/*
* Eliminates all variables defined as evidence.
* The order of the variables that are not eliminated is
* the same order in the original function.
*/
private ProbabilityFunction check_evidence(ProbabilityFunction pf) {
int i, j, k, v, aux_i;
boolean markers[] = new boolean[bn.number_variables()];
int n = build_evidence_markers(pf, markers);
// Handle special cases
if (n == 0) return (null); // No variable remains
if (n == pf.number_variables()) return (pf); // No relevant evidence
// Calculate necessary quantities in such a
// way that the order of variables in the original
// function is not altered.
int joined_indexes[] = new int[n];
for (i = 0, j = 0, v = 1; i < pf.number_variables(); i++) {
aux_i = pf.get_variable(i).get_index();
if (markers[aux_i] == true) {
joined_indexes[j] = aux_i;
j++;
v *= bn.get_probability_variable(aux_i).number_values();
}
}
// Create new function to be filled with joined variables
ProbabilityFunction new_pf = new ProbabilityFunction(bn, n, v, null);
for (i = 0; i < n; i++) new_pf.set_variable(i, bn.get_probability_variable(joined_indexes[i]));
// Loop through the values
check_evidence_loop(new_pf, pf);
return (new_pf);
}
/*
* 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);
}