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libpca C++ library

A C++ library for principal component analysis

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libpca is a C++ library for principal component analysis and related transformations. It comes with example and unit tests. libpca is successfully tested on Linux and MacOSX using g++ (>=4.6), clang++ (>=3.2), and icc (>=14.0).

libpca requires Armadillo (>=3.2.4) which can be obtained as a pre-compiled package on most distributions or directly from

libpca is being developed by Christian Blume. Contact Christian at for any questions or comments.

libpca C++ library Web Site


Algorithms, Statistics


MIT License


  • computes a principal component analysis
  • computes energy, eigenvalues, eigenvectors, principal components
  • option to normalize the data matrix
  • option to bootstrap the eigenproblem to obtain uncertainty estimates of energy and eigenvalues
  • methods to project data records to the space of principal components and back
  • method to reduce the number of eigenvectors affecting the data record projections
  • methods to check the accuracy of the solution to the eigenproblem
  • methods to save and load pca properties to and from files
  • pca offers a standard C++ interface using not more than primitive types, std::string, and std::vector
  • libpca comes with example and unit tests
  • a great deal of libpca runs in parallel thanks to Armadillo


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