def gb_coarse_fine_cell_mapping(
gb: pp.GridBucket, gb_ref: pp.GridBucket, tol=1e-8
) -> None:
""" Wrapper for coarse_fine_cell_mapping to construct mapping for grids in
GridBucket.
Adds a node_prop to each grid in gb. The key is 'coarse_fine_cell_mapping',
and is the mapping generated by 'coarse_fine_cell_mapping(...)'.
Note: No node prop is added to the reference grids in gb_ref.
Parameters
----------
gb : pp.GridBucket
Coarse grid bucket
gb_ref : pp.GridBucket
Refined grid bucket
tol : float, Optional
Tolerance for point_in_poly* -methods
"""
grids = gb.get_grids()
grids_ref = gb_ref.get_grids()
assert len(grids) == len(
grids_ref
), "Weakly check that GridBuckets refer to same domains"
assert np.allclose(
np.append(*gb.bounding_box()), np.append(*gb_ref.bounding_box())
), "Weakly check that GridBuckets refer to same domains"
# This method assumes a consistent node ordering between grids.
# At least assign one.
gb.assign_node_ordering(overwrite_existing=False)
gb_ref.assign_node_ordering(overwrite_existing=False)
# Add node prop on the coarse grid to map from coarse to fine cells.
gb.add_node_props(keys="coarse_fine_cell_mapping")
for i in np.arange(len(grids)):
g, g_ref = grids[i], grids_ref[i]
node_num = gb.node_props(g, "node_number")
node_num_ref = gb_ref.node_props(g_ref, "node_number")
assert node_num == node_num_ref, "Weakly check that grids refer to same domain."
# Compute the mapping for this grid-pair,
# and assign the result to the node of the coarse gb
mapping = coarse_fine_cell_mapping(g, g_ref, point_in_poly_tol=tol)
gb.set_node_prop(g, key="coarse_fine_cell_mapping", val=mapping)
def gb_coarse_fine_cell_mapping(
gb: pp.GridBucket, gb_ref: pp.GridBucket, tol=1e-8
):
""" Wrapper for coarse_fine_cell_mapping to construct mapping for grids in GridBucket.
Parameters
----------
gb : pp.GridBucket
Coarse grid bucket
gb_ref : pp.GridBucket
Refined grid bucket
tol : float, Optional
Tolerance for point_in_poly* -methods
Returns
-------
mapping : list of tuples with entries (pp.GridBucket, pp.GridBucket, sps.csc_matrix)
The first entry is the coarse grid.
The second entry is the refined grid.
The third entry is the mapping from coarse to fine cells
"""
grids = gb.get_grids()
grids_ref = gb_ref.get_grids()
assert len(grids) == len(grids_ref), "Weakly check that GridBuckets refer to same domains"
assert np.array_equal(np.append(*gb.bounding_box()), np.append(*gb_ref.bounding_box())), \
"Weakly check that GridBuckets refer to same domains"
# This method assumes a consistent node ordering between grids. At least assign one.
gb.assign_node_ordering(overwrite_existing=False)
gb_ref.assign_node_ordering(overwrite_existing=False)
n_grids = len(grids)
# mappings = [None]*n_grids
mappings = {'gb': gb, 'gb_ref': gb_ref}
for i in np.arange(n_grids):
g, g_ref = grids[i], grids_ref[i]
node_num, node_num_ref = gb._nodes[g]['node_number'], gb_ref._nodes[g_ref]['node_number']
assert node_num == node_num_ref, "Weakly check that grids refer to same domain."
mapping = coarse_fine_cell_mapping(g, g_ref, tol=tol)
mappings[(g, g_ref)] = {'node_number': node_num,
'data': gb.node_props(g),
'data_ref': gb_ref.node_props(g_ref)}
return mappings
def gb_refinement(
gb: pp.GridBucket, gb_ref: pp.GridBucket, tol: float = 1e-8, mode: str = "nested"
):
"""Wrapper for coarse_fine_cell_mapping to construct mapping for grids in
GridBucket.
Adds a node_prop to each grid in gb. The key is 'coarse_fine_cell_mapping',
and is the mapping generated by 'coarse_fine_cell_mapping(...)'.
Currently, only nested refinement is supported; more general cases are also
possible.
Note: No node prop is added to the reference grids in gb_ref.
Parameters
----------
gb : pp.GridBucket
Coarse grid bucket
gb_ref : pp.GridBucket
Refined grid bucket
tol : float, Optional
Tolerance for point_in_poly* -methods
mode : str, Optional
Refinement mode. Defaults to 'nested', corresponds to refinement by splitting.
Acknowledgement: The code was contributed by Haakon Ervik.
"""
grids = gb.get_grids()
grids_ref = gb_ref.get_grids()
assert len(grids) == len(
grids_ref
), "Weakly check that GridBuckets refer to same domains"
assert np.allclose(
np.append(*gb.bounding_box()), np.append(*gb_ref.bounding_box())
), "Weakly check that GridBuckets refer to same domains"
# This method assumes a consistent node ordering between grids. At least assign one.
gb.assign_node_ordering(overwrite_existing=False)
gb_ref.assign_node_ordering(overwrite_existing=False)
# Add node prop on the coarse grid to map from coarse to fine cells.
gb.add_node_props(keys="coarse_fine_cell_mapping")
for i in np.arange(len(grids)):
g, g_ref = grids[i], grids_ref[i]
node_num, node_num_ref = (
gb._nodes[g]["node_number"],
gb_ref._nodes[g_ref]["node_number"],
)
assert node_num == node_num_ref, "Weakly check that grids refer to same domain."
# Compute the mapping for this grid-pair,
# and assign the result to the node of the coarse gb
if mode == "nested":
mapping = structured_refinement(g, g_ref, point_in_poly_tol=tol)
else:
raise NotImplementedError("Unknown refinement mode")
gb.set_node_prop(grid=g, key="coarse_fine_cell_mapping", val=mapping)