DiviK package

Tools within this package

• Clustering at your command line with fit-clusters

• Set of algorithm implementations for unsupervised analyses

  • Clustering

    • - hands-free clustering method with built-in feature selection

    • for selecting the number of clusters

    • for selecting the number of clusters

    • Modular with custom distance metrics and initializations

  • • data-driven feature selection

  • • - generates samples of fixed number of rows from given dataset, preserving groups proportion

    • - generates samples of random observations within boundaries of an original dataset, and preserving the rotation of the data

The recommended way to use this software is through . This is the most convenient way, if you want to use divik application.

To install latest stable version use:

Prerequisites for installation of base package:

• Python 3.6 / 3.7 / 3.8

• compiler capable of compiling the native C code and OpenMP support

You should have it already installed with GCC compiler, but if somehow not, try the following:

OpenMP is available as part of LLVM. You may need to install it with conda:

Having prerequisites installed, one can install latest base version of the package:

If you want to have compatibility with , you can install necessary extras with:

Note: Remember about \ before [ and ] in zsh shell.

You can install all extras with:

If you are using DiviK to run the analysis that could fail to fit RAM of your computer, consider disabling the default parallelism and switch to . It's easy to achieve through configuration:

• set all parameters named n_jobs to 1;

• set all parameters named allow_dask to True.

Note: Never set n_jobs>1 and allow_dask=True at the same time, the computations will freeze due to how multiprocessing and dask handle parallelism.

It can happen if the he gamred_native package (part of divik package) was compiled with different numpy ABI than scikit-learn. This could happen if you used different set of compilers than the developers of the scikit-learn package.

In such a case, a handler is defined to display the stack trace. If the trace comes from _matlab_legacy.py, the most probably this is the issue.

To resolve the issue, consider following the installation instructions once again. The exact versions get updated to avoid the issue.

Contribution guide will be developed soon.

Format the code with:

This software is part of contribution made by , rest of which is published .