mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-28 23:58:09 +08:00
131 lines
4.8 KiB
Python
131 lines
4.8 KiB
Python
import numpy as np
|
|
from BaseMesh import BaseMesh
|
|
from DiffOperators import DiffOperators
|
|
from utils import mkvc, ndgrid, volTetra, indexCube, faceInfo
|
|
|
|
|
|
class LogicallyOrthogonalMesh(BaseMesh, DiffOperators): # , LOMGrid
|
|
"""
|
|
LogicallyOrthogonalMesh is a mesh class that deals with logically orthogonal meshes.
|
|
|
|
"""
|
|
def __init__(self, nodes, x0=None):
|
|
assert type(nodes) == list, "'nodes' variable must be a list of np.ndarray"
|
|
|
|
for i, nodes_i in enumerate(nodes):
|
|
assert type(nodes_i) == np.ndarray, ("nodes[%i] is not a numpy array." % i)
|
|
assert nodes_i.shape == nodes[0].shape, ("nodes[%i] is not the same shape as nodes[0]" % i)
|
|
|
|
assert len(nodes[0].shape) == len(nodes), "Dimension mismatch"
|
|
assert len(nodes[0].shape) > 1, "Not worth using LOM for a 1D mesh."
|
|
|
|
super(LogicallyOrthogonalMesh, self).__init__(np.array(nodes[0].shape)-1, x0)
|
|
|
|
assert len(nodes[0].shape) == len(self.x0), "Dimension mismatch. x0 != len(h)"
|
|
|
|
# Save nodes to private variable _gridN as vectors
|
|
self._gridN = np.ones((nodes[0].size, self.dim))
|
|
for i, node_i in enumerate(nodes):
|
|
self._gridN[:, i] = mkvc(node_i)
|
|
|
|
def gridCC():
|
|
doc = "Cell-centered grid."
|
|
|
|
def fget(self):
|
|
if self._gridCC is None:
|
|
ccV = (self.nodalVectorAve*mkvc(self.gridN))
|
|
self._gridCC = ccV.reshape((-1, self.dim), order='F')
|
|
return self._gridCC
|
|
return locals()
|
|
_gridCC = None # Store grid by default
|
|
gridCC = property(**gridCC())
|
|
|
|
def gridN():
|
|
doc = "Nodal grid."
|
|
|
|
def fget(self):
|
|
if self._gridN is None:
|
|
raise Exception("Someone deleted this. I blame you.")
|
|
return self._gridN
|
|
return locals()
|
|
_gridN = None # Store grid by default
|
|
gridN = property(**gridN())
|
|
|
|
# --------------- Geometries ---------------------
|
|
#
|
|
#
|
|
# ------------------- 2D -------------------------
|
|
#
|
|
# node(i,j) node(i,j+1)
|
|
# A -------------- B
|
|
# | |
|
|
# | cell(i,j) |
|
|
# | I |
|
|
# | |
|
|
# D -------------- C
|
|
# node(i+1,j) node(i+1,j+1)
|
|
#
|
|
# ------------------- 3D -------------------------
|
|
#
|
|
#
|
|
# node(i,j,k+1) node(i,j+1,k+1)
|
|
# E --------------- F
|
|
# /| / |
|
|
# / | / |
|
|
# / | / |
|
|
# node(i,j,k) node(i,j+1,k)
|
|
# A -------------- B |
|
|
# | H ----------|---- G
|
|
# | /cell(i,j) | /
|
|
# | / I | /
|
|
# | / | /
|
|
# D -------------- C
|
|
# node(i+1,j,k) node(i+1,j+1,k)
|
|
def vol():
|
|
doc = "Construct cell volumes of the 3D model as 1d array."
|
|
|
|
def fget(self):
|
|
if(self._vol is None):
|
|
if self.dim == 2:
|
|
A, B, C, D = indexCube('ABCD', np.array([self.nNx, self.nNy]))
|
|
normal, area, length = faceInfo(np.c_[self.gridN, np.zeros((self.nN, 1))], A, B, C, D)
|
|
self._vol = area
|
|
elif self.dim == 3:
|
|
# Each polyhedron can be decomposed into 5 tetrahedrons
|
|
# T1 = [A B D E]; % cutted edge
|
|
# T2 = [B E F G]; % cutted edge
|
|
# T3 = [B D E G]; % mid
|
|
# T4 = [B C D G]; % cutted edge
|
|
# T5 = [D E G H]; % cutted edge
|
|
A, B, C, D, E, F, G, H = indexCube('ABCDEFGH', np.array([self.nNx, self.nNy, self.nNz]))
|
|
|
|
v1 = volTetra(self.gridN, A, B, D, E) # cutted edge
|
|
v2 = volTetra(self.gridN, B, E, F, G) # cutted edge
|
|
v3 = volTetra(self.gridN, B, D, E, G) # mid
|
|
v4 = volTetra(self.gridN, B, C, D, G) # cutted edge
|
|
v5 = volTetra(self.gridN, D, E, G, H) # cutted edge
|
|
|
|
self._vol = v1 + v2 + v3 + v4 + v5
|
|
return self._vol
|
|
return locals()
|
|
_vol = None
|
|
vol = property(**vol())
|
|
|
|
|
|
if __name__ == '__main__':
|
|
nc = 5
|
|
h1 = np.cumsum(np.r_[0, np.ones(nc)/(nc)])
|
|
h2 = np.cumsum(np.r_[0, np.ones(nc)/(nc)])
|
|
h3 = np.cumsum(np.r_[0, np.ones(nc)/(nc)])
|
|
dee3 = False
|
|
if dee3:
|
|
X, Y, Z = ndgrid(h1, h2, h3, vector=False)
|
|
M = LogicallyOrthogonalMesh([X, Y, Z])
|
|
else:
|
|
X, Y = ndgrid(h1, h2, vector=False)
|
|
M = LogicallyOrthogonalMesh([X, Y])
|
|
|
|
# print M.r(M.gridCC, format='M')
|
|
# print M.gridN[:, 0]
|
|
print np.sum(M.vol)
|