B dc @sdZddlZddlZddlZddlZddlZddlmZmZddlm Z m Z ddlm Z m Z ddlm Z ddlmZmZddlmZmZdd lmZmZdd lmZmZdd lmZmZdd lmZmZmZmZdd lmZddl m!Z!ddl"Zddl#m$Z$m%Z%ddl&Zddl'ZddlZddl(m)Z)ddZ*dIddZ+dJddZ,dKd d!Z-dLd"d#Z.dMd%d&Z/dNd'd(Z0gZ1e12d)d*d+d,d-d.gd/d0d1d2d3gZ3d4d5Z4d6d7Z5d8d9Z6Gd:d;d;e7Z8ej9dd?Z:dPd@dAZ;dBdCZdFZ?GdGdHdHej@jAZBdS)QzQ This modules contains functions reading, generating, and segmenting strain data N) TimeSerieszeros)ArrayFrequencySeries)MultiDetOptionAppendActionMultiDetOptionAction)MultiDetOptionActionSpecial)DictOptionActionMultiDetDictOptionAction) required_optsrequired_opts_multi_ifo)ensure_one_optensure_one_opt_multi_ifo)copy_opts_for_single_ifocomplex_same_precision_as) InjectionSetSGBurstInjectionSet)resample_to_delta_tlowpasshighpassmake_frequency_series) filter_zpk) spa_distance)FFTIFFT) kaiserordcCs d|>S)zReturn the smallest integer power of 2 larger than the argument. Parameters ---------- n : int A positive integer. Returns ------- m : int Smallest integer power of 2 larger than n. ) bit_length)nr`/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/pycbc/strain/strain.pynext_power_of_2*s r!@@median>@I@@Fc s|rtd|ddnt|j} t| t| } d| tjj | j d9<t | dtjj | dddj d9<| r dt t } t| d t d } | t }j| tj}tjjtjj| j djd |d }dd|| |<tjj| t | t|jt|j|d d }tj|d |j}tjj|t|j|dd}t||j}tj|d|<|rt||j}tj||d<|}|r||}njd|}|||d9}|}| r || | dt|| |}| r@|d|}d|d| <d|d| dd<t||kd}tj|t ||t|j}fdd||D}|S)a Automatic identification of loud transients for gating purposes. This function first estimates the PSD of the input time series using the FindChirp Welch method. Then it whitens the time series using that estimate. Finally, it computes the magnitude of the whitened series, thresholds it and applies the FindChirp clustering over time to the surviving samples. Parameters ---------- strain : TimeSeries Input strain time series to detect glitches over. psd_duration : {float, 4} Duration of the segments for PSD estimation in seconds. psd_stride : {float, 2} Separation between PSD estimation segments in seconds. psd_avg_method : {string, 'median'} Method for averaging PSD estimation segments. low_freq_cutoff : {float, 30} Minimum frequency to include in the whitened strain. threshold : {float, 50} Minimum magnitude of whitened strain for considering a transient to be present. cluster_window : {float, 5} Length of time window to cluster surviving samples over, in seconds. corrupt_time : {float, 4} Amount of time to be discarded at the beginning and end of the input time series. high_frequency_cutoff : {float, None} Maximum frequency to include in the whitened strain. If given, the input series is downsampled accordingly. If omitted, the Nyquist frequency is used. output_intermediates : {bool, False} Save intermediate time series for debugging. g?ldas)methodr)dtypeNzstrain_conditioned.wavF)delta_tcopyepoch)seg_len seg_strideZ avg_methodZrequire_exact_data_fitg?Zhann)low_frequency_cutoffZ trunc_methodg@gzstrain_whitened.wavzstrain_whitened_mag.npyrcsg|]}|jjqSr)r- start_time).0idx)strainrr sz(detect_loud_glitches..)!rr.int sample_ratenumpyarangefloatpycbctypesrr*lenZ save_to_wavr!r3rrr-psdwelch interpolatedurationinverse_spectrum_truncationdelta_finfto_frequencyseries to_timeseriesabssavewhereeventsZfindchirp_cluster_over_windowarray)r6 psd_duration psd_strideZpsd_avg_methodlow_freq_cutoff thresholdcluster_window corrupt_timeZhigh_freq_cutoffZoutput_intermediatesZcorrupt_lengthwZstrain_pad_lengthZ pad_startZpad_endZ pad_epochZ strain_padr@ZkminkmaxZ strain_tildeZnormmagindicesZ cluster_idxtimesr)r6r detect_loud_glitches9sn(  "           rYrsinglec) si}t}js&js&js&jrjr2j}jr>j}tdtdr`j r`j }nd}jrt j j jj jjjj|dnbjsjrt j j|j jjjj|dn,jrt j jj jjjjnxjs jrttdjj}|dj7}dj} j} j} j} tj| dd} jrtd t jjj| | | d d }n.jd krtd t jjj| | | f| }jd krtdtt j || d| jjdnBtdddl!m"}||jjjjj#| | d| d$| std}|d7}|d7}|d7}|d7}t%|j sj&sj'rt%dj(rj)rj*rtdt+j,dtdt-.j(}t-.j)}t/j*}t01t-j2|||j3r&tdj3}|j,rFtdt+j,djrltdt4djdd |dk rtd!|j5j 6d"dj7j8|d#}j'rtd$t9j'}|j5j 6d"dj7d%|d&krtd'|1t jj:n6|d(kr.td)|1t jj2nt%d*;|j|j?dkrt|g}x*|D]"\}}}j@||jAd,|d-qzWfd.d/|D|d0<jBdk r|g|d1<xtCjDD]}tEjBjFj,jjGd2}fd3d/|D}|d1|7<x*|D]"\}}}j@||jAd,|d-q"Wt>|dkrttd4d5Hd6d/|DnPqWj,rtdt+j,djIrtd7tJjIdtd8rjKrL}ddlM}|NjO}x&|D]}t j j jKtP|jQjRd9} | |1jS} t jjTjO|d:}!|!1|jS}!tUjVj}"t jW|!|jX}!|!Y}#tZt-[|"djSd;}$|#d|"|$|"d9<|#t>|#|"d|$d|"9<|#L}!t\t>|!t>|d}%|d|%|!d|%| Ld|%8<qW|Yjrdtd<tUjj}&tUt>jj}'|&|'j]rtd=j]}(jQd>|(fg}|^jRd>|(ft_||dk r|_`|_aS)?aParses the CLI options related to strain data reading and conditioning. Parameters ---------- opt : object Result of parsing the CLI with OptionParser, or any object with the required attributes (gps-start-time, gps-end-time, strain-high-pass, pad-data, sample-rate, (frame-cache or frame-files), channel-name, fake-strain, fake-strain-seed, fake-strain-from-file, gating_file). dyn_range_fac : {float, 1}, optional A large constant to reduce the dynamic range of the strain. precision : string Precision of the returned strain ('single' or 'double'). inj_filter_rejector : InjFilterRejector instance; optional, default=None If given send the InjFilterRejector instance to the inject module so that it can store a reduced representation of injections if necessary. Returns ------- strain : TimeSeries The time series containing the conditioned strain data. zReading Frames frame_sieveN)r3end_timesievezGenerating Fake Strainr,g?rzReading ASD from fileT)Z is_asd_file zeroNoisezMaking PSD for strainzMaking zero-noise time series)r-r/zMaking colored noiser) colored_noise)seedr9r2Zfilter_durationz4Actual sample rate of generated data does not match z(that expected. 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Adds the options used to call the pycbc.strain.from_cli function to an optparser as an OptionGroup. This should be used if you want to use these options in your code. Parameters ----------- parser : object OptionParser instance. gps_times : bool, optional Include ``--gps-start-time`` and ``--gps-end-time`` options. Default is True. zOptions for obtaining h(t)zThese options are used for generating h(t) either by reading from a file or by generating it. 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Use datafind to get the needed frame file(s) of this type.z --frame-sievezT(optional), Only use frame files where the URL matches the regular expression given.z --fake-strainz5Name of model PSD for generating fake gaussian noise.r^)rchoicesz--fake-strain-extra-argsz PARAM:VALUEz4(optional) Extra arguments passed to the PSD models.)ractionmetavarrrrz--fake-strain-seedz|jd?d@tdtdAdB|jdCdDtdtdEdB|jdFdGtdtdHdB|jdItdtd|jd[tdtd\d]d|jd^td_d`dadb|jdctdtdddedfdP|jdgtdtdddhdidP|jdjtdtdddhdkdP|jdltdtdddmdndP|jdotdtdpdqdrdpdsgdt|jdutdtdTdvd|jdwtdtdTdxd|jdytdtdTdzd|jd{tdtdTd|d|S)}a Adds the options used to call the pycbc.strain.from_cli function to an optparser as an OptionGroup. This should be used if you want to use these options in your code. Parameters ----------- parser : object OptionParser instance. gps_times : bool, optional Include ``--gps-start-time`` and ``--gps-end-time`` options. 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NrFc /s2d|_|_j|_j|_|r&|} nj} d| |_t| |j|_|jdd|_|} |} srtj |nJ| stj |} n tj } | krd}|d7}|d| 7}t |stj |nL| stj |}n tj }|krd}|d 7}|d |7}t || | }| |}}|tj }|tj }||}|j}|j}tt t|t|}tt |t|}g|_g|_xt|dD]z}t|||j}t|| j}t||}|j|t| j}t||j}t||}|j|qWt|}t|| j}t||}|j|||d|| }t| |j}t| | j}t||}|j|t|j|_g} g}!tj j}"tj j}#|r:td r:j}$fd d |$D}$fdd |$D}%xt|j|jD]\}&}'|'j}(|'j})|(|&j}*|)|&j}+|"|*kr|(|"|*7}(|#|+kr|)|+|#8})|rtd rd},jd}-x.|%D]&}.|.|+|-kr|.|*|-krd},qW|,sqJ|(|)krJ| |&|!t|(|)qJW| |_|!|_dS)zb Determine how to chop up the strain data into smaller segments for analysis. Ng?r,rz-Trigger start time must be within analysable zwindow. Asked to start from %d zbut can only analyse from %d.z+Trigger end time must be within analysable zwindow. Asked to end at %d zbut can only analyse to %d.rcs(g|] }t|krt|kr|qSr)r<)r4time) trigger_end trigger_startrr r72sz+StrainSegments.__init__..cs$g|]}t|tjjqSr)r<r3r9)r4r)r6rr r73sFrT)_fourier_segmentsr6r-r9rCrEr8Ztime_lenZfreq_lenr3rxr\r:ceilr<segment_slicesanalyze_slicesrslicerr.deepcopyZfull_segment_slicesrtr end_timesziprstop)/selfr6segment_lengthsegment_start_padsegment_end_padrrfilter_inj_onlyinjection_windowallow_zero_paddingr0Z seg_end_padZ seg_start_padZmin_start_timerZ max_end_timeZthrowaway_sizeZ seg_widthZ analyzableZ data_startZdata_endZdata_durZnum_segsZ seg_offsetZnsegZ seg_startZseg_end seg_sliceZ ana_startZana_endZ ana_slice remainingZsegment_slices_redZanalyze_slices_redZtrig_start_idxZ trig_end_idxrZinj_idxseganarrZ cum_startZcum_endZ analyze_thisZ inj_windowZinj_idr)r6rrr __init__s                              zStrainSegments.__init__cCs|jsg|_xt|j|jD]\}}|jdkrN|jt|jkrNt|j|}np|jdkr|jd|j}| |j t|}n>|jt|jkr|j|jd}| |jt|jt|}||_ |j|j|_ ||_ |j|qW|jS)a Return a list of the FFT'd segments. Return the list of FrequencySeries. Additional properties are added that describe the strain segment. The property 'analyze' is a slice corresponding to the portion of the time domain equivalent of the segment to analyze for triggers. The value 'cumulative_index' indexes from the beginning of the original strain series. rN)rrrrrrr?r6rZ prepend_zerosZ append_zerosZanalyzeZcumulative_indexrr)rrrZfreq_segZ strain_chunkrrr fourier_segmentsUs$  zStrainSegments.fourier_segmentsc Cs*|||j|j|j|j|j|j|j|jd S)zjCalculate the segmentation of the strain data for analysis from the command line options. )rrrrrrrr)rrrtrig_start_time trig_end_timerrr)clsrmr6rrr rpsszStrainSegments.from_clicCs|dd}|jdtddd|jdtddd|jd td d |jd td d |jdtdd |jdddd|jdddd|jddtdddS)Nz!Options for segmenting the strainzThese options are used to determine how to segment the strain into smaller chunks, and for determining the portion of each to analyze for triggers. z--trig-start-timerz3(optional) The gps time to start recording triggers)rrrz--trig-end-timez2(optional) The gps time to stop recording triggersz--segment-lengthz-The length of each strain segment in seconds.)rrz--segment-start-padzKThe time in seconds to ignore of the beginning of each segment in seconds. z--segment-end-padzDThe time in seconds to ignore at the end of each segment in seconds.z--allow-zero-padding store_truezEAllow for zero padding of data to analyze requested times, if needed.)rrz--filter-inj-onlyz0Analyze only segments that contain an injection.z--injection-windowaIf using --filter-inj-only then only search for injections within +/- injection window of the injections's end time. 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NOTE: Reverts to full analysis if two injections are in the same segment.)rrr)rrr8r<)rr segment_grouprrr insert_segment_option_groups(  z*StrainSegments.insert_segment_option_groupc Cs:|||j||j||j||j||j||j|jdS)zjCalculate the segmentation of the strain data for analysis from the command line options. )rrrrrrr)rrrrrrr)rrmr6rrrr rs z"StrainSegments.from_cli_single_ifocCs,i}x"|D]}|||||||<q W|S)zjCalculate the segmentation of the strain data for analysis from the command line options. )r)rrmZ strain_dictrZstrain_segmentsrrrr rs  z"StrainSegments.from_cli_multi_ifosc Cs|dd}|jdtddtddd|jd tddtdd d|jd tdtd d d|jdtdtddd|jdtdtddd|jdddd|jdddddS)Nz!Options for segmenting the strainzThese options are used to determine how to segment the strain into smaller chunks, and for determining the portion of each to analyze for triggers. z--trig-start-timerrzIFO:TIMEz3(optional) The gps time to start recording triggers)rrrrrrz--trig-end-timez2(optional) The gps time to stop recording triggersz--segment-lengthz IFO:LENGTHz-The length of each strain segment in seconds.)rrrrrz--segment-start-padzKThe time in seconds to ignore of the beginning of each segment in seconds. z--segment-end-padzDThe time in seconds to ignore at the end of each segment in seconds.z--allow-zero-paddingrzEAllow for zero padding of data to analyze requested times, if needed.)rrz--filter-inj-onlyz0Analyze only segments that contain an injection.)rrr8r)rrrrrr %insert_segment_option_group_multi_ifos.  z4StrainSegments.insert_segment_option_group_multi_ifoz--segment-lengthz--segment-start-padz--segment-end-padcCst|||jdS)N)r r)rrmrrrr verify_segment_optionssz%StrainSegments.verify_segment_optionscCs"x|D]}t||||jqWdS)N)r r)rrmrrrrrr verify_segment_options_multi_ifos z/StrainSegments.verify_segment_options_multi_ifo)NrrNNFNF)__name__ __module__ __qualname____doc__rr classmethodrprrrrrrrrrrr rs"   % ! ri)maxsizec Cs||dd}d||}tt||d|dd}tt|t|d|dd}|r`t||} |} |} nt||} |} |} | | | fS)a Create memory and engine for class-based FFT/IFFT Currently only supports R2C FFT / C2R IFFTs, but this could be expanded if use-cases arise. Parameters ---------- npoints_time : int Number of time samples of the real input vector (or real output vector if doing an IFFT). dtype : np.dtype The dtype for the real input vector (or real output vector if doing an IFFT). np.float32 or np.float64 I think in all cases. delta_t : float (default: 1) delta_t of the real vector. If not given this will be set to 1, and we will assume it is not needed in the returned TimeSeries/FrequencySeries ifft : boolean (default: False) By default will use the FFT class, set to true to use IFFT. uid : int (default: 0) Provide a unique identifier. This is used to provide a separate set of memory in the cache, for instance if calling this from different codes. r,rg?)r*F)r-r.)rEr.)rrrrrr) npoints_timer*r-ifftuidZ npoints_freqZ delta_f_tmpZvecZvectilde fft_classinvecoutvecrrr ,create_memory_and_engine_for_class_based_ffts,     rc Csddlm}|r"t|dd}nt|}y |j}Wn tk rT|sNd}nYnX||}t|||||d\} } } |dk r|jdd| jdd<| |r|r| j| j9_n| j| j 9_|r| } | S)a Executes a cached FFT Parameters ----------- invec_data : Array Array which will be used as input when fft_class is executed. normalize_by_rate : boolean (optional, default:False) If True, then normalize by delta_t (for an FFT) or delta_f (for an IFFT). ifft : boolean (optional, default:False) If true assume this is an IFFT and multiply by delta_f not delta_t. Will do nothing if normalize_by_rate is False. copy_output : boolean (optional, default:True) If True we will copy the output into a new array. This avoids the issue that calling this function again might overwrite output. However, if you know that the output array will not be used before this function might be called again with the same length, then setting this to False will provide some increase in efficiency. The uid can also be used to help ensure that data doesn't get unintentionally overwritten! uid : int (default: 0) Provide a unique identifier. This is used to provide a separate set of memory in the cache, for instance if calling this from different codes. r)real_same_precision_asrr,)r-rrN) pycbc.typesrr?r-AttributeErrorr_dataexecute_delta_fZ_delta_tr.) Z invec_dataZnormalize_by_rater copy_outputrrrr-r*rrrrrr execute_cached_fft+s6  rcOst||ddiS)a Executes a cached IFFT Parameters ----------- invec_data : Array Array which will be used as input when fft_class is executed. normalize_by_rate : boolean (optional, default:False) If True, then normalize by delta_t (for an FFT) or delta_f (for an IFFT). copy_output : boolean (optional, default:True) If True we will copy the output into a new array. This avoids the issue that calling this function again might overwrite output. However, if you know that the output array will not be used before this function might be called again with the same length, then setting this to False will provide some increase in efficiency. The uid can also be used to help ensure that data doesn't get unintentionally overwritten! uid : int (default: 0) Provide a unique identifier. This is used to provide a separate set of memory in the cache, for instance if calling this from different codes. rT)r)argsrrrr execute_cached_ifftksrikim.i['cseZdZddddddddd d d d d d d d d d d d ejd d d d d d d ffdd ZeddZeddZddZ ddZ ddZ ddZ ddZ ddZd%fd!d" Zed#d$ZZS)& StrainBufferiig.@gi@g@g @g?NTrc % stt|j|||d||d||_||_||_d|_d|_d|_||_ |dk rt j |j} t d|t| t j j||||| ||d|_|dk rt|||d}!t|jdkr|jddkrd |!d <t d |n$t j |j|!d <t d |t| t j j|||f|!|_|dk rZ|dkr*td|dkrsuperrrr2 analyze_flagsdata_quality_flagsstatedqidq dq_paddingr=ruZflag_names_to_bitmaskrrrsbinZ StatusBufferdictr?rxZ iDQBufferhighpass_frequencyhighpass_reductionhighpass_bandwidthrrrrjrkrr9rpsd_abort_differencepsd_recalculate_differencepsd_segment_length psd_samplespsd_inverse_lengthr@psdsr8rrr:r|r6r raw_bufferrbetahighpass_samplesrwr-factor corruptionZpsd_corruptiontotal_corruption trim_paddingrN reduced_padsegmentsadd_hard_counttaper_immediate_strain)%r frame_srcrvr3rr9r2rrrrrrr rrrrjrk state_channeldata_quality_channel idq_channelidq_state_channel idq_thresholdrrrrrr r rrZ sb_kwargsZ strain_lenrZresample_corruption) __class__rr rsk            zStrainBuffer.__init__cCs |j|jS)z< Return the start time of the current valid segment of data )r\ blocksize)rrrr r3kszStrainBuffer.start_timecCs"t|jjt|j|j|jS)z: Return the end time of the current valid segment of data )r<r6r3r?rr9)rrrr r\pszStrainBuffer.end_timecCs*tt|j|j|j|_|dS)zm Reset the countdown timer, so that we don't analyze data long enough to generate a new PSD. 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A new one will be generated when it is next required N)r@r)rrrr r.|szStrainBuffer.invalidate_psdcCs,t|j|j}t|j}||jd|d}tjj|j||||dd}t |dd|j tj |_ |jr|j rt|jj |j |jj |j krtd|j|jj |j dS|jr |jr t|jj |j |jj |jkr td|j|jj |j ||_i|_dS||_i|_td |j|j dS) z Recalculate the psd rr,)r0r1gffffff?z'Skipping recalculation of %s PSD, %s-%sTz$%s PSD is CRAZY, aborting!!!!, %s-%sFzRecalculating %s PSD, %s)r8r9rr?r6rr=r@rArr2 DYN_RANGE_FACdistrrIrrrsdetectorrr)rr0esr@rrr recalculate_psds*    "zStrainBuffer.recalculate_psdcCs||jkrtd|}t|j}t|||j|jd}t|j||dtd}|jj||jj |_||j krt j |j |j}t j j|t|j|j|jd}|j|_t j |j |}t j j|t|j|j|jd}||_||j |<|j |}||j}|jdkrt|dtd}||jt||j} |jd|j} | jd| f| jd| fg} t| | t| d td} |j|j|jj | _n|} || _ | |j|<|j|} | S) a Return overwhitened data Parameters ---------- delta_f: float The sample step to generate overwhitened frequency domain data for Returns ------- htilde: FrequencySeries Overwhited strain data g?r,F)rr)r2rg@gT)r"r8r?r6r9r!rSTRAINBUFFER_UNIQUE_ID_1_epochr-rr=r@rBrErDrr2rpsdtrSTRAINBUFFER_UNIQUE_ID_2r r3r\rSTRAINBUFFER_UNIQUE_ID_3)rrEZ buffer_lengthr2r3Zfseriesr7r@Z overwhiteZ overwhite2Z taper_windowrZfseries_trimmedrrrr overwhitened_datasR              zStrainBuffer.overwhitened_datacCs*|js dS|j|j|jtjjs&dSdS)zdCheck that the current set of triggers could be influenced by a hardware injection. 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