actsnclass.Canvas¶
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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).
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load_metrics
(path_to_files: list, strategy_list: list)¶ Load metrics and identify set of metrics.
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set_plot_dimensions
()¶ Set directives for plot sizes based on number of metrics.
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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)
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__init__
()¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
()Initialize self. 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.