Using the Design Exploration API

Accessing studies in a model

accessing studies in a model Follow the steps below to access an existing study in a model. You can access the model_studies object of a model by typing the command below, where the parameter passed in is the path of the model file:

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ms=DE.get_model_studies  (r'$AME\demo\Platform\OptimizationRobustnessDOE\
Optimization\DesignOptimization.ame')

You can access the study required from the model_studies object by typing the command below, where the first parameter is “study name” and second is the “type of study”.

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ms=DE.get_model_studies  (r'$AME\demo\Platform\OptimizationRobustnessDOE\
Optimization\DesignOptimization.ame')

Figure 11: Accessing a design exploration study in a model

Creating a new study in a model

Follow the steps below to create a new study in a model.

Access the model_studies object for the model with a given path.

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ms=DE.get_model_studies  (r'$AME\demo\Platform\OptimizationRobustnessDOE\
Optimization\DesignOptimization.ame')

You can create a study by typing the command below, where the first parameter is the “name of study” and second parameter is the “type of study”

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study=ms. create_study ( "new_study" , Study.study_type.OPT)

The function above can be called with a second parameter as a string referring to the type of study as below:

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study=ms. create_study ( "new_study" , "OPT")

You can save all the studies in the model_studies object by typing the command: print (ms.save_studies() )

Figure 12: Creating a new study

The new study name  “new_study”  and of type “OPT” has been created and saved in the model. You can see the created study in the model by opening the model in Simcenter Amesim and accessing the Design exploration window for that model.

Setting the alogrithm to study and the properties of the alogrithm

setting the algorithm to study and the properties of the algorithm

You can set the algorithm to the previously created study. You can get the list of possible algorithms for a study by typing:

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study.get_available_algorithms()

You can set an algorithm to a study by typing the command below where the parameter passed in is algorithm name:

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algo=study.set_algorithm('GeneticAlgorithm')

You can get the available properties for an algorithm by typing:

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algo.get_properties()

You can set the property of an algorithm by typing the command below, where the parameters passed in are property_name and the value for that property consecutively:

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algo.set_property('Population_Size', 50)

Figure 13: Setting the algorithm to study

Setting the properties of parameters in a study

setting the properties of parameters in a study

You can get a parameter in a study and set its properties. You can get the list of parameters in the study and store it in the variable param_list by typing:

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 param_list=study.get_parameters()

You can get the first param in the list to the variable first_param by typing:

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 first_param=param_list[0]

You can get the list of properties applicable to that parameter by typing:

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first_param.get_properties()

You can set the property “Used” for that param to “True” by typing:

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first_param.set_property('Used', True)

Figure 14: Setting the properties of a parameter

Running a study

running a study

You can run a study by typing:

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 study.run()

Figure 15: Running a study

Figure 16: Successful completion of a study run

The study has been run and its results have been printed in the console. If any errors or warnings arise during study execution, they will be displayed in the console.