def test_pipeline(sampler, problem):
"""Check that a typical pipeline runs through."""
# optimization
optimizer = optimize.ScipyOptimizer(options={'maxiter': 10})
result = optimize.minimize(
problem, n_starts=3, optimizer=optimizer)
# sample
result = sample.sample(
problem, sampler=sampler, n_samples=100, result=result)
# some plot
visualize.sampling_1d_marginals(result)
plt.close()
def test_sampling_1d_marginals():
"""Test pypesto.visualize.sampling_1d_marginals"""
result = create_sampling_result()
visualize.sampling_1d_marginals(result)
# call with custom arguments
visualize.sampling_1d_marginals(result,
i_chain=1,
stepsize=5,
size=(10, 10))
# call with other modes
visualize.sampling_1d_marginals(result, plot_type='hist')
visualize.sampling_1d_marginals(result, plot_type='kde', bw='silverman')
def test_pipeline(sampler, problem):
"""Check that a typical pipeline runs through."""
# optimization
optimizer = optimize.ScipyOptimizer(options={'maxiter': 10})
result = optimize.minimize(problem,
n_starts=3,
optimizer=optimizer,
filename=None)
# sample
result = sample.sample(problem,
sampler=sampler,
n_samples=100,
result=result,
filename=None)
# remove warnings in test/sample/test_sample.
# Warning here: pypesto/visualize/sampling.py:1104
# geweke test
sample.geweke_test(result=result)
# some plot
visualize.sampling_1d_marginals(result)
plt.close()