pastas.plotting.modelplots.Plotting.stacked_results#

pastas.plotting.modelplots.Plotting.stacked_results(tmin: pandas.Timestamp | str | None = None, tmax: pandas.Timestamp | str | None = None, stackcolors: dict[str, str] | list[str] | None = None, stacklegend: bool = False, stacklegend_kws: dict | None = None, **kwargs) → list[pastas.typing.Axes]#

Create a results plot, similar to ml.plots.results(), in which the individual contributions of stresses (in stressmodels with multiple stresses) are stacked.

Parameters:

  • tmin (pandas.Timestamp or str, optional) – A string or pandas.Timestamp with the start date for the period (E.g. ‘1980-01-01 00:00:00’). Strings are converted to pandas.Timestamp internally.

  • tmax (pandas.Timestamp or str, optional) – A string or pandas.Timestamp with the end date for the period (E.g. ‘2020-01-01 00:00:00’). Strings are converted to pandas.Timestamp internally.

  • stackcolors (dict or list, optional) – Either dictionary with stress names as keys and colors as values, or a list of colors. By default None which applies colors according to the order of stresses in the StressModel. Passing a dictionary can be useful to apply the same color to each stress across multiple figures.

  • stacklegend (bool, optional) – Add legend to the stacked plot.

  • stacklegend_kws (dict, optional) – dict with keyword arguments for stackplot legend

Returns:

axes

Return type:

list of axes objects