:mod:`altar.distributions` ========================== .. py:module:: altar.distributions Submodules ---------- .. toctree:: :titlesonly: :maxdepth: 1 Base/index.rst Distribution/index.rst Gaussian/index.rst Uniform/index.rst UnitGaussian/index.rst Package Contents ---------------- Classes ~~~~~~~ .. autoapisummary:: altar.distributions.distribution Functions ~~~~~~~~~ .. autoapisummary:: altar.distributions.uniform altar.distributions.gaussian altar.distributions.ugaussian .. py:class:: distribution Bases: :class:`altar.protocol` The protocol that all AlTar probability distributions must satisfy .. attribute:: parameters .. attribute:: doc :annotation: = the number of model parameters that i take care of .. attribute:: offset .. attribute:: doc :annotation: = the starting point of my parameters in the overall model state .. method:: initialize(self, **kwds) Initialize with the given random number generator .. method:: initializeSample(self, theta) Fill my portion of {theta} with initial random values from my distribution. .. method:: priorLikelihood(self, theta, prior) Fill my portion of {prior} with the likelihoods of the samples in {theta} .. method:: verify(self, theta, mask) Check whether my portion of the samples in {theta} are consistent with my constraints, and update {mask}, a vector with zeroes for valid samples and non-zero for invalid ones .. method:: sample(self) Sample the distribution using a random number generator .. method:: density(self, x) Compute the probability density of the distribution at {x} .. method:: vector(self, vector) Fill {vector} with random values .. method:: matrix(self, matrix) Fill {matrix} with random values .. method:: pyre_default(cls) :classmethod: Supply a default implementation .. function:: uniform() .. function:: gaussian() .. function:: ugaussian()