Eigenvalue computation using scipy.sparse.linalg.eig

[momchilmm]

Currently, the eigenvalues are computed using numpy.linalg.eigh, which returns all eigenvalues of a matrix. For large matrices, it could be much more efficient to use instead something like scipy.sparse.linalg.eig, where only a specified number of eigenvalues is computed. To make this compatible with the 'autograd' backend, an autograd primitive should be defined for that function, which shouldn't be too hard starting from the primitive for numpy.linalg.eigh, which can already be found in pygme.primitives.py.

[momchilmm]

This is now available although in most cases one should probably still just use the numpy eigh (default).