Getting started#
Installation (for most users)#
You can install Tc1D in your Python environment using pip.
pip install tc1d
Thermochronometer ages are calculated using Tcages, which is installed automatically with Tc1D.
Warning
If you choose to install Tc1D versions older than 0.5.0, you will also need to install the thermochronometer age prediction programs available in the v0.2 release of Tc_core in order for Tc1D to work properly. Installing the latest version of Tc1D is strongly recommended.
Installation (for parallel MCMC inversions)#
You can include support for parallel Markov-Chain Monte Carlo (MCMC) inversions in Tc1D by installing using the following options in pip.
pip install "tc1d[mpi]"
Note
This should work in Linux and macOS, but you may need to install OpenMPI or MPICH for MPI support. In Windows, MPI is available via ms-mpi or IntelMPI, but you will need to install that software manually for MPI support.
Running a basic model#
After installation, an example model with 10 km of exhumation and default values for all other parameters can be run from the command line as follows:
tc1d-cli --ero-option1 10.0
Note
It is also possible to define parameters and run Tc1D using Python function calls or an input file. These cases are described in the user guide.
Model options#
A full list of options that can be used with Tc1D can be found by running the code with the --help flag (or no specified flags):
tc1d-cli --help
This will return a usage statement and list of flags the code accepts.
Example notebooks#
Additional examples of how to run Tc1D can be found in a set of Jupyter notebooks, which you can try online using the launch binder button on the Tc1D GitHub page, for example. To get a local copy of all of the notebooks and their data files, run
tc1d-notebooks
This downloads the notebooks matching your installed version of Tc1D into a new tc1d-notebooks directory. Use tc1d-notebooks --help to see how to choose a different location or version.
The notebooks are also available as a ZIP file attached to each Tc1D release and the notebooks for the latest release can be downloaded directly.
To run the notebooks locally you will also need JupyterLab, which can be installed along with Tc1D using
pip install "tc1d[notebook]"