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Running T3

General

Executing T3 can be done via two ways:

  • using an input file, or
  • using the Python API

Other than subtle differences described here, both approaches are equivalent as they can define the same parameters which will be processed via the same routines.

Note: Most examples in these documentation pages are in a Python API format rather than a yaml input file** format.

T3 also has a function for writing a corresponding YAML input file after defining parameters via the API, see the How-to guides for more details.

Activate the environment

To use T3, first activate the T3 environment. Type either:

conda activate t3_env

or, if you have set up the recommended aliases, simply type:

t3e

Arguments

T3 has three minor arguments (project, project_directory, and verbose) and three primary arguments (t3, rmg, and qm).

The project argument is required. It is a string representing the T3 project name.

The project_directory argument is optional. It is a string representing the path to the local project directory where all the project files are stored. If not specified, it will be set to the folder in which the input file is located if T3 is being executed using an input file, or to a respective subfolder with the project's name under the Projects folder in the T3 repository.

The verbose argument is optional. It is an integer representing the logging level used by T3. Allowed values are: 10: debug level (very verbose), 20: info level (default), 30: warnings and errors only, 40: errors only. Pass None to this argument to avoid saving a log file.

The primary arguments specify various options for the different respective packages (T3, RMG, and QM which currently only supports ARC Of these three, only the rmg argument is required. The qm argument must be specified if QM-based model refinement is desired (in most cases it is!). The t3 argument contains optional T3-related directives and should commonly be specified.

The RMG arguments in T3 are written in an underscore_lower_case (snake_case) syntax, while many are in a camelCase syntax in RMG. A few RMG arguments have different names altogether in T3. These arguments are:

  • kinetics_libraries: In the RMG database block, the kinetics_libraries argument replaces the legacy RMG reactionLibraries argument.
  • core_tolerance: In the RMG model block, the core_tolerance argument replaces the legacy RMG toleranceMoveToCore argument. See the How-to guides for more details.
  • conditions_per_iteration: In the RMG reactors block, the conditions_per_iteration argument replaces the legacy RMG nSims argument.
  • Species definitions are different than in RMG, see the How-to guides for more details.
  • Reactors definitions are different than in RMG, see the How-to guides for more details.

Note: Some of the RMG default values have been changed in T3, see the schema for details

Use the below reference guide to learn more about these arguments.

Reference guide

T3 has several types of reference guides:

  • The tutorials are a great place to start with, and provide an excellent basic reference guide. In T3's tutorials you can find complete, functioning, and worked-out examples with explanations.
  • The commented input file in T3's examples shows all available input arguments along with a brief explanation.
  • A pydentic schema is used to validate the input file, and could also be used as a reference for the various allowed arguments.

Where next?

New users should start learning how to use T3 by reading and executing the tutorials.

For advanced features and specific examples for solving complex problems, see the how-to guides.