dmx-learn 1.0.0

A package for estimating heterogeneous probability density functions.

dmx-learn - (Distributed Mixture Learning) A package for distributed heterogeneous density estimation. With only a few lines of code you can specify and fit complex models on variable-length heterogenous data.

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📚 Documentation

View the full documentation on Read the Docs:

👉 https://dmx-learn.readthedocs.io/en/latest/

Installation

User installation with pip

> pip install --user /path/to/package

Building with mpi4py and umap-learn

> cd /path/to/package
> pip install --user .[optional]

Stats Examples

Examples using stats distributions that run locally are located in ./dmx/examples/

> export PYHONPATH=$PYTHONPATH:/path./to/dmx-learn
> PYTHONPATH=/path/to/package/ python ./dmx/examples/stats_examples/mixture_example.py

Running with Spark

Examples that run with Apache Spark are located in./dmx/examples_spark/

First build a wheel

> cd /path/to/dmx-learn
> pip install setuptools wheel
> python setup.py bdist_wheel

Run the example with below

> /path/to/spark/bin/spark-submit --master local[*] --py-files /path/to/package/dist/dmx-learn-0.1.8.4-py3-none-any.whl ./dmx/examples_spark/mixture_example.py

Running with MPI4PY

Examples that run with mpi4py are located in ./dmx/mpi4py/examples/

Below will run the example ./dmx/mpi4py/examples/estimation_example.py with 4 cores.

> export PYHONPATH=$PYTHONPATH:/path./to/dmx-learn
> mpiexec -n 4 python /path/to/package/dmx/mpi4py/examples/estimation_example.py