VTK到Matplotlib使用Numpy

问题描述 投票:10回答:2

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中处理它。问题是我不知道如何从VTK文件中获取点/单元数据(例如,通过给出标量的名称)并使用vtk_to_numpy将它们加载到numpy数组中

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可以完成任务,但我正在尝试发布一些数据而无需打开Paraview。任何帮助表示赞赏

编辑1

我发现这个pdf tutorial对于学习处理VTK文件的基础知识非常有用

python arrays numpy matplotlib vtk
2个回答
7
投票

我终于找到了一种方法(可能不是最佳的)来完成这项工作。这里的例子是轮廓绘制从vtk文件中提取的温度场:

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() 


6
投票

我不知道你的数据集是什么样的,所以这里只有一些方法可以获得点位置和标量值:

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())

如果你可以使用tvtk会有点容易:

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()

如果你想在matplotib中做contour绘图,我认为你需要一个网格,你可能需要使用一些VTK类将数据集转换为网格,例如vtkProbeFilter

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