graphs package

TuningCurveGraph

class autompc.graphs.TuningCurveGraph

Graph tuning curve for either pipeline or model tuning result.

__call__(ax, tune_result)

Parameters:

• ax (matplotlib.axes.Axes) – Axes object on which to create graph

• tune_result (ModelTuneResult or PipelineTuneResult) – Tuning result to plot

KstepPredAccGraph

class autompc.graphs.KstepPredAccGraph(system, trajs, kmax, logscale=False, metric='rmse')

Create k-step model prediction accuracy graph.

__init__(system, trajs, kmax, logscale=False, metric='rmse')

Parameters:

• system (System) – System on which models are being evaluted

• trajs (List of Trajectory) – Evaluation trajectory set

• kmax (int) – Maximum horizon to evaluate

• logscale (bool) – Use log scale on y-axis if true

• metric (string) – Prediction accuracy metric to use. One of “rmse” or “rmsmens”

add_model(model, label)

Add a model for comparison

Parameters:

• model (Model) – Model to compare

• label (string) – Label for model