pairs plotting
Code author: jhkwakkel <j.h.kwakkel (at) tudelft (dot) nl>
This module provides R style pairs plotting functionality.

pairs_plotting.pairs_scatter(results, outcomes_to_show=[], group_by=None, grouping_specifiers=None, ylabels={}, legend=True, point_in_time=1, **kwargs)
Generate a R style pairs
scatter multiplot. In case of timeseries data, the end states are used.
Parameters: 
 results – return from perform_experiments.
 outcomes_to_show – list of outcome of interest you want to plot. If
empty, all outcomes are plotted.
 group_by – name of the column in the cases array to group results by.
Alternatively, index can be used to use indexing arrays
as the basis for grouping.
 grouping_specifiers – set of categories to be used as a basis for
grouping by. Grouping_specifiers is only
meaningful if group_by is provided as well. In
case of grouping by index, the grouping
specifiers should be in a dictionary where the
key denotes the name of the group.
 ylabels – ylabels is a dictionary with the outcome names as keys, the
specified values will be used as labels for the y axis.
 legend – boolean, if true, and there is a column specified for
grouping, show a legend.
 point_in_time – the point in time at which the scatter is to be made.
If None is provided, the end states are used.
point_in_time should be a valid value on time

Return type:  a figure instance
and a dict with the individual axes.

Note
the current implementation is limited to seven different
categories in case of column, categories, and/or discretesize.
This limit is due to the colors specified in COLOR_LIST.

pairs_plotting.pairs_lines(results, outcomes_to_show=[], group_by=None, grouping_specifiers=None, ylabels={}, legend=True, **kwargs)
Generate a R style pairs
lines multiplot. It shows the behavior of two outcomes over time against
each other. The origin is denoted with a circle and the end is denoted
with a ‘+’.
Parameters: 
 results – return from perform_experiments.
 outcomes_to_show – list of outcome of interest you want to plot. If
empty, all outcomes are plotted.
 group_by – name of the column in the cases array to group results by.
Alternatively, index can be used to use indexing arrays
as the basis for grouping.
 grouping_specifiers – set of categories to be used as a basis for
grouping by. Grouping_specifiers is only
meaningful if group_by is provided as well. In
case of grouping by index, the grouping
specifiers should be in a dictionary where the
key denotes the name of the group.
 ylabels – ylabels is a dictionary with the outcome names as keys, the
specified values will be used as labels for the y axis.
 legend – boolean, if true, and there is a column specified for
grouping, show a legend.
 point_in_time – the point in time at which the scatter is to be made.
If None is provided, the end states are used.
point_in_time should be a valid value on time

Return type:  a figure instance
and a dict with the individual axes.


pairs_plotting.pairs_density(results, outcomes_to_show=[], group_by=None, grouping_specifiers=None, ylabels={}, point_in_time=1, log=True, gridsize=50, colormap='jet', filter_scalar=True)
Generate a R style pairs
hexbin density multiplot. In case of timeseries data, the end states are
used.
hexbin makes hexagonal binning plot of x versus y, where x, y are 1D
sequences of the same length, N. If C is None (the default), this is a
histogram of the number of occurences of the observations at (x[i],y[i]).
For further detail see matplotlib on hexbin
Parameters: 
 results – return from perform_experiments.
 outcomes_to_show – list of outcome of interest you want to plot. If
empty, all outcomes are plotted.
 group_by – name of the column in the cases array to group results by.
Alternatively, index can be used to use indexing arrays
as the basis for grouping.
 grouping_specifiers – set of categories to be used as a basis for
grouping by. Grouping_specifiers is only
meaningful if group_by is provided as well. In
case of grouping by index, the grouping
specifiers should be in a dictionary where the
key denotes the name of the group.
 ylabels – ylabels is a dictionary with the outcome names as keys, the
specified values will be used as labels for the y axis.
 point_in_time – the point in time at which the scatter is to be made.
If None is provided, the end states are used.
point_in_time should be a valid value on time
 log – boolean, indicating whether density should be log scaled.
Defaults to True.
 gridsize – controls the gridsize for the hexagonal binning
 cmap – color map that is to be used in generating the hexbin. For
details on the available maps,
see pylab.
(Defaults = jet)
 filter_scalar – boolean, remove the nontimeseries outcomes.
Defaults to True.

Return type:  a figure instance
and a dict with the individual axes.
