def conditional_transition_probability(self, steps, ensemble, force=False):
"""
This transition's conditional transition probability for a given
ensemble.
The conditional transition probability for an ensemble is the
probability that a path in that ensemble makes the transition from
state A to state B.
Parameters
----------
steps : iterable of :class:`.MCStep`
cycles to analyze
ensemble : Ensemble
which ensemble to calculate the CTP for
force : bool (False)
if true, cached results are overwritten
"""
samples = sampleset_sample_generator(steps)
n_acc = 0
n_try = 0
for samp in samples:
if samp.ensemble is ensemble:
if self.stateB(samp.trajectory.get_as_proxy(-1)):
n_acc += 1
n_try += 1
ctp = float(n_acc)/n_try
logger.info("CTP: " + str(n_acc) + "/" + str(n_try) + "=" + str(ctp)
+ "\n")
try:
self.ctp[ensemble] = ctp
except AttributeError:
self.ctp = { ensemble : ctp }
return ctp
def all_statistics(self, steps, weights=None, force=False):
"""
Run all statistics for all ensembles.
"""
# TODO: speed this up by just running over all samples once and
# dealing them out to the appropriate histograms
for ens in self.ensembles:
samples = sampleset_sample_generator(steps)
self.ensemble_statistics(ens, samples, weights, force)
