B }d0a@sdZddlZddlmZddlmZddlmZddlm Z ddl m Z m Z dd l mZdd lmZdd lmZd Zd ZdZddZddZddZed/ddZd0ddZddZed1ddZed2d d!Zed3d#d$Zd4d'd(Zdddd)ed*dfd+d,Z dddd)ed*dfd-d.Z!dS)5zzThis module provides methods to calculate the astrophysical sensitive distance of an instrumental power-spectral density. N)wraps)pi)trapz)interp1d)units constants) Spectrogram) TimeSeries)round_to_powerz(Duncan Macleod z%Alex Urban ZmediancCs8t||dd}tjdtjdt|dS)aDetermine the innermost stable circular orbit (ISCO) frequency Parameters ---------- mass1 : `float` the mass (in solar masses) of the first binary component mass2 : `float` the mass (in solar masses) of the second binary component Returns ------- fisco : `~astropy.units.Quantity` linear frequency (Hz) of the innermost stable circular orbit solMasskggƱ d-@Hz)rQuantitytorcGr)mass1mass2mtotalr]/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/gwpy/astro/range.py_get_isco_frequency.src KsDt|ts@y|jf|}Wn$ttfk r>d}t|YnX|S)aCheck that the input is a spectrogram, or compute one if compatible Parameters ---------- hoft : `~gwpy.timeseries.TimeSeries` or `~gwpy.spectrogram.Spectrogram` record of gravitational-wave strain output from a detector **kwargs : `dict`, optional additional keyword arguments to `~gwpy.timeseries.TimeSeries.spectrogram` Returns ------- hoft : `~gwpy.spectrogram.Spectrogram` a time-frequency `Spectrogram` of the input zCould not produce a spectrogram from the input, please pass an instance of gwpy.timeseries.TimeSeries or gwpy.spectrogram.Spectrogram) isinstancer spectrogramAttributeError TypeError)hoftkwargsmsgrrr_get_spectrogramDs r!cstfdd}|S)Ncs2|jdtjkr"|}|d|f||S)Nz1/Hz)unitrrview override_unit)psdargsr)funcrrdecorated_funcas z&_preformat_psd..decorated_func)r)r(r)r)r(r_preformat_psd`sr*ffffff?Fc Cs|jdk}t|dd}t|dd}||}||d|d}|rRdnddtjd |tjtjd d d td |d }d|||j|d|dS)aApproximate the inspiral sensitive distance PSD from a GW strain PSD This method returns the power spectral density (in ``Mpc**2 / Hz``) to which a compact binary inspiral with the given component masses would be detectable given the instrumental PSD. The calculation is defined in: https://dcc.ligo.org/LIGO-T030276/public Parameters ---------- psd : `~gwpy.frequencyseries.FrequencySeries` the instrumental power-spectral-density data snr : `float`, optional the signal-to-noise ratio for which to calculate range, default: `8` mass1 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the first binary component, default: `1.4` mass2 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the second binary component, default: `1.4` horizon : `bool`, optional if `True`, return the maximal 'horizon' sensitive distance, otherwise return the angle-averaged range, default: `False` Returns ------- rspec : `~gwpy.frequencyseries.FrequencySeries` the calculated inspiral sensitivity PSD [Mpc^2 / Hz] rr r g333333?g?gr - @gUUUUUU?rg?`gUUUUUU?r"gz Mpc^2 / Hz) frequenciesrrrrrrr) r&snrrrhorizonfrangerZmchirpZ prefactorrrrsensemon_range_psdls$ 0r4c Cst||}t|p|jd}t|p&|d}||krLtd|||f|}|jd}||k||k@} t|| ||||d} tjt | j |j | | j tj dddS)aOApproximate the inspiral sensitive distance from a GW strain PSD This method returns the distance (in megaparsecs) to which a compact binary inspiral with the given component masses would be detectable given the instrumental PSD. The calculation is as defined in: https://dcc.ligo.org/LIGO-T030276/public Parameters ---------- psd : `~gwpy.frequencyseries.FrequencySeries` the instrumental power-spectral-density data snr : `float`, optional the signal-to-noise ratio for which to calculate range, default: `8` mass1 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the first binary component, default: `1.4` mass2 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the second binary component, default: `1.4` fmin : `float`, optional the lower frequency cut-off of the integral, default: `psd.df` fmax : `float`, optional the maximum frequency limit of the integral, defaults to innermost stable circular orbit (ISCO) frequency horizon : `bool`, optional if `True`, return the maximal 'horizon' sensitive distance, otherwise return the angle-averaged range, default: `False` Returns ------- range : `~astropy.units.Quantity` the calculated inspiral range [Mpc] Examples -------- Grab some data for LIGO-Livingston around GW150914 and generate a PSD: >>> from gwpy.timeseries import TimeSeries >>> hoft = TimeSeries.fetch_open_data('H1', 1126259446, 1126259478) >>> hoff = hoft.psd(fftlength=4) Now we can calculate the :func:`sensemon_range`: >>> from gwpy.astro import sensemon_range >>> r = sensemon_range(hoff, fmin=30) >>> print(r) 70.4612102889 Mpc rzIUpper frequency bound greater than %s-%s ISCO frequency of %s, using ISCO)r1rrr2)r#g?Mpc) rrrdfwarningswarnr0rr4rvaluer#ZHertz) r&r1rrfminfmaxr2Zfiscofr3 integrandrrrsensemon_ranges:    r>c Cs^yddlm}m}Wn2tk rF}zt|d|_Wdd}~XYnXddlm}|||fS)Nr)rangefind_root_redshifta; gwpy.astro's inspiral_range and inspiral_range_psd functions require the extra package 'inspiral-range' to provide cosmologically-corrected distance calculations, please install that package and try again, or install gwpy with the 'astro' extra via `python -m pip install gwpy[astro]`) CBCWaveform)inspiral_ranger?r@ModuleNotFoundErrorstrr Zinspiral_range.waveformrA)r?r@excrArrr_import_inspiral_ranges rFc st\}}}jdj|dkf||d||fdd} |r^j| n |dkjdk| d} | \} } t| | d| ddfd} td | d | d jdk} | | d dkd| _ | S) acCalculate the cosmology-corrected inspiral sensitive distance PSD This method returns the power spectral density (in ``Mpc**2 / Hz``) to which a compact binary inspiral with the given component masses would be detectable given the instrumental PSD. The calculation is defined in Belczynski et. al (2014): https://dx.doi.org/10.1088/0004-637x/789/2/120 Parameters ---------- psd : `~gwpy.frequencyseries.FrequencySeries` the instrumental power-spectral-density data snr : `float`, optional the signal-to-noise ratio for which to calculate range, default: `8` mass1 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the first binary component, default: `1.4` mass2 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the second binary component, default: `1.4` horizon : `bool`, optional if `True`, return the maximal 'horizon' luminosity distance, otherwise return the angle-averaged comoving distance, default: `False` **kwargs : `dict`, optional additional keyword arguments to `~inspiral_range.waveform.CBCWaveform` Returns ------- rspec : `~gwpy.frequencyseries.FrequencySeries` the calculated inspiral sensitivity PSD [Mpc^2 / Hz] See also -------- sensemon_range_psd for the method based on LIGO-T030276, also known as LIGO SenseMonitor inspiral-range the package which does heavy lifting for waveform simulation and cosmology calculations rr)m1m2csjdk|S)Nr)SNRr9)z)r<inspiralr&r1rrKz$inspiral_range_psd..)z_horHF)Z bounds_errorZ fill_valuerz Mpc^2 / Hz) rFr0rr9cosmoluminosity_distanceZz_scalertype__array_finalize__r%f0)r&r1rrr2r range_funcr@rArNdistZfzhzoutr)r<rKr&r1rinspiral_range_psds2 ".  rZc  st\}} } jdj} |p$jj}|p8t| ddd}| |k| |k@| | f||d|| fdd} tj|rj | n|| j| dd d S) aCalculate the cosmology-corrected inspiral sensitive distance This method returns the distance (in megaparsecs) to which a compact binary inspiral with the given component masses would be detectable given the instrumental PSD. The calculation is defined in Belczynski et. al (2014): https://dx.doi.org/10.1088/0004-637x/789/2/120 Parameters ---------- psd : `~gwpy.frequencyseries.FrequencySeries` the instrumental power-spectral-density data snr : `float`, optional the signal-to-noise ratio for which to calculate range, default: `8` mass1 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the first binary component, default: `1.4` mass2 : `float`, `~astropy.units.Quantity`, optional the mass (`float` assumed in solar masses) of the second binary component, default: `1.4` fmin : `float`, optional the lower frequency cut-off of the integral, default: `psd.df` fmax : `float`, optional the maximum frequency limit of the integral, defaults to the rest-frame innermost stable circular orbit (ISCO) frequency horizon : `bool`, optional if `True`, return the maximal 'horizon' luminosity distance, otherwise return the angle-averaged comoving distance, default: `False` **kwargs : `dict`, optional additional keyword arguments to `~inspiral_range.waveform.CBCWaveform` Returns ------- range : `~astropy.units.Quantity` the calculated inspiral range [Mpc] Examples -------- Grab some data for LIGO-Livingston around GW150914 and generate a PSD: >>> from gwpy.timeseries import TimeSeries >>> hoft = TimeSeries.fetch_open_data('H1', 1126259446, 1126259478) >>> hoff = hoft.psd(fftlength=4) Now, we can calculate the :func:`inspiral_range`: >>> from gwpy.astro import inspiral_range >>> r = inspiral_range(hoff, fmin=30) >>> print(r) 70.4612102889 Mpc See also -------- sensemon_range for the method based on LIGO-T030276, also known as LIGO SenseMonitor inspiral-range the package which does heavy lifting for waveform simulation and cosmology calculations rlower)which)rGrHcsj|S)N)rIr9)rJ)r3rKr&r1rrrLrMz inspiral_range..)rNrOr5)r#) rFr0rr9r6r rrrQrR) r&r1rrr:r;r2rrVr@rAr<rNr)r3rKr&r1rrB\sH  rB{Gz?cCsT|jdk}tj|tjdtdtjd}||d|||j|dS)aGCalculate the frequency-dependent GW burst range from a strain PSD Parameters ---------- psd : `~gwpy.frequencyseries.FrequencySeries` the instrumental power-spectral-density data snr : `float`, optional the signal-to-noise ratio for which to calculate range, default: `8` energy : `float`, optional the relative energy output of the GW burst, default: `0.01` (GRB-like burst) Returns ------- rangespec : `~gwpy.frequencyseries.FrequencySeries` the burst range `FrequencySeries` [Mpc (default)] rg?rg?gr5)r0rrZM_sunrrr)r&r1energyr3arrrburst_range_spectrums   radc Cs|jdj}|p|jdj}|p,|dj}||k||k@}t||||dd}t|j||}tj||||jdddS)aCalculate the integrated GRB-like GW burst range from a strain PSD Parameters ---------- psd : `~gwpy.frequencyseries.FrequencySeries` the instrumental power-spectral-density data snr : `float`, optional the signal-to-noise ratio for which to calculate range, default: ``8`` energy : `float`, optional the relative energy output of the GW burst, defaults to ``1e-2`` for a GRB-like burst fmin : `float`, optional the lower frequency cutoff of the burst range integral, default: ``100 Hz`` fmax : `float`, optional the upper frequency cutoff of the burst range integral, default: ``500 Hz`` Returns ------- range : `~astropy.units.Quantity` the GRB-like-burst sensitive range [Mpc (default)] Examples -------- Grab some data for LIGO-Livingston around GW150914 and generate a PSD >>> from gwpy.timeseries import TimeSeries >>> hoft = TimeSeries.fetch_open_data('H1', 1126259446, 1126259478) >>> hoff = hoft.psd(fftlength=4) Now we can calculate the :func:`burst_range`: >>> from gwpy.astro import burst_range >>> r = burst_range(hoff, fmin=30) >>> print(r) 42.5055584195 Mpc rr[)r1r_r)r#gUUUUUU?r5) r0rr9r6rarrrr#) r&r1r_r:r;r<r3r=rYrrr burst_ranges, rdZhannr"c svp ddddkr$dkr$tn dkr0tt|||||||d}tfdd|D} | || d| S) a Measure timeseries trends of astrophysical detector range (Mpc) directly from strain Parameters ---------- hoft : `~gwpy.timeseries.TimeSeries` or `~gwpy.spectrogram.Spectrogram` record of gravitational-wave strain output from a detector stride : `float`, optional desired step size (seconds) of range timeseries, required if `hoft` is an instance of `TimeSeries` fftlength : `float`, optional number of seconds in a single FFT overlap : `float`, optional number of seconds of overlap between FFTs, defaults to the recommended overlap for the given window (if given), or 0 window : `str`, `numpy.ndarray`, optional window function to apply to timeseries prior to FFT, see :func:`scipy.signal.get_window` for details on acceptable formats method : `str`, optional FFT-averaging method, defaults to median averaging, see :meth:`~gwpy.timeseries.TimeSeries.spectrogram` for more details nproc : `int`, optional number of CPUs to use in parallel processing of FFTs, default: 1 range_func : `callable`, optional the function to call to generate the range for each stride, defaults to ``inspiral_range`` unless ``energy`` is given as a keyword argument to the range function **rangekwargs : `dict`, optional additional keyword arguments to :func:`burst_range` or :func:`inspiral_range` (see "Notes" below), defaults to inspiral range with `mass1 = mass2 = 1.4` solar masses Returns ------- out : `~gwpy.timeseries.TimeSeries` timeseries trends of astrophysical range Notes ----- This method is designed to quantify a gravitational-wave detector's sensitive range as a function of time. It supports the range to compact binary inspirals and to unmodelled GW bursts, each a class of transient event. See also -------- gwpy.timeseries.TimeSeries.spectrogram for the underlying power spectral density estimator inspiral_range for the function that computes inspiral range burst_range for the function that computes burst range range_spectrogram for a `~gwpy.spectrogram.Spectrogram` of the range integrand gffffff?)rrNr_)stride fftlengthoverlapwindowmethodnproccsg|]}|fjqSr)r9).0r&)rV rangekwargsrr ssz$range_timeseries..r5)rdrBr!r rTr%) rrerfrgrhrirjrVrlrYr)rVrlrrange_timeseriessL   rnc sp ddddkr$dkr$tn dkr0tt|||||||d}|jd} td|jd} tdt | d j d d d} | | k| | k@t fd d |D} | || dkrdnd| | _| S)a Calculate the average range or range power spectrogram (Mpc or Mpc^2 / Hz) directly from strain Parameters ---------- hoft : `~gwpy.timeseries.TimeSeries` or `~gwpy.spectrogram.Spectrogram` record of gravitational-wave strain output from a detector stride : `float`, optional number of seconds in a single PSD (i.e., step size of spectrogram), required if `hoft` is an instance of `TimeSeries` fftlength : `float`, optional number of seconds in a single FFT overlap : `float`, optional number of seconds of overlap between FFTs, defaults to the recommended overlap for the given window (if given), or 0 window : `str`, `numpy.ndarray`, optional window function to apply to timeseries prior to FFT, see :func:`scipy.signal.get_window` for details on acceptable formats method : `str`, optional FFT-averaging method, defaults to median averaging, see :meth:`~gwpy.timeseries.TimeSeries.spectrogram` for more details nproc : `int`, optional number of CPUs to use in parallel processing of FFTs, default: 1 fmin : `float`, optional low frequency cut-off (Hz), defaults to `1/fftlength` fmax : `float`, optional high frequency cut-off (Hz), defaults to Nyquist frequency of `hoft` range_func : `callable`, optional the function to call to generate the range for each stride, defaults to ``inspiral_range`` unless ``energy`` is given as a keyword argument to the range function **rangekwargs : `dict`, optional additional keyword arguments to :func:`burst_range_spectrum` or :func:`inspiral_range_psd` (see "Notes" below), defaults to inspiral range with `mass1 = mass2 = 1.4` solar masses Returns ------- out : `~gwpy.spectrogram.Spectrogram` time-frequency spectrogram of astrophysical range Notes ----- This method is designed to show the contribution to a gravitational-wave detector's sensitive range across frequency bins as a function of time. It supports the range to compact binary inspirals and to unmodelled GW bursts, each a class of transient event. If inspiral range is requested and `fmax` exceeds the frequency of the innermost stable circular orbit (ISCO), the output will extend only up to the latter. See also -------- gwpy.timeseries.TimeSeries.spectrogram for the underlying power spectral density estimator inspiral_range_psd for the function that computes inspiral range integrand burst_range_spectrum for the function that computes burst range integrand range_timeseries for `TimeSeries` trends of the astrophysical range gffffff?)rrNr_)rerfrgrhrirjrr:r;r[r\)r]csg|]}|fjqSr)r9)rkr&)r3rVrlrrrmsz%range_spectrogram..r5z Mpc^2 / Hz)rarZr!r0rrrpopr6r r9r rTr%rU) rrerfrgrhrirjrVrlr<r:r;rYr)r3rVrlrrange_spectrogram{s2W    rp)r+r,r,F)r+r,r,NNF)r+r,r,F)r+r,r,NNF)r+r^)r+r^rbrc)"__doc__r7 functoolsrmathrZscipy.integraterZscipy.interpolaterZastropyrrrr Z timeseriesr utilsr __author__ __credits__ZDEFAULT_FFT_METHODrr!r*r4r>rFrZrBrardrnrprrrrsT         < N J ` @ X