matrix_sq.h
2.5 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
#ifndef RTS_MATRIX_H
#define RTS_MATRIX_H
//#include "rts/vector.h"
#include <string.h>
#include <iostream>
#include <stim/math/vector.h>
#include <stim/math/vec3.h>
#include <stim/cuda/cudatools/callable.h>
namespace stim{
template <class T, int N>
struct matrix_sq
{
//the matrix will be stored in column-major order (compatible with OpenGL)
T M[N*N];
CUDA_CALLABLE matrix_sq()
{
for(int r=0; r<N; r++)
for(int c=0; c<N; c++)
if(r == c)
(*this)(r, c) = 1;
else
(*this)(r, c) = 0;
}
CUDA_CALLABLE matrix_sq(T rhs[N*N])
{
memcpy(M,rhs, sizeof(T)*N*N);
}
CUDA_CALLABLE matrix_sq<T,N> set(T rhs[N*N])
{
memcpy(M, rhs, sizeof(T)*N*N);
return *this;
}
//create a symmetric matrix given the rhs values, given in column-major order
CUDA_CALLABLE void setsym(T rhs[(N*N+N)/2]){
const size_t L = (N*N+N)/2; //store the number of values
size_t r, c;
r = c = 0;
for(size_t i = 0; i < L; i++){ //for each value
if(r == c) M[c * N + r] = rhs[i];
else M[c*N + r] = M[r * N + c] = rhs[i];
r++;
if(r == N) r = ++c;
}
}
CUDA_CALLABLE T& operator()(int row, int col)
{
return M[col * N + row];
}
CUDA_CALLABLE matrix_sq<T, N> operator=(T rhs)
{
int Nsq = N*N;
for(int i=0; i<Nsq; i++)
M[i] = rhs;
return *this;
}
// M - rhs*I
CUDA_CALLABLE matrix_sq<T, N> operator-(T rhs)
{
for(int i=0; i<N; i++)
for(int j=0 ; j<N; j++)
if(i == j)
M[i*N+j] -= rhs;
return *this;
}
template<typename Y>
vec<Y> operator*(vec<Y> rhs){
unsigned int M = rhs.size();
vec<Y> result;
result.resize(M);
for(int r=0; r<M; r++)
for(int c=0; c<M; c++)
result[r] += (*this)(r, c) * rhs[c];
return result;
}
template<typename Y>
CUDA_CALLABLE vec3<Y> operator*(vec3<Y> rhs){
vec3<Y> result = 0;
for(int r=0; r<3; r++)
for(int c=0; c<3; c++)
result[r] += (*this)(r, c) * rhs[c];
return result;
}
std::string toStr()
{
std::stringstream ss;
for(int r = 0; r < N; r++)
{
ss << "| ";
for(int c=0; c<N; c++)
{
ss << (*this)(r, c) << " ";
}
ss << "|" << std::endl;
}
return ss.str();
}
static matrix_sq<T, N> identity() {
matrix_sq<T, N> I;
I = 0;
for (size_t i = 0; i < N; i++)
I.M[i * N + i] = 1;
return I;
}
};
} //end namespace rts
template <typename T, int N>
std::ostream& operator<<(std::ostream& os, stim::matrix_sq<T, N> M)
{
os<<M.toStr();
return os;
}
//#if __GNUC__ > 3 && __GNUC_MINOR__ > 7
//template<class T, int N> using rtsMatrix = rts::matrix<T, N>;
//#endif
#endif