Installation#
You can install Tcplotter using pip.
pip install tcplotter
This also installs Tcages, which provides the thermochronometer age prediction codes used by Tcplotter. Pre-built packages are available for Linux, macOS and Windows, so no compilers are needed.
Note: Tcplotter versions up to 0.4.0 required installing separate age prediction programs. This is no longer necessary from version 0.5.0 onwards.
Installing the latest version of Tcplotter from GitHub#
You can install the latest development version of Tcplotter directly from GitHub using pip:
pip install git+https://github.com/HUGG/tcplotter.git
Tcplotter requires Python >= 3.10. All required Python libraries (matplotlib, numpy, scipy and tcages) are installed automatically.
If you would like to modify the code, you can instead clone the repository and do an editable install:
git clone https://github.com/HUGG/tcplotter.git
cd tcplotter
pip install -e .
Testing the installation#
At this point you should have a working Tcplotter installation. You can test it by running one of the Tcplotter command-line programs. For example, you could run the following in a terminal where Tcplotter is installed:
eu-vs-radius
This should produce a contour plot of cooling ages and closure temperatures for a range of effective uranium and grain radius values.
Optional graphical progress bar#
It is possible to enable a graphical progress bar with tcplotter when using it in a Jupyter notebook. This requires the ipywidgets library. ipywidgets can also be installed using pip or conda:
pip install ipywidgets
or
conda install -c conda-forge ipywidgets