Mathc matrices/c32e
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c00a.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, 15,
0,1,0, 20,
0,0,1, 2};
double **T = ca_A_mR(ta, i_mR(R3,C4));
double **A = r_mR( i_mR(R3,C3),9);
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("\n");
printf(" a X*Y + b X*Z + c Z**(1/2) = d \n");
printf(" e X*Y + f X*Z + g Z**(1/2) = h \n");
printf(" i X*Y + j X*Z + k Z**(1/2) = l \n");
printf("\n");
printf(" With X = 5, Y = 3, Z = 4 \n");
printf(" You have X*Y = 15, X*Z = 20, Z**(1/2) = 2 \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,S7,P3,C6);
stop();
clrscrn();
printf(" If :\n\n A = r_mR(i_mR(R3,C3),9); ");
p_mR(A,S7,P3,C6);
printf(" And :\n\n T :");
p_mR(T,S7,P3,C6);
printf(" I suggest this matrix : A*T = Ab\n\n"
" Ab : ");
p_mR(AT,S8,P3,C6);
stop();
clrscrn();
printf("\n With the Gauss Jordan function :\n"
"Ab:");
p_mR(Ab,S7,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 X*Y + b X*Z + c Z**(1/2) = d
e X*Y + f X*Z + g Z**(1/2) = h
i X*Y + j X*Z + k Z**(1/2) = l
With X = 5, Y = 3, Z = 4
You have X*Y = 15, X*Z = 20, Z**(1/2) = 2
In fact, you want to find a matrix,
which has this reduced row-echelon form :
Ab:
+1.000 +0.000 +0.000 +15.000
+0.000 +1.000 +0.000 +20.000
+0.000 +0.000 +1.000 +2.000
Press return to continue.
If :
A = r_mR(i_mR(R3,C3),9);
+2.000 -1.000 -6.000
+2.000 -7.000 -6.000
-6.000 +6.000 +7.000
And :
T :
+1.000 +0.000 +0.000 +15.000
+0.000 +1.000 +0.000 +20.000
+0.000 +0.000 +1.000 +2.000
I suggest this matrix : A*T = Ab
Ab :
+2.000 -1.000 -6.000 -2.000
+2.000 -7.000 -6.000 -122.000
-6.000 +6.000 +7.000 +44.000
Press return to continue.
With the Gauss Jordan function :
Ab:
+1.000 -0.000 -0.000 +15.000
+0.000 +1.000 +0.000 +20.000
+0.000 -0.000 +1.000 +2.000
Press return to continue.