function gen_items($space, $covariate)
{
global $N_ITEMS, $dims, $COVARIATE_NAME;
# Create an item bank to store the items.
# Setting the property "sizeHint" increases allocation efficiency
# It's a bit kludgy, but the php gtk bindings require passing
# the name of the object to the objects constructor in order to
# set the construction properties.
$bank = new OscatsItemBank('OscatsItemBank', array("sizeHint" => $N_ITEMS));
# Create the items
for ($i = 0; $i < $N_ITEMS; $i++) {
# First we create an IRT model container for our item
# We have to specify which dimensions to be used with the "dims" array
# (in this case, we use both of the dimensions of the space)
$model = new OscatsModelL2p('OscatsModelL2p', array("space" => $space, "dims" => $dims, "covariates" => $covariate));
# Then, set the parameters. Here there are 4:
# Discrimination on two dimensions, difficulty, and covariate coef.
$model->set_param_by_name("Diff", Oscats::rnd_normal(sqrt(3)));
$model->set_param_by_name("Discr.Cont.1", Oscats::rnd_uniform_range(0, 1));
$model->set_param_by_name("Discr.Cont.2", Oscats::rnd_uniform_range(0, 2));
$model->set_param_by_name($COVARIATE_NAME, Oscats::rnd_uniform_range(0.5, 1.5));
# Create an item based on this model
# This is equivalent to oscats_item_new(0, model) in C
$item = new OscatsItem(0, $model);
# Add the item to the item bank
$bank->add_item($item);
# Since php is garbage collected, we don't have to worry about
# reference counting.
}
return $bank;
}
function gen_examinees($space)
{
global $N_EXAMINEES;
$dim = $space->get_dim_by_name("Cont.1");
$ret = array();
for ($i = 0; $i < $N_EXAMINEES; $i++) {
# Latent IRT ability parameter. This is a one-dimensional test.
$theta = new OscatsPoint('OscatsPoint', array("space" => $space));
# Sample the ability from N(0,1) distribution
$theta->set_cont($dim, Oscats::rnd_normal(1));
# Create a new examinee
$e = new OscatsExaminee();
# Set the examinee's true (simulated) ability
$e->set_sim_theta($theta);
$ret[] = $e;
}
return $ret;
}