使用Numpy将VTK转换为Matplotlib [英] VTK to Matplotlib using Numpy
问题描述
我想从 VTK 文件中提取一些数据(例如标量)以及它们在网格上的坐标,然后在 Matplotlib 中进行处理.问题是我不知道如何从VTK文件中获取点/像元数据(例如,通过给出标量的名称),然后使用 vtk_to_numpy
I want to extract some data (e.g. scalars) from a VTK file along with their coordinates on the grid then process it in Matplotlib. The problem is I dont know how to grab the point/cell data from the VTK file (by giving the name of the scalar, for instance) and load them into a numpy array using vtk_to_numpy
我的代码应如下所示:
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:我知道 Paraview 可以完成此任务,但是我正在尝试对某些数据进行后期处理,而不必打开Paraview.感谢您的帮助
PS:I know that Paraview could do the task, but I am trying post process some data without having to open Paraview. Any help is appreciated
编辑1
我发现此 pdf教程对于学习处理VTK的基础知识非常有用文件
I found this pdf tutorial to be very useful to learn the basics of handling VTK files
推荐答案
我终于想出了一种方法(可能不是最佳方法)来完成这项工作.这里的示例是绘制从vtk文件提取的温度场的轮廓图:
I finally figured a way (maybe not the optimal) that does the job. The example here is contour plotting a temperature field extracted from a vtk file:
import matplotlib.pyplot as plt
import matplotlib.cm as cm
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()
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