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TensorMesh now inherits BaseMesh (worked with Luz!)
tests for tensorMesh and utils (e.g. ndgrid) are included and pass Split the TensorMesh into Grid and View
This commit is contained in:
Rowan Cockett
+69
-244
@@ -1,257 +1,82 @@
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#-------------------------------------------------------------------------------
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# Packages
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#-------------------------------------------------------------------------------
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import numpy as np
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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from BaseMesh import BaseMesh
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from TensorGrid import TensorGrid
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from TensorView import TensorView
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#-------------------------------------------------------------------------------
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# Class definition
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#-------------------------------------------------------------------------------
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class TensorMesh:
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"""
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Define nodal, cell-centered and staggered tensor meshes for 1, 2 and 3
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dimensions.
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class TensorMesh(BaseMesh, TensorGrid, TensorView):
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"""
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# ---------------------- Properties --------------------------------------
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h = None # Array Spacing or cell-sizes in each direction
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x0 = None # Array Origin (x1,x2,x3)
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dim = None # Int Dimension
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n = None # Array Number of cells in each direction
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nC = None # Int Total number of cells
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nE = None # Int Total number of edges
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nF = None # Int Total number of faces
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# ----------------------- Methods ----------------------------------------
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def __init__(self,h,x0):
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"""Compute number of edges,faces and cell-centers """
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# Assign values to properties
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self.h = h
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self.x0 = x0
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#Compute derived properties
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self.dim = np.size(x0)
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#Compute the num of cells in each direction
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self.n = np.zeros((self.dim,1))
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for d in range(self.dim):
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self.n[d] = np.size(h[d])
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# Compute the number of cell-centers
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self.nC = np.prod(self.n)
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# Compute the number of edges (makes sense only for 3D)
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# Equivalent to:
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# nEdges = n[0] * (n[1]+1) * (n[2]+1)
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# + (n[0]+1) * ny[1] * (nz[2]+1)
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# + (n[0]+1) * (ny[1]+1)* (nz[2])
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if self.dim == 3:
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self.nE = np.prod(np.kron(np.ones((3,1)),self.n.T)+np.ones((3,3))-np.eye(3),1)
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print self.nE
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# Compute the number of faces (makes sense only for 2 and 3D)
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# Equivalent to
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# nFaces = (n[0]+1) * n[1] * n[2]
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# + n[0] * (ny[1]+1) * nz[2]
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# + n[0] * ny[1] * (nz[2]+1)
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if self.dim >=2:
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self.nF = np.prod(np.kron(np.ones((self.dim,1)),self.n.T)+np.eye(self.dim),1)
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print self.nF
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TensorMesh is a mesh class that deals with tensor product meshes.
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def xin(self,i):
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"""Construct the 1D nodal mesh from the ith-component of h. Return an array."""
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return np.insert(np.cumsum(self.h[i-1]),0,0.0) + self.x0[i-1]
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def xic(self,i):
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"""Construct the 1D cell-centerd mesh from the ith-component of h. Return an array."""
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return .5*( np.insert(np.cumsum(self.h[i-1][:,0:-1]),0,0.0) + np.cumsum(self.h[i-1]))
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Any Mesh that has a constant width along the entire axis
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such that it can defined by a single width vector, called 'h'.
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e.g.
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hx = np.array([1,1,1])
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hy = np.array([1,2])
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hz = np.array([1,1,1,1])
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mesh = TensorMesh([hx, hy, hz])
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"""
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def __init__(self, h, x0=None):
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super(TensorMesh, self).__init__(np.array([len(x) for x in h]), x0)
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assert len(h) == len(x0), "Dimension mismatch. x0 != len(h)"
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for i, h_i in enumerate(h):
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assert type(h_i) == np.ndarray, ("h[%i] is not a numpy array." % i)
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# Ensure h contains 1D vectors
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self._h = [x.ravel() for x in h]
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def h():
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doc = "h is a list containing the cell widths of the tensor mesh in each dimension."
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fget = lambda self: self._h
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return locals()
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h = property(**h())
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def hx():
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doc = "Width of cells in the x direction"
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fget = lambda self: self._h[0]
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return locals()
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hx = property(**hx())
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def hy():
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doc = "Width of cells in the y direction"
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fget = lambda self: None if self.dim < 2 else self._h[1]
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return locals()
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hy = property(**hy())
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def hz():
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doc = "Width of cells in the z direction"
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fget = lambda self: None if self.dim < 3 else self._h[2]
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return locals()
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hz = property(**hz())
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def getNodalGrid(self):
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"""Construct nodal grid for 1, 2 and 3 dimensions"""
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if self.dim==1:
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return [self.xin(1)]
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elif self.dim==2:
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return self.ndgrid([self.xin(1),self.xin(2)])
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elif self.dim==3:
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return self.ndgrid([self.xin(1),self.xin(2),self.xin(3)])
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def ndgrid(self, xin):
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"""Form tensorial grid for 1, 2 and 3 dimensions. Return X1,X2,X3 arrays depending on the dimension"""
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ei = lambda i : np.ones((np.size(xin[i-1]),1))
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if self.dim==1:
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return [xin]
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elif self.dim==2:
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X1 = np.kron(ei(2),xin[0]).reshape(-1,1)
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X2 = np.kron(xin[1],ei(1).T).reshape(-1,1)
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return X1,X2
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elif self.dim==3:
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X1 = np.kron(ei(3),np.kron(ei(2),xin[0])).reshape(-1,1)
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X2 = np.kron(ei(3).T,np.kron(xin[1],ei(1).T)).reshape(-1,1)
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X3 = np.kron(xin[2],np.kron(ei(2),ei(1))).T.reshape(-1,1)
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return X1,X2,X3
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def getCellCenteredGrid(self):
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"""Construct cell-centered grid for 1, 2 and 3 dimensions."""
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if self.dim==1:
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return [self.xic(1)]
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elif self.dim==2:
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return self.ndgrid([self.xic(1),self.xic(2)])
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elif self.dim==3:
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return self.ndgrid([self.xic(1),self.xic(2),self.xic(3)])
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def getFaceStgGrid(self,direction):
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"""Construct the face staggered grids for 2 and 3 dimensions."""
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if self.dim==1:
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print 'Error: dimension must be larger than 1'
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elif self.dim==2:
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if direction == 1:
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return self.ndgrid([self.xin(1),self.xic(2)])
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elif direction == 2:
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return self.ndgrid([self.xic(1),self.xin(2)])
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else:
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print 'Error: direction must be equal to 1 or 2'
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elif self.dim==3:
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if direction == 1:
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return self.ndgrid([self.xin(1),self.xic(2),self.xic(3)])
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elif direction == 2:
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return self.ndgrid([self.xic(1),self.xin(2),self.xic(3)])
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elif direction == 3:
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return self.ndgrid([self.xic(1),self.xic(2),self.xin(3)])
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else:
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print 'Error: direction must be equal to 1, 2 or 3'
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def getEdgeStgGrid(self,direction):
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"""Construct the edge staggered grids for 3 dimension case."""
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if self.dim != 3:
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print 'Error: dimension must be equal to 3'
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else:
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if direction == 1:
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return self.ndgrid([self.xic(1),self.xin(2),self.xin(3)])
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elif direction == 2:
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return self.ndgrid([self.xin(1),self.xic(2),self.xin(3)])
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elif direction == 3:
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return self.ndgrid([self.xin(1),self.xin(2),self.xic(3)])
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else:
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print 'Error: direction must be equal to 1, 2 or 3'
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def plotImage(self,I):
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if self.dim==1:
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fig = plt.figure(1)
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fig.clf()
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ax=plt.subplot(111)
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if np.size(I)==self.n[0]:
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print 'cell-centered image'
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xx = self.getCellCenteredGrid()
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ax.plot(xx[0],I,'ro')
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elif np.size(I)==self.n[0]+1:
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print 'nodal image'
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xx = self.getNodalGrid()
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ax.plot(xx[0],I,'bs')
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fig.show()
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def plotGrid(self):
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"""Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions."""
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if self.dim == 1:
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fig = plt.figure(1)
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fig.clf()
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ax = plt.subplot(111)
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xn = self.getNodalGrid()
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xc = self.getCellCenteredGrid()
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print xn
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ax.hold(True)
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ax.plot(xn,np.ones(np.shape(xn)),'bs')
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ax.plot(xc,np.ones(np.shape(xc)),'ro')
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ax.plot(xn,np.ones(np.shape(xn)),'k--')
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ax.grid(True)
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ax.hold(False)
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ax.set_xlabel('x1')
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fig.show()
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elif self.dim == 2:
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fig = plt.figure(2)
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fig.clf()
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ax = plt.subplot(111)
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xn = self.getNodalGrid()
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xc = self.getCellCenteredGrid()
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xs1 = self.getFaceStgGrid(1)
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xs2 = self.getFaceStgGrid(2)
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ax.hold(True)
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ax.plot(xn[0],xn[1],'bs')
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ax.plot(xc[0],xc[1],'ro')
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ax.plot(xs1[0],xs1[1],'g>')
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ax.plot(xs2[0],xs2[1],'g^')
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ax.grid(True)
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ax.hold(False)
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ax.set_xlabel('x1')
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ax.set_ylabel('x2')
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fig.show()
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elif self.dim == 3:
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fig = plt.figure(3)
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fig.clf()
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ax = fig.add_subplot(111, projection='3d')
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xn = self.getNodalGrid()
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xc = self.getCellCenteredGrid()
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xfs1 = self.getFaceStgGrid(1)
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xfs2 = self.getFaceStgGrid(2)
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xfs3 = self.getFaceStgGrid(3)
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xes1 = self.getEdgeStgGrid(1)
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xes2 = self.getEdgeStgGrid(2)
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xes3 = self.getEdgeStgGrid(3)
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ax.hold(True)
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ax.plot(xn[0],xn[1],'bs',zs=xn[2])
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ax.plot(xc[0],xc[1],'ro',zs=xc[2])
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ax.plot(xfs1[0],xfs1[1],'g>',zs=xfs1[2])
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ax.plot(xfs2[0],xfs2[1],'g<',zs=xfs2[2])
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ax.plot(xfs3[0],xfs3[1],'g^',zs=xfs3[2])
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ax.plot(xes1[0],xes1[1],'k>',zs=xes1[2])
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ax.plot(xes2[0],xes2[1],'k<',zs=xes2[2])
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ax.plot(xes3[0],xes3[1],'k^',zs=xes3[2])
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ax.grid(True)
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ax.hold(False)
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ax.set_xlabel('x1')
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ax.set_ylabel('x2')
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ax.set_zlabel('x3')
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fig.show()
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if __name__ == '__main__':
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print('Welcome to tensor mesh!')
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testDim = 1
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h1 = 0.3*np.ones((1,7))
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h1[:,0] = 0.5
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h1[:,-1] = 0.6
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h2 = .5* np.ones((1,4))
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h3 = .4* np.ones((1,6))
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x0 = np.zeros((3,1))
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h1 = 0.3*np.ones((1, 7))
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h1[:, 0] = 0.5
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h1[:, -1] = 0.6
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h2 = .5 * np.ones((1, 4))
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h3 = .4 * np.ones((1, 6))
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x0 = np.zeros((3, 1))
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if testDim == 1:
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h = [h1]
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x0 = x0[0]
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elif testDim==2:
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h = [h1,h2]
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x0 = x0[0]
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elif testDim == 2:
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h = [h1, h2]
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x0 = x0[0:2]
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else:
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h = [h1,h2,h3]
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I = np.linspace(0,1,8)
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M = TensorMesh(h,x0)
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xn = M.plotGrid()
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h = [h1, h2, h3]
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I = np.linspace(0, 1, 8)
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M = TensorMesh(h, x0)
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xn = M.plotGrid()
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