pint.random_models.random_models

pint.random_models.random_models(fitter, rs_mean, ledge_multiplier=4, redge_multiplier=4, iter=1, npoints=100)[source]

Uses the covariance matrix to produce gaussian weighted random models.

Returns fake toas for plotting and a list of the random models’ phase resid objects. rs_mean determines where in residual phase the lines are plotted, edge_multipliers determine how far beyond the selected toas the random models are plotted. This uses an approximate method based on the cov matrix, it doesn’t use MCMC.

Parameters:

  • fitter – fitter object with model and toas to vary from

  • rs_mean – average phase residual for toas in fitter object, used to plot random models

  • ledge_multiplier – how far the lines will plot to the left in multiples of the fit toas span, default 4

  • redge_multiplier – how far the lines will plot to the right in multiples of the fit toas span, default 4

  • iter – how many random models will be computed, default 1

  • npoints – how many fake toas will be related for the random lines, default 100

Returns:

  • TOAs object containing the evenly spaced fake toas to plot the random lines with

  • list of residual objects for the random models (one residual object each)