B dn@sBdZddlZddlZddlZddlmZGdddeZdgZdS)z[ This modules provides classes for evaluating distributions based on a fixed set of points N) VARARGS_DELIMc@sJeZdZdZdZddZdddZdd Zd d Zd d Z e ddZ dS) FixedSamplesa A distribution consisting of a collection of a large number of fixed points. Only these values can be drawn from, so the number of points may need to be large to properly reflect the paramter space. This distribution is intended to aid in using nested samplers for semi-abitrary or complicated distributions where it is possible to provide or draw samples but less straightforward to provide an analytic invcdf. This class numerically approximates the invcdf for 1 or 2 dimensional distributions (but no higher). Parameters ---------- params : This of parameters this distribution should use samples : dict of arrays or FieldArray Sampled points of the distribution. May contain transformed parameters which are different from the original distribution. If so, an inverse mapping is provided to associate points with other parameters provided. Z fixed_samplescCs||_||_|j|d|_t|jdt|j|_|j|_|j|j|_tt |jt|jksnt t|dkrt ddS)Nrg?zBOnly one or two parameters supported for fixed sample distribution) paramssamplesp1lenfracargsortsortp1sortednumpyuniqueAssertionError ValueError)selfrrrm/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/pycbc/distributions/fixedsamples.py__init__/s  zFixedSamples.__init__c s.tjjdtj|dfddjDS)zDraw random valuer)highsizecsi|]}j||qSr)r).0p)irrr Asz$FixedSamples.rvs..)r randomrandintrrr)rrkwdsr)rrrrvs>szFixedSamples.rvscKsi}||jd}tt|t|j}|t|jkrDt|jd}|dkrPd}|j|||jd<}t|jdkrz|S||jd}t|j|d|j}t|j|d|j}||kr||}}tj |j ||dd} |j |jd} tj | | dd} | }tj | |dd} tt|t| } | t| krLt| d} | dkrZd} | | ||jd<tj |j| |dd} | | ||jd<|S)z(Map unit cube to parameters in the spacerr)Zndmin) rintroundrrr r searchsortedr arrayr rr )roriginalnewu1i1Zp1vu2lrregionp2Zp2parti2Zp1partrrrcdfinvCs:   zFixedSamples.cdfinvcKs|S)z' Apply boundary conditions (none here) r)rrrrrapply_boundary_conditionsksz&FixedSamples.apply_boundary_conditionscKsdS)z$ Dummy function, not the actual pdf rr)rrrrr__call__oszFixedSamples.__call__cs*ddlm}ddlm}m}m}ddlm}|t| |d|| |d|} d } ||| d} t | d kr|t d t d | djtt| d fd djjDd } ||| dt dkr d|gdGfddd|} | || j<|S)ak Return instance based on config file Return a new instance based on the config file. This will draw from a single distribution section provided in the config file and apply a single transformation section if desired. If a transformation is applied, an inverse mapping is also provided for use in the config file. r)read_distributions_from_config)read_transforms_from_configapply_transforms BaseTransform) transformssubnamez sample-sizez {}_sample)sectionrzLFixed sample distrubtion only supports a single distribution to sample from.z0Drawing samples for fixed sample distribution:%s)rcsi|]}||qSrr)rr)rrrrsz,FixedSamples.from_config..z {}_transformcs@eZdZZjZjZdZ Z e Z fddZ dS)z'FixedSamples.from_config..Thookrcs8tj|jfddjD}||S)Ncs i|]}|j|qSr)r )rr)idxrrrrrszEFixedSamples.from_config..Thook.transform..)r r"r p1nameoutputsZ format_output)rmapsout)r)r8rr transformsz1FixedSamples.from_config..Thook.transformN) __name__ __module__ __qualname__namer:Z_inputsinputsZ_outputsr9r r r r=r)rrrr6transrrThooksrD)Zpycbc.distributionsr1Zpycbc.transformsr2r3r4r5splitrZ get_opt_tagformatrrlogginginforr floatZdtypenamesrA)clscpr7tagr1r2r3r4Zglobal_transformsrZdistsecdistZtransecrDr)rrrr6rCr from_configss,            zFixedSamples.from_configN)r) r>r?r@__doc__rArrr.r/r0 classmethodrOrrrrrs (r) rPrGr Z numpy.randomZpycbcrobjectr__all__rrrrs