IR-eT dZddlZddlZddlmZddlmZmZddl m Z m Z m Z ddl mZddlmZejdgfejdgfejdgfejdgfejdgfgZejdgfejd dgfejd dgfgZejejejejgZGd d Z Gd d Z!GddZ"Gdde Z#GddZ$GddZ%Gdde Z&GddZ'ej(ddd d ggdd d ggdej(dd d gdgd d gdgdej)ddd d ggdd d ggdej)ddd d ggd d gdgdej)dddd d gdgd d gdgdej)ddd d ggdd d gdgdej)d dd d ggdd d gd d ggdejd d !dd d ggd d gdejd d !dd gd dej*d d dd d"dd d ggd#d#gdej*d d dd d"dd gd$dejd d !ejd d!zgd%d&dejd d !ejd d!zd d d d gd d ggd ddgfdej+,ej-ej.dd d'gj/ej0dgej-d(d(gd(d)gd(d*gd(d+gd(d,ggdgZ1ej23d-e1d.Z4d/Z5Gd0d1e Z6d2Z7d3Z8d4Z9ej23d-ej*ejd ej:ej;ej<ej=d56gej2>e d78d9Z?ej23d-ej@ejd ejAej=d:6gej2>e d78d;ZBej23d-ej*ejd zej@ejd zej*ejd zej*ejd z ej*ejd zej(dejd zej)d<ejd zgd=ZCej23d-ej(dej)dej)d<gd>ZDdS)?zD This module tests fitting and model evaluation with various inputs N)assert_allclose)fittingmodels)Fittable1DModel FittableModelModel) Parameter) HAS_SCIPYceZdZdZdZejdedZ ejde dZ dS) TestInputTypez This class tests that models accept numbers, lists and arrays. Add new models to one of the lists above to test for this. cd|_d|_tjddd|_tjddd|_tjddddf\|_|_dS)Ng333333@g@r 皙?) xynparangex1y1mgridy2x2selfs Alib/python3.11/site-packages/astropy/modeling/tests/test_input.py setup_classzTestInputType.setup_class,s_)Ar3'')Ar3''8CRC!G,)modelparamscp||}||j||j||jdSN)rrrrr!r"ms r test_input1DzTestInputType.test_input1D3s> E6N $&  $'  $' r c||}||j|j||j|j||j|jdSr$)rrrrrrr%s r test_input2DzTestInputType.test_input2D:sU E6N $&$& $'47 $'47r N) __name__ __module__ __qualname____doc__rpytestmark parametrizemodel1d_paramsr'model2d_paramsr)r rrr%s --- [0.AABA  [0.AABAr rczeZdZdZdZdZdZdZdZdZ dZ d Z e j e d e j d ed Ze j e d e j d edZe j e d e j d edZe j e d e j d edZdS) TestFittingz/Test various input options to fitting routines.ctjd|_tjddddf\|_|_dS)Nrrrrrrrrs rrzTestFitting.setup_classE5)B--#2#ss(+r ctjgd}tjd}gd|_||j}t j}|||j|}t|j|ddS)z1 set 1D x, 1pset)rr r r Hz>atolN) rarrayr Polynomial1D parametersrrLinearLSQFitterr)rexpectedp1rpfitr!s rtest_linear_fitter_1setz#TestFitting.test_linear_fitter_1setIs8LLL))   # #$  R[[&((R"%%((DDDDDDr ctjddgddgddgddgg}tjdd}gd|_i}t dD]}||g||j|<tjdddi|}||jd }tj }|||j|}t|j |d d S)z%1 set 1D x, 2 sets 1D y, 2 param_setsrr r r:n_models)rI?rJ@rK@rLmodel_set_axisFrNr;r<N)r:) rr>rr?r@range param_namesrrrAr param_setsrrBrCr"irrDr!s rtest_linear_fitter_Nsetz#TestFitting.test_linear_fitter_NsetTs8aVaVaVaV<==  Q / / /@@@ q / /A)*AF2>!$ % %  ? ?1 ? ? ? R . . .&((R"%%((DDDDDDr ctjgdgj}tjd}gd|_||j}tj}|||j|}t|j |ddS)z71 pset, 1 set 1D x, 1 set 1D y, Chebyshev 1D polynomial)g@g@gC@gq@r:)rr r r:{Gz?r<N) rr>Tr Chebyshev1Dr@rrrArrR)rrBch1rrDr!s rtest_linear_fitter_1dchebz%TestFitting.test_linear_fitter_1dchebcs8       ##% S\\&((S$'2&&((DDDDDDr ctjgdgj}tjd}gd|_||j}tj}|||j|}t|j |ddS)zH 1 pset, 1 set 1D x, 1 set 1D y, Legendre 1D polynomial )g@g@gm@gv@r:)r r r:rM-q=r<N) rr>rXr Legendre1Dr@rrrArrR)rrBleg1rrDr!s rtest_linear_fitter_1dlegendz'TestFitting.test_linear_fitter_1dlegendws 8       ##&,, T$']]&((T47B''((EEEEEEr cDtjd}gd|_gd}||j|j}t j}|||j|j|}t|j|dt||j|j|ddS)Nr )rr r r:rMr]r<)r Polynomial2Dr@rrrrAr)rp2rBzrDr!s rtest_linear_fitter_1set2dz%TestFitting.test_linear_fitter_1set2ds   # #*** %%% Btvtv  &((R++((EEEEdfdf--q{CCCCCCr c0d}tjt|5tjd}||j}tjdd}t j}|||j|ddddS#1swxYwYdS)z A ValueError is raised if a 1 data set (1d x, 1d y) is fit with a model with multiple parameter sets. zHNumber of data sets .* is expected to equal the number of parameter setsmatchrbr rGN)r.raises ValueErrorrr?rrrA)rMESSAGErCrrDs rtest_wrong_numpsetzTestFitting.test_wrong_numpsets X ]:W 5 5 5 " "$Q''BDGB$Q333B*,,D DTWb ! ! !  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R . . .&((R"%%((DDDDDDr requires scipyreasonfitterc|}tjddd}||j}|||j|}t|jgddS)z.1 set 1D x, 1 set 1D y, 1 pset NonLinearFitterrr:皙?)meanstddev)rr:rwN)r Gaussian1Drrr@)rrug1rr!s rtest_nonlinear_lsqt_1set_1dz'TestFitting.test_nonlinear_lsqt_1set_1dsg  r# 6 6 6 R[[r47B''(,,,77777r c |}d}tjt|5tjddgddgddgd }||jd }|||j|}d d d d S#1swxYwYd S)z51 set 1D x, 1 set 1D y, 2 param_sets, NonLinearFitterz6Non-linear fitters can only fit one data set at a timerhgffffff$@rr:g @gq= ףp?rwr )rxryrHFrON)r.rjrkrrzr)rrurlr{r_s rtest_nonlinear_lsqt_Nset_1dz'TestFitting.test_nonlinear_lsqt_Nset_1dsK ]:W 5 5 5 ( ("r !S4+BDGE222Br47B''A  ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( (sAA88A<?A<c|}tjdddddd}||j|j}|||j|j|}t |jgdd S) z.1 set 2d x, 1set 2D y, 1 pset, NonLinearFitterrr:rM333333?rwr)x_meany_meanx_stddevy_stddevtheta)rr:rMrrwrN)r Gaussian2Drrrr@)rrug2rer!s rtest_nonlinear_lsqt_1set_2dz'TestFitting.test_nonlinear_lsqt_1set_2ds   qS3a    Btvtv  r46461--(*A*A*ABBBBBr c x|}d}tjt|5tjddgddgddgddgddgddgd }||j|j}|||j|j|}d d d d S#1swxYwYd S) z41 set 2d x, 1set 2D y, 2 param_sets, NonLinearFitterTInput argument .* does not have the correct dimensions in .* for a model set with .*rhrr:rMrrwrr )rrrrHN)r.rjrkrrrflattenr)rrurlrrer~s rtest_nonlinear_lsqt_Nset_2dz'TestFitting.test_nonlinear_lsqt_Nset_2ds  ]:W 5 5 5 . ."RAAss!fB46>>##TV^^%5%566Ar46461--A . . . . . . . . . . . . . . . . . .sA:B//B36B3N)r*r+r,r-rrErUr[r`rfrmrqr.r/skipifr r0fittersr|rrrr3r rr5r5Bs99,,, E E E E E EEEE(FFF,DDD""" EEE. 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[Xw//..0/@?...r r5cHeZdZdZdZdZdZdZdZdZ dZ d Z d Z d S) TestEvaluationzs Test various input options to model evaluation TestFitting actually covers evaluation of polynomials ctjd|_tjddddf\|_|_dS)Nrr7rs rrzTestEvaluation.setup_classr8r ctjddgddgddgd}||jd}tj|dd d f|d d d fz tjgksJd S) zY This case covers: N param sets , 1 set 1D x --> N 1D y data rr:rwr rGFrOrNr )rrzrrallnonzeror>)rr{rs rtest_non_linear_NYsetz$TestEvaluation.test_non_linear_NYsets  Bx!Q#sa H H H R . . .vr!QQQ$x"QT(*3355"EFFFFFFFr ctjddgddgddgd}tj|j|jg}||}t |dddf|dddfd dS) zU This case covers: N param sets , N sets 1D x --> N N sets 1D y data rr:rwr rGNrr r]r<)rrzrr>rr)rr{xxrs rtest_non_linear_NXYsetz%TestEvaluation.test_non_linear_NXYsets  Bx!Q#sa H H H Xtw( ) ) RVV111a4"QQQT(======r chtjd}||j}|jdksJdS)z 1 data set, 1 pset, Polynomial1DrM)rN)rr?rshaperrCrs rtest_p1_1set_1psetz!TestEvaluation.test_p1_1set_1psets<  # # R[[x5      r ctjdd}|tj|j|jgjd}|jdksJt|dddf|d ddfd dS) z'N data sets, N param_sets, Polynomial1DrMr rGrO)rr rNr r]r<)rr?rr>rrXrrrs rtest_p1_nset_npsetz!TestEvaluation.test_p1_nset_npset"s Q / / / R$'47+,,.r B B Bx7""""1aaa4"QT(======r cttjd}||j|j}|jdksJdS)z#1 pset, 1 2D data set, Polynomial2Drb)rrN)rrcrrr)rrdres rtest_p2_1set_1psetz!TestEvaluation.test_p2_1set_1pset*sB  # # Btvtv  w(""""""r ctjdd}tj|j|jg}tj|j|jg}|||}|jdksJdS)z$N param_sets, N 2D data sets, Poly2drbr rG)r rrN)rrcrr>rrr)rrdryyres rtest_p2_nset_npsetz!TestEvaluation.test_p2_nset_npset1sq Q / / / Xtvtv& ' ' Xtvtv& ' ' Br2JJw+%%%%%%r c.tj|j|jgj}d|d<d|d<d|d<t jdddgd d gd }||d }t |j|j||d }t ||dS)z Test model set with negative model_set_axis. In this case model_set_axis=-1 is identical to model_set_axis=1. d)rrr rc)r rrbr r r:rM)c0c1rHrrON)rr>rrXrr?rr)rrrCryy1s rtest_nset_domainzTestEvaluation.test_nset_domain:sXtw( ) ) +444  1v1a&1 E E E R2 & & &"(+++bA&&&C     r ctjddgddgg}tjddd|}tjddddf\}}|||dS)NrJg?r:g@g@) cov_matrixr)rr>rrr)rcovgrrs rtest_evaluate_gauss2dz$TestEvaluation.test_evaluate_gauss2dKsfhc S!H-..  c3 < < <xSbS!1 !Qr N) r*r+r,r-rrrrrrrrrr3r rrrs ,,,GGG>>>!!!>>>###&&&!!!"r rcLeZdZeZeZedZdS) TModel_1_1c||z|zSr$r3)rrCrds revaluatezTModel_1_1.evaluateVs2v{r N)r*r+r,r rCrd staticmethodrr3r rrrRsC B B\r rcBeZdZdZdZdZdZdZdZdZ dZ d Z d S) &TestSingleInputSingleOutputSingleModela A suite of tests to check various cases of parameter and input combinations on models with n_input = n_output = 1 on a toy model with n_models=1. Many of these tests mirror test cases in ``astropy.modeling.tests.test_parameters.TestParameterInitialization``, except that this tests how different parameter arrangements interact with different types of model inputs. ctdd}|d}t|tsJtj|dksJ|dksJdS)O Scalar parameters with a scalar input should return a scalar. r rrroN)r isinstancefloatrndimrtrs r#test_scalar_parameters_scalar_inputzJTestSingleInputSingleOutputSingleModel.test_scalar_parameters_scalar_inputfs\ q"   AcFF!U#####wqzzQCxxxxxxr c tdd}|tjddz}t|tjsJtj|dksJtj|gdksJdS) Scalar parameters should broadcast with an array input to result in an array output of the same shape as the input. r rrbrrp r7N)rrrrndarrayrrrs r%test_scalar_parameters_1d_array_inputzLTestSingleInputSingleOutputSingleModel.test_scalar_parameters_1d_array_inputqs q"   AbillS ! !!RZ(((((x{{d""""va33334444444r c:tdd}|tjddddz}t |tjsJtj|dksJtj|gdgd gksJd S) rr rror r:rr r:rrrrrNrrrreshaperrrrrs r%test_scalar_parameters_2d_array_inputzLTestSingleInputSingleOutputSingleModel.test_scalar_parameters_2d_array_input}s q"   Abill""1a((3. / /!RZ(((((x{{f$$$$vaNNNOOO<<=======r cXtdd}|tjdddddz}t |tjsJtj|dksJtj|dd gd d gd d ggddgddgddgggksJdS)rr r r r:rr r:r rrrrrrc+WNrrs r%test_scalar_parameters_3d_array_inputzLTestSingleInputSingleOutputSingleModel.test_scalar_parameters_3d_array_inputs q"   Abimm##Aq!,,s2 3 3!RZ(((((x{{i''''v cS#Jc 3sc3Z$6        r ctddgddg}|d}t|tjsJtj|dksJtj|ddgksJd S) Array parameters should all be broadcastable with each other, and with a scalar input the output should be broadcast to the maximum dimensions of the parameters. r r rrrr rzN)rrrrrrrs r%test_1d_array_parameters_scalar_inputzLTestSingleInputSingleOutputSingleModel.test_1d_array_parameters_scalar_inputs} 1vBx ( ( AcFF!RZ(((((x{{d""""vaC:o&&&&&&&r ctddgddg}|ddg}tj|dksJtj|dd gksJ|dgdgg}tj|d ksJtj|dd gd d ggksJd }t jt |5|gdddddS#1swxYwYdS)e When given an array input it must be broadcastable with all the parameters. r r rrrrrr r rrzWself input argument 'x' of shape .* cannot be broadcast with parameter 'p1' of shape .*rhrr,Nrrrrr.rjrkrrrrrls r'test_1d_array_parameters_1d_array_inputzNTestSingleInputSingleOutputSingleModel.test_1d_array_parameters_1d_array_inputsU 1vBx ( ( QSz]]x||t####vbS#J&''''' Qu~  x||v%%%%vbc3Z#s4455555 ! ]:W 5 5 5   Aooo                     s>CC Cc8tddgddggddgddgg}|d d gd d gg}tj|d ksJtj|ddgddggksJ|d ggd gggd ggd gggg}tj|dksJtj|ddgddggddgddgggddgddggddgddggggksJd}t jt | 5|gd!gd"gd#d#d#d#S#1swxYwYd#S)$rr r r:rMrr(rrrrrrMr r r r rrrBXrTself input argument .* of shape .* cannot be broadcast with parameter .* of shape .*rhrrXNrrs r'test_2d_array_parameters_2d_array_inputzNTestSingleInputSingleOutputSingleModel.test_2d_array_parameters_2d_array_inputs AA'2r(RH)= > > Qc S#J' ( (x||v%%%%vbc3Z#s4455555 Q3%C5'"seWug$67 8 8x|||++++v *sCj)S#Jc +CD*sCj)S#Jc +CD        ]:W 5 5 5 2 2 A0 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2s0DDDc tgdgdggdgdgggd}|gd}tj|dksJt|gdgd ggd gd gg|d gggd gggdgggg}tj|dksJt|gdgdggdgdgggdgdggdgdgggdgdggdgdgggdS)rrWg{Gz?gQ?g{Gz?g?gQ?gQ?g{Gz?g ףp= ?rg)\(?gQ?r r r:rrrr r r:Q&@Q6@p= ׃@@Gz&@ 6@Hz@@p= #&@Gz6@Q@@333333&@\(6@(\@@rrrr:r r r:r g ףp= (@g(\*@rg(@gQ*@rg)\((@gGz.*@rgQ8(@g= ףp=*@g(\5@r gHz7@g ףp= 5@rg(\7@gR5@rgףp= 7@g5@rgQ7@g(\?@g(\@@r g ףp= ?@gfffff@@rgR?@g ףp= @@rg?@gGz@@rN)rrrrrrrrs r*test_mixed_array_parameters_1d_array_inputzQTestSingleInputSingleOutputSingleModel.test_mixed_array_parameters_1d_array_inputs ###%7%7%78###%7%7%78  II   Q|||__x||y(((( &&&(=(=(=>&&&(=(=(=>    Q2$RD6(rdVH- . .x|||++++ +**,A,A,AB***,A,A,AB +**,A,A,AB***,A,A,AB +**,A,A,AB***,A,A,AB      r N r*r+r,r-rrrrrrrr(r3r rrr[s    5 5 5 > > >   $ ' ' '.222<* * * * * r rcBeZdZdZdZdZdZdZdZdZ dZ d Z d S) #TestSingleInputSingleOutputTwoModela A suite of tests to check various cases of parameter and input combinations on models with n_input = n_output = 1 on a toy model with n_models=2. Many of these tests mirror test cases in ``astropy.modeling.tests.test_parameters.TestParameterInitialization``, except that this tests how different parameter arrangements interact with different types of model inputs. With n_models=2 all outputs should have a first dimension of size 2 (unless defined with model_set_axis != 0). ctddgddgd}|d}tj|dksJtj|dd gksJd S) z Scalar parameters with a scalar input should return a 1-D array with size equal to the number of models. r r rrrGrrrrNrrrrrs rrzGTestSingleInputSingleOutputTwoModel.test_scalar_parameters_scalar_inputsj 1vBx! 4 4 4 AcFFx{{d""""vaC:o&&&&&&&r ctddgddgd}d}tjt|5|t jdd zd d d n #1swxYwY|d d g}t j|d ksJt j|d dgksJ|d d gd}t j|dksJt j|d dgddggksJ|gdd}t j|dksJt j|gdgdgksJd S) The dimension of the input should match the number of models unless model_set_axis=False is given, in which case the input is copied across all models. r r rrrGrrhrbrNrrrrFrOrrrrr)rrr)rrr)rr.rjrkrrrr)rrrlrry3s rrzITestSingleInputSingleOutputTwoModel.test_scalar_parameters_1d_array_input$s 1vBx! 4 4 4  ]:W 5 5 5 " " AbillS ! ! ! " " " " " " " " " " " " " " "QSz]]x||t####vbS#J&''''' QSz% 0 0 0x||v%%%%vbc3Z#s4455555 Qu 5 5 5x||v%%%%vb___ooo>>???????s!A!!A%(A%ctddgddgd}|tjddddz}tj|d ksJtj|gd gd gksJ|tjddddzd }tj|dksJtj|gd gdggdgd ggksJdS)r/r r rrrGror:rrr)rri FrOr r)rrN)rrrrrrr's rrzITestSingleInputSingleOutputTwoModel.test_scalar_parameters_2d_array_inputCs& 1vBx! 4 4 4 Qry||##Aq))C/ 0 0x||v%%%%vb^^^___==>>>>> Qry||##Aq))C/ F F Fx||y((((v NNNOOO4~~~6WX X       r ctddgddgd}tjdddddz}||}tj|d ksJtj|d d gd d gddggddgddgddgggksJ||d}tj|dksJtj|tj|d z|dzgksJdS)r/r r rrrGrr:rrrrrrrrinii6iiibFrO)r r r:r r2N)rrrrrrr>)rrdatarrs rrzITestSingleInputSingleOutputTwoModel.test_scalar_parameters_3d_array_inputVs( 1vBx! 4 4 4y}}$$Q1--3 QtWWx||y((((v cS#Jc 3sc3Z$6      QtE * * *x|||++++vbBHdRi%;<<<=======r ctgdgdggdgdgd}|d}tj|dksJtj|gd gd gksJd S) rrrMrbrorr2<r rGrrrrr)rNr-rs rrzITestSingleInputSingleOutputTwoModel.test_1d_array_parameters_scalar_inputns  999- lll/KVW X X X AcFFx{{f$$$$vaOOO___==>>>>>>>r cntgdgdggdgdgd}d}tjt|5|gd }d d d n #1swxYwY|d d g}t j|d ksJt j|gdgdgksJd}tjt|5|d d gd}d d d n #1swxYwY|gd d}t j|d ksJt j|gdgdgksJd S)z When the input is an array, if model_set_axis=False then it must broadcast with the shapes of the parameters (excluding the model_set_axis). 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As of writing there are not enough controls to adjust how outputs from such a model should be formatted (currently the shapes of outputs are assumed to be directly associated with the shapes of corresponding inputs when n_inputs == n_outputs). 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