moabb.analysis.plotting.score_plot#

moabb.analysis.plotting.score_plot(data, pipelines=None, orientation='vertical', chance_level=None)[source]#

Plot scores for all pipelines and all datasets.

Parameters:

data (pandas.DataFrame) – Output of Results.to_dataframe().
pipelines (list of str | None) – Pipelines to include in this plot.
orientation (str) – Plot orientation, one of ["vertical", "v", "horizontal", "h"]. Defaults to "vertical".
chance_level (None, float, or dict) –
Chance level to display on the plot. Defaults to None.
- None : defaults to 0.5 for all datasets (backward compatible).
- float : uniform chance level for all datasets.
- dict : per-dataset chance levels. Can be a simple {dataset_name: float} mapping or the output of chance_by_chance. When the dict includes 'adjusted' entries, adjusted significance threshold lines are also drawn.

Returns: