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Plotters

Plotters generate diagnostic visualizations after each calibration iteration. They are passed to CalibManager and called automatically at the end of each iteration.

Available plotters

Class Module Description
BasePlotter plotters.base_plotter Abstract base — subclass to create custom plots
LikelihoodPlotter plotters.likelihood_plotter Likelihood scores across iterations
SiteDataPlotter plotters.site_data_plotter Model vs. reference data overlays per site
OptimToolPlotter plotters.optim_tool_plotter Parameter space and regression diagnostics for OptimTool
OptimToolPBNBPlotter plotters.optim_tool_pbnb_plotter Branch-and-bound region diagnostics
OptimToolSPSAPlotter plotters.optim_tool_spsa_plotter SPSA step-size and gradient diagnostics
SeparatrixBHMPlotter plotters.separatrix_bhm_plotter Separatrix boundary plots

BasePlotter

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from idmtools_calibra.plotters.base_plotter import BasePlotter

Abstract base class. Subclass this to write a custom plotter.

Constructor

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BasePlotter(combine_sites=True)
Parameter Type Default Description
combine_sites bool True Whether to aggregate results across all sites into a single plot

Abstract method

visualize(iteration_state)

Called by CalibManager at the end of each iteration.

Parameter Type Description
iteration_state IterationState Full state of the current iteration, including samples, results, and paths

Helper methods

Method Returns Description
get_iteration_directory() str Path to the current iteration's output folder
get_plot_directory() str Path to the shared _plots/ folder (created if absent)
all_results (property) DataFrame All results from iteration_state.all_results

combine_by_site(site_name, analyzer_names, results) (staticmethod)

Sum analyzer scores for a given site into a <site>_total column in results.

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BasePlotter.combine_by_site('my_site', ['analyzer1', 'analyzer2'], results_df)

Custom plotter example

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from idmtools_calibra.plotters.base_plotter import BasePlotter
import matplotlib.pyplot as plt

class MyPlotter(BasePlotter):
    def visualize(self, iteration_state):
        results = iteration_state.all_results
        fig, ax = plt.subplots()
        ax.plot(results['__sample_index__'], results['total'], 'o')
        ax.set_xlabel('Sample index')
        ax.set_ylabel('Total likelihood')
        fig.savefig(f'{self.get_plot_directory()}/scores_iter{iteration_state.iteration}.png')
        plt.close(fig)

LikelihoodPlotter

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from idmtools_calibra.plotters.likelihood_plotter import LikelihoodPlotter

Plots the distribution of likelihood scores across samples for each iteration, showing how the algorithm converges over time.

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LikelihoodPlotter(combine_sites=True)

SiteDataPlotter

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from idmtools_calibra.plotters.site_data_plotter import SiteDataPlotter

Overlays the best-fit model output against the reference data for each calibration site.

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SiteDataPlotter(combine_sites=True)

OptimToolPlotter

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from idmtools_calibra.plotters.optim_tool_plotter import OptimToolPlotter

Generates diagnostics specific to OptimTool: parameter scatter plots, regression R² values, and the evolution of the search center and radius over iterations.

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OptimToolPlotter(combine_sites=True)

OptimToolPBNBPlotter

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from idmtools_calibra.plotters.optim_tool_pbnb_plotter import OptimToolPBNBPlotter

Visualizes the branch-and-bound region partition for OptimToolPBNB calibrations.

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OptimToolPBNBPlotter(combine_sites=True)

OptimToolSPSAPlotter

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from idmtools_calibra.plotters.optim_tool_spsa_plotter import OptimToolSPSAPlotter

Plots SPSA-specific diagnostics including step size decay and estimated gradient direction.

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OptimToolSPSAPlotter(combine_sites=True)

SeparatrixBHMPlotter

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from idmtools_calibra.plotters.separatrix_bhm_plotter import SeparatrixBHMPlotter

Visualizes the separatrix (decision boundary) estimated by the BHM algorithm.

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SeparatrixBHMPlotter(combine_sites=True)

Using multiple plotters

Pass a list of plotters to CalibManager. Each runs after every iteration:

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from idmtools_calibra.plotters.likelihood_plotter import LikelihoodPlotter
from idmtools_calibra.plotters.site_data_plotter import SiteDataPlotter
from idmtools_calibra.plotters.optim_tool_plotter import OptimToolPlotter

calib = CalibManager(
    ...,
    plotters=[
        LikelihoodPlotter(),
        SiteDataPlotter(),
        OptimToolPlotter(),
    ],
)