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