A Python implementation of the moving average principal components analysis methods from GIFT
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 and introduced by Li et al. 20071.
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 ↩
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Moving Average Principal Component Analysis for fMRI data
We found that mapca demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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