pytwin.TwinModel#

class pytwin.TwinModel(model_filepath)#

The public class to evaluate a twin model given a twin model file (with .twin extension) created with Ansys Twin Builder. After being initialized, a twin model object can be evaluated with two modes (step-by-step or batch mode) to make predictions. Parametric workflows are also supported.

Parameters:

model_filepathstr: File path to the twin model (with .twin) extension.

Examples

Create a twin model object given the file path to the twin model file. Initialize two parameters and two inputs of the twin model. Then evaluate two steps and retrieve results in a dictionary.

>>> from pytwin import TwinModel
>>>
>>> twin_model = TwinModel(model_filepath='path_to_your_twin_model.twin')
>>>
>>> twin_model.initialize_evaluation(parameters={'param1': 1., 'param2': 2.}, inputs={'input1': 1., 'input2': 2.})
>>> outputs = dict()
>>> outputs['Time'] = [twin_model.evaluation_time]
>>> outputs['output1'] = [twin_model.outputs['output1']]
>>> outputs['output2'] = [twin_model.outputs['output2']]
>>>
>>> twin_model.evaluate_step_by_step(step_size=0.1, inputs={'input1': 10., 'input2': 20.})
>>> outputs['Time'].append(twin_model.evaluation_time)
>>> outputs['output1'].append(twin_model.outputs['output1'])
>>> outputs['output2'].append(twin_model.outputs['output2'])
>>>
>>> twin_model.evaluate_step_by_step(step_size=0.1, inputs={'input1': 20., 'input2': 30.})
>>> outputs['Time'].append(twin_model.evaluation_time)
>>> outputs['output1'].append(twin_model.outputs['output1'])
>>> outputs['output2'].append(twin_model.outputs['output2'])

Methods

`TwinModel.evaluate_batch`(inputs_df)	Evaluate the twin model with historical input values given with a data frame.
`TwinModel.evaluate_step_by_step`(step_size[, ...])	Evaluate the twin model at time instant t + step_size given inputs at time instant t.
`TwinModel.get_available_view_names`(rom_name)	Get a list of available view names for a given Reduced Order Model (ROM) available in the TwinModel.
`TwinModel.get_geometry_filepath`(rom_name)	Get the geometry file associated to a Reduced Order Model (ROM) available in the TwinModel.
`TwinModel.get_image_filepath`(rom_name, view_name)	Get the image file associated to a Reduced Order Model (ROM) available in the TwinModel and evaluated at the given time instant.
`TwinModel.get_rom_directory`(rom_name)	Get working directory path for a given Reduced Order Model (ROM) available in the TwinModel.
`TwinModel.get_snapshot_filepath`(rom_name[, ...])	Get the snapshot file associated to a Reduced Order Model (ROM) available in the TwinModel and evaluated at the given time instant.
`TwinModel.initialize_evaluation`([...])	Initialize the twin model evaluation with: (1) a dictionary of parameters values and/or inputs (start) values OR (2) a json configuration file (see example below).
`TwinModel.load_state`(model_id, evaluation_time)	Load a state that has been saved by a TwinModel instantiated with same .twin file.
`TwinModel.save_state`()	Save the state of a TwinModel.

Attributes

`TwinModel.evaluation_is_initialized`	Return true if evaluation has been initialized.
`TwinModel.evaluation_time`	Return a floating point number that is the current twin model evaluation time (in second).
`TwinModel.id`	Model unique id
`TwinModel.initialization_time`	Return a floating point number that is the time at which the twin model has been initialized.
`TwinModel.inputs`	Return a dictionary with input values at current evaluation time.
`TwinModel.instantiation_time`	Return a floating point number that is the time at which the twin model has been instantiated.
`TwinModel.model_dir`	Model directory (within the global working directory)
`TwinModel.model_filepath`	Return a string that is the twin model filepath that has been verified and loaded.
`TwinModel.model_log`	Path to model log file that is used at TwinRuntime instantiation (because we don't know the model name before having instantiated it and this can't use the model_dir in the log file path that is given at instantiation).
`TwinModel.model_log_link`	Path to symbolic link to the log file in the temporary folder and that is stored in the model_dir.
`TwinModel.model_temp`	Model temporary directory (within the global working directory).
`TwinModel.name`	Model name.
`TwinModel.outputs`	Return a dictionary with output values at current evaluation time.
`TwinModel.parameters`	Return a dictionary with parameter values at current evaluation time.
`TwinModel.tbrom_directory_path`	Return TBROM directory path.
`TwinModel.tbrom_info`	Return a dictionary with TBROM model names included in the Twin and their corresponding 3D visualization capabilities available (e.g.
`TwinModel.tbrom_names`	Return available TBROM model names.