public static void test()
{
ProblemSize ps = new()
{
chain_num = 10,
cr_num = 3,
gen_num = 10,
pair_num = 3,
par_num = 10
};
ProblemValue pv = new()
{
chain_filename = "problem0_chain00.txt",
gr_filename = "problem0_gr.txt",
gr_threshold = 1.2,
jumpstep = 5,
printstep = 10,
restart_read_filename = "",
restart_write_filename = "problem0_restart.txt",
limits = new double[ps.par_num * 2]
};
for (int j = 0; j < ps.par_num; j++)
{
pv.limits[0 + j * 2] = -10.0;
pv.limits[1 + j * 2] = +10.0;
}
Dream.dream(ref ps, ref pv, prior_sample, prior_density, sample_likelihood);
}
private static Dream.DensityResult prior_density(int par_num, double[] zp, int zpIndex = 0)
public static void test()
{
ProblemSize ps = new()
{
chain_num = 10,
cr_num = 3,
gen_num = 10,
pair_num = 3,
//par_num = 100;
par_num = 5
};
covariance_initialize(ps.par_num);
ProblemValue pv = new()
{
chain_filename = "problem1_chain00.txt",
gr_filename = "problem1_gr.txt",
gr_threshold = 1.2,
jumpstep = 5,
printstep = 10,
restart_read_filename = "",
restart_write_filename = "problem1_restart.txt",
limits = new double[ps.par_num * 2]
};
for (int j = 0; j < ps.par_num; j++)
{
pv.limits[0 + j * 2] = 9.9;
pv.limits[1 + j * 2] = +10.0;
}
Dream.dream(ref ps, ref pv, prior_sample, prior_density, sample_likelihood);
}
private static void covariance_initialize(int par_num)