IR-e dZddlZddlZddlZddlmZgdZdZej ej e j Z dZdZGdd ej ZGd d eZGd deZdS)z> Optimization algorithms used in `~astropy.modeling.fitting`. N)AstropyUserWarning) OptimizationSLSQPSimplexdgHz>)lJ)lJ)ceZdZdZgZdZedZejdZedZ e jdZ edZ e jdZ d Z ed Z e jd Zd S) raE Base class for optimizers. Parameters ---------- opt_method : callable Implements optimization method Notes ----- The base Optimizer does not support any constraints by default; individual optimizers should explicitly set this list to the specific constraints it supports. c\||_t|_t|_t |_dS)N) _opt_methodDEFAULT_MAXITER_maxiter DEFAULT_EPS_eps DEFAULT_ACC_acc)self opt_methods ;lib/python3.11/site-packages/astropy/modeling/optimizers.py__init__zOptimization.__init__0s#%'   c|jS)zMaximum number of iterations.r rs rmaxiterzOptimization.maxiter6s }rc||_dS)z Set maxiter.Nrrvals rrzOptimization.maxiter;s rc|jS)z>Step for the forward difference approximation of the Jacobian.rrs repszOptimization.eps@ yrc||_dS)zSet eps value.Nrrs rrzOptimization.epsE rc|jS)zRequested accuracy.rrs racczOptimization.accJr rc||_dS)z Set accuracy.Nr$rs rr%zOptimization.accOr"rc$|jjd}|S)Nz()) __class____name__)rfmts r__repr__zOptimization.__repr__Ts(,,, rc|jS)zReturn the optimization method.)r rs rrzOptimization.opt_methodXs rc td)Nz'Subclasses should implement this method)NotImplementedErrorrs r__call__zOptimization.__call__]s!"KLLLrN)r) __module__ __qualname____doc__supported_constraintsrpropertyrsetterrr%r+rabcabstractmethodr/rrrrs+    X ^^X ZZX ZZ  X  MMMMMrr) metaclassc0eZdZdZgdZfdZdZxZS)ra) Sequential Least Squares Programming optimization algorithm. The algorithm is described in [1]_. It supports tied and fixed parameters, as well as bounded constraints. Uses `scipy.optimize.fmin_slsqp`. References ---------- .. [1] http://www.netlib.org/toms/733 )boundseqconsineqconsfixedtiedcnddlm}t|ddddd|_dS)Nr) fmin_slsqp)final_func_valnumiter exit_modemessage)scipy.optimizerAsuperrfit_info)rrAr(s rrzSLSQP.__init__qsK------ $$$"    rc |d|j|d<d|vr |j|d<d|vr |j|d<|dd}|dfdjD}d |D}t j|}|D]2}|dtd|d<|d td |d <3t j|t }t j j } t j j } |j ||f|d ||| | d |\} } } }}| |j d<| |j d<||j d<||j d<|dkrtjdt | |j fS) Run the solver. Parameters ---------- objfunc : callable objection function initval : iterable initial guess for the parameter values fargs : tuple other arguments to be passed to the statistic function kwargs : dict other keyword arguments to be passed to the solver riterepsilonr% verblevelNrc0g|]}t|Sr8)getattr).0namemodels r z"SLSQP.__call__..s#CCCt$$CCCrc8g|]}|j |j|jSr8)r>r?r;)rPpars rrSz"SLSQP.__call__..s(LLLSYL#(L#*LLLr)dtypeT)args full_outputdispr;r<ieqconsrBrCrDrEzLThe fit may be unsuccessful; check fit_info['message'] for more information.)popr rr param_namesnpasarrayDEFAULT_BOUNDSfloatarrayr<r=rrHwarningswarnr)robjfuncinitvalfargskwargsrZparsr;ir<r= fitparamsrBrCrDmessrRs @rr/zSLSQP.__call__|s  It}==v F " " $ F9     IF5Mzz+t,,aCCCC1BCCCLLLLLF## ) )At|%a(!t|%a(!F%000%,''8EN++>Mdo   ?  ? ?  ? ? ; >7It+9 &'#* i %. k"#' i >> M<"    $-''rr)r0r1r2r3rr/ __classcell__r(s@rrrbs`  NMM      ?(?(?(?(?(?(?(rrc0eZdZdZgdZfdZdZxZS)ra= Neald-Mead (downhill simplex) algorithm. This algorithm [1]_ only uses function values, not derivatives. Uses `scipy.optimize.fmin`. References ---------- .. [1] Nelder, J.A. and Mead, R. (1965), "A simplex method for function minimization", The Computer Journal, 7, pp. 308-313 )r;r>r?cnddlm}t|ddddd|_dS)Nr)fmin)rBrCrDnum_function_calls)rFrrrGrrH)rsimplexr(s rrzSimplex.__init__sK222222 !!!""&    rc 0d|vr |j|d<d|vr"|d|_|dd|vr"|d|_|d|dd}|j||f||j|dd|\}}}} } ||jd<||jd <| |jd <| |jd <|jd d krt jd tn+|jd dkrt jdt||jfS)rJrr%xtolrMNT)rXrvrZrYrBrCrDrsrVzLThe fit may be unsuccessful; Maximum number of function evaluations reached.zBThe fit may be unsuccessful; Maximum number of iterations reached.)r rr\rrHrcrdr) rrerfrgrhrZrkrBrCfuncallsrDs rr/zSimplex.__call__sn F " " $ F9  F??u DI JJu    V  vDI JJv   zz+t,,BQ$/  C  C C C C ? >7Hi+9 &'#* i %. k".6 *+ = % * * MB"     ]; '1 , , MT"   $-''rrmros@rrrs_  877      3(3(3(3(3(3(3(rr)r2r6rcnumpyr^astropy.utils.exceptionsr__all__r sqrtfinforarr rr`ABCMetarrrr8rrrs4 777777 . . .bghbhuoo)**  $BMBMBMBMBMS[BMBMBMBMJY(Y(Y(Y(Y(LY(Y(Y(xM(M(M(M(M(lM(M(M(M(M(r