B zdO@sHdZddlZddlmZddlmZddlmZmZGdddeZ dS) z%Classes for individual Markov chains.N) JointProposal) BaseChain) ChainData detect_dtypesc@seZdZdZdAddZdddd Zed d Zed d ZeddZ eddZ e j ddZ eddZ e j ddZ ddZ eddZej ddZeddZej ddZeddZed d!Zed"d#Zed$d%Zed&d'Zed(d)Zej d*d)Zed+d,Zed-d.Zd/d0Zd1d2Zed3d4Zed5d6Zed7d8Zed9d:Zd;d<Zd=d>Zd?d@Z dS)BChaina) A Markov chain. The chain requires a ``model`` to be provided. This can be any object that can be called with keyword arguments that map parameter names to values. When called, the object must return a tuple of two or three elements. The first element must be a float representing the log likelihood at that point; the second must be a float representing the log prior at that point. Additionally, the model may return a dictionary as a third element in the tuple that maps strings to arbitrary data. This additional data will be stored as ``blob`` data. Parameters ---------- parameters : list or tuple List of the parameter names to sample. model : object Any object that can be called with keyword arguments that map parameter names to values. When called, the object must a tuple of ``logl, logp`` where ``logp`` is the log prior and ``logl`` is the log likelihood at the given point. The model may optionally return a dictionary in addition that maps strings to any arbitrary data. proposals : list of epsie.proposals instances List of proposal classes to use for the parameters. There must be one and only one proposal for every parameter. A single proposal may cover multiple parameters. Proposals must be instances of classes that inherit from :py:class:`epsie.proposals.BaseProposal`. bit_generator : :py:class:`epsie.BIT_GENERATOR` instance, optional Use the given random bit generator for generating random variates. If an int or None is provided, a generator will be created instead using ``bit_generator`` as a seed. chain_id : int, optional An interger identifying which chain this is. Default is 0. beta : float, optional The inverse temperature of the chain. Default is 1. Attributes ---------- parameters iteration lastclear scratchlen positions stats acceptance blobs start_position stats0 blob0 current_position current_stats current_blob bit_generator random_state state hasblobs transdimensional chain_id : int or None Integer identifying the chain. proposal_dist : JointProposal The joint proposal used for all parameters. Nr?cCs||_||_d|_|j|d|i|_||_||_d|_d|_d|_ t ||_ t ddg|_ t ddgdt id|_d|_d|_d|_d|_d|_d|_d|_dS) N bit_generatorrlogllogpZacceptance_ratioaccepted)dtypesF) parametersmodeltransdimensional_store_proposals proposal_distbetachain_id _iteration _lastclear _scratchlenr _positions_statsbool _acceptance_blobs _hasblobs_start_proposed_positionZ_logp0Z_logl0_blob0)selfrr proposalsr rrr#^/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/epsie/chain/chain.py__init__Xs*  zChain.__init__)r c Gsjd}x@|D]8}y|jr$d|_|d7}Wq tk r@d|_Yq Xq W|jr\|dkr\tdt|d|iS)zJStore either a ``JointProposal`` or the transdimensional proposal rTrFz[Can only provide a single transdimensinal proposals that includes the constituent proposalsr )rAttributeError ValueErrorr)r!r r"countpropr#r#r$rrs  zChain._store_proposalscCs|jS)z Whether the model returns blobs.)r)r!r#r#r$hasblobsszChain.hasblobscCs|jS)z/The number of times the chain has been stepped.)r)r!r#r#r$ iterationszChain.iterationcCs|jS)zMReturns the iteration of the last time the chain memory was cleared. )r)r!r#r#r$ lastclearszChain.lastclearcCs|jS)z%The length of the scratch space used.)r)r!r#r#r$ scratchlenszChain.scratchlencCs||_y|j|Wntk r*YnXy|j|Wntk rPYnXy|j|Wntk rvYnX|jry|j|Wntk rYnXdS)aSet the scratch length to the given value. This will immediately increase the scratch length to ``n``. If the chain is already longer than ``n``, this will have no immediate impact. However, the next time ``clear`` is called, the scratch length will be reset to ``n``. Parameters ---------- n : int The length to set. N)rrZset_lenr'rrr*r)r!nr#r#r$r-s$cCs|jdkrtd|jS)zDictionary mapping parameters to their start position. If the start position hasn't been set, raises a ``ValueError``. NzStarting position not set!)rr')r!r#r#r$start_positions zChain.start_positioncCs||_t||j_|jf|}|jr0|y|\}}}d|_Wn&t k rj|\}}d}d|_YnX|jrt |t st dt |t|d|_||d|_||_dS)a-Sets the starting position. This also evaulates the log likelihood and log prior at the starting position, as well as determine if the model returns blob data. Parameters ---------- position : dict Dictionary mapping parameters to values. TNFz+model must return blob data as a dictionary)r )r r )copyrrrr rr_activate_proposalsrr' isinstancedict TypeErrorrkeysrstats0blob0)r!positionrr r blobr#r#r$r/s$        csxjjD] }|jr Pq Wtj|jj|j<xL|jD]B}ttfdd|j Drdd|_ nd|_ |j dkr:t dq:Wt dd|jD_dS)z+Decide which proposals are initially activecsg|]}j|qSr#)r).0p)r!r#r$ sz-Chain._activate_proposals..FTNz@must provide `birth distribution` for transdimensional proposalscSsg|] }|jqSr#)active)r;r<r#r#r$r=s)rr"rintr_indexallnumpyisnanrr>Zbirth_distributionr'array _active_props)r!r)Zptdr#)r!r$r1s   zChain._activate_proposalscCs |j}|jS)zDictionary of the log likelihood and log prior at the start position. Raises a ``ValueError`` if the start position has not been set yet. )r/_stats0)r!_r#r#r$r6sz Chain.stats0cCs&|dtj krtd||_dS)zSets the starting stats. Parameters ---------- dict, numpy structred array of len 1, or numpy.void Dictionary or numpy array/void object mapping parameter names to the starting statistics. r z*starting position is outside of the prior!N)rBinfr'r0rF)r!statsr#r#r$r6s cCs |j}|jdkrd}n|j}|S)zThe blob data of the starting position, as a dictionary. Raises a ``ValueError`` if ``set_start`` has not been run yet. N)r/r )r!rGr:r#r#r$r7s  z Chain.blob0cCs:|dk r0|}|jdkr0t|t|d|_||_dS)zSets the starting blob. Parameters ---------- blob: dict Dictionary mapping blob parameters to their values. N)r )r0rrr5rr )r!r:r#r#r$r7#s  cCs$|jdkrtd|jdt|S)z:The history of all of the positions, as a structred array.rzGNo positions as chain hasn't been stepped yet; run step() at least onceN)r+r'rlen)r!r#r#r$ positions4s zChain.positionscCs$|jdkrtd|jdt|S)z\The log likelihoods and log priors of the positions, as a structured array. rzCNo stats as chain hasn't been stepped yet; run step() at least onceN)r+r'rrJ)r!r#r#r$rI<s z Chain.statscCs$|jdkrtd|jdt|S)NrzHNo acceptance as chain hasn't been stepped yet; run step() at least once)r+r'rrJ)r!r#r#r$ acceptanceFs zChain.acceptancecCs4|jdkrtd|jr,|jdt|}nd}|S)zThe history of all of the blob data, as a structured array. If the model does not return blobs, this is just ``None``. rzCNo blobs as chain hasn't been stepped yet; run step() at least onceN)r+r'r*rrJ)r!blobsr#r#r$rMMs  z Chain.blobscCs,t|dkr|j}n|jt|d}|S)z0Dictionary of the current position of the chain.rr)rJr/rasdict)r!posr#r#r$current_position\s zChain.current_positioncCs|jdkrtd|jS)z9Dictionary of the current proposed position of the chain.rzONo proposed position as chain hasn't been stepped yet; run step() at least once)r+r'r)r!r#r#r$proposed_positiones zChain.proposed_positioncCs ||_dS)z0Sets the current proposed position of the chain.N)r)r!rQr#r#r$rQmscCs,t|dkr|j}n|jt|d}|S)z\Dictionary giving the log likelihood and log prior of the current position. rr)rJr6rrN)r!rIr#r#r$ current_statsrs zChain.current_statscCs8|js d}n(t|dkr |j}n|jt|d}|S)zDictionary of the blob data of the current position. If the model does not return blobs, just returns ``None``. Nrr)r*rJr7rrN)r!r:r#r#r$ current_blob}s  zChain.current_blobcCsl|jdkr`|j|_|j|j|j|_|j|j|j |j|j r`|j |_ |j |j|j|_|S)zClears memory of the current chain, and sets start position to the current position. New scratch space will be created with length equal to ``scratch_len``. r)rrPrrclearr-rRrFrrr*rSr rr)r!r#r#r$rTs z Chain.clearcCsNd|dk|t|}|j||j||j|d}|jrJ|j||d<|S)z5Returns all of the chain data at the requested index.r)rKrIrLrM)rJrrrrr)r!indexoutr#r#r$ __getitem__szChain.__getitem__cCs|jjS)N)rr )r!r#r#r$r szChain.bit_generatorcCs|jjS)z$Returns the random number generator.)rrandom_generator)r!r#r#r$rYszChain.random_generatorcCs|jjS)z/Returns the current state of the bit generator.)r random_state)r!r#r#r$rZszChain.random_statecCsji}|j|d<|jj|d<|j|d<|j|d<|j|d<|j|d<|j|d<|jrZ|j}nd}||d <|S) zReturns the current state of the chain. The state consists of everything needed such that setting a chain's state using another's state will result in identical results. rrr+rPrQrRr*NrS) rrstater+rPrQrRr*rS)r!r[r:r#r#r$r[s       z Chain.statecCs|d|_||d|_|d|_|d|_|d|_|d|_|d|_|d|_ |j |dt |j|j _|jr|d S) a@Sets the state of the chain using the given dict. .. warning:: Running this will clear the chain's current memory, and replace its current position with what is saved in the state. Parameters ---------- state : dict Dictionary of state values. rr+rPrRr*rSrQrN)rrTrrr0rr6rr7rQr set_staterrr rr1)r!r[r#r#r$r\s       zChain.set_statec Cs|||j|||j}|jjsD||j|||j||7}|dkrVd}d} nDt|}t|rtd|j |j|||jj |j } | |k} | |fS)z8Calculates the acceptance ratio and evaluates acceptancerg?TzdNaN acceptance! chain: {}; beta: {}; current position: {}; proposed position: {}; proposal state: {}) rrZ symmetricZlogpdfrBexprCr'formatrr[rYuniform) r!r r proposal current_logp current_logl current_posZlogararacceptur#r#r$_acceptance_ratios     zChain._acceptance_ratiocCsB|j}|j}|j}|jr(|d|ji|j|}||_ |j f|}|j r\|\}}}n |\}}d}|d} |d} |t j krd} d} n||||| | |\} } | r|jr|d|_|} ||d}n|jr|d}|} |}|}t|}| |j|<||j|<| | f|j|<|j r$||j|<|jd7_|j||S) z#Evolves the chain by a single step._stateNr r Fg)r r r)rPrRrSrupdaterErZjumpr0rQrrrBrHrgpoprJrrrrr)r!rcrRrSr`r9r r r:rbrarerdrOrI__rVr#r#r$stepsN              z Chain.step)Nrr)!__name__ __module__ __qualname____doc__r%rpropertyr*r+r,r-setterr/r1r6r7rKrIrLrMrPrQrRrSrTrXr rYrZr[r\rgrlr#r#r#r$rsD=     ! 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