static bool check_type(compile_t* c, LLVMValueRef ptr, LLVMValueRef desc,
ast_t* pattern_type, LLVMBasicBlockRef next_block)
{
switch(ast_id(pattern_type))
{
case TK_NOMINAL:
// We are trying to capture the match expression as a nominal.
return check_nominal(c, desc, pattern_type, next_block);
case TK_TUPLETYPE:
// We are trying to capture the match expression as a tuple.
return check_tuple(c, ptr, desc, pattern_type, next_block);
case TK_UNIONTYPE:
// We are trying to capture the match expression as a union.
return check_union(c, ptr, desc, pattern_type, next_block);
case TK_ISECTTYPE:
// We are trying to capture the match expression as an intersection.
return check_isect(c, ptr, desc, pattern_type, next_block);
case TK_ARROW:
// We are trying to capture the match expression as a viewpoint type, so
// try again with the right-hand side of the arrow.
return check_type(c, ptr, desc, ast_childidx(pattern_type, 1),
next_block);
default: {}
}
assert(0);
return false;
}
/* pick up information(startTime, stopTime, dt) from model data to optimizer struct
* author: Vitalij Ruge
*/
static inline void pickUpBounds(OptDataBounds * bounds, OptDataDim * dim, DATA* data){
char ** inputName;
double min, max, nominal, x0;
double *umin, *umax, *unom;
modelica_boolean nominalWasSet;
modelica_boolean * nominalWasSetInput;
const int nx = dim->nx;
const int nv = dim->nv;
const int nu = dim->nu;
const int nt = dim->nt;
const int NV = dim->NV;
long double tmp;
int i, j;
dim->inputName = (char**) malloc(nv*sizeof(char*));
bounds->vnom = malloc(nv*sizeof(double));
bounds->scalF = malloc(nv*sizeof(long double));
bounds->vmin = malloc(nv*sizeof(double));
bounds->vmax = malloc(nv*sizeof(double));
bounds->u0 = malloc(nu*sizeof(double));
nominalWasSetInput = (modelica_boolean*)malloc(nv*sizeof(modelica_boolean));
inputName = dim->inputName;
umin = bounds->vmin + nx;
umax = bounds->vmax + nx;
unom = bounds->vnom + nx;
data->callback->pickUpBoundsForInputsInOptimization(data,umin, umax, unom, nominalWasSetInput, inputName, bounds->u0, &bounds->preSim);
for(i = 0; i < nx; ++i){
min = data->modelData.realVarsData[i].attribute.min;
max = data->modelData.realVarsData[i].attribute.max;
nominal = data->modelData.realVarsData[i].attribute.nominal;
nominalWasSet = data->modelData.realVarsData[i].attribute.useNominal;
x0 = data->localData[1]->realVars[i];
check_nominal(bounds, min, max, nominal, nominalWasSet, i, x0);
data->modelData.realVarsData[i].attribute.nominal = bounds->vnom[i];
bounds->scalF[i] = 1.0/bounds->vnom[i];
bounds->vmin[i] = min * bounds->scalF[i];
bounds->vmax[i] = max * bounds->scalF[i];
}
for(j=0; i<dim->nv; ++i,++j){
bounds->u0[j] = fmin(fmax(bounds->u0[j], umin[j]), umax[j]);
check_nominal(bounds, umin[j], umax[j], unom[j], nominalWasSetInput[j], i, fabs(bounds->u0[j]));
bounds->scalF[i] = 1.0 / bounds->vnom[i];
bounds->vmin[i] *= bounds->scalF[i];
bounds->vmax[i] *= bounds->scalF[i];
}
free(nominalWasSetInput);
bounds->Vmin = malloc(NV*sizeof(double));
bounds->Vmax = malloc(NV*sizeof(double));
for(i = 0, j = 0; i < nt ; ++i, j += nv){
memcpy(bounds->Vmin + j, bounds->vmin, nv*sizeof(double));
memcpy(bounds->Vmax + j, bounds->vmax, nv*sizeof(double));
}
}
