optiSLang postprocessing incorporates Python scripting for flexible generation and configuration of result data monitoring. This includes customizable default generation scripts for various postprocessing purposes as well as a Python console and customizable shortcut buttons for executing Python commands during the postprocessing. Examples for Python scripting can be found here.

Postprocessing Generation

When you open a postprocessing database file (*.omdb, *.bin), a suitable default generation script is deduced using the type of result data and is then called to generate and configure the postprocessing.

The default generation scripts are located in the postprocessing scripting directory within the optiSLang installation directory ([install_dir]/optiSLang/scripting/postprocessing/command_scripts). You can also define custom script directories. The following scripts are available:

The default generation scripts can be edited to customize the postprocessing. You can also create user-defined generation scripts that can be used either from the Postprocessing window or the Postprocessing node.

To open a custom script in the Postprocessing window, from the menu bar, select File > Reload as > Use custom script.

To use the custom script in the optiSLang workflow:

A generated script generally consists of at least three parts. First, create the postprocessing visuals by creating the corresponding visual object, providing a name and the data that is displayed by the visual.

anthill = Visuals.Anthill(Id("Anthill plot"), data_id)
        

The term data_id refers to the currently loaded postprocessing database. Visuals created that way by default inherit the global settings. They, for example, display the parameters and/or responses that are set in the global dimension selection controls.

The second step is to configure the visual if the default settings are not suitable.

anthill.SetAbscissa ("parameter_1")
        

This example call tells the anthill visual to display the values of parameter_1 at the abscissa, regardless of a potential differing global setting.

The third step is to add the created visual to the postprocessing.

control_container.add_control (
    anthill, 
    True, 
    RELATIVE_POSITIONING, 
    1/2., 0, 1/2., 1/2.
)
        

This example call adds the anthill visual to the postprocessing, using the specified position and size relative to the size of the postprocessing main window and sets the visibility to true.

Python Console

You can access the Python console by selecting View > Dock Widgets > Python console. It is used to execute Python commands that access and configure global attributes like design selection or styling, as well as attributes of individual postprocessing visuals like visibility and positioning. Python commands can be executed by either typing or pasting Python code into the text field and pressing Enter or selecting Execute or Execute script file from the multi-selection button. You can also create shortcuts in the monitoring toolbar for your custom Python scripts

The following functionality can be customized using Python scripting:

Custom Script Directories

You can define custom directories for your Python scripts. Scripts inside either your custom or the default scripting directories are displayed as shortcuts in the toolbar and as an entry in the menu of the script type. Currently, there are two different types of scripts:

Postprocessing generation scripts:

Monitoring Python scripts:

You can find an example script in the default directory (quick_optimization.py).

By placing a script in the directory it is recognized and displayed as described previously. You can define an icon for the script inside the toolbar by placing an image with the same name as the script in the same directory. You can change the custom directory path by setting the path as the value of the following environment variables:

Alternatively, you can define them using the following command line arguments:

custom-command-script-directory

custom-execute-script-directory

Custom Python Script Configuration

The monitoring Python scripts are displayed in a drop-down list in the toolbar and in a sub-menu of the File menu by default. You can define a configuration file in JSON format to change its displayed name and to create a separate button in the toolbar for it.

The different configuration parameters are:

An example of how to configure a script named my_custom_script.py:

{
    "display_name": "My custom script",
    "show_as_button": true
}
        

Python Scripting for Text Import

Running the following Python code in the Python console adds a Postprocessing node to the Scenery pane with the Settings file and Non interactive mode settings configured.

pp_node = actors.PostprocessingActor("Postproceessing")

pp_node.mdb_path = „D:\\develop\\oscillator_robustness.csv“

pp_node.text_import_settings_file = „D:\\develop\\oscillator_robustness.json“
pp_node.text_import_non_interactive = true

add_actor( pp_node )