Files
2016-05-29 22:18:22 -07:00

197 lines
6.2 KiB
Python

import numpy as np
from scipy import sparse as sp
from matutils import mkvc, ndgrid, sub2ind, sdiag
from codeutils import asArray_N_x_Dim
from codeutils import isScalar
import os
def exampleLrmGrid(nC, exType):
assert type(nC) == list, "nC must be a list containing the number of nodes"
assert len(nC) == 2 or len(nC) == 3, "nC must either two or three dimensions"
exType = exType.lower()
possibleTypes = ['rect', 'rotate']
assert exType in possibleTypes, "Not a possible example type."
if exType == 'rect':
return list(ndgrid([np.cumsum(np.r_[0, np.ones(nx)/nx]) for nx in nC], vector=False))
elif exType == 'rotate':
if len(nC) == 2:
X, Y = ndgrid([np.cumsum(np.r_[0, np.ones(nx)/nx]) for nx in nC], vector=False)
amt = 0.5-np.sqrt((X - 0.5)**2 + (Y - 0.5)**2)
amt[amt < 0] = 0
return [X + (-(Y - 0.5))*amt, Y + (+(X - 0.5))*amt]
elif len(nC) == 3:
X, Y, Z = ndgrid([np.cumsum(np.r_[0, np.ones(nx)/nx]) for nx in nC], vector=False)
amt = 0.5-np.sqrt((X - 0.5)**2 + (Y - 0.5)**2 + (Z - 0.5)**2)
amt[amt < 0] = 0
return [X + (-(Y - 0.5))*amt, Y + (-(Z - 0.5))*amt, Z + (-(X - 0.5))*amt]
def meshTensor(value):
"""
**meshTensor** takes a list of numbers and tuples that have the form::
mT = [ float, (cellSize, numCell), (cellSize, numCell, factor) ]
For example, a time domain mesh code needs
many time steps at one time::
[(1e-5, 30), (1e-4, 30), 1e-3]
Means take 30 steps at 1e-5 and then 30 more at 1e-4,
and then one step of 1e-3.
Tensor meshes can also be created by increase factors::
[(10.0, 5, -1.3), (10.0, 50), (10.0, 5, 1.3)]
When there is a third number in the tuple, it
refers to the increase factor, if this number
is negative this section of the tensor is flipped right-to-left.
.. plot::
from SimPEG import Mesh
tx = [(10.0,10,-1.3),(10.0,40),(10.0,10,1.3)]
ty = [(10.0,10,-1.3),(10.0,40)]
M = Mesh.TensorMesh([tx, ty])
M.plotGrid(showIt=True)
"""
if type(value) is not list:
raise Exception('meshTensor must be a list of scalars and tuples.')
proposed = []
for v in value:
if isScalar(v):
proposed += [float(v)]
elif type(v) is tuple and len(v) == 2:
proposed += [float(v[0])]*int(v[1])
elif type(v) is tuple and len(v) == 3:
start = float(v[0])
num = int(v[1])
factor = float(v[2])
pad = ((np.ones(num)*np.abs(factor))**(np.arange(num)+1))*start
if factor < 0: pad = pad[::-1]
proposed += pad.tolist()
else:
raise Exception('meshTensor must contain only scalars and len(2) or len(3) tuples.')
return np.array(proposed)
def closestPoints(mesh, pts, gridLoc='CC'):
"""
Move a list of points to the closest points on a grid.
:param BaseMesh mesh: The mesh
:param numpy.ndarray pts: Points to move
:param string gridLoc: ['CC', 'N', 'Fx', 'Fy', 'Fz', 'Ex', 'Ex', 'Ey', 'Ez']
:rtype: numpy.ndarray
:return: nodeInds
"""
pts = asArray_N_x_Dim(pts, mesh.dim)
grid = getattr(mesh, 'grid' + gridLoc)
nodeInds = np.empty(pts.shape[0], dtype=int)
for i, pt in enumerate(pts):
if mesh.dim == 1:
nodeInds[i] = ((pt - grid)**2).argmin()
else:
nodeInds[i] = ((np.tile(pt, (grid.shape[0],1)) - grid)**2).sum(axis=1).argmin()
return nodeInds
def ExtractCoreMesh(xyzlim, mesh, meshType='tensor'):
"""
Extracts Core Mesh from Global mesh
:param numpy.ndarray xyzlim: 2D array [ndim x 2]
:param BaseMesh mesh: The mesh
This function ouputs::
- actind: corresponding boolean index from global to core
- meshcore: core SimPEG mesh
Warning: 1D and 2D has not been tested
"""
from SimPEG import Mesh
if mesh.dim == 1:
xyzlim = xyzlim.flatten()
xmin, xmax = xyzlim[0], xyzlim[1]
xind = np.logical_and(mesh.vectorCCx>xmin, mesh.vectorCCx<xmax)
xc = mesh.vectorCCx[xind]
hx = mesh.hx[xind]
x0 = [xc[0]-hx[0]*0.5, yc[0]-hy[0]*0.5]
meshCore = Mesh.TensorMesh([hx, hy], x0=x0)
actind = (mesh.gridCC[:,0]>xmin) & (mesh.gridCC[:,0]<xmax)
elif mesh.dim == 2:
xmin, xmax = xyzlim[0,0], xyzlim[0,1]
ymin, ymax = xyzlim[1,0], xyzlim[1,1]
yind = np.logical_and(mesh.vectorCCy>ymin, mesh.vectorCCy<ymax)
zind = np.logical_and(mesh.vectorCCz>zmin, mesh.vectorCCz<zmax)
xc = mesh.vectorCCx[xind]
yc = mesh.vectorCCy[yind]
hx = mesh.hx[xind]
hy = mesh.hy[yind]
x0 = [xc[0]-hx[0]*0.5, yc[0]-hy[0]*0.5]
meshCore = Mesh.TensorMesh([hx, hy], x0=x0)
actind = (mesh.gridCC[:,0]>xmin) & (mesh.gridCC[:,0]<xmax) \
& (mesh.gridCC[:,1]>ymin) & (mesh.gridCC[:,1]<ymax) \
elif mesh.dim == 3:
xmin, xmax = xyzlim[0,0], xyzlim[0,1]
ymin, ymax = xyzlim[1,0], xyzlim[1,1]
zmin, zmax = xyzlim[2,0], xyzlim[2,1]
xind = np.logical_and(mesh.vectorCCx>xmin, mesh.vectorCCx<xmax)
yind = np.logical_and(mesh.vectorCCy>ymin, mesh.vectorCCy<ymax)
zind = np.logical_and(mesh.vectorCCz>zmin, mesh.vectorCCz<zmax)
xc = mesh.vectorCCx[xind]
yc = mesh.vectorCCy[yind]
zc = mesh.vectorCCz[zind]
hx = mesh.hx[xind]
hy = mesh.hy[yind]
hz = mesh.hz[zind]
x0 = [xc[0]-hx[0]*0.5, yc[0]-hy[0]*0.5, zc[0]-hz[0]*0.5]
meshCore = Mesh.TensorMesh([hx, hy, hz], x0=x0)
actind = (mesh.gridCC[:,0]>xmin) & (mesh.gridCC[:,0]<xmax) \
& (mesh.gridCC[:,1]>ymin) & (mesh.gridCC[:,1]<ymax) \
& (mesh.gridCC[:,2]>zmin) & (mesh.gridCC[:,2]<zmax)
else:
raise(Exception("Not implemented!"))
return actind, meshCore
if __name__ == '__main__':
from SimPEG import Mesh
import matplotlib.pyplot as plt
tx = [(10.0,10,-1.3),(10.0,40),(10.0,10,1.3)]
ty = [(10.0,10,-1.3),(10.0,40)]
M = Mesh.TensorMesh([tx, ty])
M.plotGrid()
plt.gca().axis('tight')
plt.show()