Using gwpopulation_pipe
The format of gwpopulation_pipe
is based on the bilby_pipe
package.
The most important executables are:
gwpopulation_pipe
- the main executable that builds abash
script for local use andHTCondor
for submission to a computing cluster. If you’re interested inSLURM
support please let us know.gwpopulation_pipe_collection
- reads in posterior samples for individual events and combines them into a single file containing the requested parameters and files containing data products used to estimate the search sensitivity, which are also downsampled.gwpopulation_pipe_analysis
- reads in the output ofgwpopulation_pipe_collection
and performs the population analysis usingBilby
and/ornumpyro
.gwpopulation_pipe_plot
- makes plots of the results of the population analysis.gwpopulation_pipe_to_common_format
- converts the result files to the common format for LVK population analyses.
gwpopulation_pipe
help
Other documentation pages describe how to specify some of these arguments in more detail, but
here is a brief overview of the command line arguments for gwpopulation_pipe
.
For reference, here is the full output of
$ gwpopulation_pipe --help
usage: gwpopulation_pipe [-h] [-v] [--version] [--run-dir RUN_DIR]
[--log-dir LOG_DIR] [--label LABEL] [--user USER]
[--vt-file VT_FILE]
[--vt-ifar-threshold VT_IFAR_THRESHOLD]
[--vt-snr-threshold VT_SNR_THRESHOLD]
[--vt-function VT_FUNCTION] [--prior-file PRIOR_FILE]
[--request-gpu REQUEST_GPU]
[--require-gpus REQUIRE_GPUS]
[--backend {numpy,cupy,jax}] [--cosmo COSMO]
[--cosmology COSMOLOGY] [--all-models ALL_MODELS]
[--source-files SOURCE_FILES]
[--existing-data-directory EXISTING_DATA_DIRECTORY]
[--parameters PARAMETERS] [--ignore IGNORE]
[--sample-regex SAMPLE_REGEX]
[--preferred-labels PREFERRED_LABELS] [--plot PLOT]
[--n-simulations N_SIMULATIONS]
[--samples-per-posterior SAMPLES_PER_POSTERIOR]
[--collection-seed COLLECTION_SEED]
[--data-label DATA_LABEL]
[--distance-prior DISTANCE_PRIOR]
[--mass-prior MASS_PRIOR] [--spin-prior SPIN_PRIOR]
[--max-redshift MAX_REDSHIFT]
[--minimum-mass MINIMUM_MASS]
[--maximum-mass MAXIMUM_MASS] [--sampler SAMPLER]
[--sampler-kwargs SAMPLER_KWARGS]
[--vt-parameters VT_PARAMETERS]
[--enforce-minimum-neffective-per-event ENFORCE_MINIMUM_NEFFECTIVE_PER_EVENT]
[--injection-file INJECTION_FILE]
[--injection-index INJECTION_INDEX]
[--sample-from-prior SAMPLE_FROM_PRIOR]
[--post-plots POST_PLOTS]
[--make-summary MAKE_SUMMARY]
[--n-post-samples N_POST_SAMPLES]
ini
Positional Arguments
- ini
Configuration ini file
Named Arguments
- -v, --verbose
Verbose output
Default:
False
- --version
show program’s version number and exit
Generic arguments
Generic arguments
- --run-dir
Output directory for posterior samples
Default:
'outdir'
- --log-dir
Output directory for writing log files
Default:
'logs'
- --label
Run label
Default:
'label'
- --user
User name
- --vt-file
File to load VT data from or a glob string matching multiple files to combine.
- --vt-ifar-threshold
IFAR threshold for resampling injections
Default:
1
- --vt-snr-threshold
IFAR threshold for resampling injections. This is only used for O1/O2 injections
Default:
11
- --vt-function
Function to generate selection function from.
Default:
'injection_resampling_vt'
- --prior-file
Prior file containing priors for all considered parameters
- --request-gpu
Whether to request a GPU for the relevant jobs.
Default:
0
- --require-gpus
The GPU requirements to pass for HTCondor.
Default:
'DeviceName=="GeForce GTX 1050 Ti"'
- --backend
Possible choices: numpy, cupy, jax
The backend to use for the analysis, default is jax
Default:
'jax'
- --cosmo
Whether to fit cosmological parameters.
Default:
False
- --cosmology
Cosmology to use for the analysis, this should be one of FlatLambdaCDM, FlatwCDM, WMAP1, WMAP3, WMAP5, WMAP7, WMAP9, Planck13, Planck15, Planck18, Planck15_LAL. Some of these are fixed pre-defined cosmologies while others are parameterized cosmologies. If a parameterized cosmology is used the parameters relevant parameters should be included in the prior specification.
Default:
'Planck15_LAL'
Analysis models
Analysis models
- --all-models
All models to use, formatted as a json string
- --source-files
Files containing source models to use for user-defined models. These files are transferred to the execute node when using the HTCondor file transfer mechanism. If the job is being run locally the file should be in the users PYTHONPATH.
Data collection arguments
Data collection arguments
- --existing-data-directory
Directory containing existing data
Default:
'/fail'
- --parameters
Parameters that are fit with the model. These are the parameters that will be extracted from the posterior samples and should follow Bilby naming conventions with the exception that all masses are assumed to be in the source frame. Here is a list of parameters for which prior factors will be properly accounted. mass_1: source frame primary mass, mass_2: source frame secondary mass, mass_1_detector: detector frame primary mass, mass_2_detector: detector frame secondary mass, chirp_mass: source frame chirp mass, chirp_mass_detector: detector frame chirp mass,mass_ratio: mass ratio, redshift: redshift, luminosity_distance: luminosity distance,a_1: primary spin magnitude, a_2: secondary spin magnitude, cos_tilt_1: cosine primary spin tilt, cos_tilt_2: cosine secondary spin tilt, chi_1: aligned primary spin, chi_2: aligned secondary spin.Any other parameters will be assumed to have a flat prior.These parameters are also used to set the fiducial prior values. No redundancy checks are performed so users should be careful to not include unused parameters as that may have unintended consequences.
- --ignore
Events to ignore.
- --sample-regex
Pattern to match for sample files
- --preferred-labels
Run labels to search for in sample files
- --plot
Whether to generate diagnostic plots
Default:
True
- --n-simulations
Number of posteriors to simulate
- --samples-per-posterior
Number of samples per posterior. If larger than the number of samples in the shortest posterior dataset, will ignore this input.
Default:
1000000
- --collection-seed
Seed for the downsampling of the posteriors for each event. For reproducibility.
- --data-label
Label for data product.
Default:
'posteriors'
- --distance-prior
Distance prior format, e.g., euclidean, comoving. ‘euclidean’ assumes the distance prior goes like D^2. ‘comoving’ assumes sources are uniformly distributed in the comoving frame using the Planck15_LAL cosmology. Can be in the format of a dict with the same keys as the sample-regex
Default:
'comoving'
- --mass-prior
- Mass prior used during the initial sampling, must match one of the following options.
‘flat-detector’: Flat in detector frame primary and secondary masses. ‘chirp-mass’: Flat in detector frame chirp mass and mass ratio. ‘flat-detector-components’: Flat in detector frame primary and secondary masses. This is the default for LVK samples and the same as the deprecated ‘flat-detector’ option. ‘flat-source-components’: Flat in source frame primary and secondary masses. ‘flat-detector-chirp-mass-ratio’: Flat in detector frame chirp mass and mass ratio. This is the same as the deprecated ‘chirp-mass’ option. Can be in the format of a dict with the same keys as the sample-regex
Default:
'flat-detector'
- --spin-prior
Spin prior, the only supported spin prior assumes the spins are isotropically distributed with a flat prior on the magnitude. Can be in the format of a dict with the same keys as the sample-regex.
Default:
'component'
Arguments describing analysis jobs
Analysis arguments
- --max-redshift
The maximum redshift considered, this should match the injections.
Default:
2.3
- --minimum-mass
The minimum mass considered, this should match the injections and is important for smoothed mass models.
Default:
2
- --maximum-mass
The maximum mass considered, this should match the injections and is important for smoothed mass models.
Default:
100
- --sampler
The sampler to use, the default is dynesty
Default:
'dynesty'
- --sampler-kwargs
Dictionary of sampler-kwargs to pass in, e.g., {nlive: 1000} OR pass pre-defined set of sampler-kwargs {Default, FastTest}
Default:
'Default'
- --vt-parameters
Which parameters to include in the VT estimate, should be some combination of mass, redshift, spin parameters, see the ‘–parameters’ option for more details.
- --enforce-minimum-neffective-per-event
Require that all Monte Carlo integrals for the single event marignalizaed likleihoods have at least as many effective samples as the number of events.
Default:
True
Arguments describing injections
Injection arguments
- --injection-file
JSON file containing population parameters, should be pandas readable.
- --injection-index
Index in injection file to use.
- --sample-from-prior
Simulate posteriors from prior.
Post processing arguments
Post arguments
- --post-plots
Whether to make post-processing plots.
Default:
True
- --make-summary
Whether to make a summary page.
Default:
True
- --n-post-samples
Number of samples to use in the common format script
Default:
5000