Mathc matrices/c32c
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c02a.c |
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/* ------------------------------------ */
/* Save as : c00a.c */
/* ------------------------------------ */
#include "v_a.h"
/* ------------------------------------ */
int main(void)
{
time_t t;
srand(time(&t));
double ta[R3*C4]={ 1,0,0, 1,
0,1,0, 1,
0,0,1, 1};
double **T = ca_A_mR(ta, i_mR(R3,C4));
double **A = rE_mR( i_mR(R3,C3),999.,1E-3);
double **AT = mul_mR(A,T, i_mR(R3,C4));
double **Ab = gj_TP_mR(c_mR(AT, i_Abr_Ac_bc_mR(R3,C3,C1)));
printf(" You want to create this nonlinear system of equations :\n");
printf(" (A, B, C [0..2pi])\n");
printf("\n");
printf(" a sin(A) + b sin(B) + c sin(C) = d\n");
printf(" e sin(A) + f sin(B) + g sin(C) = h\n");
printf(" i sin(A) + j sin(B) + k sin(C) = l\n");
printf("\n");
printf(" With sin(A) = 1, sin(B) = 1, sin(C) = 1 \n");
printf("\n");
printf(" In fact, you want to find a matrix, \n");
printf(" which has this reduced row-echelon form :\n\n"
"Ab:");
p_mR(T,S5,P0,C6);
stop();
clrscrn();
printf(" If :\n\n A = rE_mR(i_mR(R3,C3),999.,1E-3); ");
p_mR(A,S5,P3,C6);
printf(" And :\n\n T :");
p_mR(T,S5,P3,C6);
printf(" I suggest this matrix : A*T = Ab\n\n"
" Ab : ");
p_mR(AT,S5,P3,C6);
stop();
clrscrn();
printf("\n With the Gauss Jordan function :\n"
"Ab:");
p_mR(Ab,S5,P3,C6);
stop();
f_mR(Ab);
f_mR(A);
f_mR(T);
f_mR(AT);
return 0;
}
/* ------------------------------------ */
/* ------------------------------------ */
Le but de ce travail est de créer des systèmes dont on connait le résultat par avance.
Exemple de sortie écran :
You want to create this nonlinear system of equations :
(A, B, C [0..2pi])
a sin(A) + b sin(B) + c sin(C) = d
e sin(A) + f sin(B) + g sin(C) = h
i sin(A) + j sin(B) + k sin(C) = l
With sin(A) = 1, sin(B) = 1, sin(C) = 1
In fact, you want to find a matrix,
which has this reduced row-echelon form :
Ab:
+1 +0 +0 +1
+0 +1 +0 +1
+0 +0 +1 +1
Press return to continue.
If :
A = rE_mR(i_mR(R3,C3),999.,1E-3);
+0.479 -0.154 -0.501
+0.992 -0.763 -0.591
-0.843 +0.708 +0.088
And :
T :
+1.000 +0.000 +0.000 +1.000
+0.000 +1.000 +0.000 +1.000
+0.000 +0.000 +1.000 +1.000
I suggest this matrix : A*T = Ab
Ab :
+0.479 -0.154 -0.501 -0.176
+0.992 -0.763 -0.591 -0.362
-0.843 +0.708 +0.088 -0.047
Press return to continue.
With the Gauss Jordan function :
Ab:
+1.000 +0.000 +0.000 +1.000
+0.000 +1.000 +0.000 +1.000
+0.000 +0.000 +1.000 +1.000
Press return to continue.