mixins module provides a set of tools for interfacing
with external libraries such as VTK. These modules are only imported if those
external packages are available in the active Python environment and provide
extra functionality that different finite volume meshes can inherrit.
This module provides a way for
discretize meshes to be
converted to VTK data objects (and back when possible) if the
VTK Python package is available.
vtkInterface class becomes inherrited by all mesh objects and allows
users to directly convert any given mesh by calling that mesh’s
method (note that this method will not be available if VTK is not available).
This functionality was originally developed so that discretize could be interoperable with PVGeo, providing a direct interface for discretize meshes within ParaView and other VTK powered platforms. This interoperablity allows users to visualize their finite volume meshes and model data from discretize along side all their other datasets in a common rendering environment.
Here’s an example of the types of integrated visualizations that are possible in ParaView leveraging the link between discretize and PVGeo:
Laguna del Maule Bouguer Gravity
This data scene is was produced from the Laguna del Maule Bouguer Gravity example provided by Craig Miller (see Maule volcanic field, Chile. Refer to Miller et al 2016 EPSL for full details.)
The rendering below shows several data sets and a model integrated together:
- Point Data: the Bouguer gravity anomalies
- Topography Surface
- Inverted Model: The model has been both sliced and thresholded for low values
Assign the model(s) to the VTK dataset as CellData
This class is full of methods that enable
discretizemeshes to be converted to VTK data objects (and back when possible). This is inherritted by the
BaseMeshclass so all these methods are available to any mesh object!
TensorMeshare all currently implemented. The
CylMeshis not implemeted and will raise and excpetion. The following is an example of how to use the VTK interface to construct VTK data objects or write VTK files.
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]) # Get a VTK data object mesh.toVTK() # Save this mesh to a VTK file mesh.writeVTK('sample_mesh')
Note that if your mesh is defined on a reference frame that is not the traditional <X,Y,Z> system with vectors of \((1,0,0)\), \((0,1,0)\), and \((0,0,1)\), then the mesh will be rotated to be on the traditional reference frame. The previous example snippet provides a
vtkRectilinearGridobject because that tensor mesh lies on the traditional reference frame. If we alter the reference frame, then we yield a
vtkStructuredGridthat is the same mesh rotated in space.
# Defined a rotated reference frame mesh.axis_u = (1,-1,0) mesh.axis_v = (-1,-1,0) mesh.axis_w = (0,0,1) # Check that the referenc fram is valid mesh._validate_orientation() # Yield the rotated vtkStructuredGrid mesh.toVTK() # or write it out to a VTK format mesh.writeVTK('sample_rotated')
The two above code snippets produce a
vtkStructuredGridrespecitvely. To demonstarte the difference, we have plotted the two datasets next to eachother where the first mesh is in green and its data axes are parrallel to the traditional cartesian reference frame. The second, rotated mesh is shown in red and its data axii are rotated from the traditional cartesian refence frame as specified by the
Convert this mesh object to it’s proper VTK data object with the given model dictionary as the cell data of that dataset.
Parameters: models (dict(numpy.ndarray)) – Name(‘s) and array(‘s). Match number of cells
writeVTK(mesh, fileName, models=None, directory='')¶
Makes and saves a VTK object from this mesh and given models
Provides a convienance method for reading VTK Rectilinear Grid files as
readVTK(TensorMesh, fileName, directory='')¶
Read VTK Rectilinear (vtr xml file) and return Tensor mesh and model
Return type: tuple Returns: (TensorMesh, modelDictionary)