IR-eFddgZddlmZddlZddlmZdZdZd Z d Z dS) bls_fastbls_slow)partialNbls_implc Vtt||||||}t||S)aKCompute the periodogram using a brute force reference method. t : array-like Sequence of observation times. y : array-like Sequence of observations associated with times t. ivar : array-like The inverse variance of ``y``. period : array-like The trial periods where the periodogram should be computed. duration : array-like The durations that should be tested. oversample : The resolution of the phase grid in units of durations. use_likeliood : bool If true, maximize the log likelihood over phase, duration, and depth. Returns ------- power : array-like The periodogram evaluated at the periods in ``period``. depth : array-like The estimated depth of the maximum power model at each period. depth_err : array-like The 1-sigma uncertainty on ``depth``. duration : array-like The maximum power duration at each period. transit_time : array-like The maximum power phase of the transit in units of time. This indicates the mid-transit time and it will always be in the range (0, period). depth_snr : array-like The signal-to-noise with which the depth is measured at maximum power. log_likelihood : array-like The log likelihood of the maximum power model. )r _bls_slow_one_apply)tyivarperiodduration oversampleuse_likelihoodfs Klib/python3.11/site-packages/astropy/timeseries/periodograms/bls/methods.pyrr s.L  q!T8ZPPA !V  c ,t|||||||S)aOCompute the periodogram using an optimized Cython implementation. t : array-like Sequence of observation times. y : array-like Sequence of observations associated with times t. ivar : array-like The inverse variance of ``y``. period : array-like The trial periods where the periodogram should be computed. duration : array-like The durations that should be tested. oversample : The resolution of the phase grid in units of durations. use_likeliood : bool If true, maximize the log likelihood over phase, duration, and depth. Returns ------- power : array-like The periodogram evaluated at the periods in ``period``. depth : array-like The estimated depth of the maximum power model at each period. depth_err : array-like The 1-sigma uncertainty on ``depth``. duration : array-like The maximum power duration at each period. transit_time : array-like The maximum power phase of the transit in units of time. This indicates the mid-transit time and it will always be in the range (0, period). depth_snr : array-like The signal-to-noise with which the depth is measured at maximum power. log_likelihood : array-like The log likelihood of the maximum power model. r)r r rrrrrs rrr6sL Aq$*n M MMrc ltj df}d|z}tj|} |D]} | |z } tjd|| z| } | D]\} tj|| z | z |z|z|z d| zk}|}tj||}tj||}tj||||z|z }tj||||z|z }||z }tjd|z d|z z}||z }dtj|||z dz||zz}|dtj|||z dz||zzz }|r|}n|}|dkr||dkr||||| | | z|z||ff}^|dS)zAA private function to compute the brute force periodogram result.Ng?rg?gr)npinfminarangeabssumsqrt)r r rrrrrbesthpmin_tdurd_phasephaset0m_inm_outivar_inivar_outy_iny_outdepth depth_errsnrloglike objectives rr r _s VGT?D vB F1IIE,, " !Vg-w77' ' B61u9r>B.&82=>>sJDEEfT$Z((Gvd5k**H6!D'DJ.//'9DF1U8d5k122X=EDLEg h >??I)#CRVTAdG^$9DJ$FGGGG sRVUQtW_$:T$Z$GHHH HG #  qyyYa00!!ev- 9' R 7Nrc ztttjt t||S)N)tuplemaprarrayzip)rrs rr r s) RXsC6NN344 5 55r) __all__ functoolsrnumpyr_implrrrr r rrr<s z "'''T&N&N&NR333l66666r