dynamicviz 0.0.1

DynamicViz provides a wrapper for generating and interpreting dynamic visualizations from traditional static dimensionality reduction visualization methods

Dynamic visualization

Eric Sun

Python package for generating bootstrap visualizations of high-dimensional data. Great for assessing stability of visualizations and increasing robustness of interpretations. Also included are methods for computing variance scores along with classical concordance scores for quantifying the quality of a visualization.

Installation and setup

Currently, the easiest to port the package is to clone the directory and then install the requirements for using the package. To do this, first clone the repository using git (you can install git following the instructions here):

git clone https://github.com/sunericd/dynamicviz.git

We recommend setting up a conda environment to install the requirements for the package (instructions for installing conda and what conda environment can do can be found here). Installation of requirements can then be done with the following commands:

conda create -n dynamicviz python=3.8
conda activate dynamicviz

cd dynamicviz
pip install -r requirements.txt

To test that the installation is working correctly, you can use the Jupyter notebook tutorial.ipynb (requires installing Jupyter, instructions found here, and adding the conda environment we just created to the Jupyter notebook kernels, instructions found here) or the test script test.py (under development). We are working on providing direct installation over PyPI (pip) in the next few weeks.