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
|
#include <u.h>
#include <libn.h>
#include <libmath.h>
// -----------------------------------------------------------------------
// Vector
void
linalg·normalize(math·Vector vec)
{
double norm;
norm = blas·norm(vec.len, vec.data, 1);
blas·scale(vec.len, 1/norm, vec.data, 1);
}
// TODO: Write blas wrappers that eat vectors for convenience
// -----------------------------------------------------------------------
// Matrix
//
// NOTE: all matrices are row major oriented
/*
* linalg·lq
* computes the LQ decomposition of matrix M: M = LQ
* L is lower triangular
* Q is orthogonal -> transp(Q) * Q = I
*
* m: matrix to factorize. changes in place
* + lower triangle -> L
* + upper triangle -> all reflection vectors stored in rows
* w: working buffer: len = ncols!
*/
error
linalg·lq(math·Matrix m, math·Vector w)
{
int i, j, len;
double *row, mag;
enum {
err·nil,
err·baddims,
};
if (m.dim[0] > m.dim[1]) {
return err·baddims;
}
for (i = 0; i < m.dim[0]; i++, m.data += m.dim[1]) {
row = m.data + i;
len = m.dim[0] - i;
// TODO: Don't want to compute norm twice!!
w.data[0] = math·sgn(row[0]) * blas·norm(len, row, 1);
blas·axpy(len, 1.0, row, 1, w.data, 1);
mag = blas·norm(len, w.data, 1);
blas·scale(len, 1/mag, w.data, 1);
blas·copy(len - m.dim[0], w.data, 1, m.data + i, 1);
}
return err·nil;
}
|
