actsnclass.Canvas

class actsnclass.Canvas

Canvas object, handles and plot information from multiple strategies.

Variables:

  • axis_label_size (int) – Size of font in axis labels.

  • canonical (pd.DataFrame) – Data from Canonical strategy.

  • fig_size (tuple) – Figure dimensions.

  • rand_sampling (pd.DataFrame) – Data from Random Sampling strategy.

  • tick_label_size (int) – Size of tick labels in both axis.

  • ncolumns (int) – Number of columns in panel grid.

  • nlines (int) – Number of lines in panel grid.

  • nmetrics (int) – Number of metric elements (panels in plot).

  • metrics_names (list) – List of names for metrics to be plotted.

  • unc_sampling (pd.DataFrame) – Data from Uncertainty Sampling strategy.

  • colors (dict) – Colors corresponding to each strategy. They were chosen to follow Mondrian’s color palette. Do not change and try to keep the same palette in adding new elements.

  • labels (dict) – Labels to appear on plot for each strategy.

  • markers (dict) – Plot markers for each strategy.

  • strategies (dict) – Dictionary connecting each data frame to its standard nomenclature (not the plot labels).

load_metrics(path_to_files: list, strategy_list: list)

Load metrics and identify set of metrics.

set_plot_dimensions()

Set directives for plot sizes based on number of metrics.

plot_metrics(output_plot_file: str, strategies_list: list)

Generate plot for all metrics in files and strategies given as input.

Examples

Define input variables

>>> path_to_files = ['results/metrics_canonical.dat',
>>>                  'results/metrics_random.dat',
>>>                  'results/metrics_unc.dat']
>>> strategies_list = ['Canonical', 'RandomSampling', 'UncSampling']
>>> output_plot = 'plots/metrics1_unc.png'

Initiate the Canvas object, read and plot the results for each metric and strategy.

>>> cv = Canvas()
>>> cv.load_metrics(path_to_files=path_to_files,
>>>                    strategies_list=strategies_list)
>>> cv.set_plot_dimensions()
>>> cv.plot_metrics(output_plot_file=output_plot,
>>>                 strategies_list=strategies_list)
__init__()

Methods

__init__()

load_metrics(path_to_files, strategies_list)

Load and identify set of metrics.

plot_metrics(output_plot_file, strategies_list)

Generate plot for all metrics in files and strategies given as input.

set_plot_dimensions()

Set directives for plot sizes.