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

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 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