discretize.base.BaseTensorMesh¶
-
class
discretize.base.
BaseTensorMesh
(*args, **kwargs)[source]¶ Bases:
discretize.base.base_mesh.BaseMesh
Base class for tensor-product style meshes
This class contains properites and methods that are common to cartesian and cylindrical meshes defined by tensor-produts of vectors describing cell spacings.
Do not use this class directly, instead, inherit it if you plan to develop a tensor-style mesh (e.g. a spherical mesh) or use the
discretize.TensorMesh()
class to create a cartesian tensor mesh.Required Properties:
axis_u (
Vector3
): Vector orientation of u-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Xaxis_v (
Vector3
): Vector orientation of v-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Yaxis_w (
Vector3
): Vector orientation of w-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Zh (a tuple of
Array
): h is a list containing the cell widths of the tensor mesh in each dimension., a tuple (each item is a list or numpy array of <class ‘float’> with shape (*)) with length between 1 and 3origin (
Array
): origin of the mesh (dim, ), a list or numpy array of <class ‘float’>, <class ‘int’> with shape (*)reference_system (
String
): The type of coordinate reference frame. Can take on the values cartesian, cylindrical, or spherical. Abbreviations of these are allowed., a unicode string, Default: cartesian
- Attributes
axis_u
axis_u (
Vector3
): Vector orientation of u-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Xaxis_v
axis_v (
Vector3
): Vector orientation of v-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Yaxis_w
axis_w (
Vector3
): Vector orientation of w-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Zcell_centers
Cell-centered grid.
cell_centers_x
Cell-centered grid vector (1D) in the x direction.
cell_centers_y
Cell-centered grid vector (1D) in the y direction.
cell_centers_z
Cell-centered grid vector (1D) in the z direction.
dim
The dimension of the mesh (1, 2, or 3).
edge_tangents
Edge Tangents
edges_x
Edge staggered grid in the x direction.
edges_y
Edge staggered grid in the y direction.
edges_z
Edge staggered grid in the z direction.
face_normals
Face Normals
faces_x
Face staggered grid in the x direction.
faces_y
Face staggered grid in the y direction.
faces_z
Face staggered grid in the z direction.
h
h (a tuple of
Array
): h is a list containing the cell widths of the tensor mesh in each dimension., a tuple (each item is a list or numpy array of <class ‘float’> with shape (*)) with length between 1 and 3h_gridded
Returns an (nC, dim) numpy array with the widths of all cells in order
hx
Width of cells in the x direction
hy
Width of cells in the y direction
hz
Width of cells in the z direction
n_cells
Total number of cells in the mesh.
n_edges
Total number of edges.
n_edges_per_direction
The number of edges in each direction
n_edges_x
Number of x-edges
n_edges_y
Number of y-edges
n_edges_z
Number of z-edges
n_faces
Total number of faces.
n_faces_per_direction
The number of faces in each direction
n_faces_x
Number of x-faces
n_faces_y
Number of y-faces
n_faces_z
Number of z-faces
n_nodes
Total number of nodes
nodes
Nodal grid.
nodes_x
Nodal grid vector (1D) in the x direction.
nodes_y
Nodal grid vector (1D) in the y direction.
nodes_z
Nodal grid vector (1D) in the z direction.
normals
normals has been deprecated. See face_normals for documentation
origin
origin (
Array
): origin of the mesh (dim, ), a list or numpy array of <class ‘float’>, <class ‘int’> with shape (*)reference_is_rotated
True if the axes are rotated from the traditional <X,Y,Z> system
reference_system
reference_system (
String
): The type of coordinate reference frame. Can take on the values cartesian, cylindrical, or spherical. Abbreviations of these are allowed., a unicode string, Default: cartesianrotation_matrix
Builds a rotation matrix to transform coordinates from their coordinate system into a conventional cartesian system.
tangents
tangents has been deprecated. See edge_tangents for documentation
vectorCCx
vectorCCx has been deprecated. See cell_centers_x for documentation
vectorCCy
vectorCCy has been deprecated. See cell_centers_y for documentation
vectorCCz
vectorCCz has been deprecated. See cell_centers_z for documentation
vectorNx
vectorNx has been deprecated. See nodes_x for documentation
vectorNy
vectorNy has been deprecated. See nodes_y for documentation
vectorNz
vectorNz has been deprecated. See nodes_z for documentation
- x0
Methods
copy
()Make a copy of the current mesh
deserialize
(value, **kwargs)Creates HasProperties instance from serialized dictionary
equal
(other)Determine if two HasProperties instances are equivalent
from_omf
(element)Convert an OMF element to it’s proper
discretize
type.getInterpolationMat
(*args, **kwargs)getInterpolationMat has been deprecated.
getTensor
(*args, **kwargs)getTensor has been deprecated.
get_interpolation_matrix
(loc[, …])Produces linear interpolation matrix
get_tensor
(key)Returns a tensor list.
isInside
(*args, **kwargs)isInside has been deprecated.
is_inside
(pts[, location_type])Determines if a set of points are inside a mesh.
plotGrid
(*args, **kwargs)plotGrid has been deprecated.
plotImage
(*args, **kwargs)plotImage has been deprecated.
plotSlice
(*args, **kwargs)plotSlice has been deprecated.
plot_3d_slicer
(v[, xslice, yslice, zslice, …])Plot slices of a 3D volume, interactively (scroll wheel).
plot_grid
([ax, nodes, faces, centers, …])Plot the nodal, cell-centered and staggered grids.
plot_image
(v[, v_type, grid, view, ax, …])Plots fields on the given mesh.
plot_slice
(v[, v_type, normal, ind, grid, …])Plots slice of fields on the given 3D mesh.
projectEdgeVector
(*args, **kwargs)projectEdgeVector has been deprecated.
projectFaceVector
(*args, **kwargs)projectFaceVector has been deprecated.
project_edge_vector
(edge_vector)Project vectors onto the edges of the mesh
project_face_vector
(face_vector)Project vectors onto the faces of the mesh.
save
([file_name, verbose])Save the mesh to json :param str file: file_name for saving the casing properties :param str directory: working directory for saving the file
serialize
([include_class, save_dynamic])Serializes a HasProperties instance to dictionary
toVTK
([models])Convert this mesh object to it’s proper VTK or
pyvista
data object with the given model dictionary as the cell data of that dataset.to_omf
([models])Convert this mesh object to it’s proper
omf
data object with the given model dictionary as the cell data of that dataset.to_vtk
([models])Convert this mesh object to it’s proper VTK or
pyvista
data object with the given model dictionary as the cell data of that dataset.validate
()Call all registered class validator methods
writeVTK
(file_name[, models, directory])Makes and saves a VTK object from this mesh and given models
write_vtk
(file_name[, models, directory])Makes and saves a VTK object from this mesh and given models
Examples using discretize.base.BaseTensorMesh
¶
Attributes¶
-
BaseTensorMesh.
axis_u
¶ axis_u (
Vector3
): Vector orientation of u-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: X
-
BaseTensorMesh.
axis_v
¶ axis_v (
Vector3
): Vector orientation of v-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Y
-
BaseTensorMesh.
axis_w
¶ axis_w (
Vector3
): Vector orientation of w-direction. For more details see the docs for therotation_matrix
property., a 3D Vector of <class ‘float’> with shape (3), Default: Z
-
BaseTensorMesh.
cell_centers
¶ Cell-centered grid.
-
BaseTensorMesh.
cell_centers_x
¶ Cell-centered grid vector (1D) in the x direction.
-
BaseTensorMesh.
cell_centers_y
¶ Cell-centered grid vector (1D) in the y direction.
-
BaseTensorMesh.
cell_centers_z
¶ Cell-centered grid vector (1D) in the z direction.
-
BaseTensorMesh.
dim
¶ The dimension of the mesh (1, 2, or 3).
- Returns
- int
dimension of the mesh
-
BaseTensorMesh.
edge_tangents
¶ Edge Tangents
- Returns
- numpy.ndarray
normals, (n_edges, dim)
-
BaseTensorMesh.
edges_x
¶ Edge staggered grid in the x direction.
-
BaseTensorMesh.
edges_y
¶ Edge staggered grid in the y direction.
-
BaseTensorMesh.
edges_z
¶ Edge staggered grid in the z direction.
-
BaseTensorMesh.
face_normals
¶ Face Normals
- Returns
- numpy.ndarray
normals, (n_faces, dim)
-
BaseTensorMesh.
faces_x
¶ Face staggered grid in the x direction.
-
BaseTensorMesh.
faces_y
¶ Face staggered grid in the y direction.
-
BaseTensorMesh.
faces_z
¶ Face staggered grid in the z direction.
-
BaseTensorMesh.
h
¶ h (a tuple of
Array
): h is a list containing the cell widths of the tensor mesh in each dimension., a tuple (each item is a list or numpy array of <class ‘float’> with shape (*)) with length between 1 and 3
-
BaseTensorMesh.
h_gridded
¶ Returns an (nC, dim) numpy array with the widths of all cells in order
-
BaseTensorMesh.
hx
¶ Width of cells in the x direction
- Returns
- numpy.ndarray
Deprecated since version 0.5.0: hx will be removed in discretize 1.0.0 to reduce namespace clutter, please use mesh.h[0].
-
BaseTensorMesh.
hy
¶ Width of cells in the y direction
- Returns
- numpy.ndarray or None
Deprecated since version 0.5.0: hy will be removed in discretize 1.0.0 to reduce namespace clutter, please use mesh.h[1].
-
BaseTensorMesh.
hz
¶ Width of cells in the z direction
- Returns
- numpy.ndarray or None
Deprecated since version 0.5.0: hz will be removed in discretize 1.0.0 to reduce namespace clutter, please use mesh.h[2].
-
BaseTensorMesh.
n_cells
¶ Total number of cells in the mesh.
- Returns
- int
number of cells in the mesh
Notes
Also accessible as nC.
Examples
>>> import discretize >>> import numpy as np >>> import matplotlib.pyplot as plt >>> mesh = discretize.TensorMesh([np.ones(n) for n in [2,3]]) >>> mesh.plot_grid(centers=True, show_it=True) >>> print(mesh.n_cells)
(Source code, png, pdf)
-
BaseTensorMesh.
n_edges
¶ Total number of edges.
- Returns
- int
sum([n_edges_x, n_edges_y, n_edges_z])
Notes
Also accessible as nE.
-
BaseTensorMesh.
n_edges_per_direction
¶ The number of edges in each direction
- Returns
- n_edges_per_directiontuple
[n_edges_x, n_edges_y, n_edges_z], (dim, )
Notes
Also accessible as vnE.
Examples
>>> import discretize >>> import matplotlib.pyplot as plt >>> import numpy as np >>> M = discretize.TensorMesh([np.ones(n) for n in [2,3]]) >>> M.plot_grid(edges=True, show_it=True)
(Source code, png, pdf)
-
BaseTensorMesh.
n_edges_x
¶ Number of x-edges
- Returns
- int
Notes
Also accessible as nEx.
-
BaseTensorMesh.
n_edges_y
¶ Number of y-edges
- Returns
- int
Notes
Also accessible as nEy.
-
BaseTensorMesh.
n_edges_z
¶ Number of z-edges
- Returns
- int
Notes
Also accessible as nEz.
-
BaseTensorMesh.
n_faces
¶ Total number of faces.
- Returns
- int
sum([n_faces_x, n_faces_y, n_faces_z])
Notes
Also accessible as nF.
-
BaseTensorMesh.
n_faces_per_direction
¶ The number of faces in each direction
- Returns
- n_faces_per_directiontuple
[n_faces_x, n_faces_y, n_faces_z], (dim, )
Notes
Also accessible as vnF.
Examples
>>> import discretize >>> import numpy as np >>> import matplotlib.pyplot as plt >>> M = discretize.TensorMesh([np.ones(n) for n in [2,3]]) >>> M.plot_grid(faces=True, show_it=True)
(Source code, png, pdf)
-
BaseTensorMesh.
n_faces_x
¶ Number of x-faces
- Returns
- int
Notes
Also accessible as nFx.
-
BaseTensorMesh.
n_faces_y
¶ Number of y-faces
- Returns
- int
Notes
Also accessible as nFy.
-
BaseTensorMesh.
n_faces_z
¶ Number of z-faces
- Returns
- int
Notes
Also accessible as nFz.
-
BaseTensorMesh.
n_nodes
¶ Total number of nodes
- Returns
- int
number of nodes in the mesh
Notes
Also accessible as nN.
Examples
>>> import discretize >>> import numpy as np >>> import matplotlib.pyplot as plt >>> mesh = discretize.TensorMesh([np.ones(n) for n in [2,3]]) >>> mesh.plot_grid(nodes=True, show_it=True) >>> print(mesh.n_nodes)
(Source code, png, pdf)
-
BaseTensorMesh.
nodes
¶ Nodal grid.
-
BaseTensorMesh.
nodes_x
¶ Nodal grid vector (1D) in the x direction.
-
BaseTensorMesh.
nodes_y
¶ Nodal grid vector (1D) in the y direction.
-
BaseTensorMesh.
nodes_z
¶ Nodal grid vector (1D) in the z direction.
-
BaseTensorMesh.
normals
¶ normals has been deprecated. See face_normals for documentation
-
BaseTensorMesh.
origin
¶ origin (
Array
): origin of the mesh (dim, ), a list or numpy array of <class ‘float’>, <class ‘int’> with shape (*)
-
BaseTensorMesh.
reference_is_rotated
¶ True if the axes are rotated from the traditional <X,Y,Z> system with vectors of \((1,0,0)\), \((0,1,0)\), and \((0,0,1)\)
-
BaseTensorMesh.
reference_system
¶ reference_system (
String
): The type of coordinate reference frame. Can take on the values cartesian, cylindrical, or spherical. Abbreviations of these are allowed., a unicode string, Default: cartesian
-
BaseTensorMesh.
rotation_matrix
¶ Builds a rotation matrix to transform coordinates from their coordinate system into a conventional cartesian system. This is built off of the three axis_u, axis_v, and axis_w properties; these mapping coordinates use the letters U, V, and W (the three letters preceding X, Y, and Z in the alphabet) to define the projection of the X, Y, and Z durections. These UVW vectors describe the placement and transformation of the mesh’s coordinate sytem assuming at most 3 directions.
Why would you want to use these UVW mapping vectors the this rotation_matrix property? They allow us to define the realationship between local and global coordinate systems and provide a tool for switching between the two while still maintaing the connectivity of the mesh’s cells. For a visual example of this, please see the figure in the docs for the
InterfaceVTK
.
-
BaseTensorMesh.
tangents
¶ tangents has been deprecated. See edge_tangents for documentation
-
BaseTensorMesh.
vectorCCx
¶ vectorCCx has been deprecated. See cell_centers_x for documentation
-
BaseTensorMesh.
vectorCCy
¶ vectorCCy has been deprecated. See cell_centers_y for documentation
-
BaseTensorMesh.
vectorCCz
¶ vectorCCz has been deprecated. See cell_centers_z for documentation
-
BaseTensorMesh.
vectorNx
¶ vectorNx has been deprecated. See nodes_x for documentation
-
BaseTensorMesh.
vectorNy
¶ vectorNy has been deprecated. See nodes_y for documentation
-
BaseTensorMesh.
vectorNz
¶ vectorNz has been deprecated. See nodes_z for documentation
-
BaseTensorMesh.
x0
¶
Methods¶
-
BaseTensorMesh.
copy
()¶ Make a copy of the current mesh
-
classmethod
BaseTensorMesh.
deserialize
(value, **kwargs)¶ Creates HasProperties instance from serialized dictionary
This uses the Property deserializers to deserialize all JSON-compatible dictionary values into their corresponding Property values on a new instance of a HasProperties class. Extra keys in the dictionary that do not correspond to Properties will be ignored.
Parameters:
value - Dictionary to deserialize new instance from.
trusted - If True (and if the input dictionary has
'__class__'
keyword and this class is in the registry), the new HasProperties class will come from the dictionary. If False (the default), only the HasProperties class this method is called on will be constructed.strict - Requires
'__class__'
, if present on the input dictionary, to match the deserialized instance’s class. Also disallows unused properties in the input dictionary. Default is False.assert_valid - Require deserialized instance to be valid. Default is False.
Any other keyword arguments will be passed through to the Property deserializers.
-
BaseTensorMesh.
equal
(other)¶ Determine if two HasProperties instances are equivalent
Equivalence is determined by checking if all Property values on two instances are equal, using
Property.equal
.
-
static
BaseTensorMesh.
from_omf
(element)¶ Convert an OMF element to it’s proper
discretize
type. Automatically determines the output type. Returns both the mesh and a dictionary of model arrays.
-
BaseTensorMesh.
getInterpolationMat
(*args, **kwargs)¶ getInterpolationMat has been deprecated. See get_interpolation_matrix for documentation
-
BaseTensorMesh.
getTensor
(*args, **kwargs)¶ getTensor has been deprecated. See get_tensor for documentation
-
BaseTensorMesh.
get_interpolation_matrix
(loc, location_type='cell_centers', zeros_outside=False, **kwargs)[source]¶ Produces linear interpolation matrix
- Parameters
- locnumpy.ndarray
Location of points to interpolate to
- location_typestr
What to interpolate (see below)
location_type can be:
'Ex', 'edges_x' -> x-component of field defined on x edges 'Ey', 'edges_y' -> y-component of field defined on y edges 'Ez', 'edges_z' -> z-component of field defined on z edges 'Fx', 'faces_x' -> x-component of field defined on x faces 'Fy', 'faces_y' -> y-component of field defined on y faces 'Fz', 'faces_z' -> z-component of field defined on z faces 'N', 'nodes' -> scalar field defined on nodes 'CC', 'cell_centers' -> scalar field defined on cell centers 'CCVx', 'cell_centers_x' -> x-component of vector field defined on cell centers 'CCVy', 'cell_centers_y' -> y-component of vector field defined on cell centers 'CCVz', 'cell_centers_z' -> z-component of vector field defined on cell centers
- Returns
- scipy.sparse.csr_matrix
M, the interpolation matrix
-
BaseTensorMesh.
get_tensor
(key)[source]¶ Returns a tensor list.
- Parameters
- keystr
Which tensor (see below)
key can be:
'CC', 'cell_centers' -> location of cell centers 'N', 'nodes' -> location of nodes 'Fx', 'faces_x' -> location of faces with an x normal 'Fy', 'faces_y' -> location of faces with an y normal 'Fz', 'faces_z' -> location of faces with an z normal 'Ex', 'edges_x' -> location of edges with an x tangent 'Ey', 'edges_y' -> location of edges with an y tangent 'Ez', 'edges_z' -> location of edges with an z tangent
- Returns
- list
list of the tensors that make up the mesh.
-
BaseTensorMesh.
isInside
(*args, **kwargs)¶ isInside has been deprecated. See is_inside for documentation
-
BaseTensorMesh.
is_inside
(pts, location_type='nodes', **kwargs)[source]¶ Determines if a set of points are inside a mesh.
- Parameters
pts (numpy.ndarray) – Location of points to test
- Return type
- Returns
inside, numpy array of booleans
-
BaseTensorMesh.
plotGrid
(*args, **kwargs)¶ plotGrid has been deprecated. See plot_grid for documentation
-
BaseTensorMesh.
plotImage
(*args, **kwargs)¶ plotImage has been deprecated. See plot_image for documentation
-
BaseTensorMesh.
plotSlice
(*args, **kwargs)¶ plotSlice has been deprecated. See plot_slice for documentation
-
BaseTensorMesh.
plot_3d_slicer
(v, xslice=None, yslice=None, zslice=None, v_type='CC', view='real', axis='xy', transparent=None, clim=None, xlim=None, ylim=None, zlim=None, aspect='auto', grid=[2, 2, 1], pcolor_opts=None, fig=None, **kwargs)¶ Plot slices of a 3D volume, interactively (scroll wheel).
If called from a notebook, make sure to set
%matplotlib notebook
See the class discretize.View.Slicer for more information.
It returns nothing. However, if you need the different figure handles you can get it via
fig = plt.gcf()
and subsequently its children via
fig.get_children()
and recursively deeper, e.g.,
fig.get_children()[0].get_children().
One can also provide an existing figure instance, which can be useful for interactive widgets in Notebooks. The provided figure is cleared first.
-
BaseTensorMesh.
plot_grid
(ax=None, nodes=False, faces=False, centers=False, edges=False, lines=True, show_it=False, **kwargs)¶ Plot the nodal, cell-centered and staggered grids.
- Parameters
- axmatplotlib.axes.Axes or None, optional
The axes to draw on. None produces a new Axes.
- nodes, faces, centers, edges, linesbool, optional
Whether to plot the corresponding item
- show_itbool, optional
whether to call plt.show()
- colorColor or str, optional
If lines=True, the color of the lines, defaults to first color.
- linewidthfloat, optional
If lines=True, the linewidth for the lines.
- Returns
- matplotlib.axes.Axes
Axes handle for the plot
- Other Parameters
- edges_x, edges_y, edges_z, faces_x, faces_y, faces_zbool, optional
When plotting a
TreeMesh
, these are also options to plot the individual component items.- cell_linebool, optional
When plotting a
TreeMesh
, you can also plot a line through the cell centers in order.- slice{‘both’, ‘theta’, ‘z’}
When plotting a
CylindricalMesh
, which dimension to slice over.
Notes
Excess arguments are passed on to plot
Examples
Plotting a 2D TensorMesh grid
>>> from matplotlib import pyplot as plt >>> import discretize >>> import numpy as np >>> h1 = np.linspace(.1, .5, 3) >>> h2 = np.linspace(.1, .5, 5) >>> mesh = discretize.TensorMesh([h1, h2]) >>> mesh.plot_grid(nodes=True, faces=True, centers=True, lines=True) >>> plt.show()
(Source code, png, pdf)
Plotting a 3D TensorMesh grid
>>> from matplotlib import pyplot as plt >>> 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.plot_grid(nodes=True, faces=True, centers=True, lines=True) >>> plt.show()
Plotting a 2D CurvilinearMesh
>>> from matplotlib import pyplot as plt >>> import discretize >>> X, Y = discretize.utils.exampleLrmGrid([10, 10], 'rotate') >>> M = discretize.CurvilinearMesh([X, Y]) >>> M.plot_grid() >>> plt.show()
Plotting a 3D CurvilinearMesh
>>> from matplotlib import pyplot as plt >>> import discretize >>> X, Y, Z = discretize.utils.exampleLrmGrid([5, 5, 5], 'rotate') >>> M = discretize.CurvilinearMesh([X, Y, Z]) >>> M.plot_grid() >>> plt.show()
Plotting a 2D TreeMesh
>>> from matplotlib import pyplot as plt >>> import discretize >>> M = discretize.TreeMesh([32, 32]) >>> M.insert_cells([[0.25, 0.25]], [4]) >>> M.plot_grid() >>> plt.show()
Plotting a 3D TreeMesh
>>> from matplotlib import pyplot as plt >>> import discretize >>> M = discretize.TreeMesh([32, 32, 32]) >>> M.insert_cells([[0.3, 0.75, 0.22]], [4]) >>> M.plot_grid() >>> plt.show()
-
BaseTensorMesh.
plot_image
(v, v_type='CC', grid=False, view='real', ax=None, clim=None, show_it=False, pcolor_opts=None, stream_opts=None, grid_opts=None, range_x=None, range_y=None, sample_grid=None, stream_thickness=None, stream_threshold=None, **kwargs)¶ Plots fields on the given mesh.
- Parameters
- vnumpy.ndarray
values to plot
- v_type{‘CC’,’CCV’, ‘N’, ‘F’, ‘Fx’, ‘Fy’, ‘Fz’, ‘E’, ‘Ex’, ‘Ey’, ‘Ez’}
Where the values of v are defined.
- view{‘real’, ‘imag’, ‘abs’, ‘vec’}
How to view the array.
- axmatplotlib.axes.Axes, optional
The axes to draw on. None produces a new Axes.
- climtuple of float, optional
length 2 tuple of (vmin, vmax) for the color limits
- range_x, range_ytuple of float, optional
length 2 tuple of (min, max) for the bounds of the plot axes.
- pcolor_optsdict, optional
Arguments passed on to
pcolormesh
- gridbool, optional
Whether to plot the edges of the mesh cells.
- grid_optsdict, optional
If
grid
is true, arguments passed on toplot
for grid- sample_gridtuple of numpy.ndarray, optional
If
view
== ‘vec’, mesh cell widths (hx, hy) to interpolate onto for vector plotting- stream_optsdict, optional
If
view
== ‘vec’, arguments passed on tostreamplot
- stream_thicknessfloat, optional
If
view
== ‘vec’, linewidth forstreamplot
- stream_thresholdfloat, optional
If
view
== ‘vec’, only plots vectors with magnitude above this threshold- show_itbool, optional
Whether to call plt.show()
- numberingbool, optional
For 3D TensorMesh only, show the numbering of the slices
- annotation_colorColor or str, optional
For 3D TensorMesh only, color of the annotation
Examples
2D
TensorMesh
plotting>>> from matplotlib import pyplot as plt >>> 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.plot_image(v) >>> plt.show()
(Source code, png, pdf)
3D
TensorMesh
plotting>>> 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.plot_image(v, annotation_color='k') >>> plt.show()
-
BaseTensorMesh.
plot_slice
(v, v_type='CC', normal='Z', ind=None, grid=False, view='real', ax=None, clim=None, show_it=False, pcolor_opts=None, stream_opts=None, grid_opts=None, range_x=None, range_y=None, sample_grid=None, stream_threshold=None, stream_thickness=None, **kwargs)¶ Plots slice of fields on the given 3D mesh.
- Parameters
- vnumpy.ndarray
values to plot
- v_type{‘CC’,’CCV’, ‘N’, ‘F’, ‘Fx’, ‘Fy’, ‘Fz’, ‘E’, ‘Ex’, ‘Ey’, ‘Ez’}, or tuple of these options
Where the values of v are defined.
- normal{‘Z’, ‘X’, ‘Y’}
Normal direction of slicing plane.
- indNone, optional
index along dimension of slice. Defaults to the center index.
- view{‘real’, ‘imag’, ‘abs’, ‘vec’}
How to view the array.
- axmatplotlib.axes.Axes, optional
The axes to draw on. None produces a new Axes. Must be None if
v_type
is a tuple.- climtuple of float, optional
length 2 tuple of (vmin, vmax) for the color limits
- range_x, range_ytuple of float, optional
length 2 tuple of (min, max) for the bounds of the plot axes.
- pcolor_optsdict, optional
Arguments passed on to
pcolormesh
- gridbool, optional
Whether to plot the edges of the mesh cells.
- grid_optsdict, optional
If
grid
is true, arguments passed on toplot
for the edges- sample_gridtuple of numpy.ndarray, optional
If
view
== ‘vec’, mesh cell widths (hx, hy) to interpolate onto for vector plotting- stream_optsdict, optional
If
view
== ‘vec’, arguments passed on tostreamplot
- stream_thicknessfloat, optional
If
view
== ‘vec’, linewidth forstreamplot
- stream_thresholdfloat, optional
If
view
== ‘vec’, only plots vectors with magnitude above this threshold- show_itbool, optional
Whether to call plt.show()
Examples
Plot a slice of a 3D
TensorMesh
solution to a Laplace’s equaiton.First build the mesh:
>>> from matplotlib import pyplot as plt >>> import discretize >>> from pymatsolver import Solver >>> import numpy as np >>> hx = [(5, 2, -1.3), (2, 4), (5, 2, 1.3)] >>> hy = [(2, 2, -1.3), (2, 6), (2, 2, 1.3)] >>> hz = [(2, 2, -1.3), (2, 6), (2, 2, 1.3)] >>> M = discretize.TensorMesh([hx, hy, hz])
then build the necessary parts of the PDE:
>>> q = np.zeros(M.vnC) >>> q[[4, 4], [4, 4], [2, 6]]=[-1, 1] >>> q = discretize.utils.mkvc(q) >>> A = M.face_divergence * M.cell_gradient >>> b = Solver(A) * (q)
and finaly, plot the vector values of the result, which are defined on faces
>>> M.plot_slice(M.cell_gradient*b, 'F', view='vec', grid=True, pcolor_opts={'alpha':0.8}) >>> plt.show()
(Source code, png, pdf)
-
BaseTensorMesh.
projectEdgeVector
(*args, **kwargs)¶ projectEdgeVector has been deprecated. See project_edge_vector for documentation
-
BaseTensorMesh.
projectFaceVector
(*args, **kwargs)¶ projectFaceVector has been deprecated. See project_face_vector for documentation
-
BaseTensorMesh.
project_edge_vector
(edge_vector)¶ Project vectors onto the edges of the mesh
Given a vector, edge_vector, in cartesian coordinates, this will project it onto the mesh using the tangents
- Parameters
- edge_vectornumpy.ndarray
edge vector with shape (n_edges, dim)
- Returns
- numpy.ndarray
projected edge vector, (n_edges, )
-
BaseTensorMesh.
project_face_vector
(face_vector)¶ Project vectors onto the faces of the mesh.
Given a vector, face_vector, in cartesian coordinates, this will project it onto the mesh using the normals
- Parameters
- face_vectornumpy.ndarray
face vector with shape (n_faces, dim)
- Returns
- numpy.ndarray
projected face vector, (n_faces, )
-
BaseTensorMesh.
save
(file_name='mesh.json', verbose=False, **kwargs)¶ Save the mesh to json :param str file: file_name for saving the casing properties :param str directory: working directory for saving the file
-
BaseTensorMesh.
serialize
(include_class=True, save_dynamic=False, **kwargs)¶ Serializes a HasProperties instance to dictionary
This uses the Property serializers to serialize all Property values to a JSON-compatible dictionary. Properties that are undefined are not included. If the HasProperties instance contains a reference to itself, a
properties.SelfReferenceError
will be raised.Parameters:
include_class - If True (the default), the name of the class will also be saved to the serialized dictionary under key
'__class__'
save_dynamic - If True, dynamic properties are written to the serialized dict (default: False).
Any other keyword arguments will be passed through to the Property serializers.
-
BaseTensorMesh.
toVTK
(models=None)¶ Convert this mesh object to it’s proper VTK or
pyvista
data object with the given model dictionary as the cell data of that dataset.- Parameters
- modelsdict(numpy.ndarray)
Name(‘s) and array(‘s). Match number of cells
-
BaseTensorMesh.
to_omf
(models=None)¶ Convert this mesh object to it’s proper
omf
data object with the given model dictionary as the cell data of that dataset.- Parameters
- modelsdict(numpy.ndarray)
Name(‘s) and array(‘s). Match number of cells
-
BaseTensorMesh.
to_vtk
(models=None)¶ Convert this mesh object to it’s proper VTK or
pyvista
data object with the given model dictionary as the cell data of that dataset.- Parameters
- modelsdict(numpy.ndarray)
Name(‘s) and array(‘s). Match number of cells
-
BaseTensorMesh.
validate
()¶ Call all registered class validator methods
These are all methods decorated with
@properties.validator
. Validator methods are expected to raise a ValidationError if they fail.
-
BaseTensorMesh.
writeVTK
(file_name, models=None, directory='')¶ Makes and saves a VTK object from this mesh and given models
- Parameters
- file_namestr
path to the output vtk file or just its name if directory is specified
- modelsdict
dictionary of numpy.array - Name(‘s) and array(‘s). Match number of cells
- directorystr
directory where the UBC GIF file lives
-
BaseTensorMesh.
write_vtk
(file_name, models=None, directory='')¶ Makes and saves a VTK object from this mesh and given models
- Parameters
- file_namestr
path to the output vtk file or just its name if directory is specified
- modelsdict
dictionary of numpy.array - Name(‘s) and array(‘s). Match number of cells
- directorystr
directory where the UBC GIF file lives