`altar.bayesian.CoolingStep`

Module Contents

Classes

class altar.bayesian.CoolingStep.CoolingStep(beta, theta, likelihoods, sigma=None, **kwds)

Encapsulation of the state of the calculation at some particular β value

beta

theta

prior

data

posterior

sigma

mean

std

classmethod start(cls, annealer): Build the first cooling step by asking {model} to produce a sample set from its initializing prior, compute the likelihood of this sample given the data, and compute a (perhaps trivial) posterior

classmethod allocate(cls, annealer)

classmethod alloc(cls, samples, parameters): Allocate storage for the parts of a cooling step

clone(self): Make a new step with a duplicate of my state

computePosterior(self): Compute the posterior from prior, data, and beta

statistics(self): Compute the statistics of samples :return:

print(self, channel, indent=' ' * 2): Print info about this step

save_hdf5(self, path=None, iteration=None, psets=None)

Save Coolinging Step to HDF5 file :param step altar.bayesian.CoolingStep: :param path altar.primitives.path:

Returns:: None

load_hdf5(self, path=None, iteration=0): load CoolingStep from HDF5 file