PyMODINIT_FUNC initjit(void)
{
PyThunk_Init();
initialize_thunk_methods();
initialize_operation();
initialize_thunk_as_number();
initialize_thunk_as_sequence();
initialize_parser();
initialize_compiler();
initialize_scheduler();
initialize_thunk_as_mapping();
//initialize module
PyObject *m = Py_InitModule3("jit", module_methods, module_docstring);
if (m == NULL)
return;
create_threads();
}
bool PostKriging::initialize( const Parameters_handler* parameters,
Error_messages_handler* errors )
{
std::cout << "initializing algorithm PostKriging \n";
this->extract_parameters(parameters);
std::string harddata_grid_name = parameters->value( "Hard_Data.value" );
errors->report( harddata_grid_name.empty(),
"Hard_Data", "No hard data specified" );
if( !harddata_grid_name.empty() ) {
grid_ = 0;
bool ok = geostat_utils::create( grid_, harddata_grid_name,
"Grid_Name", errors );
if( !ok || !grid_ ) return false;
}
else
return false;
is_non_param_cdf_ = parameters->value( "is_non_param_cdf.value" ) == "1";
if(is_non_param_cdf_)
{
std::vector< std::string > prop_name = String_Op::decompose_string(
parameters->value( "props.value" ), ";" );
for(std::vector< std::string >::iterator it_str = prop_name.begin();
it_str != prop_name.end(); it_str++ )
props.push_back(grid_->property( *it_str ));
std::vector< float > thresh = String_Op::to_numbers<float>( parameters->value( "marginals.value" ) );
errors->report( thresh.size() != props.size() , "marginals.value",
"The marginal must have the same lengths than the indicator properties" );
non_param_cdf_ = new Non_param_cdf<>(thresh.begin(),thresh.end());
//Set the tail extrapolation functions
geostat_utils::set_cdf_extrapolation_tail(parameters,errors,
*non_param_cdf_,"lowerTailCdf", "upperTailCdf");
}
else {
std::string prop_name = parameters->value( "gaussian_mean_prop.value" );
props.push_back( grid_->property( prop_name ));
errors->report( props[0] == NULL , "mean_prop.value", "That property does not exist" );
prop_name = parameters->value( "gaussian_var_prop.value" );
props.push_back( grid_->property( prop_name ) );
errors->report( props[1] == NULL , "var_prop.value", "That property does not exist" );
gaussian_cdf_ = new Gaussian_cdf();
}
mean_ = parameters->value( "mean.value" ) == "1";
iqr_ = parameters->value( "iqr.value" ) == "1";
cond_var_ = parameters->value( "cond_var.value" ) == "1";
quantile_ = parameters->value( "quantile.value" ) == "1";
prob_above_ = parameters->value( "prob_above.value" ) == "1";
prob_below_ = parameters->value( "prob_below.value" ) == "1";
if(mean_)
check_input_string(errors,parameters,"mean_prop");
if(cond_var_)
check_input_string(errors,parameters,"cond_var_prop");
if(iqr_)
check_input_string(errors,parameters,"iqr_prop");
if(quantile_){
check_input_string(errors,parameters,"quantile_prop",0.,1.);
check_input_string(errors,parameters,"quantile_vals",0.,1.);
}
if(prob_above_) {
check_input_string( errors,parameters,"prob_above_prop");
check_input_string(errors,parameters,"prob_above_vals");
}
if(prob_below_) {
check_input_string( errors,parameters,"prob_below_prop");
check_input_string(errors,parameters,"prob_below_vals");
}
if( !errors->empty() ) return false;
if(mean_)
initialize_operation(mean_prop_,errors,parameters,"mean");
if(cond_var_)
initialize_operation(cond_var_prop_,errors,parameters,"cond_var");
if(iqr_)
initialize_operation(iqr_prop_,errors,parameters,"iqr");
if(quantile_) {
initialize_operation( quantile_props_, quantile_vals_,errors,parameters,"quantile");
std::sort(quantile_vals_.begin(),quantile_vals_.end());
if( quantile_vals_.front() < 0 && quantile_vals_.back() > 1 )
errors->report("quantile","Quantiles must be between 0 and 1");
}
if(prob_above_)
initialize_operation( prob_above_props_, prob_above_vals_,errors,parameters,"prob_above");
if(prob_below_)
initialize_operation( prob_below_props_, prob_below_vals_,errors,parameters,"prob_below");
if( !errors->empty() )
return false;
return true;
}