pastas.plotting.modelplots.Plotting.results#

pastas.plotting.modelplots.Plotting.results(tmin: pandas.Timestamp | str | None = None, tmax: pandas.Timestamp | str | None = None, figsize: tuple = (10, 8), split: bool = False, adjust_height: bool = True, return_warmup: bool = False, block_or_step: str = 'step', stderr: bool = False, fig: pastas.typing.Figure | None = None, **kwargs) → pastas.typing.Axes#

Plot different results in one window to get a quick overview.

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.

  • figsize (tuple, optional) – tuple of size 2 to determine the figure size in inches.

  • split (bool, optional) – Split the stresses in multiple stresses when possible. Default is False.

  • adjust_height (bool, optional) – Adjust the height of the graphs, so that the vertical scale of all the subplots on the left is equal. Default is True.

  • return_warmup (bool, optional) – Show the warmup-period. Default is false.

  • block_or_step (str, optional) – Plot the block- or step-response on the right. Default is ‘step’.

  • stderr (bool, optional) – If True the standard error of the parameter values are shown. Please be aware of the conditions for reliable uncertainty estimates, more information here: https://pastas.readthedocs.io/stable/examples/diagnostic_checking.html

  • fig (matplotib.Figure instance, optional) – Optionally provide a matplotib.Figure instance to plot onto.

  • **kwargs (dict, optional) – Optional arguments, passed on to the matplotlib.pyplot.figure method.

Return type:

list of matplotlib.axes.Axes

Examples

>>> ml.plots.results()