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:
T3 has three minor arguments (
and three primary arguments (
project argument is required. It is a string representing the T3 project name.
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.
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,
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
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_librariesargument replaces the legacy RMG
core_tolerance: In the RMG model block, the
core_toleranceargument replaces the legacy RMG
toleranceMoveToCoreargument. See the How-to guides for more details.
conditions_per_iteration: In the RMG reactors block, the
conditions_per_iterationargument replaces the legacy RMG
- 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.
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.
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.