Lin Alg Cpp

lazy image, vector promise, pseudoinverse, regularization, C++, class library Hot points: - _efficient_ and _fool-proof_ implementations of level 1 and 2 "BLAS" (element-wise operations + various multiplications) - transpositions and determinant evaluation/inversion - operations on a single row/col/diagonal of a matrix - Lazy vector and Matrices (promises) , and ElementAction iterators for fast sweeping actions - Hooks-Jeevse multidimensional optimization - Aitken-Lagrange interpolation over a grid of uniform or arbitrary mesh - *Singular Value Decomposition* of a rectangular matrix, with an application to solve Ax=b, where A does not have to be square, and b does not have to be a vector. In a case of a rectangular matrix A, this effectively solves a least-squares problem. - Brent's efficient univariate optimization and root finding (with a guaranteed conversion) - with a validation code to verify everything - with a rather commented source and CW8 projects Contents: README - not just a plain README file libla.pi - CW8 project to make a library, libla.a libla.a - compiled library for a PowerMac v*.pi - projects to run a validation code v*.dat - output produced by the validation code (for verification and asserting accuracy) NumMath.dr - tells what the other files are for *.h, *.cc - source code files Language: C++, CodeWarrior 7/8 System: System 7.5 Note: the code is equivalent to that submitted to netlib: this is because exactly the same code compiles both on a Mac and under UNIX (Solaris 2.4). However, the present submission has the code neatly arranged into CW projects. It also includes the compiled PowerMac library. Comments-to: oleg@ponder.csci.unt.edu, oleg@unt.edu I'll really appreciate any comment/question etc if any. Thank you for your consideration indeed, Oleg