def sample(n_samps, path=None):
if path is not None:
dirname = os.path.dirname(path)
if not os.path.exists(dirname):
os.makedirs(dirname)
iters = []
nfevals = []
target_lnpdf.counter = 0
start = time()
timestamps = []
cur_theta = prior.rvs(1)
cur_lnpdf = target_lnpdf(cur_theta, without_prior=True)
all_samples = []
samples = []
for i in range(1, n_samps+1):
[cur_theta, cur_lnpdf] = ess_update(cur_theta, prior_chol, target_lnpdf, pdf_params=(True,),
cur_lnpdf=cur_lnpdf)
samples.append(cur_theta)
if i> 1 and i % 1000 == 0:
all_samples.append(np.array(samples))
samples = []
iters.append(i)
nfevals.append(target_lnpdf.counter)
timestamps.append(time() - start)
if path is not None:
np.savez(path+"processed_data", iter=iters, samples=np.array(all_samples), fevals=np.array(nfevals),
true_means=target_mixture.get_numpy_means(), true_covs=target_mixture.get_numpy_covs(),
timestamps=np.array(timestamps))
print("done")
def sample(n_samps, seed=1, path=None):
if path is not None:
dirname = os.path.dirname(path)
if not os.path.exists(dirname):
os.makedirs(dirname)
unknown_params = [1, 2] + np.arange(4, 12).tolist()
num_dimensions = len(unknown_params)
target_lnpdf = build_Goodwin(unknown_params,
seed=seed,
sigma=np.sqrt(0.2),
parameters=np.array([
10., 1.97, 0.46, 0.53, 0.02878028,
0.13585575, 1.57070286, 0.75737477,
0.28929913, 1.52671658, 1.26995194,
1.89562767
]))
prior = normal_pdf(np.zeros(num_dimensions), 1e1 * np.eye(num_dimensions))
prior_chol = np.linalg.cholesky(prior.cov)
iters = []
nfevals = []
target_lnpdf.counter = 0
def target_lnpdf_no_prior(theta):
return target_lnpdf(theta) - prior.logpdf(theta)
start = time()
timestamps = []
cur_theta = prior.rvs(1)
cur_lnpdf = target_lnpdf_no_prior(cur_theta)
all_samples = []
samples = []
for i in range(1, n_samps + 1):
[cur_theta, cur_lnpdf] = ess_update(cur_theta,
prior_chol,
target_lnpdf_no_prior,
pdf_params=(),
cur_lnpdf=cur_lnpdf)
samples.append(cur_theta)
if i > 1 and i % 1000 == 0:
all_samples.append(np.array(samples))
samples = []
iters.append(i)
nfevals.append(target_lnpdf.counter)
timestamps.append(time() - start)
if path is not None:
np.savez(path + "processed_data",
iter=iters,
samples=np.exp(np.array(all_samples)),
fevals=np.array(nfevals),
timestamps=np.array(timestamps))
print("done")