krylov 0.0.2

Krylov subspace methods.

Forked from André Gaul's KryPy, krylov provides Krylov subspace methods for Python. It is more advanced than SciPy's linalg methods in that it

• allows arbitrary inner products,
• return many interesting statistics, e.g., the residual norms,
• lets the user adjust more parameters, e.g., the orthogonalization method in GMRES, and
• is fully blocked/vectorized. krylov is written completely in Python.

Install with

pip install krylov

and use as

import numpy
import krylov

A = numpy.diag([1.0e-3] + list(range(2, 101)))
b = numpy.ones(100)

# sol, info = krylov.cg(A, b)
# sol, info = krylov.minres(A, b)
sol, info = krylov.gmres(A, b)

# sol is None if no solution has been found
# onfo.resnorms contains the relative residual norms and some more data

# plot residuals
import matplotlib.pyplot as plt

plt.semilogy(info.resnorms)
plt.show()

Testing

To run the krylov unit tests, check out this repository and type

pytest

License

krylov is published under the MIT license.