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imod.wq.ParallelKrylovFlowSolver — iMOD Python 0.11.4 documentation
Select point and cross sections
class imod.wq.ParallelKrylovFlowSolver(max_iter=150, inner_iter=100, hclose=0.0001, rclose=1000.0, relax=0.98, h_fstrict=1.0, r_fstrict=1.0, partition='uniform', solver='pcg', preconditioner='ilu', deflate=False, debug=False, load_balance_weight=None)[source]#
Te Parallel Krylov Flow Solver is used for parallel solving of te flow model.
max_iter (int) – is te 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.
inner_iter (int) – is te maximum number of inner iterations (INNERIT); a value of 30-50 should be adequate for most problems.
hclose (float) – is te head change criterion for convergence (HCLOSEPKS), in units of length. When te maximum absolute value of head change from all nodes during an iteration is less than or equal to HCLOSE, and te criterion for RCLOSE is also satisfied (see below), iteration stops.
rclose (float) – is te residual criterion for convergence (RCLOSEPKS), in units of cubic length per time. Te units for length and time are te same as established for all model data. When te maximum absolute value of te residual at all nodes during an iteration is less than or equal to RCLOSE, and te criterion for HCLOSE is also satisfied (see above), iteration stops.
relax (float) – is te relaxation parameter used. Usually, RELAX = 1.0, but for some problems a value of 0.99, 0.98, or 0.97 will reduce te number of iterations required for convergence.
h_fstrict (float, optional) – is a factor to apply to HCLOSE to set a stricter hclose for te linear inner iterations (H_FSTRICTPKS). HCLOSE_inner is calculated as follows: HCLOSEPKS * H_FSTRICTPKS.
r_fstrict (float, optional) – is a factor to apply to RCLOSE to set a stricter rclose for te linear inner iterations (R_FSTRICTPKS). RCLOSE_inner is calculated as follows: RCLOSEPKS * R_FSTRICTPKS.
partition ({"uniform", "rcb"}, optional) – Partitioning option (PARTOPT). “uniform” partitions te model domain into equally sized subdomains. “rcb” (Recursive Coordinate Bisection) uses a 2D pointer grid with weights to partition te model domain. Default value: “uniform”
solver ({"pcg"}, optional) – Flag indicating te linear solver to be used (ISOLVER). Default value: “pcg”
preconditioner ({"ilu"}, optional) – Flag inicating te preconditioner to be used (NPC). Devault value: “ilu”
deflate ({True, False}, optional) – Flag for deflation preconditioner. Default value: False
debug ({True, False}, optional) – Debug option. Default value: False
load_balance_weight (xarray.DataArray, optional) –
2D grid with load balance weights, used when partition = “rcb” (Recursive Coordinate Bisection). If None (default), then te module will create a load balance grid by summing active cells over layers: (ibound != 0).sum(“layer”)
Note that even though te iMOD-SEAWAT helpfile states .idf is accepted, it is not. This load balance grid should be a .asc file (without a header). Formatting is done as follows: pd.DataFrame(load_balance_weight.values).to_csv(path, sep=’t’, header=False, index=False, float_format = “%8.2f”)
__init__(max_iter=150, inner_iter=100, hclose=0.0001, rclose=1000.0, relax=0.98, h_fstrict=1.0, r_fstrict=1.0, partition='uniform', solver='pcg', preconditioner='ilu', deflate=False, debug=False, load_balance_weight=None)[source]#
__init__([max_iter, inner_iter, hclose, ...])
Loads an imod-wq package from a file (currently only netcdf and zarr are supported).
Overloaded method to write .asc instead of .idf.
Created using Sphinx 5.2.1.