B d| @sZddlZddlZddlmZmZddlmZdZddZ ddd Z dd d Z dddZ dS)N) TimeSeriescomplex_same_precision_as) RandomStateicCs*t}t|d}|d}|j||ddS)a# Return block of normal random numbers Parameters ---------- seed : {None, int} The seed to generate the noise.sd sample_rate: float Sets the variance of the white noise Returns -------- noise : numpy.ndarray Array of random numbers lg?)sizescale) BLOCK_SAMPLESrnormal)seed sample_ratenumrngZvariancerf/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/pycbc/noise/reproduceable.pyblocks r@c st}tt||}tt||}||dkr@|d8}t|ddtfddt||ddD}t|d||d}| ||S) a# Generate data with a white Gaussian (normal) distribution Parameters ---------- start_time : int Start time in GPS seconds to generate noise end_time : int End time in GPS seconds to generate noise sample-rate: float Sample rate to generate the data at. Keep constant if you want to ensure continuity between disjoint time spans. seed : {None, int} The seed to generate the noise. Returns -------- noise : TimeSeries A TimeSeries containing gaussian noise rl l csg|]}t|qSr)r).0i)r svrr Qsznormal..g?)delta_tepoch) rintnumpyfloorrrandintZ concatenateZaranger time_slice) startendr r Z block_dursedatatsr)r rrr 3s r ?cCs|}t||jdd}t|} |||} xHtt|D]8} | | dkrh|| d|j| <|| dkrF| |j| <qFWt||} t||d|} |jdd|kr0tj |dd|}dtj j d|| |dd}| t |}|}|| |t| ||| |}n.tj |d| }dtj j d|| |dd}t||j}|d||d }~t||||||d }|}|||9}~|jd|d }~|||S) a Create noise from a PSD Return noise from the chosen PSD. Note that if unique noise is desired a unique seed should be provided. Parameters ---------- psd : pycbc.types.FrequencySeries PSD to color the noise start_time : int Start time in GPS seconds to generate noise end_time : int End time in GPS seconds to generate nosie seed : {None, int} The seed to generate the noise. sample_rate: {16384, float} The sample rate of the output data. Keep constant if you want to ensure continuity between disjoint time spans. low_frequency_cutof : {1.0, float} The low frequency cutoff to pass to the PSD generation. filter_duration : {128, float} The duration in seconds of the coloring filter Returns -------- noise : TimeSeries A TimeSeries containing gaussian noise colored by the given psd. rrrg?g@Zhann)low_frequency_cutoffZ trunc_methodNg?)r r )r)copyrdelta_flenresizemaxranger"pycbcpsdZ interpolateZinverse_spectrum_truncationZastyperZ to_timeseriesZrollZto_frequencyseriesclearZ squared_normr r)r. start_timeend_timer r r&filter_durationrflenZoldlenZmax_valrZfil_lenZwn_durZkminZasdZ white_noiseZcoloredrrr colored_noiseVsZ!           r4c CsFd|}t||dd} tj|| ||} t| |||||||dS)a Create noise from an analytic PSD Return noise from the chosen PSD. Note that if unique noise is desired a unique seed should be provided. Parameters ---------- psd_name : str Name of the analytic PSD to use. start_time : int Start time in GPS seconds to generate noise end_time : int End time in GPS seconds to generate nosie seed : {None, int} The seed to generate the noise. sample_rate: {16384, float} The sample rate of the output data. Keep constant if you want to ensure continuity between disjoint time spans. low_frequency_cutof : {10.0, float} The low frequency cutoff to pass to the PSD generation. filter_duration : {128, float} The duration in seconds of the coloring filter Returns -------- noise : TimeSeries A TimeSeries containing gaussian noise colored by the given psd. g?rr)r r r&r2r)rr-r.Z from_stringr4) Zpsd_namer0r1r r r&r2rr(r3r.rrrnoise_from_strings"r5)rr)rrr$r%r$)rrr$r%r$) rZ pycbc.psdr-Z pycbc.typesrrZ numpy.randomrrrr r4r5rrrrs  $ ]