Read the docs at https://statdepth.readthedocs.io/en/latest/.
This package implements depth calculation and visualization methods for univariate time series data, multivariate time series data, and pointcloud data. This README will now mostly be development information. To see how to use the package, visit the documentation at the link above.
To install from pip, run
pip install statdepth
To install locally, run
pip install .
Or to install directly from this repo,
pip install git+https://github.com/braingeneers/functional_depth_methods
To set up the development environment as a Conda env, run
conda env create --file environment.yml
This code is written in Python, with most methods written in Numpy. It also uses numba, a high performance Python compiler. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN, so this should remove any speed issues Python has.
Depending on how this ends up being used, dask may also be implemented for parallelization.