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author | Arun Isaac | 2022-01-08 13:14:30 +0530 |
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committer | Arun Isaac | 2022-01-08 13:14:30 +0530 |
commit | 89d4e7984ca26315e2f645beee7aea0e52d5cb2a (patch) | |
tree | ef3a5b2cb30e35bc740f45765590928cf99f8760 /python/README.md | |
parent | b8d499871bdd6d5ccf42f7cd41b5c6f6d1fa090c (diff) | |
download | nsmc-main.tar.gz nsmc-main.tar.lz nsmc-main.zip |
* README.org: Advertise python code.
* python/README.md: New file.
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diff --git a/python/README.md b/python/README.md new file mode 100644 index 0000000..8a061c3 --- /dev/null +++ b/python/README.md @@ -0,0 +1,36 @@ +This repository is the source code accompanying the following papers. +- [An O(n) algorithm for generating uniform random vectors in n-dimensional cones](https://arxiv.org/abs/2101.00936) +- [An algorithm for estimating volumes and other integrals in n dimensions](https://arxiv.org/abs/2007.06808) + +However, most of the code for [An O(n) algorithm for generating +uniform random vectors in n-dimensional +cones](https://arxiv.org/abs/2101.00936) has been released as a +separate library—sambal. See [PyPI +page](https://pypi.org/project/sambal/) and +[source](https://git.systemreboot.net/sambal). + +# Dependencies + +The code depends on the following dependencies. Please install them +before running the scripts. A python virtual environment may be an +easy way to do this. + +- Python 3 +- matplotlib +- numpy +- scipy +- sambal + +# Run + +The core functions are in `nsmc.py`. The experiments are in the +scripts `distribution-volumes.py`, `distribution-integrals.py` and +`spheroid.py`. Run those scripts as +``` +$ python3 distribution-volumes.py +$ python3 distribution-integrals.py +$ python3 spheroid.py +``` +Plots of the number of samples versus the dimension get written to the +current directory. Play around with the number of trials, dimensions, +and relative error tolerances in the scripts. |