/**
* Adds a new CPD to the transition model.
* @param factor
* A factor that represents the conditional probability distribution.
* The arguments of this factor must be either time-t or time-t+1
* arguments of one or more timed processes.
* @param p
* The process, for which the CPD is being added. The argument
* factor must contain the t+1-step argument of process p.
*/
void add_factor(process_type p, const F& factor) {
assert(factor.arguments().count(p->next()) > 0);
for (argument_type v : factor.arguments()) {
int t = boost::any_cast<int>(v.index());
assert(t == current_step || t == next_step);
}
processes_.insert(p);
transition.add_factor(p->next(), factor);
}
//! Initialize the oracle
void init() {
assert(params.valid());
// Initialize the random number generator
rng.seed(static_cast<unsigned>(params.random_seed));
uniform_prob = boost::uniform_real<double>(0,1);
// Construct the graph and make CPTs
if (num_finite() > 2 * params.num_parents) {
for (size_t j = 2 * params.num_parents; j < num_finite(); ++j) {
// Choose NUM_PARENTS random parents
finite_domain parents;
std::vector<size_t> r(randperm(j, rng));
for (size_t k = 0; k < params.num_parents; ++k)
parents.insert(finite_seq[r[k]]);
parents.insert(finite_seq[j]);
tablef f(parents.plus(finite_seq[j]));
// RIGHT HERE NOW: MAKE FACTOR
bn.add_factor(parents, finite_seq[j]);
}
}
}
/**
* Adds a new factor to the prior distribution.
* @param factor
* A factor that represents the conditional probability distribution.
* The arguments of this factor must be time-t arguments of one or
* more timed processes.
* @param v
* The head of the conditional probability distribution.
*/
void add_factor(argument_type head, const F& factor) {
assert(factor.arguments().count(head) > 0);
check_index(factor.arguments(), current_step);
prior.add_factor(head, factor);
}
