalar * matrix, result is a matrix of the same type than the input matrix
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template<typename T, typename U>
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constexpr typename std::enable_if<std::is_arithmetic<U>::value, TMat22<T>>::type PURE
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operator*(U lhs, const TMat22<T>& rhs) {
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return rhs * lhs;
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}
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// ----------------------------------------------------------------------------------------
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/* FIXME: this should go into TMatSquareFunctions<> but for some reason
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* BASE<T>::col_type is not accessible from there (???)
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*/
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template<typename T>
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constexpr typename TMat22<T>::col_type PURE diag(const TMat22<T>& m) {
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return matrix::diag(m);
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}
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} // namespace details
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// ----------------------------------------------------------------------------------------
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typedef details::TMat22<double> mat2;
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typedef details::TMat22<float> mat2f;
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// ----------------------------------------------------------------------------------------
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} // namespace math
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#undef PURE
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namespace std {
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template <typename T>
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constexpr void swap(math::details::TMat22<T>& lhs, math::details::TMat22<T>& rhs) noexcept {
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// This generates much better code than the default implementation
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// It's unclear why, I believe this is due to an optimization bug in the clang.
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//
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// math::details::TMat22<T> t(lhs);
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// lhs = rhs;
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// rhs = t;
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//
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// clang always copy lhs on the stack, even if it's never using it (it's using the
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// copy it has in registers).
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const T t00 = lhs[0][0];
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const T t01 = lhs[0][1];
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const T t10 = lhs[1][0];
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const T t11 = lhs[1][1];
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lhs[0][0] = rhs[0][0];
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lhs[0][1] = rhs[0][1];
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lhs[1][0] = rhs[1][0];
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lhs[1][1] = rhs[1][1];
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rhs[0][0] = t00;
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rhs[0][1] = t01;
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rhs[1][0] = t10;
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rhs[1][1] = t11;
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}
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}
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#endif // MATH_MAT2_H_
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