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Changelog

lazymatrix 0.1.0

Initial CRAN submission.

New Features

  • Introduced lazy evaluation framework for working with normalized sparse matrices
  • Represent large sparse matrices symbolically with the S4 object LazyMatrix
  • Fundamental matrix operations like matrix-vector multiplication and transpose matrix-vector multiplication supported for the LazyMatrix object
  • Added support for subsetting methods, mirroring matrix objects from base R and Matrix. The symbolic equivalent of column vectors is called LazyColumn
  • Implemented specific statistical algorithms, LSQR, truncated partial SVD, for showcasing how lazymatrix can be implemented
  • Optimized internal C++ loops for sparse matrix operations using RcppArmadillo.

Improvements

  • Optimized matrix multiplication for lazy objects to avoid materialization
  • Added vignette demonstrating typical workflow with large sparse datasets

Bug Fixes

  • No known bugs fixed in initial release

Documentation

  • Added comprehensive roxygen2 documentation for all exported functions
  • Included example code in each function’s documentation
  • Wrote getting started vignette covering installation and basic usage

Internal Changes

  • Utilized Matrix package for underlying sparse matrix representation
  • Implemented partial SVD using irlba