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Pure Python Linear Algebra

Features

  • Basic matrix and vector operations: multiplication, summation, scaling, transposition, inversion.
  • Some more advanced matrix decompositions:
    • QR decomposition
    • SVD decomposition

Why use PYLA

PYLA is

  • Lightweight. It is much smaller than Numpy
  • Standard pure Python. It should work on every pyhton implementation, that is decent enough.
  • Generic. It is not limited by floats. Particularly, you can use GMPY's long floats with all matrix algorithms.

Performance

Performance is not a primary goal for PYLA. If you need performance, use of native libraries, such as Numpy, is highly recommended. As a a consequence, no special effort was done to increase performance. However, the algorithms themselves are