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voiage.plot.voi_curves.plot_evpi_vs_wtp

plot_evpi_vs_wtp

Section titled “plot_evpi_vs_wtp”
plot_evpi_vs_wtp([positional or keyword] evpi_values: np.ndarray | list[float] = None, [positional or keyword] wtp_thresholds: np.ndarray | list[float] = None, [positional or keyword] xlabel: str = 'Willingness-to-Pay Threshold', [positional or keyword] ylabel: str = 'EVPI', [positional or keyword] title: str = 'Expected Value of Perfect Information vs. WTP', [positional or keyword] ax: Axes | None = None, [variadic keyword] plot_kwargs: object = {}) -> Axes

Plot EVPI against willingness-to-pay thresholds.

Parameters

Section titled “Parameters”

evpi_values : numpy.ndarray or list[float] EVPI values for each threshold. wtp_thresholds : numpy.ndarray or list[float] Willingness-to-pay thresholds. xlabel : str, default=“Willingness-to-Pay Threshold” X-axis label. ylabel : str, default=“EVPI” Y-axis label. title : str, default=“Expected Value of Perfect Information vs. WTP” Plot title. ax : matplotlib.axes.Axes, optional Axes to draw on. **plot_kwargs : object Keyword arguments forwarded to ax.plot.

Returns

Section titled “Returns”

matplotlib.axes.Axes Axes containing the EVPI curve.

Parameters:

  • evpi_values np.ndarray | list[float]
  • wtp_thresholds np.ndarray | list[float]
  • xlabel str (default: 'Willingness-to-Pay Threshold')
  • ylabel str (default: 'EVPI')
  • title str (default: 'Expected Value of Perfect Information vs. WTP')
  • ax Axes | None (default: None)
  • plot_kwargs object (default: {})

Returns: Axes