Tensor Mesh¶

class
discretize.
TensorMesh
(h=None, x0=None, **kwargs)[source]¶ Bases:
discretize.TensorMesh.BaseTensorMesh
,discretize.BaseMesh.BaseRectangularMesh
,discretize.View.TensorView
,discretize.DiffOperators.DiffOperators
,discretize.InnerProducts.InnerProducts
,discretize.MeshIO.TensorMeshIO
TensorMesh is a mesh class that deals with tensor product meshes.
Any Mesh that has a constant width along the entire axis such that it can defined by a single width vector, called ‘h’.
hx = np.array([1, 1, 1]) hy = np.array([1, 2]) hz = np.array([1, 1, 1, 1]) mesh = Mesh.TensorMesh([hx, hy, hz])
Example of a padded tensor mesh using
discretize.utils.meshutils.meshTensor()
:import discretize M = discretize.TensorMesh([ [(10, 10, 1.3), (10, 40), (10, 10, 1.3)], [(10, 10, 1.3), (10, 20)] ]) M.plotGrid()
(Source code, png, hires.png, pdf)
For a quick tensor mesh on a (10x12x15) unit cube:
mesh = discretize.TensorMesh([10, 12, 15])
Required Properties:
 h (a list of
Array
): h is a list containing the cell widths of the tensor mesh in each dimension., a list (each item is a list or numpy array of <class ‘float’> with shape (*)) with length between 0 and 3  x0 (
Array
): origin of the mesh (dim, ), a list or numpy array of <class ‘float’> with shape (*)

vol
¶ Construct cell volumes of the 3D model as 1d array.

areaFx
¶ Area of the xfaces

areaFy
¶ Area of the yfaces

areaFz
¶ Area of the zfaces

area
¶ Construct face areas of the 3D model as 1d array.

edgeEx
¶ xedge lengths

edgeEy
¶ yedge lengths

edgeEz
¶ zedge lengths

edge
¶ Construct edge legnths of the 3D model as 1d array.

faceBoundaryInd
¶ Find indices of boundary faces in each direction

cellBoundaryInd
¶ Find indices of boundary faces in each direction
 h (a list of
Mesh IO¶

class
discretize.MeshIO.
TensorMeshIO
[source]¶ Bases:
object

classmethod
readUBC
(TensorMesh, fileName, directory='')[source]¶ Wrapper to Read UBC GIF 2D and 3D tensor mesh and generate same dimension TensorMesh.
Input: :param str fileName: path to the UBC GIF mesh file or just its name if directory is specified :param str directory: directory where the UBC GIF file lives
Output: :rtype: TensorMesh :return: The tensor mesh for the fileName.

classmethod
readVTK
(TensorMesh, fileName, directory='')[source]¶ Read VTK Rectilinear (vtr xml file) and return Tensor mesh and model
Input: :param str fileName: path to the vtr model file to read or just its name if directory is specified :param str directory: directory where the UBC GIF file lives
Output: :rtype: tuple :return: (TensorMesh, modelDictionary)

writeVTK
(mesh, fileName, models=None, directory='')[source]¶ Makes and saves a VTK rectilinear file (vtr) for a Tensor mesh and model.
Input: :param str fileName: path to the output vtk file or just its name if directory is specified :param str directory: directory where the UBC GIF file lives :param dict models: dictionary of numpy.array  Name(‘s) and array(‘s). Match number of cells

readModelUBC
(mesh, fileName, directory='')[source]¶  Read UBC 2D or 3D Tensor mesh model
 and generate Tensor mesh model
Input: :param str fileName: path to the UBC GIF mesh file to read or just its name if directory is specified :param str directory: directory where the UBC GIF file lives
Output: :rtype: numpy.ndarray :return: model with TensorMesh ordered

writeModelUBC
(mesh, fileName, model, directory='')[source]¶ Writes a model associated with a TensorMesh to a UBCGIF format model file.
Input: :param str fileName: File to write to or just its name if directory is specified :param str directory: directory where the UBC GIF file lives :param numpy.ndarray model: The model

writeUBC
(mesh, fileName, models=None, directory='', comment_lines='')[source]¶ Writes a TensorMesh to a UBCGIF format mesh file.
Input: :param str fileName: File to write to :param str directory: directory where to save model :param dict models: A dictionary of the models :param str comment_lines: comment lines preceded with ‘!’ to add

classmethod
Mesh Viewing¶

class
discretize.View.
TensorView
[source]¶ Bases:
object
Provides viewing functions for TensorMesh
This class is inherited by TensorMesh

plotImage
(v)[source]¶ Plots scalar fields on the given mesh.
Input:
Parameters: v (numpy.array) – vector Optional Inputs:
Parameters:  vType (str) – type of vector (‘CC’, ‘N’, ‘F’, ‘Fx’, ‘Fy’, ‘Fz’, ‘E’, ‘Ex’, ‘Ey’, ‘Ez’)
 ax (matplotlib.axes.Axes) – axis to plot to
 showIt (bool) – call plt.show()
3D Inputs:
Parameters: import discretize import numpy as np M = discretize.TensorMesh([20, 20]) v = np.sin(M.gridCC[:, 0]*2*np.pi)*np.sin(M.gridCC[:, 1]*2*np.pi) M.plotImage(v, showIt=True)
(Source code, png, hires.png, pdf)
import discretize import numpy as np M = discretize.TensorMesh([20, 20, 20]) v = np.sin(M.gridCC[:, 0]*2*np.pi)*np.sin(M.gridCC[:, 1]*2*np.pi)*np.sin(M.gridCC[:, 2]*2*np.pi) M.plotImage(v, annotationColor='k', showIt=True)
(Source code, png, hires.png, pdf)

plotSlice
(v, vType='CC', normal='Z', ind=None, grid=False, view='real', ax=None, clim=None, showIt=False, pcolorOpts=None, streamOpts=None, gridOpts=None, range_x=None, range_y=None, sample_grid=None, stream_threshold=None)[source]¶ Plots a slice of a 3D mesh.
(Source code, png, hires.png, pdf)

plotGrid
(ax=None, nodes=False, faces=False, centers=False, edges=False, lines=True, showIt=False)[source]¶ Plot the nodal, cellcentered and staggered grids for 1,2 and 3 dimensions.
Parameters: import discretize import numpy as np h1 = np.linspace(.1, .5, 3) h2 = np.linspace(.1, .5, 5) mesh = discretize.TensorMesh([h1, h2]) mesh.plotGrid(nodes=True, faces=True, centers=True, lines=True, showIt=True)
(Source code, png, hires.png, pdf)
import discretize import numpy as np h1 = np.linspace(.1, .5, 3) h2 = np.linspace(.1, .5, 5) h3 = np.linspace(.1, .5, 3) mesh = discretize.TensorMesh([h1, h2, h3]) mesh.plotGrid(nodes=True, faces=True, centers=True, lines=True, showIt=True)
(Source code, png, hires.png, pdf)
