pastas.modelcompare.CompareModels.plot#

CompareModels.plot(smdict=None, normalized=False, param_selection=None, figsize=(10, 8), grid=True, legend=True, adjust_height=False, legend_kwargs=None)[source]#

plot the models in a comparison plot.

The resulting plot is similar to ml.plots.results().

Parameters
  • smdict (dict, optional) – dictionary with integers (index) as keys and list of stressmodel names as values that have to be in each subplot. For example, {0: [‘prec’, ‘evap’], 1: [‘rech’]} where stressmodels ‘prec’ and ‘evap’ are plotted in the first contribution/response function window and ‘rech’ in the second. By default, None, which creates a separate subplot for each stressmodel.

  • normalized (bool, optional) – normalize contributions such that minimum or maximum value is equal to zero, by default False.

  • param_selection (list, optional) – list of (sub)strings of which parameters to show in table, by default None.

  • figsize (tuple, optional) – figure size, by default (10, 8).

  • grid (bool, optional) – grid in each subplot, by default True.

  • legend (bool, optional) – add legend in each subplot, by default True.

  • 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 False. When combining stress contributions in one subplot, please also provide smdict for best results.

  • legend_kwargs (dict, optional) – pass legend keyword arguments to plots.

Return type

None