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MCPL

Monte Carlo Particle Lists

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Get MCPL

If using conda, you can simply install MCPL from the conda-forge channel. Thus, conda install -c conda-forge mcpl gives access to all the various command-line tools, and API’s for C/C++, Python, and CMake.

Alternatively you can also install MCPL via, pip install mcpl, which gives access to only the pymcpltool and the mcpl Python module. If possible, the installation via conda is recommended.

Finally, you can of course also use the tar.gz, zip or github links to download source files for the latest MCPL distribution. But take note that if you are a user of McStas, McXtrace or the ESS-dgcode framework, you likely already have MCPL available through the framework you are using.

After downloading the MCPL tar-ball or zip-file, unpack it somewhere and follow the instructions in the INSTALL file for how to proceed to build and install using either CMake (to build everything including examples) or a simple Makefile or compilation command (to build just “fat” versions of mcpltool, ssw2mcpl, mcpl2ssw, phits2mcpl, or mcpl2phits executables). Additional information can also be found in the MCPL paper (section 2.5).

To start playing around with the mcpltool, we also provide a small sample MCPL file with the distribution: example.mcpl.