def __init__(self, objective, chain, folder=None, parent=None):
QtWidgets.QDialog.__init__(self, parent)
self.setupUi(self)
self.objective = objective
self.folder = folder
self.chain = chain
if folder is None:
self.folder = os.getcwd()
if self.chain is None:
model_file_name, ok = QtWidgets.QFileDialog.getOpenFileName(
self, "Select chain file"
)
if not ok:
return
self.folder = os.path.dirname(model_file_name)
try:
self.chain = load_chain(model_file_name)
except Exception as e:
# a chain load will go wrong quite often I'd expect
self.chain = None
print(repr(e))
return
self.chain = chain
if len(self.chain.shape) == 3:
steps, walkers, varys = self.chain.shape
self.chain_size.setText(
"steps: {}, walkers: {}, varys: {}".format(
steps, walkers, varys
)
)
else:
steps, temps, walkers, varys = self.chain.shape
self.chain_size.setText(
"steps: {}, temps: {}, walkers: {}, varys: {}".format(
steps, temps, walkers, varys
)
)
self.total_samples.setText("Total samples: {}".format(steps * walkers))
self.burn.setMaximum(steps - 1)
self.thin.setMaximum(steps - 1)
acfs = autocorrelation_chain(self.chain)
time = integrated_time(acfs, tol=1, quiet=True)
self.autocorrelation_time.setText(
"Estimated Autocorrelation Time: {}".format(time)
)
def on_buttonBox_accepted(self):
nthin = self.thin.value()
nburn = self.burn.value()
process_chain(self.objective, self.chain, nburn=nburn, nthin=nthin)
# plot the Autocorrelation function of the chain
acfs = autocorrelation_chain(self.chain, nburn=nburn, nthin=nthin)
fig = Figure()
FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot(acfs)
ax.set_ylabel('autocorrelation')
ax.set_xlabel('step')
fig.savefig(os.path.join(self.folder, 'steps-autocorrelation.png'))
def recalculate(self):
nthin = self.thin.value()
nburn = self.burn.value()
lchain = self.chain[nburn::nthin]
if len(lchain.shape) == 3:
steps, walkers, varys = lchain.shape
else:
steps, temps, walkers, varys = lchain.shape
self.total_samples.setText('Total samples: {}'.format(steps * walkers))
acfs = autocorrelation_chain(lchain)
time = integrated_time(acfs, tol=1, quiet=True)
self.autocorrelation_time.setText(
'Estimated Autocorrelation Time: {}'.format(time))
self.nplot.setMaximum(steps * walkers)
def _process_chain(objective, chain, nburn, nthin, folder=None):
# processes the chain for the ProcessMCMCDialog
if folder is None:
folder = os.getcwd()
process_chain(objective, chain, nburn=nburn, nthin=nthin)
# plot the Autocorrelation function of the chain
acfs = autocorrelation_chain(chain, nburn=nburn, nthin=nthin)
fig = Figure()
FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot(acfs)
ax.set_ylabel("autocorrelation")
ax.set_xlabel("step")
fig.savefig(os.path.join(folder, "steps-autocorrelation.png"))
def test_mcmc(self):
self.mcfitter.sample(steps=50, nthin=1, verbose=False)
assert_equal(self.mcfitter.nvary, 2)
# smoke test for corner plot
self.mcfitter.objective.corner()
# we're not doing Parallel Tempering here.
assert_(self.mcfitter._ntemps == -1)
assert_(isinstance(self.mcfitter.sampler, emcee.EnsembleSampler))
# should be able to multithread
mcfitter = CurveFitter(self.objective, nwalkers=50)
res = mcfitter.sample(steps=33, nthin=2, verbose=False, pool=2)
# check that the autocorrelation function at least runs
acfs = mcfitter.acf(nburn=10)
assert_equal(acfs.shape[-1], mcfitter.nvary)
# check the standalone autocorrelation calculator
acfs2 = autocorrelation_chain(mcfitter.chain, nburn=10)
assert_equal(acfs, acfs2)
# check integrated_time
integrated_time(acfs2, tol=5)
# check chain shape
assert_equal(mcfitter.chain.shape, (33, 50, 2))
# assert_equal(mcfitter._lastpos, mcfitter.chain[:, -1, :])
assert_equal(res[0].chain.shape, (33, 50))
# if the number of parameters changes there should be an Exception
# raised
from pytest import raises
with raises(RuntimeError):
self.p[0].vary = False
self.mcfitter.sample(1)
# can fix by making the sampler again
self.mcfitter.make_sampler()
self.mcfitter.sample(1)
