Installation

You can install T_cplotter using pip.

pip install tcplotter

Note: In order for T_cplotter to work properly you will also need to install the thermochronometer age prediction programs available in the T_ccore package.

Installing the latest version of T_cplotter from GitHub (not recommended)

Below you will find the steps to install the latest version of the T_cplotter package from GitHub. If you have difficulty with the installation, we recommend using Binder to create and save plots using T_cplotter.

1. First, you will need the several items in order to compile the software used for thermochronometer age and closure temperature calculations.

   • cmake

   • a compatible C compiler

   • a compatible C++ compiler

   You can find more information about which compilers can be used with cmake from the cmake documentation page.

2. In addition, T_cplotter requires Python >= 3.10 with the following Python libraries:

   • numpy

   • matplotlib-base

   • scipy

3. Once the required Python libraries have been installed, you can download the T_cplotter code from GitHub by visiting the T_cplotter GitHub page, clicking on the Code button on the upper right side of the page, and selecting Download ZIP. After the download completes, you can extract the files using your preferred software.

4. At this point, you will need to compile the software for calculating the thermochronometer ages using cmake. You can find instructions about how to do this on the T_ccore package GitHub page.

5. You can now do a local install of T_cplotter using pip by navigating to the bast tcplotter directory in a terminal and running the following:

   pip install -e .
   

   This will install T_cplotter locally for your use.

Testing the installation

At this point you should have a working T_cplotter installation. You can test it by running on of the T_cplotter command-line programs. For example, you could run the following in a terminal where T_cplotter 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