Flatten plot API: replace Plotter classes with module-level functions#1174
Merged
Jammy2211 merged 2 commits intomain_buildfrom Apr 3, 2026
Merged
Flatten plot API: replace Plotter classes with module-level functions#1174Jammy2211 merged 2 commits intomain_buildfrom
Jammy2211 merged 2 commits intomain_buildfrom
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Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This was referenced Apr 5, 2026
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Summary
Replace the class-based plotting API (
NestPlotter,MCMCPlotter,MLEPlotter,SamplesPlotter) with simple module-level functions. Users now callaplt.corner_anesthetic(samples=samples)instead of instantiating a plotter object. All cross-cutting concerns (test-mode skipping, convergence error handling) are preserved as decorators in a newplot_util.py.API Changes
The
autofit.plotmodule no longer exports Plotter classes. All plotting is now done via flat functions that takesamplesas the first argument, with optionalpath,filename, andformatkwargs for output control.NestPlotter,MCMCPlotter,MLEPlotter,SamplesPlotter,Outputcorner_cornerpy(),corner_anesthetic(),subplot_parameters(),log_likelihood_vs_iteration(),output_figure()See full details below.
Test Plan
pytest test_autofit/ -x— 390 passed (1 pre-existing failure intest_covariance.pyalso fails onmain_build)py_compilesyntax checkgrepconfirms no stale references to old Plotter classes in source📋 Full API Changes (for automation & release notes)
Removed
aplt.NestPlotterclass — useaplt.corner_anesthetic()function insteadaplt.MCMCPlotterclass — useaplt.corner_cornerpy()function insteadaplt.MLEPlotterclass — useaplt.subplot_parameters()/aplt.log_likelihood_vs_iteration()insteadaplt.SamplesPlotterclass — base class, no longer neededaplt.Outputclass — output now handled viapath,filename,formatkwargs on each functionautofit.non_linear.plot.outputmodule — deletedautofit.non_linear.plot.mcmc_plottersmodule — deletedAdded
aplt.corner_cornerpy(samples, path=None, filename="corner", format="show", **kwargs)— corner plot via corner.pyaplt.corner_anesthetic(samples, path=None, filename="corner_anesthetic", format="show", **kwargs)— corner plot via anestheticaplt.subplot_parameters(samples, use_log_y=False, use_last_50_percent=False, path=None, filename="subplot_parameters", format="show")— parameter vs iteration subplotsaplt.log_likelihood_vs_iteration(samples, use_log_y=False, use_last_50_percent=False, path=None, filename="log_likelihood_vs_iteration", format="show")— log likelihood vs iterationaplt.output_figure(path=None, filename="figure", format="show")— utility for saving/showing figuresautofit.non_linear.plot.plot_utilmodule — shared decorators (skip_in_test_mode,log_plot_exception) andoutput_figureMigration
plotter = aplt.NestPlotter(samples=s); plotter.corner_anesthetic()aplt.corner_anesthetic(samples=s)plotter = aplt.MCMCPlotter(samples=s); plotter.corner_cornerpy(**kw)aplt.corner_cornerpy(samples=s, **kw)plotter = aplt.MLEPlotter(samples=s); plotter.subplot_parameters(use_log_y=True)aplt.subplot_parameters(samples=s, use_log_y=True)Output(path=p, format="png")with kwargs:path=p, format="png"on each function call🤖 Generated with Claude Code