/*
* Obtain the values for the evidence plus function.
*/
private void check_evidence_loop(ProbabilityFunction new_pf, ProbabilityFunction pf) {
int i, j, k, l, m, p, last, current;
int indexes[] = new int[bn.number_variables()];
int value_lengths[] = new int[bn.number_variables()];
for (i = 0; i < bn.number_variables(); i++) {
indexes[i] = 0;
value_lengths[i] = bn.get_probability_variable(i).number_values();
}
for (i = 0; i < bn.number_variables(); i++) {
if (bn.get_probability_variable(i).is_observed()) {
indexes[i] = bn.get_probability_variable(i).get_observed_index();
}
}
last = new_pf.number_variables() - 1;
for (i = 0; i < new_pf.number_values(); i++) {
p = new_pf.get_position_from_indexes(indexes);
new_pf.set_value(p, pf.evaluate(indexes));
indexes[new_pf.get_index(last)]++;
for (j = last; j > 0; j--) {
current = new_pf.get_index(j);
if (indexes[current] >= value_lengths[current]) {
indexes[current] = 0;
indexes[new_pf.get_index(j - 1)]++;
} else break;
}
}
}
/*
* Build an array of markers. The marker for a
* variable is true only if the variable is present in the
* input ProbabilityFunction pf and is not observed.
* Even explanatory variables can be observed and taken as
* evidence.
*/
private int build_evidence_markers(ProbabilityFunction pf, boolean markers[]) {
int i, n;
// Initialize the markers
for (i = 0; i < markers.length; i++) markers[i] = false;
// Insert the variables of the ProbabilityFunction
for (i = 0; i < pf.number_variables(); i++) markers[pf.get_index(i)] = true;
// Take the evidence out
for (i = 0; i < bn.number_variables(); i++) {
if (bn.get_probability_variable(i).is_observed()) markers[i] = false;
}
// Count how many variables remain
n = 0;
for (i = 0; i < markers.length; i++) {
if (markers[i] == true) n++;
}
return (n);
}
