def test_bad_mcmc():
constrainer = MCMCConstrainer(proposer = GaussProposal(adapt=False, scale=1e-5), nmaxsteps=100000)
N = 40
for d in 2, 7, 20:
print 'running in %d dimensions' % d
run_constrainer(d=d, N=N, constrainer=constrainer, name='rejection')
plt.savefig('test_constrainer_%d_%s.pdf' % (d, 'rejection'), bbox_inches='tight')
plt.close()
def test_bad_mcmc():
constrainer = MCMCConstrainer(proposer=GaussProposal(adapt=False,
scale=1e-5),
nmaxsteps=100000)
N = 40
for d in 2, 7, 20:
print('running in %d dimensions' % d)
run_constrainer(d=d, N=N, constrainer=constrainer, name='rejection')
plt.savefig('test_constrainer_%d_%s.pdf' % (d, 'rejection'),
bbox_inches='tight')
plt.close()
def run_constrainers(ds, Ns, constrainers):
fout = file('constrainertest.tex', 'w')
print ' %(name)30s %(d)3s %(N)3s D pvalue D pvalue iter evals efficiency' % dict(name='constrainer', d='dim', N='N')
print ' %s --- --- ---- ------ ---- ------ ----- ---------- -------------' % ('-'*30)
for d in ds:
for name, constrainer in constrainers:
for N in Ns:
results = run_constrainer(d, N, constrainer, name=name)
fout.write('%(name)s & %(d)d & %(pvalue).4f & %(shrinkage_pvalue).4f & %(niter)d & %(total_samples)d & %(efficiency).2f\\%% \\\\ \n' % results)
fout.flush()
fout.write('\hline\n')
fout.close()
def run_constrainers(ds, Ns, constrainers):
fout = file('constrainertest.tex', 'w')
print ' %(name)30s %(d)3s %(N)3s D pvalue D pvalue iter evals efficiency' % dict(
name='constrainer', d='dim', N='N')
print ' %s --- --- ---- ------ ---- ------ ----- ---------- -------------' % (
'-' * 30)
for d in ds:
for name, constrainer in constrainers:
for N in Ns:
results = run_constrainer(d, N, constrainer, name=name)
fout.write(
'%(name)s & %(d)d & %(pvalue).4f & %(shrinkage_pvalue).4f & %(niter)d & %(total_samples)d & %(efficiency).2f\\%% \\\\ \n'
% results)
fout.flush()
fout.write('\hline\n')
fout.close()
Ns=[400],
constrainers=constrainers)
def test_rejection():
constrainer = RejectionConstrainer()
N = 40
for d in 2, 7, 20:
print('running in %d dimensions' % d)
evaluate_constrainer(d=d, N=N, constrainer=constrainer, niter=400)
plt.savefig('test_constrainer_%d_%s.pdf' % (d, 'rejection'),
bbox_inches='tight')
plt.close()
if __name__ == '__main__':
import sys
if len(sys.argv) == 1:
test_all()
else:
sel = int(sys.argv[1])
i = 0
ds = (2, 7, 20)
Ns = [400]
for name, constrainer in constrainers:
for d in ds:
for N in Ns:
i = i + 1
if i == sel:
run_constrainer(d, N, constrainer, name=name)
fout.close()
def test_all():
run_constrainers(ds=(2, 7, 20), #(2, 7, 20),
Ns=[400], constrainers=constrainers)
def test_rejection():
constrainer = RejectionConstrainer()
N = 40
for d in 2, 7, 20:
print 'running in %d dimensions' % d
evaluate_constrainer(d=d, N=N, constrainer=constrainer, niter=400)
plt.savefig('test_constrainer_%d_%s.pdf' % (d, 'rejection'), bbox_inches='tight')
plt.close()
if __name__ == '__main__':
import sys
if len(sys.argv) == 1:
test_all()
else:
sel = int(sys.argv[1])
i = 0
ds=(2, 7, 20)
Ns=[400]
for name, constrainer in constrainers:
for d in ds:
for N in Ns:
i = i + 1
if i == sel:
run_constrainer(d, N, constrainer, name=name)