[Scilab-Dev] SciFunction

[Sylvestre Ledru]

HI Yann,

I am not answering to your question (sorry).
But I would like to inform you that we changed the data type declaration
in CreateVar, GetRhsVar, etc for something less cryptic:

	+ "c" => STRING_DATATYPE
	+ "S" => MATRIX_OF_STRING_DATATYPE
	+ "d" => MATRIX_OF_DOUBLE_DATATYPE
	+ "r" => MATRIX_OF_RATIONAL_DATATYPE
	+ "I" => MATRIX_OF_VARIABLE_SIZE_INTEGER_DATATYPE
	+ "i" => MATRIX_OF_INTEGER_DATATYPE
	+ "b" => MATRIX_OF_BOOLEAN_DATATYPE
	+ "z" => MATRIX_OF_COMPLEX_DATATYPE
	+ "s" => SPARSE_MATRIX_DATATYPE
	+ "l" => LIST_DATATYPE
	+ "t" => TYPED_LIST_DATATYPE
	+ "m" => MATRIX_ORIENTED_TYPED_LIST_DATATYPE
	+ "p" => SCILAB_POINTER_DATATYPE
	+ "h" => GRAPHICAL_HANDLE_DATATYPE
	+ "f" => EXTERNAL_DATATYPE
You will find the list here:
modules/core/includes/stackTypeVariable.h

Cheers,
Sylvestre

Le mercredi 06 février 2008 à 14:50 +0100, COLLETTE Yann a écrit :
> Hello,
> 
> I'm trying to interface an optimisation method under scilab (the 
> optimization method is in fortran and I'm writing the interface in C).
> My question is: how to retrieve the output parameters of a call to 
> SciFunction ?
> The following program is called several times during the run of the 
> optimization:
> 
> /////////////////////////////////////
> //  First I create some parameters. The first one will contain the "x" 
> vector and the second one the gradient of the output (I do this to give 
> the correct size to the stack. If I don't do this, scilab says it 
> doesn't know the ibegin + 1 parameter).
> 
>   // Create the first variable: x
>   n_x1_tmp = n_x;
>   m_x1_tmp = m_x;
>   CreateVar(ibegin,"d",&n_x1_tmp,&m_x1_tmp,&l_x1_tmp);
>   for(i=0;i<ndv; i++) *dstk(l_x1_tmp+i) = *dstk(l_x+i);
> 
>   // Create a fake 2nd variable on the stack. This will allow to call 
> GetRhsVar to retrieve the 2nd output argument
>   n_x2_tmp = 1;
>   m_x2_tmp = 1;
>   CreateVar(ibegin+1,"d",&n_x2_tmp,&m_x2_tmp,&l_x2_tmp);
> 
> ///////////////////////////////////
> // I call the scilab function via SciFunction
> 
> 
>   // Call to the scilab function
>   SciFunction(&ibegin,&l_fobj,&fobj_lhs,&fobj_rhs);
>   if (Err>0)
>     {
>       sciprint("conmin: error when calling objective function\n");
>       return 0;
>     } /* End If */
> 
>   n1 = ndv + 2;
> 
> ////////////////////////////////////
> // Now I get the parameters via GetRhsVar. I hope that the size of the 
> ibegin and ibegin+1 parameters are set correctly by SciFunction (first 
> free the memory and then mallocated correctly to get the output parameters).
>   // Get fobj
>   GetRhsVar(ibegin,  "d",&n_fobj_tmp, &m_fobj_tmp, &l_fobj_tmp);
>   // Get gradient of fobj
>   GetRhsVar(ibegin+1,"d",&n_dfobj_tmp,&m_dfobj_tmp,&l_dfobj_tmp);
> 
> /////////////////////////////////////
> // Finally, I store all the output parameters in temporary arrays 
> (because just after the objective function, I called the constraints 
> also via SciFunction).
> 
>   // Fill C2F(cnmn1).obj: objective function value
>   C2F(cnmn1).obj = *dstk(l_fobj_tmp);
> 
>   // DF(N1) Analytic gradient of the objective function for the current 
> decision variables, X(I).  DF(I) contains the partial derivative
>   //        of OBJ with respect to X(I).  Calculate DF(I), I = 1, NDV if 
> INFO = 3 or INFO = 4 and if NFDG = 0 or NFDG = 2.
>   double * DF = (double *)malloc(n1*sizeof(double));
>   // Fill DF(N1): gradient of objective function value
>   for(j=0;j<ndv;j++) DF[j] = *dstk(l_dfobj_tmp+j);
> 
> ///////////////////////////////////////
> // Is my strategy good or do you recommend another method ?
> 
> Your sincerely,
> 
> Yann COLLETTE
> 
> 
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