VTK in Maplotlib with Numpy

Question

I want to extract some data (for example, scalars) from a VTK file along with their coordinates on the grid, and then process it in Matplotlib . The problem is that I do not know how to capture point / cell data from a VTK file (for example, specifying a scalar name) and load it into a numpy array using vtk_to_numpy

My code should look like this:

import matplotlib.pyplot as plt
from scipy.interpolate import griddata
import numpy as np
from vtk import *
from vtk.util.numpy_support import vtk_to_numpy

# load input data
reader = vtk.vtkXMLUnstructuredGridReader()
reader.SetFileName("my_input_data.vtk")
reader.Update()

(...missing steps)

# VTK to Numpy
my_numpy_array = vtk_to_numpy(...arguments ?)

#Numpy to Matplotlib (after converting my_numpy_array to x,y and z)
CS = plt.contour(x,y,z,NbLevels)
...

PS: I know that Paraview can complete the task, but I'm trying to send some data without opening Paraview. Any help is appreciated

Change 1

I found this pdf tutorial to be very useful for learning the basics of VTK file processing.

Answer 1

- (, ), . , , vtk:

import matplotlib.pyplot as plt
from scipy.interpolate import griddata
import numpy as np
import vtk
from vtk.util.numpy_support import vtk_to_numpy

# load a vtk file as input
reader = vtk.vtkXMLUnstructuredGridReader()
reader.SetFileName("my_input_data.vtk")
reader.Update()

# Get the coordinates of nodes in the mesh
nodes_vtk_array= reader.GetOutput().GetPoints().GetData()

#The "Temperature" field is the third scalar in my vtk file
temperature_vtk_array = reader.GetOutput().GetPointData().GetArray(3)

#Get the coordinates of the nodes and their temperatures
nodes_nummpy_array = vtk_to_numpy(nodes_vtk_array)
x,y,z= nodes_nummpy_array[:,0] , nodes_nummpy_array[:,1] , nodes_nummpy_array[:,2]

temperature_numpy_array = vtk_to_numpy(temperature_vtk_array)
T = temperature_numpy_array

#Draw contours
npts = 100
xmin, xmax = min(x), max(x)
ymin, ymax = min(y), max(y)

# define grid
xi = np.linspace(xmin, xmax, npts)
yi = np.linspace(ymin, ymax, npts)
# grid the data
Ti = griddata((x, y), T, (xi[None,:], yi[:,None]), method='cubic')  

## CONTOUR: draws the boundaries of the isosurfaces
CS = plt.contour(xi,yi,Ti,10,linewidths=3,cmap=cm.jet) 

## CONTOUR ANNOTATION: puts a value label
plt.clabel(CS, inline=1,inline_spacing= 3, fontsize=12, colors='k', use_clabeltext=1)

plt.colorbar() 
plt.show() 

Answer 2

, dataset, - :

from vtk import *
from vtk.util.numpy_support import vtk_to_numpy

# load input data
reader = vtk.vtkGenericDataObjectReader()
reader.SetFileName(r"C:\Python27\VTKData\Data\uGridEx.vtk")
reader.Update()
ug  = reader.GetOutput()
points = ug.GetPoints()
print vtk_to_numpy(points.GetData())
print vtk_to_numpy(ug.GetPointData().GetScalars())

, tvtk:

from tvtk.api import tvtk
reader = tvtk.GenericDataObjectReader()
reader.file_name = r"C:\Python27\VTKData\Data\uGridEx.vtk"
reader.update()
ug = reader.output
print ug.points.data.to_array()
print ug.point_data.scalars.to_array()

contour matplotib, , , VTK , vtkProbeFilter.