Integrated getEdge/FaceInnerProduct into the tensor mesh class.

This commit is contained in:
Rowan Cockett
2013-07-30 22:12:53 -07:00
parent d8f646c7d9
commit c259a6651a
7 changed files with 39 additions and 191 deletions
+1 -1
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@@ -50,7 +50,7 @@ class DiffOperators(object):
Class creates the differential operators that you need!
"""
def __init__(self):
raise Exception('DiffOperators is a base class providing differential operators on meshes and cannot run on its own. Inherit to your favorite Mesh class.')
raise Exception('DiffOperators is a base class providing differential operators on meshes and cannot run on its own. Inherit to your favorite Mesh class.')
def faceDiv():
doc = "Construct divergence operator (face-stg to cell-centres)."
@@ -4,6 +4,28 @@ from utils import sub2ind, ndgrid, mkvc
import numpy as np
class InnerProducts(object):
"""
Class creates the inner product matrices that you need!
"""
def __init__(self):
raise Exception('InnerProducts is a base class providing inner product matrices for meshes and cannot run on its own. Inherit to your favorite Mesh class.')
def getFaceInnerProduct(self, mu):
if self._meshType == 'TENSOR':
pass
elif self._meshType == 'LOM':
pass # todo: we should be doing something slightly different here!
return getFaceInnerProduct(self, mu)
def getEdgeInnerProduct(self, sigma):
if self._meshType == 'TENSOR':
pass
elif self._meshType == 'LOM':
pass # todo: we should be doing something slightly different here!
return getEdgeInnerProduct(self, sigma)
def getFaceInnerProduct(mesh, mu):
m = np.array([mesh.nCx, mesh.nCy, mesh.nCz])
@@ -39,15 +61,15 @@ def getFaceInnerProduct(mesh, mu):
# | |/
# node(i+1,j,k) ------ edge2(i+1,j,k) ----- node(i+1,j+1,k)
# no | node | e1 | e2 | e3
# 000 | i ,j ,k | i ,j ,k | i ,j ,k | i ,j ,k
# 100 | i+1,j ,k | i+1 ,j ,k | i,j ,k | i,j ,k
# 010 | i ,j+1,k | i ,j,k | i ,j+1 ,k | i ,j,k
# 110 | i+1,j+1,k | i+1 ,j,k | i,j+1 ,k | i,j,k
# 001 | i ,j ,k | i ,j ,k | i ,j ,k | i ,j ,k+1
# 101 | i+1,j ,k | i+1 ,j ,k | i,j ,k | i,j ,k+1
# 011 | i ,j+1,k | i ,j,k | i ,j+1 ,k | i ,j,k+1
# 111 | i+1,j+1,k | i+1 ,j,k | i,j+1 ,k | i,j,k+1
# no | node | f1 | f2 | f3
# 000 | i ,j ,k | i , j, k | i, j , k | i, j, k
# 100 | i+1,j ,k | i+1, j, k | i, j , k | i, j, k
# 010 | i ,j+1,k | i , j, k | i, j+1, k | i, j, k
# 110 | i+1,j+1,k | i+1, j, k | i, j+1, k | i, j, k
# 001 | i ,j ,k | i , j, k | i, j , k | i, j, k+1
# 101 | i+1,j ,k | i+1, j, k | i, j , k | i, j, k+1
# 011 | i ,j+1,k | i , j, k | i, j+1, k | i, j, k+1
# 111 | i+1,j+1,k | i+1, j, k | i, j+1, k | i, j, k+1
P000 = Pxxx([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
P100 = Pxxx([[1, 0, 0], [0, 0, 0], [0, 0, 0]])
P010 = Pxxx([[0, 0, 0], [0, 1, 0], [0, 0, 0]])
@@ -162,4 +184,4 @@ if __name__ == '__main__':
h = [np.array([1, 2, 3, 4]), np.array([1, 2, 1, 4, 2]), np.array([1, 1, 4, 1])]
mesh = TensorMesh(h)
mu = np.ones((mesh.nC, 6))
A = getFaceInnerProduct(mesh, mu)
A = mesh.getFaceInnerProduct(mu)
+4 -1
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@@ -2,10 +2,11 @@ import numpy as np
from BaseMesh import BaseMesh
from TensorView import TensorView
from DiffOperators import DiffOperators
from InnerProducts import InnerProducts
from utils import ndgrid, mkvc
class TensorMesh(BaseMesh, TensorView, DiffOperators):
class TensorMesh(BaseMesh, TensorView, DiffOperators, InnerProducts):
"""
TensorMesh is a mesh class that deals with tensor product meshes.
@@ -21,6 +22,8 @@ class TensorMesh(BaseMesh, TensorView, DiffOperators):
mesh = TensorMesh([hx, hy, hz])
"""
_meshType = 'TENSOR'
def __init__(self, h, x0=None):
super(TensorMesh, self).__init__(np.array([x.size for x in h]), x0)
-87
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@@ -1,87 +0,0 @@
from scipy import sparse as sp
from sputils import sdiag
from utils import sub2ind, ndgrid, mkvc
import numpy as np
def getEdgeInnerProduct(mesh, sigma):
m = np.array([mesh.nCx, mesh.nCy, mesh.nCz])
nc = mesh.nC
i, j, k = np.int64(range(m[0])), np.int64(range(m[1])), np.int64(range(m[2]))
iijjkk = ndgrid(i, j, k)
ii, jj, kk = iijjkk[:, 0], iijjkk[:, 1], iijjkk[:, 2]
def Pxxx(pos):
ind1 = sub2ind(mesh.nEx, np.c_[ii + pos[0][0], jj + pos[0][1], kk + pos[0][2]])
ind2 = sub2ind(mesh.nEy, np.c_[ii + pos[1][0], jj + pos[1][1], kk + pos[1][2]]) + mesh.nE[0]
ind3 = sub2ind(mesh.nEz, np.c_[ii + pos[2][0], jj + pos[2][1], kk + pos[2][2]]) + mesh.nE[0] + mesh.nE[1]
IND = np.r_[ind1, ind2, ind3].flatten()
return sp.coo_matrix((np.ones(3*nc), (range(3*nc), IND)), shape=(3*nc, np.sum(mesh.nE))).tocsr()
# node(i,j,k+1) ------ edge2(i,j,k+1) ----- node(i,j+1,k+1)
# / /
# / / |
# edge3(i,j,k) face1(i,j,k) edge3(i,j+1,k)
# / / |
# / / |
# node(i,j,k) ------ edge2(i,j,k) ----- node(i,j+1,k)
# | | |
# | | node(i+1,j+1,k+1)
# | | /
# edge1(i,j,k) face3(i,j,k) edge1(i,j+1,k)
# | | /
# | | /
# | |/
# node(i+1,j,k) ------ edge2(i+1,j,k) ----- node(i+1,j+1,k)
# no | node | e1 | e2 | e3
# 000 | i ,j ,k | i ,j ,k | i ,j ,k | i ,j ,k
# 100 | i+1,j ,k | i ,j ,k | i+1,j ,k | i+1,j ,k
# 010 | i ,j+1,k | i ,j+1,k | i ,j ,k | i ,j+1,k
# 110 | i+1,j+1,k | i ,j+1,k | i+1,j ,k | i+1,j+1,k
# 001 | i ,j ,k+1 | i ,j ,k+1 | i ,j ,k+1 | i ,j ,k
# 101 | i+1,j ,k+1 | i ,j ,k+1 | i+1,j ,k+1 | i+1,j ,k
# 011 | i ,j+1,k+1 | i ,j+1,k+1 | i ,j ,k+1 | i ,j+1,k
# 111 | i+1,j+1,k+1 | i ,j+1,k+1 | i+1,j ,k+1 | i+1,j+1,k
P000 = Pxxx([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
P100 = Pxxx([[0, 0, 0], [1, 0, 0], [1, 0, 0]])
P010 = Pxxx([[0, 1, 0], [0, 0, 0], [0, 1, 0]])
P110 = Pxxx([[0, 1, 0], [1, 0, 0], [1, 1, 0]])
P001 = Pxxx([[0, 0, 1], [0, 0, 1], [0, 0, 0]])
P101 = Pxxx([[0, 0, 1], [1, 0, 1], [1, 0, 0]])
P011 = Pxxx([[0, 1, 1], [0, 0, 1], [0, 1, 0]])
P111 = Pxxx([[0, 1, 1], [1, 0, 1], [1, 1, 0]])
if sigma.size == mesh.nC: # Isotropic!
sigma = mkvc(sigma) # ensure it is a vector.
Sigma = sdiag(np.r_[sigma, sigma, sigma])
elif sigma.shape[1] == 3: # Diagonal tensor
Sigma = sdiag(np.r_[sigma[:, 0], sigma[:, 1], sigma[:, 2]])
elif sigma.shape[1] == 6: # Fully anisotropic
row1 = sp.hstack((sdiag(sigma[:, 0]), sdiag(sigma[:, 3]), sdiag(sigma[:, 4])))
row2 = sp.hstack((sdiag(sigma[:, 3]), sdiag(sigma[:, 1]), sdiag(sigma[:, 5])))
row3 = sp.hstack((sdiag(sigma[:, 4]), sdiag(sigma[:, 5]), sdiag(sigma[:, 2])))
Sigma = sp.vstack((row1, row2, row3))
# Cell volume
v = np.sqrt(mesh.vol)
v3 = np.r_[v, v, v]
V = sdiag(v3)*Sigma*sdiag(v3) # to keep symmetry
A = P000.T*V*P000 + P001.T*V*P001 + P010.T*V*P010 + P011.T*V*P011 + P100.T*V*P100 + P101.T*V*P101 + P110.T*V*P110 + P111.T*V*P111
A = 0.125*A
return A
if __name__ == '__main__':
from TensorMesh import TensorMesh
h = [np.array([1, 2, 3, 4]), np.array([1, 2, 1, 4, 2]), np.array([1, 1, 4, 1])]
mesh = TensorMesh(h)
sigma = np.ones((mesh.nC, 6))
A = getEdgeInnerProduct(mesh, sigma)
-87
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@@ -1,87 +0,0 @@
from scipy import sparse as sp
from sputils import sdiag
from utils import sub2ind, ndgrid, mkvc
import numpy as np
def getFaceInnerProduct(mesh, mu):
m = np.array([mesh.nCx, mesh.nCy, mesh.nCz])
nc = mesh.nC
i, j, k = np.int64(range(m[0])), np.int64(range(m[1])), np.int64(range(m[2]))
iijjkk = ndgrid(i, j, k)
ii, jj, kk = iijjkk[:, 0], iijjkk[:, 1], iijjkk[:, 2]
def Pxxx(pos):
ind1 = sub2ind(mesh.nFx, np.c_[ii + pos[0][0], jj + pos[0][1], kk + pos[0][2]])
ind2 = sub2ind(mesh.nFy, np.c_[ii + pos[1][0], jj + pos[1][1], kk + pos[1][2]]) + mesh.nF[0]
ind3 = sub2ind(mesh.nFz, np.c_[ii + pos[2][0], jj + pos[2][1], kk + pos[2][2]]) + mesh.nF[0] + mesh.nF[1]
IND = np.r_[ind1, ind2, ind3].flatten()
return sp.coo_matrix((np.ones(3*nc), (range(3*nc), IND)), shape=(3*nc, np.sum(mesh.nF))).tocsr()
# node(i,j,k+1) ------ edge2(i,j,k+1) ----- node(i,j+1,k+1)
# / /
# / / |
# edge3(i,j,k) face1(i,j,k) edge3(i,j+1,k)
# / / |
# / / |
# node(i,j,k) ------ edge2(i,j,k) ----- node(i,j+1,k)
# | | |
# | | node(i+1,j+1,k+1)
# | | /
# edge1(i,j,k) face3(i,j,k) edge1(i,j+1,k)
# | | /
# | | /
# | |/
# node(i+1,j,k) ------ edge2(i+1,j,k) ----- node(i+1,j+1,k)
# no | node | e1 | e2 | e3
# 000 | i ,j ,k | i ,j ,k | i ,j ,k | i ,j ,k
# 100 | i+1,j ,k | i+1 ,j ,k | i,j ,k | i,j ,k
# 010 | i ,j+1,k | i ,j,k | i ,j+1 ,k | i ,j,k
# 110 | i+1,j+1,k | i+1 ,j,k | i,j+1 ,k | i,j,k
# 001 | i ,j ,k | i ,j ,k | i ,j ,k | i ,j ,k+1
# 101 | i+1,j ,k | i+1 ,j ,k | i,j ,k | i,j ,k+1
# 011 | i ,j+1,k | i ,j,k | i ,j+1 ,k | i ,j,k+1
# 111 | i+1,j+1,k | i+1 ,j,k | i,j+1 ,k | i,j,k+1
P000 = Pxxx([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
P100 = Pxxx([[1, 0, 0], [0, 0, 0], [0, 0, 0]])
P010 = Pxxx([[0, 0, 0], [0, 1, 0], [0, 0, 0]])
P110 = Pxxx([[1, 0, 0], [0, 1, 0], [0, 0, 0]])
P001 = Pxxx([[0, 0, 0], [0, 0, 0], [0, 0, 1]])
P101 = Pxxx([[1, 0, 0], [0, 0, 0], [0, 0, 1]])
P011 = Pxxx([[0, 0, 0], [0, 1, 0], [0, 0, 1]])
P111 = Pxxx([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
if mu.size == mesh.nC: # Isotropic!
mu = mkvc(mu) # ensure it is a vector.
mu = sdiag(np.r_[mu, mu, mu])
elif mu.shape[1] == 3: # Diagonal tensor
mu = sdiag(np.r_[mu[:, 0], mu[:, 1], mu[:, 2]])
elif mu.shape[1] == 6: # Fully anisotropic
row1 = sp.hstack((sdiag(mu[:, 0]), sdiag(mu[:, 3]), sdiag(mu[:, 4])))
row2 = sp.hstack((sdiag(mu[:, 3]), sdiag(mu[:, 1]), sdiag(mu[:, 5])))
row3 = sp.hstack((sdiag(mu[:, 4]), sdiag(mu[:, 5]), sdiag(mu[:, 2])))
mu = sp.vstack((row1, row2, row3))
# Cell volume
v = np.sqrt(mesh.vol)
v3 = np.r_[v, v, v]
V = sdiag(v3)*mu*sdiag(v3) # to keep symmetry
A = P000.T*V*P000 + P001.T*V*P001 + P010.T*V*P010 + P011.T*V*P011 + P100.T*V*P100 + P101.T*V*P101 + P110.T*V*P110 + P111.T*V*P111
A = 0.125*A
return A
if __name__ == '__main__':
from TensorMesh import TensorMesh
h = [np.array([1, 2, 3, 4]), np.array([1, 2, 1, 4, 2]), np.array([1, 1, 4, 1])]
mesh = TensorMesh(h)
mu = np.ones((mesh.nC, 6))
A = getFaceInnerProduct(mesh, mu)
+1 -1
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@@ -64,7 +64,7 @@ class OrderTest(unittest.TestCase):
name = "Order Test"
expectedOrder = 2
tolerance = 0.85
meshSizes = [4, 8, 16, 32, 64]
meshSizes = [4, 8, 16, 32]
meshType = 'uniformTensorMesh'
meshDimension = 3
+1 -4
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@@ -1,9 +1,6 @@
import numpy as np
import unittest
from OrderTest import OrderTest
import sys
sys.path.append('../')
from getEdgeInnerProducts import *
class TestEdgeInnerProduct(OrderTest):
@@ -35,7 +32,7 @@ class TestEdgeInnerProduct(OrderTest):
sigma = np.c_[call(sigma1, Gc), call(sigma2, Gc), call(sigma3, Gc),
call(sigma4, Gc), call(sigma5, Gc), call(sigma6, Gc)]
A = getEdgeInnerProduct(self.M, sigma)
A = self.M.getEdgeInnerProduct(sigma)
numeric = E.T*A*E
analytic = 69881./21600 # Found using matlab symbolic toolbox.
err = np.abs(numeric - analytic)