simvue-moose 1.0.0

Connector to allow you to easily add Simvue tracking and monitoring to MOOSE (Multiphysics Object Oriented Simulation Environment) simulations.

Simvue Connectors - MOOSE

Allow easy connection between Simvue and MOOSE (Multiphysics Object Oriented Simulation Environment), allowing for easy tracking and monitoring of physics simulations in real time.

Website • Documentation

Implementation

A customised MooseRun class has been created which automatically does the following:

• Uploads the MOOSE input file and application Makefile as input artifacts
• Launches the MOOSE simulation as a process, triggering an alert if it encounters an error or exception
• Uploads information from the MOOSE input file as metadata
• Uploads information from the top of the console log (MOOSE version, parallelism information, mesh information etc) as metadata
• Uploads key information from the console log as events
• Creates an alert which notifies the user if a step fails to converge
• Uploads any variable values being written to CSV files as metrics
• Adds relevant metadata and tags to the run if the MOOSE Terminator stopped the run early
• Once complete, upload the any output files as artifacts

Installation

To install and use this connector, first create a virtual environment:

python -m venv venv

Then activate it:

source venv/bin/activate

And then use pip to install this module:

pip install simvue-moose

Configuration

The service URL and token can be defined as environment variables:

export SIMVUE_URL=...
export SIMVUE_TOKEN=...

or a file simvue.toml can be created containing:

[server]
url = "..."
token = "..."

The exact contents of both of the above options can be obtained directly by clicking the Create new run button on the web UI. Note that the environment variables have preference over the config file.

Usage example

from simvue_moose.connector import MooseRun

...

if __name__ == "__main__":

    ...

    # Using a context manager means that the status will be set to completed automatically,
    # and also means that if the code exits with an exception this will be reported to Simvue
    with MooseRun() as run:

        # Specify a run name, along with any other optional parameters:
        run.init(
          name = 'my-moose-simulation',                                 # Run name
          metadata = {'initial_temp': 30},                              # Metadata
          tags = ['moose', 'conduction'],                               # Tags
          description = 'MOOSE simulation of thermal conduction.',      # Description
          folder = '/moose/conduction/coffee_cup'                       # Folder path
        )

        # Set folder details if necessary
        run.set_folder_details(
          metadata = {'mesh': 'coffee_cup'},                            # Metadata
          tags = ['moose'],                                             # Tags
          description = 'MOOSE simulations of thermal conduction'       # Description
        )

        # Can use the base Simvue Run() methods to upload extra information, eg:
        run.save_file(os.path.abspath(__file__), "code")

        # Can add alerts specific to your simulation, eg:
        run.create_metric_threshold_alert(
          name="temperature_above_eighty",        # Name of Alert
          metric="temperature",                   # Metric to monitor
          frequency=1,                            # Frequency to evaluate rule at (mins)
          rule="is above",                        # Rule to alert on
          threshold=80,                           # Threshold to alert on
          notification='email',                   # Notification type
          trigger_abort=True                      # Abort simulation if triggered
        )

        # Launch the MOOSE simulation
        run.launch(
            moose_application_path='path/to/my/moose/app',    # Path to MOOSE application
            moose_file_path='path/to/my/input_file.i',        # Path to MOOSE input file
            track_vector_postprocessors=True,                 # Whether to track vector postprocessors
            track_vector_positions=False,                     # Whether to track positions of vectors
            run_in_parallel=True,                             # Whether to run in parallel using MPI
            num_processors=2                                  # Number of cores to use if in parallel

            )

License

Released under the terms of the Apache 2 license.

Citation

To reference Simvue, please use the information outlined in this citation file.