I am a climate scientist and Matlab offers a lot to me : great matrix syntax, very fast algorithms (SVD, matrix inversion, FFT), large mindshare (cf Central File Exchange), and advanced toolboxes for statistics, spectral analysis and the like.
Not being a programmer by birth, I couldn't care less about the fact that it's not a general purpose language ; it is very adequate for my own purpose.
BUT... it is proprietary, pretty expensive, and at the moment I am considering problems that require parallel computations on dozens of CPU. Matlab has a Parallel Computation Toolbox that is a joke (<= 8 CPUS at a time, monopolizing the same number of licenses), and that is why I am considering Python.
Does NumPy enable parallel computations ? Is it reasonably easy to translate Matlab code into NumPy ?
Is there a good library of linear algebra routines (like SVD, eigendecompositions, inversions, LU, Cholesky decompositions, etc..) ? A large user community with a comprehensive archive ?
BUT... it is proprietary, pretty expensive, and at the moment I am considering problems that require parallel computations on dozens of CPU. Matlab has a Parallel Computation Toolbox that is a joke (<= 8 CPUS at a time, monopolizing the same number of licenses), and that is why I am considering Python.
Does NumPy enable parallel computations ? Is it reasonably easy to translate Matlab code into NumPy ? Is there a good library of linear algebra routines (like SVD, eigendecompositions, inversions, LU, Cholesky decompositions, etc..) ? A large user community with a comprehensive archive ?