The matplotlib-based module elaps.plot provides plot() that plots a series
of metric data sets as produced by Report.evaluate(). If any of
the provided data sets contains a range, it produces a line-plot,
otherwise a bar-plot.
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plot() takes the following arguments, all of which but the first are optional.
(required)
The datasets to be plotted as a list of two-element tuples consisting of the
legend entry and the data set as returned by Report.apply_metric().
(default: ["med"])
A list of statistics to be plotted. May contain "min", "med", "max",
"avg", "std", and "all".
"min" through "avg" on their own are plotted as lines (or simple bars); when
both "min" and "max" are present, the range between them ("min-max") is
filled; "std" fills the range between of the average +/- one standard
deviation; "all" plots all data points as markers.
(default: built-in color set)
A list of colors for the datasets in the same order.
(default: built-in styles)
A dict of style options for different statistics that overwrite the built-in
options. Relevant: the statistics names, "min-max" and "legend". Allowed
values: keyword arguments (dict) for matplotlib's plot() method
(fill_between() for "min-max" and "std").
(default: no label)
The plots x-axis label. Ignored for bar-plots.
(default: no label)
The plots y-axis label.
(default: {})
Keyword arguments (dict) for matplotlib's legend() method (e.g., for
custom legend placement).
(default: pyplot.gcf())
The matplotlib Figure in which to plot.
plot() returns a matplotlib Figure that can be further modified or exported
via its savefig() method.