minke package¶

Submodules¶

minke.distribution module¶

minke.distribution.burst_dist(minimum, maximum, size=1)[source]¶

Generate an hrss drawn from the distribution [ r + 50/r ] as desired by the Burst group for observing MDCs

minke.distribution.even_time(start, stop, rate, jitter=0)[source]¶

Produce an evenly-distributed set of times which has some jitter.

Parameters:	start : int The gps start time of the set. stop : int The gps end time of the set. rate : int The rate of events per year. jitter : float The number of seconds around which the time can “jitter”. This has the effect of adding a small random time on to each time returned in the distribution, up to a maximum of half the jitter value, or taking away up to half the jitter value.
Returns:	times : ndarray A numpy array of gps times where injections should be made.

minke.distribution.favorable_sky(net, time)[source]¶

Wander through the skies, searching for a most favorable location — draw extrinsic parameters as if the network antenna pattern magnitude were the PDF.

minke.distribution.log_uniform(lower, upper, number)[source]¶

Draw uniformly in the log of a predefined range.

Parameters:	lower : float The lower hrss value (n.b. not the lower log(hrss) value) upper : float The upper hrss value (n.b. not the upper log(hrss) value) number : int The number of samples to be drawn from the distribution.
Returns:	sample : float An sample value drawn from the log uniform distribution.

minke.distribution.sky_params(net, time, ra, dec, psi, incl=3.141592653589793)[source]¶

minke.distribution.supernova_angle(num, divisions=10)[source]¶

Draw from a discrete distribution of angles.

minke.distribution.uniform_dec(num)[source]¶

Declination distribution: uniform in sin(dec). num controls the number of draws.

minke.distribution.uniform_interval(interval, num)[source]¶

Return a number, or a list of numbers which are sampled from a uniform distribution.

Parameters:	interval : tuple (lower, upper) The interval which the uniform distribution covers. num : int The number of samples which should be drawn from the distribution.
Returns:	sample : float or list A sample, or a list of samples.

Notes

http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.random_sample.html#numpy.random.random_sample

minke.distribution.uniform_phi(num)[source]¶

Uniform in (0, 2pi) distribution. num controls the number of draws.

minke.distribution.uniform_sky(number=1)[source]¶

Get a set of (RA, declination, polarization) randomized appopriately to astrophysical sources isotropically distributed in the sky.

minke.distribution.uniform_theta(num)[source]¶

Uniform in cos distribution. num controls the number of draws.

minke.distribution.uniform_time(tstart, tstop, number)[source]¶

Get a set of randomized (integer) event times.

minke.mdctools module¶

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This file is a part of Minke, a tool for generating simulated gravitational wave signals, used for characterising and training search algorithms.

Minke was created by Daniel Williams, based on work started by Chris Pankow and others, and is built around the LALSimulation library.

class minke.mdctools.Frame(start, duration, ifo)[source]¶

Represents a frame, in order to prepare the injection frames

Methods

generate_gwf(mdc, directory[, channel, …])	Produce the gwf file which corresponds to the MDC set over the period of this frame.
get_rowlist(mdcs)	Return the rows from an MDC set which correspond to this frame.

calculate_n_injections
generate_log

calculate_n_injections(mdcs)[source]¶

generate_gwf(mdc, directory, channel='SCIENCE', force=False, rate=16384.0)[source]¶

Produce the gwf file which corresponds to the MDC set over the period of this frame.

Parameters:

mdc : MDCSet object The MDC set which should be used to produce this frame. directory : str The root directory where all of the frames are to be stored, for example “/home/albert.einstein/data/mdc/frames/” would cause the SineGaussian injections to be made in the directories under “/home/albert.einstein/data/mdc/frames/sg” channel : str The name of the channel which the injections should be made into. This is prepended by the initials for each interferometer, so there will be a channel for each interferometer in the gwf. force : bool If true this forces the recreation of a GWF file even if it already exists.

generate_log(mdc)[source]¶

get_rowlist(mdcs)[source]¶

Return the rows from an MDC set which correspond to this frame.

Parameters:	mdcs : MDCSet object The set of MDCs from which the rows are to be found.

class minke.mdctools.FrameSet(frame_list)[source]¶

Methods

full_frameset(mdc, directory[, channel, force])	Produce the gwf files which corresponds to the MDC set over the period of the frames in this collection.
full_logfile(mdc, location)	Produce a log file for the entire frame set

full_frameset(mdc, directory, channel='SCIENCE', force=False)[source]¶

Produce the gwf files which corresponds to the MDC set over the period of the frames in this collection.

Parameters:

mdc : MDCSet object The MDC set which should be used to produce this frame. directory : str The root directory where all of the frames are to be stored, for example “/home/albert.einstein/data/mdc/frames/” would cause the SineGaussian injections to be made in the directories under “/home/albert.einstein/data/mdc/frames/sg” channel : str The name of the channel which the injections should be made into. This is prepended by the initials for each interferometer, so there will be a channel for each interferometer in the gwf. force : bool If true this forces the recreation of a GWF file even if it already exists.

full_logfile(mdc, location)[source]¶

Produce a log file for the entire frame set

class minke.mdctools.HWFrameSet(ifos=['H1', 'L1'])[source]¶

Methods

full_frameset(mdc, directory[, force])

Produce the gwf files which corresponds to the MDC set over the period of the frames in this collection.

full_frameset(mdc, directory, force=False)[source]¶

Produce the gwf files which corresponds to the MDC set over the period of the frames in this collection.

Parameters:

mdc : MDCSet object The MDC set which should be used to produce this frame. directory : str The root directory where all of the frames are to be stored, for example “/home/albert.einstein/data/mdc/frames/” would cause the SineGaussian injections to be made in the directories under “/home/albert.einstein/data/mdc/frames/sg” force : bool If true this forces the recreation of a GWF file even if it already exists.

class minke.mdctools.HWInj(ifos)[source]¶

Bases: minke.mdctools.Frame

Represents a hardware injection frame.

Injection frames must be an ASCII file of the hoft sampled at the antenna sampling rate, appropriately convolved with an antenna response function.

As a result of the simplicity of this specific output format we do not need information such as start-time in the file itself, however we should have a sensible naming scheme for the ASCII files since they will need to be produced as sidecars for an xml file.

Methods

generate_gwf(mdc, directory[, channel, …])	Produce the gwf file which corresponds to the MDC set over the period of this frame.
generate_pcal(mdc, directory[, force, rate])	Produce the PCAL-ready hardware injection files as an ASCII list sampled at the detector’s sample rate.
get_rowlist(mdcs)	Return the rows from an MDC set which correspond to this frame.

calculate_n_injections
generate_log

generate_pcal(mdc, directory, force=False, rate=16384)[source]¶

Produce the PCAL-ready hardware injection files as an ASCII list sampled at the detector’s sample rate.

Parameters:

mdc : MDCSet object The signal set which should be used to generate the frame. directory : str The root directory where all of the frames are to be stored, for example “/home/albert.einstein/data/mdc/frames/” would cause the SineGaussian injections to be made in the directories under “/home/albert.einstein/data/mdc/frames/sg” force : bool If true this forces the regeneration of the file, even if it already exists.

class minke.mdctools.MDCSet(detectors, name='MDC Set', table_type='burst')[source]¶

Methods

directory_path()	Generate the directory where the frames from this MDC should be stored, so, e.g.
gravEn_row(row, frame)	Produces a gravEn-style log row for a row of the simBurstTable.
load_xml(filename[, full, start, stop])	Load the MDC Set from an XML file containing the SimBurstTable.
plot_hist(parameter)	Plot a histogram of a waveform parameter.
plot_skymap()	Plot a skymap of the injections distribution in RA and DEC on a Hammer projection.
save_xml(filename)	Save the MDC set as an XML SimBurstTable.

directory_path()[source]¶

Generate the directory where the frames from this MDC should be stored, so, e.g. Gaussians 0d100 would go in “ga/ga0d100/”

Returns:	str the folder structure

gravEn_row(row, frame)[source]¶

Produces a gravEn-style log row for a row of the simBurstTable.

Parameters:	row : int The row number of the waveforms to be measured
Returns:	str A string in the gravEn format which describes the injection.

hist_parameters = {'BTLWNB': ['hrss', 'ra', 'dec'], 'Dimmelmeier+08': ['hrss', 'ra', 'dec'], 'Gaussian': ['hrss', 'psi', 'ra', 'dec'], 'SineGaussian': ['hrss', 'psi', 'ra', 'dec']}¶

inj_families_abb = {'ADI': 'adi', 'BBHRingdown': 'rng', 'BTLWNB': 'wnb', 'Dimmelmeier+08': 'd08', 'Gaussian': 'ga', 'GenericRingdown': 'gng', 'Mueller+12': 'm12', 'Ott+13': 'o13', 'Scheidegger+10': 's10', 'SineGaussian': 'sg'}¶

inj_families_names = {'adi': 'ADI', 'd08': 'Dimmelmeier+08', 'ga': 'Gaussian', 'gng': 'GenericRingdown', 'm12': 'Mueller+12', 'o13': 'Ott+13', 'rng': 'BBHRingdown', 's10': 'Scheidegger+10', 'sg': 'SineGaussian', 'wnb': 'BTLWNB'}¶

load_xml(filename, full=True, start=None, stop=None)[source]¶

Load the MDC Set from an XML file containing the SimBurstTable.

Parameters:

filename : str The filename of the XML file. full : bool If this is true (which is the default) then all of the calculated parameters are computed from the waveform definintion. start : float The time at which the xml read-in should start. The default is “None”, in which case the xml file will be read-in from the start. end : float The last time to be read from the xml file. The default is None, which causes the xml to be read right-up to the last time in the file.

plot_hist(parameter)[source]¶

Plot a histogram of a waveform parameter.

Parameters:	parameter : str The name of the simburst table parameter which is desired for the plot.
Returns:	matplotlib figure

plot_skymap()[source]¶

Plot a skymap of the injections distribution in RA and DEC on a Hammer projection.

Returns:	matplotlib figure

save_xml(filename)[source]¶

Save the MDC set as an XML SimBurstTable.

Parameters:	filename : str The location to save the xml file. The output is gzipped, so ending it with a “.gz” would stick with convention.

waveforms = []¶

exception minke.mdctools.TableTypeError[source]¶

Bases: exceptions.Exception

minke.mdctools.mkdir(path)[source]¶

Make all of the tree of directories in a given path if they don’t already exist.

Parameters:	path : str The path to the desired directory.

minke.mdctools.source_from_row(row)[source]¶

minke.sources module¶

class minke.sources.ADI(time, sky_dist=<function uniform_sky>, filepath='stamp_adi_a_tapered.mat', decomposed_path=None)[source]¶

Bases: minke.sources.LongDuration

Accretion disk instability waveforms which are generated using the method described in LIGO-T1100093, at https://dcc.ligo.org/LIGO-T1100093. The waveforms are based off a model by MH van Putten,

M. H. van Putten, A. Levinson, H. K. Lee, T. Regimbau, M. Punturo, and G. M. Harry. Phys. Rev. D., 69(4), 044007, 2004. M. H. van Putten. Phys. Rev. Lett., 87(9), 091101, 2001.

The waveforms are stored in .mat binary files which can be read-in by SciPy.

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of the ADI waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

decompose(numrel_file, sample_rate=16384.0, step_back=0.01)[source]¶

Produce the spherial harmonic decompositions of the ADI waveform. This is a special case since it is axisymmetric.

Parameters:	numrel_file : str The location of the numerical relativity waveform file. sample_rate : float The sample rate of the output NR file. Defaults to 16384.0 Hz, and should be the same as the data rate of the detector. step_back : float The amount of time, in seconds, of the data which should be included before the peak amplitude. Defaults to 0.01 sec.
Returns:	decomposition : ndarray The re-interpolated file at the desired sample rate which is in the <time hp hc> format which can be accepted by LALSimulation.

waveform = 'ADI'¶

class minke.sources.BBHRingdown(time, phi0, mass, spin, massloss, distance, inclination, sky_dist=<function uniform_sky>)[source]¶

Bases: minke.sources.Ringdown

A class to represent BBH ringdowns.

Methods

interpolate(x_old, y_old, x_new[, method])	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

waveform = 'BBHRingdown'¶

class minke.sources.Dimmelmeier08(time, distance=0.01, sky_dist=<function uniform_sky>, filepath='signal_s15a2o05_ls.dat', decomposed_path=None)[source]¶

Bases: minke.sources.Supernova

The Dimmelmeier08 waveform.

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of the Dimmelmeier numerical waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

decompose(numrel_file, sample_rate=16384.0, step_back=0.01)[source]¶

Produce the spherial harmonic decompositions of the Dimmelmeier numerical waveform. This is a special case since it is axisymmetric.

Parameters:	numrel_file : str The location of the numerical relativity waveform file. sample_rate : float The sample rate of the NR file. Defaults to 16384.0 Hz. step_back : float The amount of time, in seconds, of the data which should be included before the peak amplitude. Defaults to 0.01 sec.
Returns:	decomposition : ndarray The l=2 mode spherical decompositions of the waveform.

waveform = 'Dimmelmeier+08'¶

class minke.sources.Gaussian(duration, hrss, time, sky_dist=<function uniform_sky>, seed=0)[source]¶

Bases: minke.sources.Waveform

A class to represent a Gaussian injection.

Methods

interpolate(x_old, y_old, x_new[, method])	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

waveform = 'Gaussian'¶

class minke.sources.LongDuration[source]¶

Bases: minke.sources.Supernova

A superclass to handle the spherial harmonic decompositions which long duration numerical relativity bursts may require.

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of a numerical waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

supernova = True¶

waveform = 'LongDuration'¶

class minke.sources.Mueller2012(theta, phi, time, distance=0.01, sky_dist=<function uniform_sky>, filepath=None, family='L15-3', decomposed_path=None)[source]¶

Bases: minke.sources.Supernova

The Mueller2012 waveform.

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of a numerical waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

decompose(numrel_file, sample_rate=16384.0, step_back=0.01)[source]¶

Produce the spherial harmonic decompositions of a numerical waveform.

Parameters:

numrel_file : str The location of the numerical relativity waveform file. sample_rate : float The sample rate of the NR file. Defaults to 16384.0 Hz. step_back : float The amount of time, in seconds, of the data which should be included before the peak amplitude. Defaults to 0.01 sec. distance : float The distance, in megaparsecs, from the observer at which the NR waveforms were simulated. Defaults to 10 kpc (i.e. 10e-3 Mpc).

Returns:

decomposition : ndarray The l=2 mode spherical decompositions of the waveform.

has_memory = True¶

waveform = 'Mueller+12'¶

class minke.sources.Ott2013(theta, phi, time, sky_dist=<function uniform_sky>, distance=0.01, filepath=None, family='s27fheat1p05', decomposed_path=None)[source]¶

Bases: minke.sources.Supernova

The Ott+2013 supernova waveform

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of a numerical waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

has_memory = True¶

waveform = 'Ott+13'¶

class minke.sources.Ringdown[source]¶

Bases: minke.sources.Waveform

A class to handle Rindown waveforms.

Methods

interpolate(x_old, y_old, x_new[, method])	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

table_type¶

alias of glue.ligolw.lsctables.SimRingdownTable

waveform = 'GenericRingdown'¶

class minke.sources.Scheidegger2010(theta, phi, time, distance=0.01, sky_dist=<function uniform_sky>, filepath=None, family='R1E1CA_L', decomposed_path=None)[source]¶

Bases: minke.sources.Supernova

The Scheidegger2010 waveform.

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of a numerical waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

waveform = 'Scheidegger+10'¶

class minke.sources.SineGaussian(q, frequency, hrss, polarisation, time, sky_dist=<function uniform_sky>, seed=0)[source]¶

Bases: minke.sources.Waveform

A class to represent a SineGaussian injection.

Methods

interpolate(x_old, y_old, x_new[, method])	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

waveform = 'SineGaussian'¶

class minke.sources.Supernova[source]¶

Bases: minke.sources.Waveform

A superclass to handle the spherial harmonic decompositions which all supernova waveforms require.

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of a numerical waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz, l=2, m=2)[source]¶

Construct the expansion parameters Hlm from T1000553. Returns the expansion parameters for l=2, m=m

decompose(numrel_file, sample_rate=16384.0, step_back=0.01)[source]¶

Produce the spherial harmonic decompositions of a numerical waveform.

Parameters:	numrel_file : str The location of the numerical relativity waveform file. sample_rate : float The sample rate of the NR file. Defaults to 16384.0 Hz. step_back : float The amount of time, in seconds, of the data which should be included before the peak amplitude. Defaults to 0.01 sec.
Returns:	decomposition : ndarray The l=2 mode spherical decompositions of the waveform.

file_distance = 0.01¶

generate_tail(sampling=16384.0, length=1, h_max=1e-23, h_min=0)[source]¶

Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.

This code was adapted from an iPython notebook provided by Marek Szczepanczyk.

The tail needs to be added to the waveform after all of the other corrections have been applied (DW: I think)

Parameters:	sampling : float The sample rate of the injection data. By default this is 16384 Hz, which is the standard advanced LIGO sampling rate. length : float The length of the tail to be added, in seconds; defaults to 1. h_max : float The strain at the beginning of the tail – the strain at the end of the NR data.

Notes

• TODO Confirm that the tail is added-on after the waveform is

convolved with the antenna pattern.

has_memory = False¶

interpolate(x_old, y_old, x_new)[source]¶

Convenience funtion to avoid repeated code

supernova = True¶

waveform = 'Supernova'¶

class minke.sources.Waveform[source]¶

Bases: object

Generic container for different source types. Currently, it checks for the waveform type and initializes itself appropriately. In the future, different sources should subclass this and override the generation routines.

Methods

interpolate(x_old, y_old, x_new[, method])	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

expnum = 1¶

interpolate(x_old, y_old, x_new, method='linear')[source]¶

Convenience funtion to avoid repeated code

numrel_data = []¶

parse_polarisation(polarisation)[source]¶

Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.

Parameters:	polarisation : str, {‘linear’, ‘circular’, ‘elliptical’, ‘inclination’} The description of the polarisation, in words.

plot(figsize=(10, 5))[source]¶

Produce a plot of the injection.

sim = []¶

table_type¶

alias of glue.ligolw.lsctables.SimBurstTable

waveform = 'Generic'¶

class minke.sources.WhiteNoiseBurst(duration, bandwidth, frequency, time, hrss=None, egw=None, sky_dist=<function uniform_sky>, seed=0)[source]¶

Bases: minke.sources.Waveform

A class to represent a WNB injection.

Methods

interpolate(x_old, y_old, x_new[, method])	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

waveform = 'BTLWNB'¶

class minke.sources.Yakunin10(time, distance=0.01, sky_dist=<function uniform_sky>, filepath='Yakunin2010/hplus-B12-WH07_tail.txt', decomposed_path=None)[source]¶

Bases: minke.sources.Supernova

The Yakunin10 waveform.

Methods

construct_Hlm(Ixx, Ixy, Ixz, Iyy, Iyz, Izz)	Construct the expansion parameters Hlm from T1000553.
decompose(numrel_file[, sample_rate, step_back])	Produce the spherial harmonic decompositions of the Dimmelmeier numerical waveform.
generate_tail([sampling, length, h_max, h_min])	Generate a “low frequency tail” to append to the end of the waveform to overcome problems related to memory in the waveform.
interpolate(x_old, y_old, x_new)	Convenience funtion to avoid repeated code
parse_polarisation(polarisation)	Convert a string description of a polarisation to an ellipse eccentricity and an ellipse angle.
plot([figsize])	Produce a plot of the injection.

table_type

decompose(numrel_file, sample_rate=16384.0, step_back=0.01)[source]¶

Produce the spherial harmonic decompositions of the Dimmelmeier numerical waveform. This is a special case since it is axisymmetric.

Parameters:	numrel_file : str The location of the numerical relativity waveform file. sample_rate : float The sample rate of the NR file. Defaults to 16384.0 Hz. step_back : float The amount of time, in seconds, of the data which should be included before the peak amplitude. Defaults to 0.01 sec.
Returns:	decomposition : ndarray The l=2 mode spherical decompositions of the waveform.

waveform = 'Yakunin+10'¶

Module contents¶