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;
}
$alg->register($test);
$alg = new OscatsAlgEstimate();
$alg->register($test);
$alg = new OscatsAlgFixedLength('OscatsAlgFixedLength', array("len" => $LEN));
$alg->register($test);
}
# Here we register the item selection criteria for the different tests
$alg = new OscatsAlgMaxFisher('OscatsAlgMaxFisher', array("A_opt" => True, "num" => 5));
$alg->register($tests[0]);
$alg = new OscatsAlgMaxFisher('OscatsAlgMaxFisher', array("num" => 5));
$alg->register($tests[1]);
$alg = new OscatsAlgMaxKl('OscatsAlgMaxKl', array("num" => 5));
$alg->register($tests[2]);
# In Example 1, we created OscatsExaminee objects for each examinee.
# Here, we'll just use one object over again for each administration.
$e = new OscatsExaminee('OscatsExaminee', array("covariates" => $covariate));
$sim_theta = new OscatsPoint('OscatsPoint', array("space" => $space));
$est_theta = new OscatsPoint('OscatsPoint', array("space" => $space));
$e->set_sim_theta($sim_theta);
$e->set_est_theta($est_theta);
print "Administering.\n";
for ($I = 0; $I < count($grid); $I++) {
$sim_theta->set_cont($dims[0], $grid[$I]);
for ($J = 0; $J < count($grid); $J++) {
print sprintf("\rAt grid point (%g, %g) ...\n", $grid[$I], $grid[$J]);
$sim_theta->set_cont($dims[1], $grid[$J]);
for ($i = 0; $i < $N_EXAMINEES; $i++) {
# "covariate" is the same OscatsCovariates object used by "e"
$covariate->set_by_name($COVARIATE_NAME, Oscats::rnd_normal(1));
print sprintf("\r%d", i);
flush();
