B dF3@s^dZddlZddlZddlZddlmZddlZGdddej Z Gddde Z ddgZ dS)zS This modules provides classes for evaluating arbitrary distributions from a file. N)boundedcszeZdZdZdZdfdd ZeddZed d Zd d Z d dZ dddZ dddZ e ddZeddZZS) ArbitraryaA distribution constructed from a set of parameter values using a kde. Bounds may be optionally provided to limit the range. Parameters ---------- bounds : dict, optional Independent bounds on one or more parameters may be provided to limit the range of the kde. bandwidth : str, optional Set the bandwidth method for the KDE. See :py:func:`scipy.stats.gaussian_kde` for details. Default is "scott". \**params : The keyword arguments should provide the names of the parameters and a list of their parameter values. If multiple parameters are provided, a single kde will be produced with dimension equal to the number of parameters. arbitraryNscottc  sJdkr ifddDtt|jft|jtkrTtdi|_i|_ x|j D]\}}t |d|drd|}|}tjj|||d}||j|<||j |<||} | r|| }|||i||<qlt |drt |dsltdqlW|jfd d |jD|_||dS) Ncsi|]}|krd|qS)N).0p)boundsrj/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/pycbc/distributions/arbitrary.py 2sz&Arbitrary.__init__..zFMust provide samples for all parameters given in the bounds dictionaryrZlogit)domainz0if specifying bounds, both bounds must be finitecsg|] }|qSrr)rr)kwargsrr Msz&Arbitrary.__init__..)updatesuperr__init__setparamskeys ValueError _transforms_tparamsr itemsnumpyisfinitepycbcZ transformsZLogit __contains__any transformget_kde_from_arrays_kde set_bandwidth) selfr bandwidthrparamZbndstparamsamplestZoutside) __class__)r rr r.s.   " zArbitrary.__init__cCs|jS)N)_params)r#rrr rPszArbitrary.paramscCs|jS)N)r!)r#rrr kdeTsz Arbitrary.kdec sx(|jD]}|krtd|qW|krd}x|jD]\}}|j|}y|||i}Wn@tk r}z"||j|krdSt|Wdd}~XYnX|||<|| |9}qDW||j fdd|jD} t | dkrt | S| SndSdS)zReturns the pdf at the given values. The keyword arguments must contain all of parameters in self's params. Unrecognized arguments are ignored. z&Missing parameter {} to construct pdf.g?gNcsg|] }|qSrr)rr)rrr rvsz"Arbitrary._pdf..r )r*rrformatrrrrr jacobianr!evaluatelenfloat) r#rrr-r%r&r(r'eZthis_pdfr)rr _pdfXs,      zArbitrary._pdfcKs&||krtj St|jf|SdS)zReturns the log of the pdf at the given values. The keyword arguments must contain all of parameters in self's params. Unrecognized arguments are ignored. N)rinflogr2)r#rrrr _logpdfszArbitrary._logpdfcCs|j|dS)N)r!r")r#Zset_bwrrr r"szArbitrary.set_bandwidthr c s|dk r|tfg}ndd|jD}t|}tj||d}|j|fddt|jDxd|D]\\}}y2|j|}||i}|j | |||<Wnt k rYnX|||<qdW|S)aGives a set of random values drawn from the kde. Parameters ---------- size : {1, int} The number of values to generate; default is 1. param : {None, string} If provided, will just return values for the given parameter. Otherwise, returns random values for each parameter. Returns ------- structured array The random values in a numpy structured array. If a param was specified, the array will only have an element corresponding to the given parameter. Otherwise, the array will have an element for each parameter in self's params. NcSsg|] }|tfqSr)r0)rrrrr rsz!Arbitrary.rvs..)dtypecs"i|]\}}|ddf|qS)Nr)riir%)drawsrr r sz!Arbitrary.rvs..) r0rintrZzerosr!Zresample enumeraterrZinverse_transformKeyError)r#sizer%r6Zarr_r&Ztdrawsr)r8r rvss"     z Arbitrary.rvscGstjt|S)zConstructs a KDE from the given arrays. \*arrays : Each argument should be a 1D numpy array to construct the kde from. The resulting KDE will have dimension given by the number of parameters. )scipystatsZ gaussian_kderZvstack)Zarraysrrr r s zArbitrary.get_kde_from_arrayscCs tddS)zZRaises a NotImplementedError; to load from a config file, use `FromFile`. zOThis class does not support loading from a config file. Use `FromFile` instead.N)NotImplementedError)clscpsection variable_argsrrr from_configszArbitrary.from_config)Nr)r)r N)__name__ __module__ __qualname____doc__namerpropertyrr+r2r5r"r> staticmethodr classmethodrF __classcell__rr)r)r rs"  '  ' rcsHeZdZdZdZd fdd ZeddZd dd Ze d d Z Z S)FromFileaA distribution that reads the values of the parameter(s) from an hdf file, computes the kde to construct the pdf, and draws random variables from it. Parameters ---------- filename : str The path to an hdf file containing the values of the parameters that want to be used to construct the distribution. Each parameter should be a separate dataset in the hdf file, and all datasets should have the same size. For example, to give a prior for mass1 and mass2 from file f, f['mass1'] and f['mass2'] contain the n values for each parameter. datagroup : str, optional The name of the group to look in for the samples. For example, if ``datagroup = 'samples'``, then parameter ``param`` will be retrived from ``f['samples'][param]``. If none provided (the default) the data sets will be assumed to be in the top level directory of the file. \**params : The keyword arguments should provide the names of the parameters to be read from the file and (optionally) their bounds. If no parameters are provided, it will use all the parameters found in the file. To provide bounds, specify e.g. mass1=[10,100]. Otherwise, mass1=None. Attributes ---------- norm : float The normalization of the multi-dimensional pdf. lognorm : float The log of the normalization. kde : The kde obtained from the values in the file. fromfileNc sl|dkrtd||_||_t|dkr.d}n t|}|j||d\}}tt|j f||d|dS)Nz/A file must be specified for this distribution.r)r)r r$) r _filename datagroupr/listrget_arrays_from_filerrPr)r#filenamerSrZpsZ param_valsbw)r)rr rs  zFromFile.__init__cCs|jS)zJstr: The path to the file containing values for the parameter(s). )rR)r#rrr rVszFromFile.filenamecsyt|d}WntdYnX|jdk r<||jn||dk rt|tsX|g}x<|D] }|kr^td||q^WnddD}fdd|D}y|jd }Wnt k rd }YnX| ||fS) aReads the values of one or more parameters from an hdf file and returns as a dictionary. Parameters ---------- params_file : str The hdf file that contains the values of the parameters. params : {None, list} If provided, will just retrieve the given parameter names. Returns ------- dict A dictionary of the parameters mapping `param_name -> array`. rzFile not found.NzParameter {} is not in {}cSsg|] }t|qSr)str)rkrrr rsz1FromFile.get_arrays_from_file..csi|]}|d|qS)rr)rr)getrr r sz1FromFile.get_arrays_from_file..r$r) h5pyFilerrS isinstancerTrr,attrsr;close)r#Z params_filerfrZ params_valuesr$r)r[r rUs,      zFromFile.get_arrays_from_filecCstj||||ddS)aReturns a distribution based on a configuration file. The parameters for the distribution are retrieved from the section titled "[`section`-`variable_args`]" in the config file. The file to construct the distribution from must be provided by setting `filename`. Boundary arguments can be provided in the same way as described in `get_param_bounds_from_config`. .. code-block:: ini [{section}-{tag}] name = fromfile filename = ra_prior.hdf min-ra = 0 max-ra = 6.28 Parameters ---------- cp : pycbc.workflow.WorkflowConfigParser A parsed configuration file that contains the distribution options. section : str Name of the section in the configuration file. variable_args : str The names of the parameters for this distribution, separated by `prior.VARARGS_DELIM`. These must appear in the "tag" part of the section header. Returns ------- BoundedDist A distribution instance from the pycbc.inference.prior module. F)Zbounds_required)rZbounded_from_config)rBrCrDrErrr rF(s% zFromFile.from_config)NN)N) rGrHrIrJrKrrLrVrUrNrFrOrr)r)r rPs !  *rP) rJr\rZ scipy.statsr?Zpycbc.distributionsrZpycbc.transformsrZ BoundedDistrrP__all__rrrr s .