Plot Module

Copyright (C) 2007-2017 Jonas Diemer, Philip Axer

TU Braunschweig, Germany

All rights reserved.

See LICENSE file for copyright and license details.

Authors:

• Jonas Diemer
• Philip Axer

Description

General purpose plotting functions: * event model plotting * gantt plotting (requires the simulation engine)

pycpa.plot.augment_range(plot_range)

Adds points around every point in plot_range for accurately plotting integer-based curves

pycpa.plot.plot_eta(eta, plot_range, label=None, color=None, show=False, filename=None)

Plot an eta function

pycpa.plot.plot_event_model(model, num_events, file_format=None, separate_plots=True, file_prefix='', ticks_at_steps=False)

Plot the Task’s eta and delta_min functions. Intervals in eta are shown half-open, as defined in [Richter2005].

Parameters:

• model (model.EventModel) – the event model
• num_events – Number of events to plot
• file_format (string) – the format of the file to be plotted
• separate_plots (bool) – whether eta and delta plots should be combined
• file_prefix (string) – prefix of file name of plots
• ticks_at_steps (bool) – If True, draw the x-axis ticks at steps of the functions. Otherwise, let matplotlib decide where to draw ticks.

Return type:

None

pycpa.plot.plot_gantt(tasks, task_results, file_name=None, show=True, xlim=None, preemtion_bar_height=0.2, height=1, hdist=1, bar_linewidth=1, min_dist_arrows=0.2, plot_event_arrival=True, plot_activation_finishing=False, annotate_tasks=True, task=None, wcrt_voffset=0.5, annotation_offset=0.2, arrow_width=0.05, arrow_head_width=0.4, arrow_head_length=0.2, arrow_xscale=1, arrow_yoffset=0.1, xticks_only_on_changes=False, color_preemtion_bar='0.30', color_execution_bar='lightblue', title='Gantt', number_xticks=20)

Plot a gantt chart of a given task list. Execution time information is taken from the task attribute q_exec_windows which is written by the simulation framework