Charts( Helipad model )

A Matplotlib-based visualizer for a variety of visualizations that display data that reflects only a single point in time (as opposed to TimeSeries, which displays data over time).

Features

• Can display a variety of plot types alongside one another, including bar charts, networks, and spatial, and can also register custom plot types with subclasses of ChartPlot (see the tutorial for an example). See the specific plot classes for features specific to built-in plot types.
• Time bar at the bottom allows the user to scrub back over the model history

Initialization Parameters

• model — Helipad, required

  The model object.

Methods

Click a method name for more detailed documentation.

• addKeypress( key, fn )

  Registers a function to be run when a key is pressed in a Matplotlib visualizer.

• addPlot( name, label, type, … )

  Adds a plot area to the Chart visualizer. Defaults to a bar chart, but can be set to any subclass of ChartPlot.

• addPlotType( clss )

  Registers a new plot type for the Charts visualizer. Registered plot types can then be added to the visualization area with Charts.addPlot().

• catchKeypress( event )

  The callback function that sends keypresses to functions defined in MPLVisualization.addKeypress(). This function should not be called directly by user code unless to simulate a keypress.

• event( t, color, **kwargs )

  Called when an event is triggered, in order to be reflected in the visualization. For example, a line is drawn in TimeSeries, and the background flashes in Charts. Any kwargs passed to model.addEvent() are passed to this function, allowing subclasses to receive custom arguments (for example, linestyle in TimeSeries.event()). This method is mandatory for subclasses to implement.

  This function is called automatically when an event is triggered and should not be called by user code.

• launch( title )

  Launches the visualization window (if in Tkinter) or cell (if in Jupyter). This method is required to be implemented by subclasses, which should call super().launch(title) after creating the Matplotlib figure object.

• scrub( t )

  Updates the visualizer with the values from model time t. This function is called when the time slider is modified and should not be called from user code.

• terminate( )

  Cleanup on model termination. This function is called automatically from model.terminate() and should not be called from user code.

• update( data )

  Updates the visualization with new data and refreshes the display. This is mandatory for any subclasses to implement. Subclasses implementing this method should also use it to store any data necessary for future visualizer operations.

  This function should only rarely be called by the user; call model.step() instead to increment the model by one period and update the graph.

Properties

• isNull — bool

  True when the model should run as-if with no visualization, for example if all the plots are unselected. False indicates the window can be launched.

• lastUpdate — int

  Because the model can be set to refresh the visualization only every so many periods, this property records the model time when data was last drawn to the visualization.

  Initial value: 0

• fig — matplotlib.Figure

  The Matplotlib Figure object used for rendering the visualization as a whole.

• plots — dict{str:Plot}

  A dict of registered Plot objects.

• activePlots — dict{str:Plot}

  A dynamic property consisting of the subset of the plots containing the Plots that are currently active.

• keys — dict{str: list[func]}

  Where functions defined in MPLVisualization.addKeypress() are stored.

  Initial value: {}

Hooks

Click a hook name for more detailed documentation.

• visualRefresh( model, visual )

  Runs when the visualizer updates, every n periods as determined by the refresh parameter.

• visualLaunch( model, visual )

  Runs when model.launchVisual() is called, after the visualization is launched. Use the modelPostSetup hook to catch before the visualization is launched.