Plotting functions for visualisation of data analysis results from the hoggorm package
Project description
hoggormplot is a python package that contains simple plotting functions for visualisation of data analysis results from the hoggorm package.
Hoggorm is a Python package for explorative multivariate statistics in Python. It contains PCA (principal component analysis), PCR (principal component regression), PLSR (partial least squares regression) and the matrix corrlation coefficients RV and RV2.
Installation
pip install hoggormplot
Requirements
hoggorm
matplotlib
Documentation
hoggormplot contains the following scripts for showcasing the use of the plotting functions for each of the implemented analysis methods:
TEST_pca.py
TEST_pcr.py
TEST_pls1.py
TEST_pls2.py
You can run this code by typing this on the commandline:
python -m hoggormplot.TEST_pca
python -m hoggormplot.TEST_pcr
python -m hoggormplot.TEST_pls1
python -m hoggormplot.TEST_pls2
The content of these files will later be moved to Ipython notebooks for easier exploration.
Latest changes
None.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for hoggormplot-0.11.1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c5183d48cca12af198519b06b77822f80a878cb1e59405b712d6aeb5b3d12e46 |
|
MD5 | 41426bb8dc0a49571f6cefd4d7baad03 |
|
BLAKE2b-256 | 58a93f4e6c958e398fccf158579976c233451c15621a8a5574546b898617ff3c |