B â‹dEIã6@sþdZddlZddlZddlZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z dd lmZdd lmZGd d „d eƒZGd d„deƒZGdd„deƒZGdd„deƒZGdd„deƒZGdd„deƒZGdd„deƒZGdd„deƒZGdd„deƒZGdd„deƒZGdd „d eƒZGd!d"„d"eƒZGd#d$„d$eƒZGd%d&„d&eƒZGd'd(„d(eƒZ Gd)d*„d*eƒZ!Gd+d,„d,eƒZ"Gd-d.„d.eƒZ#Gd/d0„d0eƒZ$Gd1d2„d2eƒZ%Gd3d4„d4eƒZ&Gd5d6„d6e&ƒZ'Gd7d8„d8e&ƒZ(Gd9d:„d:eƒZ)Gd;d<„d„d>eƒZ+Gd?d@„d@e!ƒZ,GdAdB„dBe"ƒZ-e#e_.e%e_.e&e_.e'e_.e(e_.e)e_.e*e_.ee+_.e,e!_.e-e"_.ej/eej/ee#j/e#ej/ee$j/e$ej/ee%j/e%ej/ee&j/e&ej/ee'j/e'ej/ee(j/e(ej/eej/ee)j/e)ej/ee*j/e*e+j/e+ej/ee!j/e!e,j/e,e"j/e"e-j/e-ej/ee j/e ej/eiZ0eƒeƒee j1e j2e j3e j4e j5e j6ƒee j7e j8e j9e j:e j;e j<ƒeƒeƒe+ƒeƒgZ=dCdD„e=DƒZ>e> ?e&e j1e j2e j3e j4e j5e j6ƒe&e j7e j8e j9e j:e j;e j<ƒg¡e=e>Z@dQdEdF„ZAdRdHdI„ZBdSdJdK„ZCdLdM„ZDdTdOdP„ZEdS)UzJ This modules provides classes and functions for transforming parameters. éN)Ú conversions)Ú coordinates)Ú cosmology)Úrecord)Ú parameters)ÚBounds)Ú VARARGS_DELIM)Újframe_to_l0framec@sjeZdZdZdZdZgZgZdd„Zdd„Z dd„Z d d „Z d d „Z d d„Z edd„ƒZeddd„ƒZdS)Ú BaseTransformz=A base class for transforming between two sets of parameters.NcCst|jƒ|_t|jƒ|_dS)N)ÚsetÚ_inputsÚinputsÚ_outputsÚoutputs)Úself©rú]/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/pycbc/transforms.pyÚ__init__(s zBaseTransform.__init__cCs | |¡S)N)Ú transform)rÚmapsrrrÚ__call__,szBaseTransform.__call__cCs tdƒ‚dS)z0This function transforms from inputs to outputs.z Not added.N)ÚNotImplementedError)rrrrrr/szBaseTransform.transformcCs tdƒ‚dS)zgThe inverse conversions of transform. This function transforms from outputs to inputs. z Not added.N)r)rrrrrÚinverse_transform3szBaseTransform.inverse_transformcCs tdƒ‚dS)z6The Jacobian for the inputs to outputs transformation.z#Jacobian transform not implemented.N)r)rrrrrÚjacobian9szBaseTransform.jacobiancCs tdƒ‚dS)z6The Jacobian for the outputs to inputs transformation.z#Jacobian transform not implemented.N)r)rrrrrÚinverse_jacobian=szBaseTransform.inverse_jacobianc s t|tjƒrtˆ ¡}‡fdd„|Dƒ}xHt||ƒD]:\}}y| |g|g¡}Wq2tk rj|||<Yq2Xq2W|St|tƒr”| ¡}|  ˆ¡|St dƒ‚dS)aÓThis function takes the returned dict from `transform` and converts it to the same datatype as the input. Parameters ---------- old_maps : {FieldArray, dict} The mapping object to add new maps to. new_maps : dict A dict with key as parameter name and value is numpy.array. Returns ------- {FieldArray, dict} The old_maps object with new keys from new_maps. csg|] }ˆ|‘qSrr)Ú.0Úkey)Únew_mapsrrú Vsz/BaseTransform.format_output..z&Input type must be FieldArray or dict.N) Ú isinstancerÚ FieldArrayÚkeysÚzipÚ add_fieldsÚ ValueErrorÚdictÚcopyÚupdateÚ TypeError)Zold_mapsrr!ÚvaluesrÚvalsÚoutr)rrÚ format_outputAs   zBaseTransform.format_outputc Csô|}|dkrg}|dkri}n| ¡}t| t¡ƒ}dg|t| ¡ƒ}i}xd| d ||g¡¡D]L} | |krrqd| || |¡} y t | ƒ} Wnt k r YnX|  | | i¡qdW|  |¡|f|Ž} || j tƒksè| j |tƒkrðt dƒ‚| S)a­Initializes a transform from the given section. Parameters ---------- cp : pycbc.workflow.WorkflowConfigParser A parsed configuration file that contains the transform options. section : str Name of the section in the configuration file. outputs : str The names of the parameters that are output by this transformation, separated by `VARARGS_DELIM`. These must appear in the "tag" part of the section header. skip_opts : list, optional Do not read options in the given list. additional_opts : dict, optional Any additional arguments to pass to the class. If an option is provided that also exists in the config file, the value provided will be used instead of being read from the file. Returns ------- cls An instance of the class. NÚnameú-z:outputs of class do not match outputs specified in section) r&r ÚsplitrÚlistr!ÚoptionsÚjoinÚ get_opt_tagÚfloatr$r'r) ÚclsÚcpÚsectionrÚ skip_optsÚadditional_optsÚtagZ special_argsÚ extra_argsÚoptÚvalr+rrrÚ from_confighs0    zBaseTransform.from_config)NN)Ú__name__Ú __module__Ú __qualname__Ú__doc__r-Úinverser rrrrrrrÚ staticmethodr,Ú classmethodr>rrrrr s 'r c@sTeZdZdZdZddd„Zddd„Zd d „Zd d „Zd d„Z dd„Z e dd„ƒZ dS)ÚCustomTransformaAllows for any transform to be defined. Parameters ---------- input_args : (list of) str The names of the input parameters. output_args : (list of) str The names of the output parameters. transform_functions : dict Dictionary mapping input args to a string giving a function call; e.g., ``{'q': 'q_from_mass1_mass2(mass1, mass2)'}``. jacobian : str, optional String giving a jacobian function. The function must be in terms of the input arguments. Examples -------- Create a custom transform that converts mass1, mass2 to mtotal, q: >>> t = transforms.CustomTransform(['mass1', 'mass2'], ['mtotal', 'q'], {'mtotal': 'mass1+mass2', 'q': 'mass1/mass2'}, '(mass1 + mass2) / mass2**2') Evaluate a pair of masses: >>> t.transform({'mass1': 10., 'mass2': 5.}) {'mass1': 10.0, 'mass2': 5.0, 'mtotal': 15.0, 'q': 2.0} The Jacobian for the same pair of masses: >>> t.jacobian({'mass1': 10., 'mass2': 5.}) 0.59999999999999998 ZcustomNcCsLt|tƒr|g}t|tƒr |g}t|ƒ|_t|ƒ|_||_||_| ¡dS)N)rÚstrr r rÚtransform_functionsÚ _jacobianÚ_createscratch)rZ input_argsZ output_argsrHrrrrrÇs    zCustomTransform.__init__écCs tj|dd„|jDƒd|_dS)z3Creates a scratch FieldArray to use for transforms.cSsg|] }|tf‘qSr)r4)rÚprrrrÙsz2CustomTransform._createscratch..)ÚdtypeN)rr r Ú_scratch)rÚshaperrrrJÖszCustomTransform._createscratchcCs¢y*x$|jD]}|||j|dd…<q WWnrtk rœ|t|jƒd}t|tjƒr`|j}nt|ƒ}|  |¡x$|jD]}|||j|dd…<qzWYnXdS)z¹Copies the data in maps to the scratch space. If the maps contain arrays that are not the same shape as the scratch space, a new scratch space will be created. Nr) r rNr$r0rÚnumpyÚndarrayrOÚlenrJ)rrrLÚinvalsrOrrrÚ_copytoscratchÜs    zCustomTransform._copytoscratchcCs6|t|jƒd}t|tjtfƒs(d}n tddƒ}|S)z9Determines how to slice the scratch for returning values.rN)r0r rrPrQÚslice)rrrSÚgetslicerrrÚ _getsliceòs  zCustomTransform._getslicecsLˆjdkrtdƒ‚ˆ |¡ˆ |¡‰‡‡fdd„ˆj ¡Dƒ}ˆ ||¡S)axApplies the transform functions to the given maps object. Parameters ---------- maps : dict, or FieldArray Returns ------- dict or FieldArray A map object containing the transformed variables, along with the original variables. The type of the output will be the same as the input. Nz!no transform function(s) providedcs i|]\}}ˆj|ˆ|“qSr)rN)rrLÚfunc)rVrrrú sz-CustomTransform.transform..)rHrrTrWÚitemsr,)rrr+r)rVrrrûs    zCustomTransform.transformcCsF|jdkrtdƒ‚| |¡|j|j}t|tjƒrB|| |¡}|S)Nzno jacobian provided)rIrrTrNrrPrQrW)rrr+rrrrs    zCustomTransform.jacobianc Cs”|}t| t¡ƒ}ttj| |d|¡ d¡ƒ}i}x"|D]}| |||¡}|||<q8Wd ||g¡} | | d¡r€| |d|¡} nd} ||||| dS)aLLoads a CustomTransform from the given config file. Example section: .. code-block:: ini [{section}-outvar1+outvar2] name = custom inputs = inputvar1, inputvar2 outvar1 = func1(inputs) outvar2 = func2(inputs) jacobian = func(inputs) r ú,r.rN)r) r r/rÚmaprGÚstripr3r2Ú has_option) r5r6r7rr:r rHÚvarrXÚsrrrrr> s   zCustomTransform.from_config)N)rK) r?r@rArBr-rrJrTrWrrrEr>rrrrrF£s     rFcsFeZdZdZdZd‡fdd„ Zdd„Zdd „Zd d „Zd d „Z ‡Z S)ÚMchirpQToMass1Mass2z7Converts chirp mass and mass ratio to component masses.Zmchirp_q_to_mass1_mass2Ncs~|dkrtj}|dkrtj}|dkr*tj}|dkr8tj}||_||_||_||_|j|jg|_ |j|jg|_ t t |ƒ  ¡dS)N)rÚmass1Úmass2ÚmchirpÚqÚ mass1_paramÚ mass2_paramÚ mchirp_paramÚq_paramr rÚsuperrar)rrfrgrhri)Ú __class__rrrOszMchirpQToMass1Mass2.__init__cCsLi}t ||j||j¡||j<t ||j||j¡||j<| ||¡S)aÕThis function transforms from chirp mass and mass ratio to component masses. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy >>> from pycbc import transforms >>> t = transforms.MchirpQToMass1Mass2() >>> t.transform({'mchirp': numpy.array([10.]), 'q': numpy.array([2.])}) {'mass1': array([ 16.4375183]), 'mass2': array([ 8.21875915]), 'mchirp': array([ 10.]), 'q': array([ 2.])} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. )rZmass1_from_mchirp_qrhrirfZmass2_from_mchirp_qrgr,)rrr+rrrrbs zMchirpQToMass1Mass2.transformcCsDi}||j}||j}t ||¡||j<||||j<| ||¡S)aÛThis function transforms from component masses to chirp mass and mass ratio. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy >>> from pycbc import transforms >>> t = transforms.MchirpQToMass1Mass2() >>> t.inverse_transform({'mass1': numpy.array([16.4]), 'mass2': numpy.array([8.2])}) {'mass1': array([ 16.4]), 'mass2': array([ 8.2]), 'mchirp': array([ 9.97717521]), 'q': 2.0} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. )rfrgrÚmchirp_from_mass1_mass2rhrir,)rrr+Úm1Úm2rrrr„s   z%MchirpQToMass1Mass2.inverse_transformcCs,||j}||j}|d||ddS)zWReturns the Jacobian for transforming mchirp and q to mass1 and mass2. gð?g@gš™™™™™Ù?)rhri)rrrdrerrrr¤s  zMchirpQToMass1Mass2.jacobiancCs(||j}||j}t ||¡|dS)zWReturns the Jacobian for transforming mass1 and mass2 to mchirp and q. g@)rfrgrrl)rrrmrnrrrr¬s  z$MchirpQToMass1Mass2.inverse_jacobian)NNNN) r?r@rArBr-rrrrrÚ __classcell__rr)rkrraJs" rac@sLeZdZdZdZejejgZej ej gZ dd„Z dd„Z dd„Zd d „Zd S) ÚMchirpEtaToMass1Mass2zAConverts chirp mass and symmetric mass ratio to component masses.Zmchirp_eta_to_mass1_mass2cCsLi}t |tj|tj¡|tj<t |tj|tj¡|tj<| ||¡S)aéThis function transforms from chirp mass and symmetric mass ratio to component masses. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy >>> from pycbc import transforms >>> t = transforms.MchirpEtaToMass1Mass2() >>> t.transform({'mchirp': numpy.array([10.]), 'eta': numpy.array([0.25])}) {'mass1': array([ 16.4375183]), 'mass2': array([ 8.21875915]), 'mchirp': array([ 10.]), 'eta': array([ 0.25])} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. ) rÚmass1_from_mchirp_etarrdÚetarbÚmass2_from_mchirp_etarcr,)rrr+rrrr¼s zMchirpEtaToMass1Mass2.transformcCsHi}|tj}|tj}t ||¡|tj<t ||¡|tj<| ||¡S)aæThis function transforms from component masses to chirp mass and symmetric mass ratio. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy >>> from pycbc import transforms >>> t = transforms.MchirpQToMass1Mass2() >>> t.inverse_transform({'mass1': numpy.array([8.2]), 'mass2': numpy.array([8.2])}) {'mass1': array([ 8.2]), 'mass2': array([ 8.2]), 'mchirp': array([ 9.97717521]), 'eta': 0.25} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. ) rrbrcrrlrdÚeta_from_mass1_mass2rrr,)rrr+rmrnrrrrÞs   z'MchirpEtaToMass1Mass2.inverse_transformcCsD|tj}|tj}t ||¡}t ||¡}|||||dS)zYReturns the Jacobian for transforming mchirp and eta to mass1 and mass2. é)rrdrrrrqrs)rrrdrrrmrnrrrrþs     zMchirpEtaToMass1Mass2.jacobiancCs<|tj}|tj}t ||¡}t ||¡}d||dS)zYReturns the Jacobian for transforming mass1 and mass2 to mchirp and eta. gð¿g333333ó?)rrbrcrrlrt)rrrmrnrdrrrrrrs     z&MchirpEtaToMass1Mass2.inverse_jacobianN)r?r@rArBr-rrdrrr rbrcrrrrrrrrrrpµs  "  rpc@sReZdZdZdZejejgZej gZ ddd„Z dd„Z dd „Z d d „Zd d „ZdS)ÚChirpDistanceToDistancezEConverts chirp distance to luminosity distance, given the chirp mass.Zchirp_distance_to_distanceçffffffö?cCs"t|jƒ|_t|jƒ|_||_dS)N)r r r rrÚref_mass)rrxrrrrs  z ChirpDistanceToDistance.__init__cCs4i}tj|tj|tj|jd|tj<| ||¡S)aßThis function transforms from chirp distance to luminosity distance, given the chirp mass. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy as np >>> from pycbc import transforms >>> t = transforms.ChirpDistanceToDistance() >>> t.transform({'chirp_distance': np.array([40.]), 'mchirp': np.array([1.2])}) {'mchirp': array([ 1.2]), 'chirp_distance': array([ 40.]), 'distance': array([ 39.48595679])} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. )rx)rZ#distance_from_chirp_distance_mchirprÚchirp_distancerdrxÚdistancer,)rrr+rrrrs z!ChirpDistanceToDistance.transformcCs4i}tj|tj|tj|jd|tj<| ||¡S)aáThis function transforms from luminosity distance to chirp distance, given the chirp mass. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy as np >>> from pycbc import transforms >>> t = transforms.ChirpDistanceToDistance() >>> t.inverse_transform({'distance': np.array([40.]), 'mchirp': np.array([1.2])}) {'distance': array([ 40.]), 'chirp_distance': array([ 40.52073522]), 'mchirp': array([ 1.2])} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. )rx)rryrrzrdrxr,)rrr+rrrr?s z)ChirpDistanceToDistance.inverse_transformcCsd}|d}d|j|dS)zsReturns the Jacobian for transforming chirp distance to luminosity distance, given the chirp mass. gffffffö?rdg áÛÚŒÛë?g«ªªªªªê¿)rx)rrrxrdrrrr]sz ChirpDistanceToDistance.jacobiancCsd}|d}d|j|dS)zsReturns the Jacobian for transforming luminosity distance to chirp distance, given the chirp mass. gffffffö?rdg áÛÚŒÛë?g«ªªªªªê?)rx)rrrxrdrrrresz(ChirpDistanceToDistance.inverse_jacobianN)rw)r?r@rArBr-rryrdr rzrrrrrrrrrrrvs   rvc szeZdZdZdZejejejej ej ej ej ej ejejdg Zejejejej ej ej ej gZ‡fdd„Zdd„Z‡ZS)ÚAlignTotalSpinzgConverts angles from total angular momentum J frame to orbital angular momentum L (waveform) frameZalign_total_spinÚphi_refcs*t|jƒ|_t|jƒ|_tt|ƒ ¡dS)N)r r r rrrjr{r)r)rkrrr{s  zAlignTotalSpin.__init__c sNtˆtƒrtjjfˆŽ‰‡fdd„|jDƒ}ˆjt t ˆƒ¡gt |ƒ|d}xú|D]ò}t dd„|t j |t j |t j|t jgDƒƒs6t |t j |t j |t j¡\}}}t |t j|t j|t j¡\}} } t|t j|t j|t j|d|t jtj|||| || d } x,| D]} | | || <qWqT|t j|t j<qTW|S)a\ Rigidly rotate binary so that the total angular momentum has the given inclination (iota) instead of the orbital angular momentum. Return the new inclination, s1, and s2. s1 and s2 are dimensionless spin. Note: the spins are assumed to be given in the frame defined by the orbital angular momentum. csg|]}|ˆjkr|‘qSr)Ú fieldnames)rÚn)rrrr‹sz,AlignTotalSpin.transform..)Únamescss|]}|dkVqdS)gNr)rr`rrrú sz+AlignTotalSpin.transform..r|)ZphirefÚthetajnZphijlÚspin1_aÚspin2_aÚ spin1_polarÚ spin2_polarZspin12_deltaphi)rr%rr Z from_kwargsrr#rPZzerosrRÚallrÚspin1xÚspin1yÚspin2xÚspin2yrÚcartesian_to_sphericalÚspin1zÚspin2zr rbrcÚf_refrÚpiÚ inclination) rrZ newfieldsZnewmapsÚitemZs1_aZs1_azZs1_polZs2_aZs2_azZs2_polr+rr)rrr€s>    zAlignTotalSpin.transform)r?r@rArBr-rrr‡rˆrŒr‰rŠrrbrcrŽr rrrrrorr)rkrr{ns       r{cs4eZdZdZdZ‡fdd„Zdd„Zdd„Z‡ZS) ÚSphericalToCartesiana¤Converts spherical coordinates to cartesian. Parameters ---------- x : str The name of the x parameter. y : str The name of the y parameter. z : str The name of the z parameter. radial : str The name of the radial parameter. azimuthal : str The name of the azimuthal angle parameter. polar : str The name of the polar angle parameter. Úspherical_to_cartesiancsZ||_||_||_||_||_||_|j|j|jg|_|j|j|jg|_tt |ƒ  ¡dS)N) ÚxÚyÚzÚradialÚpolarÚ azimuthalr rrjr’r)rr”r•r–r—r™r˜)rkrrrÆszSphericalToCartesian.__init__c CsT|j}|j}|j}t ||||||¡\}}}|j||j||j|i}| ||¡S)a€This function transforms from spherical to cartesian spins. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy >>> from pycbc import transforms >>> t = transforms.SphericalToCartesian('x', 'y', 'z', 'a', 'phi', 'theta') >>> t.transform({'a': numpy.array([0.1]), 'phi': numpy.array([0.1]), 'theta': numpy.array([0.1])}) {'a': array([ 0.1]), 'phi': array([ 0.1]), 'theta': array([ 0.1]), 'x': array([ 0.00993347]), 'y': array([ 0.00099667]), 'z': array([ 0.09950042])} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. ) r—r™r˜rr“r”r•r–r,) rrÚaÚazÚpor”r•r–r+rrrrÑs  zSphericalToCartesian.transformc CsT|j}|j}|j}t ||||||¡\}}}|j||j||j|i}| ||¡S)a2This function transforms from cartesian to spherical spins. Parameters ---------- maps : a mapping object Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. ) r”r•r–rr‹r—r™r˜r,) rrr”r•r–ršr›rœr+rrrrós  z&SphericalToCartesian.inverse_transform) r?r@rArBr-rrrrorr)rkrr’±s  "r’cs$eZdZdZdZ‡fdd„Z‡ZS)ÚSphericalSpin1ToCartesianSpin1aEConverts spherical spin parameters (radial and two angles) to catesian spin parameters. This class only transforms spsins for the first component mass. **Deprecation Warning:** This will be removed in a future update. Use :py:class:`SphericalToCartesian` with spin-parameter names passed in instead. Z$spherical_spin_1_to_cartesian_spin_1cs4t d |jtj¡¡tt|ƒ dddddd¡dS)Nz´Deprecation warning: the {} transform will be removed in a future update. Please use {} instead, passing spin1x, spin1y, spin1z, spin1_a, spin1_azimuthal, spin1_polar as arguments.r‡rˆrŒr‚Úspin1_azimuthalr„)ÚloggingÚwarningÚformatr-r’rjrr)r)rkrrrs  z'SphericalSpin1ToCartesianSpin1.__init__)r?r@rArBr-rrorr)rkrrsrcs$eZdZdZdZ‡fdd„Z‡ZS)ÚSphericalSpin2ToCartesianSpin2aEConverts spherical spin parameters (radial and two angles) to catesian spin parameters. This class only transforms spsins for the first component mass. **Deprecation Warning:** This will be removed in a future update. Use :py:class:`SphericalToCartesian` with spin-parameter names passed in instead. Z$spherical_spin_2_to_cartesian_spin_2cs4t d |jtj¡¡tt|ƒ dddddd¡dS)Nz´Deprecation warning: the {} transform will be removed in a future update. Please use {} instead, passing spin2x, spin2y, spin2z, spin2_a, spin2_azimuthal, spin2_polar as arguments.r‰rŠrrƒÚspin2_azimuthalr…)rŸr r¡r-r’rjr¢r)r)rkrrr/s  z'SphericalSpin2ToCartesianSpin2.__init__)r?r@rArBr-rrorr)rkrr¢#sr¢c@s0eZdZdZdZdZejgZej gZ dd„Z dS)ÚDistanceToRedshiftzConverts distance to redshift.Zdistance_to_redshiftNcCs"tjt |tj¡i}| ||¡S)akThis function transforms from distance to redshift. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: >>> import numpy >>> from pycbc import transforms >>> t = transforms.DistanceToRedshift() >>> t.transform({'distance': numpy.array([1000])}) {'distance': array([1000]), 'redshift': 0.19650987609144363} Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. )rÚredshiftrrzr,)rrr+rrrrFszDistanceToRedshift.transform) r?r@rArBr-rCrrzr r¥rrrrrrr¤>s r¤c@sJeZdZdZdZejejejdgZ ejejej ej gZ dd„Z dd„ZdS) ÚAlignedMassSpinToCartesianSpinz7Converts mass-weighted spins to cartesian z-axis spins.Z#aligned_mass_spin_to_cartesian_spinÚchi_acCsd|tj}|tj}i}t |||tj|d¡|tj<t |||tj|d¡|tj<|  ||¡S)aeThis function transforms from aligned mass-weighted spins to cartesian spins aligned along the z-axis. Parameters ---------- maps : a mapping object Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. r§) rrbrcrZ%spin1z_from_mass1_mass2_chi_eff_chi_aÚchi_effrŒZ%spin2z_from_mass1_mass2_chi_eff_chi_arr,)rrrbrcr+rrrrms  z(AlignedMassSpinToCartesianSpin.transformc CsZ|tj}|tj}|tj}|tj}tjt ||||¡dt ||||¡i}| ||¡S)a…This function transforms from component masses and cartesian spins to mass-weighted spin parameters aligned with the angular momentum. Parameters ---------- maps : a mapping object Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. r§) rrbrŒrcrr¨rr§r,)rrrbrŒrcrr+rrrr†s    z0AlignedMassSpinToCartesianSpin.inverse_transformN)r?r@rArBr-rrbrcr¨r rŒrrrrrrrrr¦asr¦c@sTeZdZdZdZejejddddgZejejej ej ej ej gZ dd„Zd d „Zd S) Ú!PrecessionMassSpinToCartesianSpinz:Converts mass-weighted spins to cartesian x-y plane spins.Z&precession_mass_spin_to_cartesian_spinÚxi1Úxi2Úphi_aÚphi_scCsèt |d|d¡}t |d|d¡}t |d|d|d|d¡}t |d|d|d|d¡}t ||d|d¡}t ||d|d¡}t ||||d|d¡}t ||||d|d¡} i} t |t j ƒrxt t j |d|dgƒ\} } | | k} | | k}t  || ||f¡| tj<t  || | |f¡| tj<t  |||| f¡| tj<t  |||| f¡| tj<nd|d|dkr´|| tj<|| tj<|| tj<| | tj<n(|| tj<| | tj<|| tj<|| tj<| || ¡S)aUThis function transforms from mass-weighted spins to caretsian spins in the x-y plane. Parameters ---------- maps : a mapping object Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. rbrcrªr«r¬r­)rZ primary_massZsecondary_massZ primary_spinZsecondary_spinZspin1x_from_xi1_phi_a_phi_sZspin1y_from_xi1_phi_a_phi_sZ'spin2x_from_mass1_mass2_xi2_phi_a_phi_sZ'spin2y_from_mass1_mass2_xi2_phi_a_phi_srrPrQr\ÚarrayÚ concatenaterr‡rˆr‰rŠr,)rrZm_pZm_sZxi_pZxi_sZspinx_pZspiny_pZspinx_sZspiny_sr+rbrcÚmask_mass1_gte_mass2Úmask_mass1_lt_mass2rrrr¯sJ        z+PrecessionMassSpinToCartesianSpin.transformc Csi}t |tj|tj|tj|tj|tj|tj¡}t  |tj|tj|tj|tj|tj|tj¡}t  |tj|tj|tj|tj|tj|tj¡|d<t  |tj|tj|tj|tj¡|d<t |t jƒrPtt j|tj|tjgƒ\}}||k}||k}t  ||||f¡|d<t  ||||f¡|d<n4|d|dkrt||d<||d<n||d<||d<| ||¡S)a‹This function transforms from component masses and cartesian spins to mass-weighted spin parameters perpendicular with the angular momentum. Parameters ---------- maps : a mapping object Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. r¬r­rªr«rbrc)rZ primary_xirrbrcr‡rˆr‰rŠZ secondary_xir¬r­rrPrQr\r®r¯r,) rrr+rªr«rbrcr°r±rrrrùsT   z3PrecessionMassSpinToCartesianSpin.inverse_transformN)r?r@rArBr-rrbrcr r‡rˆr‰rŠrrrrrrrr© s Jr©c@s>eZdZdZdZejejejej ej ej gZ dgZ dd„ZdS)ÚCartesianSpinToChiPz$Converts cartesian spins to `chi_p`.Úcartesian_spin_to_chi_pÚchi_pc CsLi}t |tj|tj|tj|tj|tj|tj¡|d<|  ||¡S)a•This function transforms from component masses and caretsian spins to chi_p. Parameters ---------- maps : a mapping object Examples -------- Convert a dict of numpy.array: Returns ------- out : dict A dict with key as parameter name and value as numpy.array or float of transformed values. r´) rr´rrbrcr‡rˆr‰rŠr,)rrr+rrrrNszCartesianSpinToChiP.transformN)r?r@rArBr-rrbrcr‡rˆr‰rŠr rrrrrrr²@sr²cs’eZdZdZdZd‡fdd„ Zedd„ƒZed d „ƒZed d „ƒZ ed d„ƒZ edd„ƒZ edd„ƒZ e dd„ƒZdd„Ze‡fdd„ƒZ‡ZS)ÚLambdaFromTOVFilea Transforms mass values corresponding to Lambda values for a given EOS interpolating from the mass-Lambda data for that EOS read in from an external ASCII file. The interpolation of the mass-Lambda data is a one-dimensional piecewise linear interpolation. If the ``redshift_mass`` keyword argument is ``True`` (the default), the mass values to be transformed are assumed to be detector frame masses. In that case, a distance should be provided along with the mass for transformation to the source frame mass before the Lambda values are extracted from the interpolation. If the transform is read in from a config file, an example code block would be: .. code-block:: ini [{section}-lambda1] name = lambda_from_tov_file mass_param = mass1 lambda_param = lambda1 distance = 40 mass_lambda_file = {filepath} If this transform is used in a parameter estimation analysis where distance is a variable parameter, the distance to be used will vary with each draw. In that case, the example code block will be: .. code-block:: ini [{section}-lambda1] name = lambda_from_tov_file mass_param = mass1 lambda_param = lambda1 mass_lambda_file = filepath If your prior is in terms of the source-frame masses (``srcmass``), then you can shut off the redshifting by adding ``do-not-redshift-mass`` to the config file. In this case you do not need to worry about a distance. Example: .. code-block:: ini [{section}-lambda1] name = lambda_from_tov_file mass_param = srcmass1 lambda_param = lambda1 mass_lambda_file = filepath do-not-redshift-mass = Parameters ---------- mass_param : str The name of the mass parameter to transform. lambda_param : str The name of the tidal deformability parameter that mass_param is to be converted to interpolating from the data in the mass-Lambda file. mass_lambda_file : str Path of the mass-Lambda data file. The first column in the data file should contain mass values, and the second column Lambda values. distance : float, optional The distance (in Mpc) of the source. Used to redshift the mass. Needed if ``redshift_mass`` is True and no distance parameter exists If None, then a distance must be provided to the transform. redshift_mass : bool, optional Redshift the mass parameters when computing the lambdas. Default is False. file_columns : list of str, optional The names and order of columns in the ``mass_lambda_file``. Must contain at least 'mass' and 'lambda'. If not provided, will assume the order is ('mass', 'lambda'). Zlambda_from_tov_fileNTc sv||_||_||_||_||_|dg|_|g|_|dkr@ddg}dd„|Dƒ}tj|j|d}||_ t t |ƒ  ¡dS)NrzÚmassÚlambdacSsg|] }|tf‘qSr)r4)rÚfnamerrrrÇsz.LambdaFromTOVFile.__init__..)rM) Z_mass_lambda_fileÚ _mass_paramÚ _lambda_paramÚ redshift_massÚ _distancer rrPZloadtxtÚ_datarjrµr) rÚ mass_paramÚ lambda_paramÚmass_lambda_filerzr»Ú file_columnsrMÚdata)rkrrrµs  zLambdaFromTOVFile.__init__cCs|jS)z!Returns the input mass parameter.)r¹)rrrrr¾ÌszLambdaFromTOVFile.mass_paramcCs|jS)z$Returns the output lambda parameter.)rº)rrrrr¿ÑszLambdaFromTOVFile.lambda_paramcCs|jS)N)r½)rrrrrÂÖszLambdaFromTOVFile.datacCs |jdS)zVReturns the mass data read from the mass-Lambda data file for an EOS. r¶)r½)rrrrÚ mass_dataÚszLambdaFromTOVFile.mass_datacCs |jdS)zXReturns the Lambda data read from the mass-Lambda data file for an EOS. r·)r½)rrrrÚ lambda_dataászLambdaFromTOVFile.lambda_datacCs|jS)zxReturns the fixed distance to transform mass samples from detector to source frame if one is specified. )r¼)rrrrrzèszLambdaFromTOVFile.distancecCs$|| ¡krd}nt |||¡}|S)aèReturns Lambda corresponding to a given mass interpolating from the TOV data. Parameters ---------- m : float Value of the mass. mass_data : array Mass array from the Lambda-M curve of an EOS. lambda_data : array Lambda array from the Lambda-M curve of an EOS. Returns ------- lambdav : float The Lambda corresponding to the mass `m` for the EOS considered. g)ÚmaxrPZinterp)Zm_srcrÃrÄZlambdavrrrÚlambda_from_tov_dataïs z&LambdaFromTOVFile.lambda_from_tov_datac Cs¬||j}|jrx|jdk r"|j}n>y |d}Wn0tk r^}zt d¡|‚Wdd}~XYnXddt t|ƒ¡}nd}|j |  |||j d|j d¡i}|  ||¡S)aÚComputes the transformation of mass to Lambda. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- out : dict or FieldArray A map between the transformed variable name and value(s), along with the original variable name and value(s). Nrzz™Either provide distance samples in the list of samples to be transformed, or provide a fixed distance value as input when initializing LambdaFromTOVFile.gð?r¶r·) r¹r»r¼ÚKeyErrorrŸr rr¥ÚabsrºrÆr½r,)rrÚmÚdÚeÚshiftr+rrrr s   zLambdaFromTOVFile.transformcsH| d ||g¡d¡r&ddi}dg}nd}d}tt|ƒj|||||dS)Nr.zdo-not-redshift-massr»F)r8r9)r^r2rjrµr>)r5r6r7rr9r8)rkrrr>1s zLambdaFromTOVFile.from_config)NTN)r?r@rArBr-rÚpropertyr¾r¿rÂrÃrÄrzrDrÆrrEr>rorr)rkrrµlsE       (rµcsveZdZdZdZd‡fdd„ Zedd„ƒZed d „ƒZed d „ƒZ ed d„ƒZ dd„Z dd„Z e ‡fdd„ƒZ‡ZS)ÚLambdaFromMultipleTOVFilesa‹Uses multiple equation of states. Parameters ---------- mass_param : str The name of the mass parameter to transform. lambda_param : str The name of the tidal deformability parameter that mass_param is to be converted to interpolating from the data in the mass-Lambda file. mass_lambda_file : str Path of the mass-Lambda data file. The first column in the data file should contain mass values, and the second column Lambda values. distance : float, optional The distance (in Mpc) of the source. Used to redshift the mass. If None, then a distance must be provided to the transform. file_columns : list of str, optional The names and order of columns in the ``mass_lambda_file``. Must contain at least 'mass' and 'lambda'. If not provided, will assume the order is ('radius', 'mass', 'lambda'). Zlambda_from_multiple_tov_filesNTc s¾||_||_||_||_||_|ddg|_|g|_i|_t|jdƒJ}xB|D]:}|  d¡} t t j   | ¡ d¡dƒ} t j  | ¡|j| <qLWWdQRXi|_|dkr¦d}||_tt|ƒ ¡dS)NÚeosrzÚrÚ Ú.r)Zradiusr¶r·)Ú _map_filer¹rºr¼r»r rÚ _eos_filesÚopenÚrstripÚintÚosÚpathÚbasenamer/ÚabspathÚ _eos_cacheÚ _file_columnsrjrÎr) rr¾r¿Úmap_filerzr»rÁÚfpÚliner¸Zeosidx)rkrrrWs$     z#LambdaFromMultipleTOVFiles.__init__cCs|jS)z!Returns the input mass parameter.)r¹)rrrrr¾usz%LambdaFromMultipleTOVFiles.mass_paramcCs|jS)z$Returns the output lambda parameter.)rº)rrrrr¿zsz'LambdaFromMultipleTOVFiles.lambda_paramcCs|jS)zVReturns the mass data read from the mass-Lambda data file for an EOS. )rÓ)rrrrrÞsz#LambdaFromMultipleTOVFiles.map_filecCs|jS)zxReturns the fixed distance to transform mass samples from detector to source frame if one is specified. )r¼)rrrrrz†sz#LambdaFromMultipleTOVFiles.distancec Csxy|j|}Wndtk rry6|j|}t|j|j||j|j|jd}||j|<Wntk rld}YnXYnX|S)z^Gets the EOS for the given index. If the index is not in range returns None. )r¾r¿rÀrzr»rÁN) rÜrÇrÔrµr¹rºr¼r»rÝ)rÚ eos_indexrÏr¸rrrÚget_eoss   z"LambdaFromMultipleTOVFiles.get_eoscCsN||j}t|dƒ}| |¡}|dk r2| |¡S|jtji}| ||¡SdS)z7Transforms mass value and eos index into a lambda valuerÏN)r¹r×rârrºrPÚnanr,)rrrÉrárÏr+rrrr¤s     z$LambdaFromMultipleTOVFiles.transformcsH| d ||g¡d¡r&ddi}dg}nd}d}tt|ƒj|||||dS)Nr.zdo-not-redshift-massr»F)r8r9)r^r2rjrÎr>)r5r6r7rr9r8)rkrrr>±s z&LambdaFromMultipleTOVFiles.from_config)NTN)r?r@rArBr-rrÍr¾r¿rÞrzrârrEr>rorr)rkrrÎ?s     rÎcs\eZdZdZdZ‡fdd„Zedd„ƒZedd„ƒZd d „Z d d „Z d d„Z dd„Z ‡Z S)ÚLoga.Applies a log transform from an `inputvar` parameter to an `outputvar` parameter. This is the inverse of the exponent transform. Parameters ---------- inputvar : str The name of the parameter to transform. outputvar : str The name of the transformed parameter. Úlogcs.||_||_|g|_|g|_tt|ƒ ¡dS)N)Ú _inputvarÚ _outputvarr rrjrär)rÚinputvarÚ outputvar)rkrrrÍs z Log.__init__cCs|jS)zReturns the input parameter.)ræ)rrrrrèÔsz Log.inputvarcCs|jS)zReturns the output parameter.)rç)rrrrréÙsz Log.outputvarcCs&||j}|jt |¡i}| ||¡S)aÅComputes :math:`\log(x)`. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- out : dict or FieldArray A map between the transformed variable name and value(s), along with the original variable name and value(s). )rærçrPrår,)rrr”r+rrrrÞs z Log.transformcCs&||j}|jt |¡i}| ||¡S)aÇComputes :math:`y = e^{x}`. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- out : dict or FieldArray A map between the transformed variable name and value(s), along with the original variable name and value(s). )rçrærPÚexpr,)rrr•r+rrrrñs zLog.inverse_transformcCs||j}d|S)aÞComputes the Jacobian of :math:`y = \log(x)`. This is: .. math:: \frac{\mathrm{d}y}{\mathrm{d}x} = \frac{1}{x}. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- float The value of the jacobian at the given point(s). gð?)ræ)rrr”rrrrs z Log.jacobiancCs||j}t |¡S)aÖComputes the Jacobian of :math:`y = e^{x}`. This is: .. math:: \frac{\mathrm{d}y}{\mathrm{d}x} = e^{x}. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- float The value of the jacobian at the given point(s). )rçrPrê)rrr”rrrrs zLog.inverse_jacobian)r?r@rArBr-rrÍrèrérrrrrorr)rkrrä¿s    räcs˜eZdZdZdZd‡fdd„ Zedd„ƒZedd „ƒZed d „ƒZ e ddd„ƒZ e ddd„ƒZ dd„Z dd„Zdd„Zdd„Zed ‡fdd„ ƒZ‡ZS)!ÚLogitaApplies a logit transform from an `inputvar` parameter to an `outputvar` parameter. This is the inverse of the logistic transform. Typically, the input of the logit function is assumed to have domain :math:`\in (0, 1)`. However, the `domain` argument can be used to expand this to any finite real interval. Parameters ---------- inputvar : str The name of the parameter to transform. outputvar : str The name of the transformed parameter. domain : tuple or distributions.bounds.Bounds, optional The domain of the input parameter. Can be any finite interval. Default is (0., 1.). Úlogit©ggð?cs\||_||_|g|_|g|_t|d|dddd|_|d|_|d|_tt |ƒ  ¡dS)NrrKrÕ)Z btype_minZ btype_max) rærçr rrÚ_boundsÚ_aÚ_brjrër)rrèréÚdomain)rkrrrHs   zLogit.__init__cCs|jS)zReturns the input parameter.)ræ)rrrrrèTszLogit.inputvarcCs|jS)zReturns the output parameter.)rç)rrrrréYszLogit.outputvarcCs|jS)z*Returns the domain of the input parameter.)rî)rrrrÚbounds^sz Logit.boundsççð?cCst ||¡t ||¡S)a„Computes the logit function with domain :math:`x \in (a, b)`. This is given by: .. math:: \mathrm{logit}(x; a, b) = \log\left(\frac{x-a}{b-x}\right). Note that this is also the inverse of the logistic function with range :math:`(a, b)`. Parameters ---------- x : float The value to evaluate. a : float, optional The minimum bound of the domain of x. Default is 0. b : float, optional The maximum bound of the domain of x. Default is 1. Returns ------- float The logit of x. )rPrå)r”ršÚbrrrrìcsz Logit.logitcCst |¡}|||d|S)a¿Computes the logistic function with range :math:`\in (a, b)`. This is given by: .. math:: \mathrm{logistic}(x; a, b) = \frac{a + b e^x}{1 + e^x}. Note that this is also the inverse of the logit function with domain :math:`(a, b)`. Parameters ---------- x : float The value to evaluate. a : float, optional The minimum bound of the range of the logistic function. Default is 0. b : float, optional The maximum bound of the range of the logistic function. Default is 1. Returns ------- float The logistic of x. gð?)rPrê)r”ršrõÚexpxrrrÚlogistic€s zLogit.logisticcCsZ||j}|j |¡}t|tjƒr*| ¡}|s6tdƒ‚|j|  ||j |j ¡i}|  ||¡S)a$Computes :math:`\mathrm{logit}(x; a, b)`. The domain :math:`a, b` of :math:`x` are given by the class's bounds. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- out : dict or FieldArray A map between the transformed variable name and value(s), along with the original variable name and value(s). z$one or more values are not in bounds) rærîÚ __contains__rrPrQr†r$rçrìrïrðr,)rrr”Úisinr+rrrr s   zLogit.transformcCs.||j}|j| ||j|j¡i}| ||¡S)a,Computes :math:`y = \mathrm{logistic}(x; a,b)`. The codomain :math:`a, b` of :math:`y` are given by the class's bounds. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- out : dict or FieldArray A map between the transformed variable name and value(s), along with the original variable name and value(s). )rçrær÷rïrðr,)rrr•r+rrrr»s zLogit.inverse_transformcCsf||j}|j |¡}t|tjƒr4| ¡s4tdƒ‚n|sFtd |¡ƒ‚|j |j ||j |j |S)aComputes the Jacobian of :math:`y = \mathrm{logit}(x; a,b)`. This is: .. math:: \frac{\mathrm{d}y}{\mathrm{d}x} = \frac{b -a}{(x-a)(b-x)}, where :math:`x \in (a, b)`. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- float The value of the jacobian at the given point(s). z$one or more values are not in boundsz{} is not in bounds) rærîrørrPrQr†r$r¡rðrï)rrr”rùrrrrÐs   zLogit.jacobiancCs0||j}t |¡}||j|jd|dS)a%Computes the Jacobian of :math:`y = \mathrm{logistic}(x; a,b)`. This is: .. math:: \frac{\mathrm{d}y}{\mathrm{d}x} = \frac{e^x (b-a)}{(1+e^y)^2}, where :math:`y \in (a, b)`. Parameters ---------- maps : dict or FieldArray A dictionary or FieldArray which provides a map between the parameter name of the variable to transform and its value(s). Returns ------- float The value of the jacobian at the given point(s). gð?g@)rçrPrêrðrï)rrr”rörrrrïs  zLogit.inverse_jacobianNc s| |d|¡}d ||g¡}d |¡}|dkr2g}|dkr@i}n| ¡}| ||¡rn| |||¡} | |¡nd} d |¡}| ||¡r¢| |||¡} | |¡nd} | dkr¶| dk sÆ| dkrØ| dk rØtd ||¡ƒ‚n"| dk rú| dt| ƒt| ƒfi¡t t |ƒ  |||||¡S)aInitializes a Logit transform from the given section. The section must specify an input and output variable name. The domain of the input may be specified using `min-{input}`, `max-{input}`. Example: .. code-block:: ini [{section}-logitq] name = logit inputvar = q outputvar = logitq min-q = 1 max-q = 8 Parameters ---------- cp : pycbc.workflow.WorkflowConfigParser A parsed configuration file that contains the transform options. section : str Name of the section in the configuration file. outputs : str The names of the parameters that are output by this transformation, separated by `VARARGS_DELIM`. These must appear in the "tag" part of the section header. skip_opts : list, optional Do not read options in the given list. additional_opts : dict, optional Any additional arguments to pass to the class. If an option is provided that also exists in the config file, the value provided will be used instead of being read from the file. Returns ------- cls An instance of the class. rèr.zmin-{}Nzmax-{}z;if providing a min(max)-{}, must also provide a max(min)-{}rñ) r3r2r¡r&r^Úappendr$r'r4rjrër>) r5r6r7rr8r9rèr`r<ršrõ)rkrrr> s2)         zLogit.from_config)rí)rórô)rórô)NN)r?r@rArBr-rrÍrèréròrDrìr÷rrrrrEr>rorr)rkrrë3s      rëc@s:eZdZdZdZeZejZejZej Z ej Z ddd„Z dS)ÚMass1Mass2ToMchirpQz#The inverse of MchirpQToMass1Mass2.Zmass1_mass2_to_mchirp_qNcCsz|dkrtj}|dkrtj}|dkr*tj}|dkr8tj}||_||_||_||_|j|jg|_ |j|jg|_ t   |¡dS)N) rrbrcrdrerfrgrhrir rr r)rrfrgrhrirrrrcszMass1Mass2ToMchirpQ.__init__)NNNN) r?r@rArBr-rarCrrrrrrrrrrûYsrûc@s<eZdZdZdZeZejZejZej Z ej Z ej Z ej Z dS)ÚMass1Mass2ToMchirpEtaz%The inverse of MchirpEtaToMass1Mass2.Zmass1_mass2_to_mchirp_etaN) r?r@rArBr-rprCrr rrrrrrrrrüwsrüc@sDeZdZdZdZeZejej gZ ej gZ ej ZejZ ejZejZdS)ÚDistanceToChirpDistancez'The inverse of ChirpDistanceToDistance.Zdistance_to_chirp_distanceN)r?r@rArBr-rvrCrrzrdr ryrrrrrrrrrrý„s rýcs@eZdZdZdZeZejZejZej Z ej Z ‡fdd„Z ‡Z S)ÚCartesianToSphericala¤Converts spherical coordinates to cartesian. Parameters ---------- x : str The name of the x parameter. y : str The name of the y parameter. z : str The name of the z parameter. radial : str The name of the radial parameter. azimuthal : str The name of the azimuthal angle parameter. polar : str The name of the polar angle parameter. r‹csDtt|ƒj|Ž|j}|j}||_||_t|jƒ|_t|jƒ|_dS)N)rjrþrr rr r r)rÚargsrr )rkrrr«s zCartesianToSpherical.__init__) r?r@rArBr-r’rCrrrrrrorr)rkrrþ‘srþcs$eZdZdZdZ‡fdd„Z‡ZS)ÚCartesianSpin1ToSphericalSpin1zÔThe inverse of SphericalSpin1ToCartesianSpin1. **Deprecation Warning:** This will be removed in a future update. Use :py:class:`CartesianToSpherical` with spin-parameter names passed in instead. Z$cartesian_spin_1_to_spherical_spin_1cs4t d |jtj¡¡tt|ƒ dddddd¡dS)Nz´Deprecation warning: the {} transform will be removed in a future update. Please use {} instead, passing spin1x, spin1y, spin1z, spin1_a, spin1_azimuthal, spin1_polar as arguments.r‡rˆrŒr‚ržr„)rŸr r¡r-rþrjrr)r)rkrrrÀs  z'CartesianSpin1ToSphericalSpin1.__init__)r?r@rArBr-rrorr)rkrr¶srcs$eZdZdZdZ‡fdd„Z‡ZS)ÚCartesianSpin2ToSphericalSpin2zÔThe inverse of SphericalSpin2ToCartesianSpin2. **Deprecation Warning:** This will be removed in a future update. Use :py:class:`CartesianToSpherical` with spin-parameter names passed in instead. Z$cartesian_spin_2_to_spherical_spin_2cs4t d |jtj¡¡tt|ƒ dddddd¡dS)Nz´Deprecation warning: the {} transform will be removed in a future update. Please use {} instead, passing spin2x, spin2y, spin2z, spin2_a, spin2_azimuthal, spin2_polar as arguments.r‰rŠrrƒr£r…)rŸr r¡r-rþrjrr)r)rkrrrÙs  z'CartesianSpin2ToSphericalSpin2.__init__)r?r@rArBr-rrorr)rkrrÏsrc@s<eZdZdZdZeZejZejZej Z ej Z ej Z ej Z dS)ÚCartesianSpinToAlignedMassSpinz.The inverse of AlignedMassSpinToCartesianSpin.Z#cartesian_spin_to_aligned_mass_spinN) r?r@rArBr-r¦rCrr rrrrrrrrrèsrc@s<eZdZdZdZeZejZejZej Z ej Z ej Z ej Z dS)Ú!CartesianSpinToPrecessionMassSpinz1The inverse of PrecessionMassSpinToCartesianSpin.Z&cartesian_spin_to_precession_mass_spinN) r?r@rArBr-r©rCrr rrrrrrrrrõsrc@s<eZdZdZdZeZejZejZej Z ej Z ej Z ej Z dS)ÚChiPToCartesianSpinz%The inverse of `CartesianSpinToChiP`.r³N) r?r@rArBr-r²rCrr rrrrrrrrrsrcs@eZdZdZdZeZejZejZej Z ej Z ‡fdd„Z ‡Z S)ÚExponentaApplies an exponent transform to an `inputvar` parameter. This is the inverse of the log transform. Parameters ---------- inputvar : str The name of the parameter to transform. outputvar : str The name of the transformed parameter. Úexponentcstt|ƒ ||¡dS)N)rjrr)rrèré)rkrrr#szExponent.__init__) r?r@rArBr-rärCrrrrrrorr)rkrrs rcs`eZdZdZdZeZejZejZej Z ej Z d ‡fdd„ Z e dd„ƒZ ed ‡fd d „ ƒZ‡ZS) ÚLogistica|Applies a logistic transform from an `input` parameter to an `output` parameter. This is the inverse of the logit transform. Typically, the output of the logistic function has range :math:`\in [0,1)`. However, the `codomain` argument can be used to expand this to any finite real interval. Parameters ---------- inputvar : str The name of the parameter to transform. outputvar : str The name of the transformed parameter. frange : tuple or distributions.bounds.Bounds, optional The range of the output parameter. Can be any finite interval. Default is (0., 1.). r÷©ggð?cstt|ƒj|||ddS)N)rñ)rjrr)rrèréÚcodomain)rkrrrAszLogistic.__init__cCs|jS)z*Returns the range of the output parameter.)rî)rrrrròDszLogistic.boundsNc s| |d|¡}|dkrg}|dkr(i}n| ¡}d ||g¡}d |¡}| ||¡rn| |||¡} | |¡nd} d |¡}| ||¡r¢| |||¡} | |¡nd} | dkr¶| dk sÆ| dkrØ| dk rØtd ||¡ƒ‚n"| dk rú| dt| ƒt| ƒfi¡t t |ƒ  |||||¡S)aInitializes a Logistic transform from the given section. The section must specify an input and output variable name. The codomain of the output may be specified using `min-{output}`, `max-{output}`. Example: .. code-block:: ini [{section}-q] name = logistic inputvar = logitq outputvar = q min-q = 1 max-q = 8 Parameters ---------- cp : pycbc.workflow.WorkflowConfigParser A parsed configuration file that contains the transform options. section : str Name of the section in the configuration file. outputs : str The names of the parameters that are output by this transformation, separated by `VARARGS_DELIM`. These must appear in the "tag" part of the section header. skip_opts : list, optional Do not read options in the given list. additional_opts : dict, optional Any additional arguments to pass to the class. If an option is provided that also exists in the config file, the value provided will be used instead of being read from the file. Returns ------- cls An instance of the class. ÚoutputNr.zmin-{}zmax-{}z;if providing a min(max)-{}, must also provide a max(min)-{}r ) r3r&r2r¡r^rúr$r'r4rjrr>) r5r6r7rr8r9rér`r<ršrõ)rkrrr>Is2)         zLogistic.from_config)r)NN)r?r@rArBr-rërCrrrrrrÍròrEr>rorr)rkrr's rcCs(g|] }|jdks|jdks| ¡‘qS)Nr“)rCr-)rZ_trrrrâsrc Csft|tƒst|ƒn|}g}xH|D]@}d}x(|D] }|| ¡sD|dkrH|nd7}q.W|| d¡7}q Wtt|ƒt|ƒƒ}|rŽt|ƒ}| |¡}g}xdtD]\}|j |¡s˜|j  |¡r¶q˜|j |¡} | r˜|  |j ¡s˜|  |¡rÞq˜|  |j ¡|  |¡q˜Wg} xTt D]L}|j  |¡rt|j |¡ƒdkr|  |j ¡|   |¡|  |j¡qW| |} t|ƒ| fS)aùDetermines if any additional parameters from the InferenceFile are needed to get derived parameters that user has asked for. First it will try to add any base parameters that are required to calculate the derived parameters. Then it will add any sampling parameters that are required to calculate the base parameters needed. Parameters ---------- requested_params : list List of parameters that user wants. variable_args : list List of parameters that InferenceFile has. valid_params : list List of parameters that can be accepted. Returns ------- requested_params : list Updated list of parameters that user wants. all_c : list List of BaseTransforms to apply. ÚÚ_ú r)rr Úisalnumr/r0Ú intersectionÚcommon_cbc_inverse_transformsrÚissubsetÚ isdisjointr r'rúÚcommon_cbc_forward_transformsrR) Zrequested_paramsZ variable_argsZ valid_paramsÚ new_paramsr<r`ÚchZ from_base_cÚ converterZ intersectZ to_base_cZall_crrrÚget_common_cbc_transformsÿs@              rFc CsZ|r|ddd…}xB|D]:}y|r.| |¡}n | |¡}Wqtk rPwYqXqW|S)a]Applies a list of BaseTransform instances on a mapping object. Parameters ---------- samples : {FieldArray, dict} Mapping object to apply transforms to. transforms : list List of BaseTransform instances to apply. Nested transforms are assumed to be in order for forward transforms. inverse : bool, optional Apply inverse transforms. In this case transforms will be applied in the opposite order. Default is False. Returns ------- samples : {FieldArray, dict} Mapping object with transforms applied. Same type as input. Néÿÿÿÿ)rrr)ÚsamplesÚ transformsrCÚtrrrÚapply_transformsO s   rcCsFd}|r&x8|D]}|| |¡9}qWnx|D]}|| |¡9}q,W|S)a'Computes the jacobian of the list of transforms at the given sample points. Parameters ---------- samples : {FieldArray, dict} Mapping object specifying points at which to compute jacobians. transforms : list List of BaseTransform instances to apply. Nested transforms are assumed to be in order for forward transforms. inverse : bool, optional Compute inverse jacobians. Default is False. Returns ------- float : The product of the jacobians of all fo the transforms. gð?)rr)rrrCÚjrrrrÚcompute_jacobiano s  rcCsxtƒjdd„|DƒŽ}g}dd„|Dƒ}xJ|rrg}x8|D]0}|j |¡r^| |¡||j8}q8| |¡q8W|}q*W|S)a°Orders transforms to ensure proper chaining. For example, if `transforms = [B, A, C]`, and `A` produces outputs needed by `B`, the transforms will be re-rorderd to `[A, B, C]`. Parameters ---------- transforms : list List of transform instances to order. Outputs ------- list : List of transformed ordered such that forward transforms can be carried out without error. cSs g|]}t|jƒt|jƒ‘qSr)r rr )rrrrrrž sz$order_transforms..cSsg|]}|‘qSrr)rrrrrr  s)r Úunionr rrúr)rrr+Ú remainingÚleftoverrrrrÚorder_transformsŒ s    r"rcCsJg}x<| |¡D].}| |d|¡}t| |||¡}| |¡qWt|ƒS)aReturns a list of PyCBC transform instances for a section in the given configuration file. If the transforms are nested (i.e., the output of one transform is the input of another), the returned list will be sorted by the order of the nests. Parameters ---------- cp : WorflowConfigParser An open config file to read. section : {"transforms", string} Prefix on section names from which to retrieve the transforms. Returns ------- list A list of the parsed transforms. r-)Zget_subsectionsr3rr>rúr")r6r7ZtransZ subsectionr-rrrrÚread_transforms_from_config® s r#)N)F)F)r)FrBrØrŸrPZpycbcrrrZpycbc.iorZpycbc.waveformrZpycbc.boundariesrrZ pycbc.pnutilsr Úobjectr rFrarprvr{r’rr¢r¤r¦r©r²rµrÎrärërûrürýrþrrrrrrrrCr-rr‡rˆrŒr‚ržr„r‰rŠrrƒr£r…rrÚextendZcommon_cbc_transformsrrrr"r#rrrrÚsþ        (k^[CW#?!,Tt(  %   l    P "