bool Edgesort::IsValidEdge(const TopoDS_Edge& edge)
{
if ( edge.IsNull() )
return false;
if ( BRep_Tool::Degenerated(edge) )
return false;
BRepAdaptor_Curve bac(edge);
Standard_Real fparam = bac.FirstParameter();
Standard_Real lparam = bac.LastParameter();
gp_Pnt fpoint = bac.Value(fparam);
gp_Pnt lpoint = bac.Value(lparam);
//do not test the distance first last in case of a full circle edge (fpoint == lastpoint)
//if ( fpoint.IsEqual(lpoint,1e-5 ) )
// return false;
gp_Pnt mpoint = bac.Value((fparam+lparam)*0.5);
Standard_Real dist = mpoint.Distance(lpoint);
if ( dist <= 1e-5 )
return false;
dist = mpoint.Distance(fpoint);
if ( dist <= 1e-5 )
return false;
return true;
}
void binary_class_predict(FILE *input, FILE *output){
int total = 0;
int *labels;
int max_nr_attr = 64;
struct svm_node *x = Malloc(struct svm_node, max_nr_attr);
dvec_t dec_values;
ivec_t true_labels;
int svm_type=svm_get_svm_type(model);
if (svm_type==NU_SVR || svm_type==EPSILON_SVR){
fprintf(stderr, "wrong svm type.");
exit(1);
}
labels = Malloc(int, svm_get_nr_class(model));
svm_get_labels(model, labels);
max_line_len = 1024;
line = (char *)malloc(max_line_len*sizeof(char));
while(readline(input) != NULL)
{
int i = 0;
double target_label, predict_label;
char *idx, *val, *label, *endptr;
int inst_max_index = -1; // strtol gives 0 if wrong format, and precomputed kernel has <index> start from 0
label = strtok(line," \t");
target_label = strtod(label,&endptr);
if(endptr == label)
exit_input_error(total+1);
while(1)
{
if(i>=max_nr_attr - 2) // need one more for index = -1
{
max_nr_attr *= 2;
x = (struct svm_node *) realloc(x,max_nr_attr*sizeof(struct svm_node));
}
idx = strtok(NULL,":");
val = strtok(NULL," \t");
if(val == NULL)
break;
errno = 0;
x[i].index = (int) strtol(idx,&endptr,10);
if(endptr == idx || errno != 0 || *endptr != '\0' || x[i].index <= inst_max_index)
exit_input_error(total+1);
else
inst_max_index = x[i].index;
errno = 0;
x[i].value = strtod(val,&endptr);
if(endptr == val || errno != 0 || (*endptr != '\0' && !isspace(*endptr)))
exit_input_error(total+1);
++i;
}
x[i].index = -1;
predict_label = svm_predict(model,x);
fprintf(output,"%g\n",predict_label);
double dec_value;
svm_predict_values(model, x, &dec_value);
true_labels.push_back((target_label > 0)? 1: -1);
if(labels[0] <= 0) dec_value *= -1;
dec_values.push_back(dec_value);
}
// validation_function(dec_values, true_labels);
accuracy(dec_values, true_labels);
bac(dec_values, true_labels);
free(labels);
free(x);
}