Coverage for C:\src\imod-python\imod\flow\slv.py: 100%
24 statements
« prev ^ index » next coverage.py v7.4.4, created at 2024-04-08 13:27 +0200
« prev ^ index » next coverage.py v7.4.4, created at 2024-04-08 13:27 +0200
1import jinja2
3from imod.flow.pkgbase import Package
6class PreconditionedConjugateGradientSolver(Package):
7 """
8 The Preconditioned Conjugate Gradient Solver is used to solve the finite
9 difference equations in each step of a MODFLOW stress period.
11 Parameters
12 ----------
13 max_iter: int
14 is the maximum number of outer iterations - that is, calss to the
15 solutions routine (MXITER). For a linear problem max_iter should be 1, unless
16 more than 50 inner iterations are required, when max_iter could be as
17 large as 10. A larger number (generally less than 100) is required for a
18 nonlinear problem.
19 inner_iter: int
20 is the number of inner iterations (iter1). For nonlinear problems,
21 inner_iter usually ranges from 10 to 30; a value of 30 will be
22 sufficient for most linear problems.
23 rclose: float
24 is the residual criterion for convergence, in units of cubic length per
25 time. The units for length and time are the same as established for all
26 model data. When the maximum absolute value of the residual at all nodes
27 during an iteration is less than or equal to RCLOSE, and the criterion
28 for HCLOSE is also satisfied (see below), iteration stops.
30 Default value: 100.0. **Nota bene**: this is aimed at regional modelling.
31 For detailed studies (e.g. lab experiments) much smaller values can be
32 required.
33 Very general rule of thumb: should be less than 10% of smallest cell volume.
34 hclose: float
35 is the head change criterion for convergence, in units of length. When
36 the maximum absolute value of head change from all nodes during an
37 iteration is less than or equal to HCLOSE, and the criterion for RCLOSE
38 is also satisfied (see above), iteration stops.
39 Default value: 1.0e-4. **Nota bene**: This is aimed at regional modelling, `
40 for detailed studies (e.g. lab experiments) much smaller values can be
41 required.
42 relax: float, optional
43 is the relaxation parameter used. Usually, RELAX = 1.0, but for some
44 problems a value of 0.99, 0.98, or 0.97 will reduce the number of
45 iterations required for convergence.
46 Default value: 0.98.
47 matrix_conditioning_method: int, optional
48 the flag used to select the matrix conditioning method
49 1 is for Modified Incomplete Cholesky (for use on scalar computers)
50 2 is for Polynomial (for use on vector computers or to conserve computer memory)
51 damp: float, optional
52 the damping factor.
53 It is typically set equal to one, which indicates
54 no damping. A value less than 1 and greater than 0 causes damping. DAMP
55 does not affect inner iterations; instead, it affects outer iterations.
56 Default value: 1.0.
57 damp_transient: float, optional
58 the damping factor for transient stress periods.
59 it is read only when `damp` is specified as a negative value.
60 If damp_transient is not read, then the single damping factor,
61 `damp`, is used for both transient and steady-state stress periods.
62 printout_interval: int, optional
63 is the printout interval for PCG.
64 If equal to zero, it is changed to 999.
65 The maximum head change (positive or negative) and
66 residual change are printed for each iteration of a time step
67 whenever the time step is an even multiple of printout_interval.
68 This printout also occurs at the end of each stress period
69 regardless of the value of printout_interval.
70 print_convergence_info: int, optional
71 a flag that controls printing of convergence information from the solver:
72 0 is for printing tables of maximum head change and residual each iteration
73 1 is for printing only the total number of iterations
74 2 is for no printing
75 3 is for printing only if convergence fails
76 """
78 _pkg_id = "pcg"
80 # TODO: update when all options are known
81 _variable_order = [
82 "max_iter",
83 "inner_iter",
84 "hclose",
85 "rclose",
86 "relax",
87 "matrix_conditioning_method",
88 "damp",
89 "damp_transient",
90 "printout_interval",
91 "print_convergence_info",
92 ]
94 _template_projectfile = jinja2.Template(
95 "0001, ({{pkg_id}}), 1, Precondition Conjugate-Gradient\n"
96 "{{max_iter}}, {{inner_iter}}, {{hclose}}, {{rclose}}, {{relax}}, "
97 "{{matrix_conditioning_method}}, {{printout_interval}}, {{print_convergence_info}}, {{damp}}, {{damp_transient}}, "
98 "{{IQERROR}}, {{QERROR}}\n"
99 )
101 def __init__(
102 self,
103 max_iter=150,
104 inner_iter=100,
105 rclose=1.0,
106 hclose=1.0e-4,
107 relax=0.98,
108 damp=1.0,
109 damp_transient=1.0,
110 matrix_conditioning_method=1,
111 printout_interval=0,
112 print_convergence_info=1,
113 ):
114 super().__init__()
115 self.dataset["max_iter"] = max_iter
116 self.dataset["inner_iter"] = inner_iter
117 self.dataset["rclose"] = rclose
118 self.dataset["hclose"] = hclose
119 self.dataset["relax"] = relax
120 self.dataset["matrix_conditioning_method"] = matrix_conditioning_method
121 self.dataset["damp"] = damp
122 self.dataset["damp_transient"] = damp_transient
123 self.dataset["printout_interval"] = printout_interval
124 self.dataset["print_convergence_info"] = print_convergence_info
126 # TODO Check with Peter what these settings do
127 # I now used the settings from the LHM here...
128 self.dataset["IQERROR"] = 1
129 self.dataset["QERROR"] = 5.0
131 def _render_projectfile(self, **kwargs):
132 d = {k: v.item() for k, v in self.dataset.items()}
133 d["pkg_id"] = self._pkg_id
135 return self._template_projectfile.render(**d)