Mathc matrices/c32e


Sommaire


Installer et compiler ces fichiers dans votre répertoire de travail.


Crystal Clear mimetype source c.png c02c.c
'
/* ------------------------------------ */
/*  Save as :   c02c.c                  */
/* ------------------------------------ */
#include      "v_a.h"
/* ------------------------------------ */
int main(void)
{
double t[R3*C4]={ 1,0,0,  15,
                  0,1,0,  20,
                  0,0,1,   2};
                   
double **T  =    ca_A_mR(t,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");
  p_mR(T,S7,P0,C6);
  getchar();

  printf(" I suggest this matrix : \n");
  p_mR(AT,S7,P0,C6);
  getchar();
  
  printf("\n  With the Gauss Jordan function :\n");
  p_mR(Ab,S7,P3,C6);
  getchar();

  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 :

     +1      +0      +0     +15 
     +0      +1      +0     +20 
     +0      +0      +1      +2 


 I suggest this matrix : 

     +2      +8      -1    +188 
     +8      +6      +8    +256 
     +2      +4      -7     +96 



  With the Gauss Jordan function :

 +1.000  +0.000  +0.000 +15.000 
 +0.000  +1.000  +0.000 +20.000 
 +0.000  +0.000  +1.000  +2.000