Skip to main content

A module for calculation of PCA with the NIPALS algorithm

Project description

A module for calculation of PCA and PLS with the NIPALS algorithm. Based on the R packages nipals and pcaMethods as well as the statistical appendixes to “Introduction to Multi- and Megavariate Data Analysis using Projection Methods (PCA & PLS)” by Eriksson et. al. Tested to give same results as the above packages and Simca, with some rounding errors.

  • Free software: MIT license


pip install nipals


To run the all tests run:


Note, to combine the coverage data from all the tox environments run:

set PYTEST_ADDOPTS=--cov-append
PYTEST_ADDOPTS=--cov-append tox


0.5.2 (2019-06-04)

  • Added compatibility with Nipals objects saved from pre-0.5 versions

0.5.1 (2019-05-23)

  • Added checks for, and optional removal of, zero variance in variables
  • Added support for Python 3.7
  • (0.5.0 was never released due to failing CI tests)

0.4.3 (2018-04-24)

  • Fixed test that failed after last bug fix

0.4.2 (2018-04-24)

  • Fixed bug with selection of starting column for cross validation of PCA

0.4.1 (2018-04-09)

  • Fixed bug with cross validation of PCA

0.4.0 (2018-04-09)

  • Added cross validations
  • Added calculation of distance to model with plots
  • Added model overview plots

0.3.0 (2018-04-05)

  • Added R2X and R2Y to the PLS class
  • Made plot color selectable also for scoreplots without classes

0.2.0 (2018-03-29)

  • Added a PLS class
  • Improved plotting
  • Fixed some problems with missing/infinite values

0.1.0 (2018-03-14)

  • First release on PyPI.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for nipals, version 0.5.2
Filename, size File type Python version Upload date Hashes
Filename, size nipals-0.5.2-py2.py3-none-any.whl (10.4 kB) File type Wheel Python version py2.py3 Upload date Hashes View
Filename, size nipals-0.5.2.tar.gz (292.7 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page