Metadata-Version: 2.1
Name: mapca
Version: 0.0.1
Summary: A Python implementation of the moving average principal components analysis methods from GIFT.
Home-page: https://github.com/me-ica/mapca
Author: mapca developers
Author-email: e.urunuela@bcbl.eu
Maintainer: Eneko Urunuela
Maintainer-email: e.urunuela@bcbl.eu
License: GPL-2.0
Download-URL: https://github.com/ME-ICA/mapca/archive/0.0.1.tar.gz
Description: # mapca
        A Python implementation of the moving average principal components analysis methods from GIFT
        
        [![Latest Version](https://img.shields.io/pypi/v/mapca.svg)](https://pypi.python.org/pypi/mapca/)
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        ## About
        
        `mapca` is a Python package that performs dimensionality reduction with principal component analysis (PCA) on functional magnetic resonance imaging (fMRI) data. It is a translation to Python of the dimensionality reduction technique used in the MATLAB-based [GIFT package](https://trendscenter.org/software/gift/) and introduced by Li et al. 2007[^1].
        
        [^1]: Li, Y. O., Adali, T., & Calhoun, V. D. (2007). Estimating the number of independent components for functional magnetic resonance imaging data. Human Brain Mapping, 28(11), 1251–1266. https://doi.org/10.1002/hbm.20359
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: dev
Provides-Extra: doc
Provides-Extra: tests
Provides-Extra: duecredit
Provides-Extra: all
