imod.wq.GeneralizedConjugateGradientSolver#

class imod.wq.GeneralizedConjugateGradientSolver(max_iter=1, inner_iter=50, cclose=1e-06, preconditioner='mic', lump_dispersion=True)[source]#

The Generalized Conjugate Gradient Solver solves the matrix equations resulting from the implicit solution of the transport equation.

Parameters
  • max_iter (int) – is the maximum number of outer iterations (MXITER); it should be set to an integer greater than one (1) only when a nonlinear sorption isotherm is included in simulation.

  • iter1 (int) – is the maximum number of inner iterations (iter1); a value of 30-50 should be adequate for most problems.

  • isolve (int) – is the type of preconditioners to be used with the Lanczos/ORTHOMIN acceleration scheme: isolve = 1: Jacobi isolve = 2: SSOR isolve = 3: Modified Incomplete Cholesky (MIC) (MIC usually converges faster, but it needs significantly more memory)

  • lump_dispersion (bool) – is an integer flag for treatment of dispersion tensor cross terms: ncrs = 0: lump all dispersion cross terms to the right-hand-side (approximate but highly efficient). ncrs = 1: include full dispersion tensor (memory intensive).

  • cclose (float) – is the convergence criterion in terms of relative concentration; a real value between 10-4 and 10-6 is generally adequate.

__init__(max_iter=1, inner_iter=50, cclose=1e-06, preconditioner='mic', lump_dispersion=True)[source]#

Methods

__init__([max_iter, inner_iter, cclose, ...])

from_file(path, **kwargs)

Loads an imod-wq package from a file (currently only netcdf and zarr are supported).

isel()

save(directory)

sel()

write_netcdf(directory, pkgname[, ...])

Write to netcdf.