B zd!@sXddlZddlZddlmZddlmZddlmZmZddl m Z Gddde Z dS) N)create_bit_generators)Chain) ChainData detect_dtypes) BaseSamplerc@s4eZdZdZd ddZddZddZd d d ZdS) MetropolisHastingsSampleraA standard Metropolis-Hastings sampler. Parameters ---------- parameters : tuple or list Names of the parameters to sample. model : object Model object. nchains : int The number of chains to create. Must be greater than zero. proposals : list, optional List of proposals to use. Any parameters that do not have a proposal provided will use the ``default_propsal``. default_proposal : an epsie.Proposal class, optional The default proposal to use for parameters not in ``proposals``. Default is :py:class:`epsie.proposals.Normal`. default_proposal_args : dict, optional Dictionary of arguments to pass to the default proposal. seed : int, optional Seed for the random number generator. If None provided, will create one. pool : Pool object, optional Specify a process pool to use for parallelization. Default is to use a single core. Nc Cs4||_||_||||||_||_||dS)N) parametersmodelZ set_proposalsseedpool create_chains) selfr r nchains proposalsZdefault_proposalZdefault_proposal_argsr r re/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/epsie/samplers/mhsampler.py__init__5s z"MetropolisHastingsSampler.__init__cs:|dkrtdt|jd}fddt|D_dS)zCreates a list of :py:class:`chain.Chain`. Parameters ---------- nchains : int The number of Markov chains to create. rznchains must be >= 1)r c s2g|]*\}}tjjddjD||dqS)cSsg|]}t|qSr)copydeepcopy).0prrr MszFMetropolisHastingsSampler.create_chains...)Z bit_generatorZchain_id)rr r r)rZcidbg)rrrrKsz;MetropolisHastingsSampler.create_chains..N) ValueErrorrr enumerateZ_chains)rrZbitgensr)rrr ?s  z'MetropolisHastingsSampler.create_chainscCsbt|jd|}tt|t|d}||jx$t|jD]\}}t||||<q@W| S)a1Concatenates dictionary attributes over all of the chains. This is a convenience function used by properties such as ``current_positions`` to gather all of the dictionary attributes from the chains. Parameters ---------- attr : str The name of the attribute to get from the chains. The attribute is assumed to return a dictionary. Returns ------- dict : Dictionary mapping parameters to arrays. The arrays have shape ``nchains``. r)Zdtypes) getattrchainsrlistkeysrextendrrasdict)rattrdoutiichainrrr_concatenate_dictsQs  z,MetropolisHastingsSampler._concatenate_dictscsFdkr"ttfdd|j}nttfdd|j}t|S)aConcatenates the given attribute over all of the chains. This is a convenience function used by properties such as ``positions`` to gather all of the array attributes from the chains. Parameters ---------- attr : str The name of the attribute to get from the chains. The attribute is assumed to return a (structred) array. item : str or array index, optional Get a particular item from the (structred) array from each chain before concatenating. Returns ------- array : The returned array has shape ``nchains x niterations``. Ncs t|S)N)r)x)r"rrz?MetropolisHastingsSampler._concatenate_arrays..cst|S)N)r)r()r"itemrrr)r*)rmaprnumpystack)rr"r+Zarrsr)r"r+r_concatenate_arrayslsz-MetropolisHastingsSampler._concatenate_arrays)NNNNN)N)__name__ __module__ __qualname____doc__rr r'r/rrrrrs r) r-rZepsierZ epsie.chainrZepsie.chain.chaindatarrbaserrrrrrs