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Plotting

Visualization tools for calibration analysis.

Full API Reference

For complete API documentation with all parameters, return types, and detailed docstrings, see the Sphinx API Reference.

Global Calibration Curves​

from mcgrad import plotting

# Plot global calibration curve
fig = plotting.plot_global_calibration_curve(
    data=df,
    score_col='prediction',
    label_col='label',
    sample_weight_col='weights',  # optional
)

fig.show()

Multicalibration Analysis​

Visualize calibration across segments:

from mcgrad import plotting

# Plot calibration curves for each segment
fig = plotting.plot_calibration_curve_by_segment(
    data=df,
    group_var='country',
    score_col='prediction',
    label_col='label',
)

fig.show()

Segment Calibration Errors​

Visualize calibration errors across multiple segments:

from mcgrad import metrics, plotting

# Create a MulticalibrationError object
mce = metrics.MulticalibrationError(
    df=df,
    label_column='label',
    score_column='prediction',
    categorical_segment_columns=['country', 'content_type'],
)

# Plot segment calibration errors
fig = plotting.plot_segment_calibration_errors(
    mce=mce,
    quantity='segments_ecce_sigma',
)

fig.show()

See the source code for more visualization options.