Dynamic visualization capabilities ================================== PyDSS uses Bokeh (https://docs.bokeh.org/en/latest/index.html) to render dynamic visuals. The visuals update as the simulatons runs, thus allowing user debug control algorithms, gain deeper insights and demonstate results in richer interactive manner. OpenDSS has limited visualization capabilities and does not support dynamic visuals. The installation come with seven plots listed below. - Frequency sweep plot - GIS plot - Histogram plot - Voltage sag plot - Time series plot - Voltage / Current heatmap plot - XY plots To enable dynamic plotting, two settings list below need to populated in the 'Scenario_settings.TOML' file. .. code-block:: python "Create dynamic plots" = false "Open plots in browser" = true - Create dynamic plots- [Bool] - Enable rendering of dynamic plots using bokeh. If set to true, an instance of bokeh server is run to render plots before the simulation stats. - Open plots in browser- [Bool] - If set to true, open plots in the default browser automatically. Will only work "Create dynamic plots" is set to true. Plot need to be defined within the 'pyPlotList.json' file for a given scenario. 'Bokeh-Visualization' project within the examples folder provide template to define each of the seven plots. Multiple plots may be created for a given scenario. All plots ate interactive and allow user to zoom, scroll, hide layers and save images as png files. .. csv-table:: An example of definations for a Voltage / Current heatmap plot :file: Network_layout.csv :header-rows: 1 .. figure:: _static/Layout.png :align: center .. csv-table:: An example of definations for a Voltage sag plot :file: Sag_plot.csv :header-rows: 1 .. figure:: _static/Voltage_sag.png :align: center Expected definations for each plot can be found here .. toctree:: :maxdepth: 2 Dynamic plots Users are able to extend current plotting capabilites by following the tutorial here .. toctree:: :maxdepth: 2 Creating custom dynamic plots