Phylourny is a toy project to apply a modified version of Felsenstein's pruning algorithm to predicting tournament, such as football or basketball tournaments. The big advantage of doing this, over just running simulations, is that we obtain higher fidelity estimations with less effort.
As stated before the algorithm used in Phylourny is a modified version of Felsenstein's pruning algorithm for evaluating the likelihood of a tree and a model given some data. As pointed out by Zhang in his book Computational Molecular Evolution this algorithm is itself a version of a method from the early Chinese mathematics to evaluate polynomials faster. We use this to enumerate the paths a team can take through the tournament in a quicker fashion than brute force enumeration.
It is probably important to note that this problem is unlikely to get to the size that this is needed. Most tournaments in the world are small, and are perfectly capable of being sampled, or of enumerating the paths explicitly.
To download Phylourny, use the command
git clone --recursive https://github.com/computations/phylourny
and to build
make
The resulting binaries will be placed in bin. Depending on the packages installed locally, there might be 3 binaries:
phylourny: The main binary.phylourny_test: The test suite.phylourny_bench: The benchmarking suite.
For most people, only the main binary will be interesting. The test binary will be useful if one needs to check the code does actually work, but the benchmarking binary contains a lot of "extra" benchmarks that are not really that relevant to the program.
The test suite will be built if CMake detects that the address sanitizer is available with the compiler used, and if the
option PHYLOURNY_BUILD_TESTS is set, which it is by default. To disable building tests, set the option
PHYLOURNY_BUILD_TESTS to OFF.
Benchmarks will be built if the flag PHYLOURNY_BUILD_BENCH is set on, which it is by default. To disable building the
benchmark suite, set PHYLOURNY_BUILD_BENCH to OFF.
There are example datasets in the experiments directory. These are a good
place to start if you want to stary using the tool.
