{ "info": { "author": "Fredrik Wallner", "author_email": "fredrik@wallner.nu", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Operating System :: Microsoft :: Windows", "Operating System :: POSIX", "Operating System :: Unix", "Programming Language :: Python", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: Implementation :: CPython", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Bio-Informatics", "Topic :: Scientific/Engineering :: Chemistry", "Topic :: Utilities" ], "description": "========\nOverview\n========\n\n\n\nA module for calculation of PCA and PLS with the NIPALS algorithm. Based on the R packages\n`nipals `_ and\n`pcaMethods `_ as well as the\nstatistical appendixes to \"Introduction to Multi- and Megavariate Data Analysis\nusing Projection Methods (PCA & PLS)\" by Eriksson et. al.\nTested to give same results as the above packages and Simca, with some rounding errors.\n\n\n* Free software: MIT license\n\nInstallation\n============\n\n::\n\n pip install nipals\n\nDocumentation\n=============\n\nhttps://python-nipals.readthedocs.io/\n\nDevelopment\n===========\n\nTo run the all tests run::\n\n tox\n\nNote, to combine the coverage data from all the tox environments run:\n\n.. list-table::\n :widths: 10 90\n :stub-columns: 1\n\n - - Windows\n - ::\n\n set PYTEST_ADDOPTS=--cov-append\n tox\n\n - - Other\n - ::\n\n PYTEST_ADDOPTS=--cov-append tox\n\nChangelog\n=========\n\n0.5.1 (2019-05-23)\n------------------\n\n* Added checks for, and optional removal of, zero variance in variables\n* Added support for Python 3.7\n* (0.5.0 was never released due to failing 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