217 lines
8.7 KiB
Python
217 lines
8.7 KiB
Python
# DO NOT MODIFY THIS FILE DIRECTLY. THIS FILE MUST BE CREATED BY
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# mf6/utils/createpackages.py
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# FILE created on February 18, 2021 16:23:05 UTC
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from .. import mfpackage
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from ..data.mfdatautil import ListTemplateGenerator
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class ModflowGwfgnc(mfpackage.MFPackage):
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"""
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ModflowGwfgnc defines a gnc package within a gwf6 model.
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Parameters
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----------
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model : MFModel
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Model that this package is a part of. Package is automatically
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added to model when it is initialized.
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loading_package : bool
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Do not set this parameter. It is intended for debugging and internal
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processing purposes only.
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print_input : boolean
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* print_input (boolean) keyword to indicate that the list of GNC
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information will be written to the listing file immediately after it
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is read.
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print_flows : boolean
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* print_flows (boolean) keyword to indicate that the list of GNC flow
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rates will be printed to the listing file for every stress period
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time step in which "BUDGET PRINT" is specified in Output Control. If
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there is no Output Control option and "PRINT_FLOWS" is specified,
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then flow rates are printed for the last time step of each stress
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period.
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explicit : boolean
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* explicit (boolean) keyword to indicate that the ghost node correction
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is applied in an explicit manner on the right-hand side of the
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matrix. The explicit approach will likely require additional outer
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iterations. If the keyword is not specified, then the correction will
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be applied in an implicit manner on the left-hand side. The implicit
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approach will likely converge better, but may require additional
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memory. If the EXPLICIT keyword is not specified, then the BICGSTAB
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linear acceleration option should be specified within the LINEAR
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block of the Sparse Matrix Solver.
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numgnc : integer
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* numgnc (integer) is the number of GNC entries.
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numalphaj : integer
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* numalphaj (integer) is the number of contributing factors.
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gncdata : [cellidn, cellidm, cellidsj, alphasj]
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* cellidn ((integer, ...)) is the cellid of the cell, :math:`n`, in
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which the ghost node is located. For a structured grid that uses the
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DIS input file, CELLIDN is the layer, row, and column numbers of the
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cell. For a grid that uses the DISV input file, CELLIDN is the layer
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number and CELL2D number for the two cells. If the model uses the
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unstructured discretization (DISU) input file, then CELLIDN is the
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node number for the cell. This argument is an index variable, which
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means that it should be treated as zero-based when working with FloPy
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and Python. Flopy will automatically subtract one when loading index
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variables and add one when writing index variables.
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* cellidm ((integer, ...)) is the cellid of the connecting cell,
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:math:`m`, to which flow occurs from the ghost node. For a structured
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grid that uses the DIS input file, CELLIDM is the layer, row, and
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column numbers of the cell. For a grid that uses the DISV input file,
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CELLIDM is the layer number and CELL2D number for the two cells. If
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the model uses the unstructured discretization (DISU) input file,
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then CELLIDM is the node number for the cell. This argument is an
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index variable, which means that it should be treated as zero-based
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when working with FloPy and Python. Flopy will automatically subtract
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one when loading index variables and add one when writing index
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variables.
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* cellidsj ((integer, ...)) is the array of CELLIDS for the
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contributing j cells, which contribute to the interpolated head value
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at the ghost node. This item contains one CELLID for each of the
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contributing cells of the ghost node. Note that if the number of
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actual contributing cells needed by the user is less than NUMALPHAJ
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for any ghost node, then a dummy CELLID of zero(s) should be inserted
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with an associated contributing factor of zero. For a structured grid
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that uses the DIS input file, CELLID is the layer, row, and column
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numbers of the cell. For a grid that uses the DISV input file, CELLID
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is the layer number and cell2d number for the two cells. If the model
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uses the unstructured discretization (DISU) input file, then CELLID
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is the node number for the cell. This argument is an index variable,
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which means that it should be treated as zero-based when working with
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FloPy and Python. Flopy will automatically subtract one when loading
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index variables and add one when writing index variables.
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* alphasj (double) is the contributing factors for each contributing
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node in CELLIDSJ. Note that if the number of actual contributing
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cells is less than NUMALPHAJ for any ghost node, then dummy CELLIDS
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should be inserted with an associated contributing factor of zero.
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The sum of ALPHASJ should be less than one. This is because one minus
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the sum of ALPHASJ is equal to the alpha term (alpha n in equation
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4-61 of the GWF Model report) that is multiplied by the head in cell
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n.
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filename : String
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File name for this package.
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pname : String
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Package name for this package.
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parent_file : MFPackage
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Parent package file that references this package. Only needed for
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utility packages (mfutl*). For example, mfutllaktab package must have
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a mfgwflak package parent_file.
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"""
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gncdata = ListTemplateGenerator(("gwf6", "gnc", "gncdata", "gncdata"))
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package_abbr = "gwfgnc"
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_package_type = "gnc"
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dfn_file_name = "gwf-gnc.dfn"
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dfn = [
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[
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"block options",
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"name print_input",
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"type keyword",
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"reader urword",
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"optional true",
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],
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[
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"block options",
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"name print_flows",
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"type keyword",
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"reader urword",
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"optional true",
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],
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[
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"block options",
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"name explicit",
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"type keyword",
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"tagged true",
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"reader urword",
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"optional true",
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],
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[
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"block dimensions",
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"name numgnc",
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"type integer",
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"reader urword",
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"optional false",
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],
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[
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"block dimensions",
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"name numalphaj",
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"type integer",
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"reader urword",
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"optional false",
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],
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[
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"block gncdata",
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"name gncdata",
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"type recarray cellidn cellidm cellidsj alphasj",
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"shape (maxbound)",
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"reader urword",
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],
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[
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"block gncdata",
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"name cellidn",
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"type integer",
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"shape",
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"tagged false",
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"in_record true",
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"reader urword",
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"numeric_index true",
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],
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[
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"block gncdata",
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"name cellidm",
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"type integer",
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"shape",
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"tagged false",
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"in_record true",
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"reader urword",
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"numeric_index true",
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],
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[
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"block gncdata",
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"name cellidsj",
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"type integer",
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"shape (numalphaj)",
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"tagged false",
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"in_record true",
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"reader urword",
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"numeric_index true",
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],
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[
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"block gncdata",
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"name alphasj",
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"type double precision",
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"shape (numalphaj)",
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"tagged false",
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"in_record true",
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"reader urword",
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],
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]
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def __init__(
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self,
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model,
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loading_package=False,
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print_input=None,
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print_flows=None,
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explicit=None,
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numgnc=None,
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numalphaj=None,
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gncdata=None,
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filename=None,
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pname=None,
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parent_file=None,
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):
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super(ModflowGwfgnc, self).__init__(
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model, "gnc", filename, pname, loading_package, parent_file
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)
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# set up variables
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self.print_input = self.build_mfdata("print_input", print_input)
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self.print_flows = self.build_mfdata("print_flows", print_flows)
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self.explicit = self.build_mfdata("explicit", explicit)
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self.numgnc = self.build_mfdata("numgnc", numgnc)
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self.numalphaj = self.build_mfdata("numalphaj", numalphaj)
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self.gncdata = self.build_mfdata("gncdata", gncdata)
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self._init_complete = True
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