GWForge.population_fisher.plot¶

Figures for population Fisher forecasts.

Attributes¶

`CREDIBLE_LEVEL`
`CONTOUR_LEVELS`

Functions¶

`corner_plot`(results[, save, title, seed, parameters, ...])	Corner plot of one or more population Fisher forecasts, overlaid.
`plot_mass_distribution`(model, result[, injections, ...])	Reconstructed primary-mass distribution with a credible band.
`plot_redshift_distribution`(model, result[, ...])	Reconstructed merger-rate redshift distribution with a credible band.

Module Contents¶

GWForge.population_fisher.plot.CREDIBLE_LEVEL = 0.9[source]¶

GWForge.population_fisher.plot.CONTOUR_LEVELS = (0.67, 0.9)[source]¶

GWForge.population_fisher.plot.corner_plot(results, save=None, title=None, seed=None, parameters=None, colours=None, palette_name='tealrose')[source]¶

Corner plot of one or more population Fisher forecasts, overlaid.

Parameters:

results (sequence of tuple) – (label, PopulationFisherResult) pairs. Every result must expose the same free parameters, so that overlaying them compares like with like.
save (str or None) – Path to write to. The figure is closed after saving.
title (str or None)
seed (int or None) – Each dataset is drawn with a freshly seeded generator, so they share the same underlying standard normals and the contours nest visually instead of jittering independently against each other.
parameters (sequence of str or None) – Restrict the plot to these. Drawn from the marginal of the full covariance, so the contours are marginalised, not the conditional ones a re-fit over a subset would give. Defaults to all of them, which is unreadable beyond about eight.
colours (sequence of str or None) – One per dataset. Defaults to the palette’s cycle, which starts teal/rose.
palette_name (str) – "tealrose" or "okabe-ito".

Return type:

matplotlib.figure.Figure

Raises:

ValueError – If the results do not share their parameter list, or a requested parameter is not among them.

GWForge.population_fisher.plot.plot_mass_distribution(model, result, injections=None, save=None, size=BAND_DRAWS, seed=None, colour=XG_COLOUR)[source]¶

Reconstructed primary-mass distribution with a credible band.

Parameters:

model (GWForge.population_fisher.model.BrokenPowerLawTwoPeakMass)
result (GWForge.population_fisher.population_fisher_term_I.PopulationFisherResult)
injections (array_like or None) – mass_1_source of the injections, drawn as a histogram behind the band.
save (str or None)
size (int)
seed (int or None)
colour (str) – Band and median colour. Defaults to the XG teal; pass GWForge.plotting.LVK_COLOUR for a 2G network.

Return type:

matplotlib.figure.Figure

GWForge.population_fisher.plot.plot_redshift_distribution(model, result, injections=None, save=None, size=BAND_DRAWS, seed=None, colour=XG_COLOUR)[source]¶

Reconstructed merger-rate redshift distribution with a credible band.

Parameters:

model (GWForge.population_fisher.model.MadauDickinsonRedshift)
result (GWForge.population_fisher.population_fisher_term_I.PopulationFisherResult)
injections (array_like or None) – Injected redshifts, drawn as a histogram behind the band.
save (str or None)
size (int)
seed (int or None)
colour (str) – Band and median colour. Defaults to the XG teal; pass GWForge.plotting.LVK_COLOUR for a 2G network.

Return type:

matplotlib.figure.Figure