def _create_embedded_2d_grid(loc_coord, glob_id):
"""
Create a 2d grid that is embedded in a 3d grid.
"""
loc_center = np.mean(loc_coord, axis=1).reshape((-1, 1))
loc_coord -= loc_center
# Check that the points indeed form a line
assert pp.geometry_property_checks.points_are_planar(loc_coord)
# Find the tangent of the line
# Projection matrix
rot = pp.map_geometry.project_plane_matrix(loc_coord)
loc_coord_2d = rot.dot(loc_coord)
# The points are now 2d along two of the coordinate axis, but we
# don't know which yet. Find this.
sum_coord = np.sum(np.abs(loc_coord_2d), axis=1)
active_dimension = np.logical_not(np.isclose(sum_coord, 0))
# Check that we are indeed in 2d
assert np.sum(active_dimension) == 2
# Sort nodes, and create grid
coord_2d = loc_coord_2d[active_dimension]
sort_ind = np.lexsort((coord_2d[0], coord_2d[1]))
sorted_coord = coord_2d[:, sort_ind]
sorted_coord = np.round(sorted_coord * 1e10) / 1e10
unique_x = np.unique(sorted_coord[0])
unique_y = np.unique(sorted_coord[1])
# assert unique_x.size == unique_y.size
g = structured.TensorGrid(unique_x, unique_y)
assert np.all(g.nodes[0:2] - sorted_coord == 0)
# Project back to active dimension
nodes = np.zeros(g.nodes.shape)
nodes[active_dimension] = g.nodes[0:2]
g.nodes = nodes
# Project back again to 3d coordinates
irot = rot.transpose()
g.nodes = irot.dot(g.nodes)
g.nodes += loc_center
# Add mapping to global point numbers
g.global_point_ind = glob_id[sort_ind]
return g
def create_embedded_line_grid(loc_coord, glob_id, tol=1e-4):
loc_center = np.mean(loc_coord, axis=1).reshape((-1, 1))
sorted_coord, rot, active_dimension, sort_ind = pp.map_geometry.project_points_to_line(
loc_coord, tol)
g = structured.TensorGrid(sorted_coord)
# Project back to active dimension
nodes = np.zeros(g.nodes.shape)
nodes[active_dimension] = g.nodes[0]
g.nodes = nodes
# Project back again to 3d coordinates
irot = rot.transpose()
g.nodes = irot.dot(g.nodes)
g.nodes += loc_center
# Add mapping to global point numbers
g.global_point_ind = glob_id[sort_ind]
return g
def create_embedded_line_grid(loc_coord, glob_id, tol=1e-4):
loc_center = np.mean(loc_coord, axis=1).reshape((-1, 1))
loc_coord -= loc_center
# Check that the points indeed form a line
if not cg.is_collinear(loc_coord, tol):
raise ValueError("Elements are not colinear")
# Find the tangent of the line
tangent = cg.compute_tangent(loc_coord)
# Projection matrix
rot = cg.project_line_matrix(loc_coord, tangent)
loc_coord_1d = rot.dot(loc_coord)
# The points are now 1d along one of the coordinate axis, but we
# don't know which yet. Find this.
sum_coord = np.sum(np.abs(loc_coord_1d), axis=1)
sum_coord /= np.amax(sum_coord)
active_dimension = np.logical_not(
np.isclose(sum_coord, 0, atol=tol, rtol=0))
# Check that we are indeed in 1d
assert np.sum(active_dimension) == 1
# Sort nodes, and create grid
coord_1d = loc_coord_1d[active_dimension]
sort_ind = np.argsort(coord_1d)[0]
sorted_coord = coord_1d[0, sort_ind]
g = structured.TensorGrid(sorted_coord)
# Project back to active dimension
nodes = np.zeros(g.nodes.shape)
nodes[active_dimension] = g.nodes[0]
g.nodes = nodes
# Project back again to 3d coordinates
irot = rot.transpose()
g.nodes = irot.dot(g.nodes)
g.nodes += loc_center
# Add mapping to global point numbers
g.global_point_ind = glob_id[sort_ind]
return g