B d"@sddZddlZddlZddlmZddlmZ ddl m Z Gddde Z Gddde ZddgZdS)z This modules provides classes for evaluating PDF, logPDF, CDF and inverse CDF from external arbitrary distributions, and drawing samples from them. N) VARARGS_DELIMc@sDeZdZdZdZdddZdddZd d Zd d Ze d dZ dS)Externala Distribution defined by external cdfinv and logpdf functions To add to an inference configuration file: .. code-block:: ini [prior-param1+param2] name = external module = custom_mod logpdf = custom_function_name cdfinv = custom_function_name2 Or call `DistributionFunctionFromFile` in the .ini file: .. code-block:: ini [prior-param] name = external_func_fromfile module = pycbc.distributions.external file_path = path column_index = index logpdf = _logpdf cdfinv = _cdfinv Parameters ---------- params : list list of parameter names custom_mod : module module from which logpdf and cdfinv functions can be imported logpdf : function function which returns the logpdf cdfinv : function function which applies the invcdf Examples -------- To instantate by hand and example of function format. You must provide the logpdf function, and you may either provide the rvs or cdfinv function. If the cdfinv is provided, but not the rvs, the random values will be calculated using the cdfinv function. >>> import numpy >>> params = ['x', 'y'] >>> def logpdf(x=None, y=None): ... p = numpy.ones(len(x)) ... return p >>> >>> def cdfinv(**kwds): ... return kwds >>> e = External(['x', 'y'], logpdf, cdfinv=cdfinv) >>> e.rvs(size=10) ZexternalNcKs,||_||_||_||_|s(|s(tddS)Nz!Must provide either rvs or cdfinv)paramslogpdfcdfinv_rvs ValueError)selfrrrvsrkwdsr i/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/pycbc/distributions/external.py__init__Ss zExternal.__init__c s2|jr|jdSfdd|jD}|jf|S)zDraw random value)sizecs i|]}tjjddd|qS)rr)r)nprandomuniform).0param)rr r asz External.rvs..)rrr)r rr Zsamplesr )rr r ]s    z External.rvscKs|S)Nr )r rr r r apply_boundary_conditionsesz"External.apply_boundary_conditionscKs |jf|S)N)r)r r r r r __call__hszExternal.__call__cCs|}|t}||d|}|dkrJ||d|}t|||d|d}n t|}||d|} t|| } d} } ||d|r||d|} t|| } ||d|r||d|}t||} |dkr||||j| | d S||| | | d S) Nmodulezpycbc.distributions.external file_path column_index)rrrrr )rrrr r)rrr r) splitrZ get_opt_tagDistributionFunctionFromFile importlib import_modulegetattrZhas_option_tagr)clscpsectionZ variable_argstagrZ modulestrrmodZ logpdfstrrrr Z cdfinvstrZrvsstrr r r from_configks,     zExternal.from_config)NNNN)r) __name__ __module__ __qualname____doc__namerr rr classmethodr&r r r r rs5 rcsFeZdZdZdZdfdd ZddZdd Zd d Zd d Z Z S)raEvaluating PDF, logPDF, CDF and inverse CDF from the external density function. Instances of this class can be called like a distribution in the .ini file, when used with `pycbc.distributions.external.External`. Please see the example in the `External` class. Parameters ---------- parameter : {'file_path', 'column_index'} The path of the external density function's .txt file, and the column index of the density distribution. By default, the first column should be the values of a certain parameter, such as "mass", other columns should be the corresponding density values (as a function of that parameter). If you add the name of the parameter in the first row, please add the '#' at the beginning. \**kwargs : All other keyword args are passed to `scipy.integrate.quad` to control the numerical accuracy of the inverse CDF. If not be provided, will use the default values in `self.__init__`. Notes ----- This class is different from `pycbc.distributions.arbitrary.FromFile`, which needs samples from the hdf file to construct the PDF by using KDE. This class reads in any continuous functions of the parameter. Zexternal_func_fromfileNc s|drtj|ddntjdd||_tj|ddd|_t||_| dd|_ | dd|_ t |jd d |jd d d |_ tttd |_|std dS)Nr)rT#)fnameunpackcommentsepsabsg h`?>epsrelri)pdfcdfrz/Must provide the path to density function file.) __contains__superrrrZloadtxtdataintrgetr1r2Zlinspacex_listcallableinterpr)r rrrkwargs) __class__r r rs  $z%DistributionFunctionFromFile.__init__cKs|jdtkrt|jd|j|j}tj||jdd|jddf|j|j dd|d}t|jd|j|j||jd<t |jd|}|S)zCalculate and interpolate the PDF by using the given density function, then return the corresponding value at the given x.r4rr3i)r1r2limit) r=r<scipy_interpolateinterp1dr8rscipy_integratequadr1r2rfloat64)r xr>Z func_unnormZ norm_constZpdf_valr r r _pdfs  z!DistributionFunctionFromFile._pdfcKst|j|f|S)z/Calculate the logPDF by calling `pdf` function.)rlogrG)r rFr>r r r _logpdfsz$DistributionFunctionFromFile._logpdfcKs|jdtkrrg}xJ|jD]@}tj|j|jdd|f|j|jdd|d}| |qWt |j||jd<t |jd|}|S)z^Calculate and interpolate the CDF, then return the corresponding value at the given x.r5ri)r1r2r@)r=r<r;rCrDrGr8r1r2appendrArBrrE)r rFr>cdf_listZx_valZcdf_xZcdf_valr r r _cdfs z!DistributionFunctionFromFile._cdfcKsz|jdtkrFg}x|jD]}|||qWt||j|jd<t|dt |jdt| di}|S)zxCalculate and interpolate the inverse CDF, then return the corresponding parameter value at the given CDF value.rr) r=r<r;rJrLrArBlistkeysrrEvalues)r r>rKZx_valueZ cdfinv_valr r r _cdfinvs z$DistributionFunctionFromFile._cdfinv)NNN) r'r(r)r*r+rrGrIrLrP __classcell__r r )r?r rsr)r*rnumpyrZscipy.integrateZ integraterCZscipy.interpolateZ interpolaterAZpycbcrobjectrr__all__r r r r s   p^