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［ 簡単な説明 ］ 行列ライブラリの使用例です。 |
（先頭に戻る）
/* test15.c */
#include <stdio.h>
#include "sslib.h"
void mprint(char *s, double a[], int m, int n);
void mprint(char *s, double a[], int m, int n)
{
int i, j, k;
printf("matrix : %s\n", s);
for(i = k = 0; i < m; i++)
{
for(j = 0; j < n; j++, k++) printf("%13.6e ", a[k]);
putchar('\n');
}
}
int main(void)
{
static double a[15] = { 3,-6, 7, 4,9999, 9, 0,-5,-2,9999, 5,-8, 6, 1,9999};
static double b[20] = {-6, 2,9999,9999,9999, 3,-9,9999,9999,9999,
5,-1,9999,9999,9999, 4, 1,9999,9999,9999};
static double av[4] = { 4.0, 1.0, 1.0, 2.0 };
double c[12], v[4], eps, *p;
int i, j, k, l, la, lb, lc, m, n, nr, t;
l = 3;
m = 3;
mprint("a", a, m, l);
mprint("b", b, m, l);
madd(a, b, c, l, l, l, m, l);
mprint("a + b", c, m, l);
msub(a, b, c, l, l, l, m, l);
mprint("a + b", c, m, l);
la = 5;
lb = 5;
lc = 4;
m = 3;
n = 4;
k = 2;
for(i = 0, p = c; i < m; i++) for (j = 0; j < lc; j++) *p++ = 0.;
mprint("a", a, m, la);
mprint("b", b, n, lb);
mprint("c", c, m, lc);
mmul2(a, b, c, la, lb, lc, m, n, k);
mprint("a * b", c, m, lc);
la = 5;
m = 3;
n = 3;
mprint("before transposition a", a, m, la);
mtra1(a, la, m, n);
mprint("after transposition a", a, m, la);
la = 5;
lb = 5;
m = 3;
n = 4;
mprint("before transposition a", a, m, la);
mprint("before transposition b", b, n, lb);
mtra2(a, b, la, lb, m, n);
mprint("after transposition b", b, n, la);
lc = 4;
m = 3;
for(i = t = 0; i < m; i++) for (j = 0; j < lc; j++, t++) c[t] = a[t];
mprint("matrix a", a, m, 5);
mprint("matrix c", c, m, lc);
printf("determinant = %22.15e\n", minver(c, lc, m, 1.e-6));
mprint("inversion c", c, m, lc);
la = 5;
lb = 5;
mmul2(a, c, b, la, lc, lb, m, m, m);
mprint("a * c", b, m, lb);
eps = 1.0e-6;
nr = 20;
l = 2;
mprint("matrix av", av, l, l);
jacobi(av, v, l, l, &nr, eps);
printf("the number of rotation = %d\n", nr);
mprint("eigen values", av, l, l);
mprint("eigen vectors", v, l, l);
return 1;
}
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（先頭に戻る）
matrix : a 3.000000e+00 -6.000000e+00 7.000000e+00 4.000000e+00 9.999000e+03 9.000000e+00 0.000000e+00 -5.000000e+00 -2.000000e+00 matrix : b -6.000000e+00 2.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 3.000000e+00 -9.000000e+00 9.999000e+03 9.999000e+03 matrix : a + b -3.000000e+00 -4.000000e+00 1.000600e+04 1.000300e+04 1.999800e+04 1.200000e+01 -9.000000e+00 9.994000e+03 9.997000e+03 matrix : a + b 9.000000e+00 -8.000000e+00 -9.992000e+03 -9.995000e+03 0.000000e+00 6.000000e+00 9.000000e+00 -1.000400e+04 -1.000100e+04 matrix : a 3.000000e+00 -6.000000e+00 7.000000e+00 4.000000e+00 9.999000e+03 9.000000e+00 0.000000e+00 -5.000000e+00 -2.000000e+00 9.999000e+03 5.000000e+00 -8.000000e+00 6.000000e+00 1.000000e+00 9.999000e+03 matrix : b -6.000000e+00 2.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 3.000000e+00 -9.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 5.000000e+00 -1.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 4.000000e+00 1.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 matrix : c 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 matrix : a * b 1.500000e+01 5.700000e+01 0.000000e+00 0.000000e+00 -8.700000e+01 2.100000e+01 0.000000e+00 0.000000e+00 -2.000000e+01 7.700000e+01 0.000000e+00 0.000000e+00 matrix : before transposition a 3.000000e+00 -6.000000e+00 7.000000e+00 4.000000e+00 9.999000e+03 9.000000e+00 0.000000e+00 -5.000000e+00 -2.000000e+00 9.999000e+03 5.000000e+00 -8.000000e+00 6.000000e+00 1.000000e+00 9.999000e+03 matrix : after transposition a 3.000000e+00 9.000000e+00 5.000000e+00 4.000000e+00 9.999000e+03 -6.000000e+00 0.000000e+00 -8.000000e+00 -2.000000e+00 9.999000e+03 7.000000e+00 -5.000000e+00 6.000000e+00 1.000000e+00 9.999000e+03 matrix : before transposition a 3.000000e+00 9.000000e+00 5.000000e+00 4.000000e+00 9.999000e+03 -6.000000e+00 0.000000e+00 -8.000000e+00 -2.000000e+00 9.999000e+03 7.000000e+00 -5.000000e+00 6.000000e+00 1.000000e+00 9.999000e+03 matrix : before transposition b -6.000000e+00 2.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 3.000000e+00 -9.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 5.000000e+00 -1.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 4.000000e+00 1.000000e+00 9.999000e+03 9.999000e+03 9.999000e+03 matrix : after transposition b 3.000000e+00 -6.000000e+00 7.000000e+00 9.999000e+03 9.999000e+03 9.000000e+00 0.000000e+00 -5.000000e+00 9.999000e+03 9.999000e+03 5.000000e+00 -8.000000e+00 6.000000e+00 9.999000e+03 9.999000e+03 4.000000e+00 -2.000000e+00 1.000000e+00 9.999000e+03 9.999000e+03 matrix : matrix a 3.000000e+00 9.000000e+00 5.000000e+00 4.000000e+00 9.999000e+03 -6.000000e+00 0.000000e+00 -8.000000e+00 -2.000000e+00 9.999000e+03 7.000000e+00 -5.000000e+00 6.000000e+00 1.000000e+00 9.999000e+03 matrix : matrix c 3.000000e+00 9.000000e+00 5.000000e+00 4.000000e+00 9.999000e+03 -6.000000e+00 0.000000e+00 -8.000000e+00 -2.000000e+00 9.999000e+03 7.000000e+00 -5.000000e+00 determinant = 4.992698820000000e+08 matrix : inversion c -8.412284e-08 1.000100e-04 6.008774e-08 4.000000e+00 -1.401907e-04 6.209067e-08 1.001362e-04 -8.000000e+00 2.002524e-01 -6.011779e-05 -1.802813e-04 -5.000000e+00 matrix : a * c 1.000000e+00 0.000000e+00 0.000000e+00 9.999000e+03 9.999000e+03 -1.602019e+00 -1.191179e-04 1.441889e-03 9.999000e+03 9.999000e+03 1.202215e+00 3.390531e-04 -1.581948e-03 9.999000e+03 9.999000e+03 matrix : matrix av 4.000000e+00 1.000000e+00 1.000000e+00 2.000000e+00 the number of rotation = 1 matrix : eigen values 4.414214e+00 0.000000e+00 0.000000e+00 1.585786e+00 matrix : eigen vectors 9.238795e-01 -3.826834e-01 3.826834e-01 9.238795e-01 |
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