我有一组存储在VTK文件中的数据,它代表一个带有数组中标量点数据的域的切割.我正在尝试生成所述标量的等高线图,使其看起来有点像使用ParaView制作的附图.我宁愿坚持使用vtk库而不是使用其他东西,比如Matplotlib,因为我认为它们会产生更好的可视化效果..
我在网上看过几个例子,但没有一个对我有效(没有错误被抛出,我最终得到的只是背景的空渲染),所有我能做的就是表面图数据(例如:这里).
这是我所拥有的代码的当前版本(非常类似于成功生成曲面图的代码):
# import data reader = vtk.vtkDataSetReader() reader.SetFileName('inputDataFiles/k_zCut.vtk') reader.ReadAllVectorsOn() reader.ReadAllScalarsOn() reader.Update() # access data data = reader.GetOutput() d = data.GetPointData() array=d.GetArray('k') # create the filter contours = vtk.vtkContourFilter() contours.SetInput(reader.GetOutput()) contours.GenerateValues(5,1.,5.) # create the mapper mapper = vtk.vtkPolyDataMapper() mapper.SetInput(contours.GetOutput()) mapper.ScalarVisibilityOff() mapper.SetScalarRange(1., 5.) # create the actor actor = vtk.vtkActor() actor.SetMapper(mapper) # create a rendering window and renderer ren = vtk.vtkRenderer() ren.SetBackground( 0.329412, 0.34902, 0.427451 ) #Paraview blue # Assign actor to the renderer ren.AddActor(actor) renWin = vtk.vtkRenderWindow() renWin.AddRenderer(ren) renWin.SetSize(750, 750) # create a renderwindowinteractor iren = vtk.vtkRenderWindowInteractor() iren.SetRenderWindow(renWin) # render renWin.Render() # screenshot w2if = vtk.vtkWindowToImageFilter() w2if.SetInput(renWin) w2if.Update() w2if.SetMagnification(5.) writer = vtk.vtkPNGWriter() writer.SetFileName("screenshot.png") writer.SetInput(w2if.GetOutput()) writer.Write() # Enable user interface interactor iren.Initialize() iren.Start()
下面你可以看到我的输入文件的缩短部分.任何帮助都感激不尽.
# vtk DataFile Version 2.0 sampleSurface ASCII DATASET POLYDATA POINTS 34813 float 0 0 0 0 -0.000191589 0 0.000264399 0.000157061 0 0 0.000313389 0 0.000264347 -0.000191923 0 0 -0.000383178 0 -0.000395709 0 0 -0.000395709 0.000156695 0 3.60174e-05 0.000486922 0 0.000528387 0 0 POLYGONS 69284 277136 3 4105 4371 3861 3 4102 3861 4371 3 4656 4371 4373 3 4105 4373 4371 3 3624 3861 3390 3 3621 3390 3861 3 4105 3863 3861 3 3624 3861 3863 3 3188 3390 2990 3 3187 2990 3390 3 3624 3390 3391 3 3188 3391 3390 POINT_DATA 34813 FIELD attributes 1 k 1 34813 float 0.849464 0.391519 1.52947 1.05206 0.391519 0.253736 1.39481 1.39481 0.636517 1.21019 0.640193 0.114295 1.12557 0.644143 0.629569 0.114295 0.485032 0.477396 1.39961 0.0860201 1.66665 1.24058 1.45939 0.483719 1.01318 0.163198 0.317574 0.792821 0.317125 0.658835
Joe Kington.. 6
如果您想对VTK使用更"pythonic"的接口,请考虑使用mayavi
/ tvtk
/mlab
.(无论哪种方式,VTK都是一个很好的选择!)
tvtk
是一个稍微更加pythonic,低级,python绑定到VTK与一些非常好的功能(例如透明使用numpy数组).
Mayavi和mlab为VTK提供了更高级别的接口.
您显示的数据文件的片段原样无效,但如果我们使用类似的:
# vtk DataFile Version 2.0 Simple VTK file example ASCII DATASET POLYDATA POINTS 9 float 3.0 0.0 0.0 1.0 1.0 0.0 0.0 3.0 0.0 3.0 0.0 1.0 1.0 1.0 1.0 0.0 3.0 1.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 3.0 2.0 TRIANGLE_STRIPS 2 14 6 0 3 1 4 2 5 6 3 6 4 7 5 8 POINT_DATA 9 SCALARS nodal float LOOKUP_TABLE default 0.0 0.1 0.0 0.3 0.6 0.3 0.8 1.0 0.8
在表面上渲染轮廓可以很简单:
from mayavi import mlab source = mlab.pipeline.open('test.vtk') lines = mlab.pipeline.contour_surface(source) mlab.show()
或者我们可以有点发烧友:
from mayavi import mlab # Make a figure with a black background fig = mlab.figure(bgcolor=(0,0,0)) # Also see methods like: fig.scene.z_plus_view(), etc fig.scene.camera.azimuth(215) source = mlab.pipeline.open('test.vtk') # Show the surface, colored by the scalars surf = mlab.pipeline.surface(source) # Draw contours of the scalars on the surface lines = mlab.pipeline.contour_surface(source) mlab.show()
如果您想对VTK使用更"pythonic"的接口,请考虑使用mayavi
/ tvtk
/mlab
.(无论哪种方式,VTK都是一个很好的选择!)
tvtk
是一个稍微更加pythonic,低级,python绑定到VTK与一些非常好的功能(例如透明使用numpy数组).
Mayavi和mlab为VTK提供了更高级别的接口.
您显示的数据文件的片段原样无效,但如果我们使用类似的:
# vtk DataFile Version 2.0 Simple VTK file example ASCII DATASET POLYDATA POINTS 9 float 3.0 0.0 0.0 1.0 1.0 0.0 0.0 3.0 0.0 3.0 0.0 1.0 1.0 1.0 1.0 0.0 3.0 1.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 3.0 2.0 TRIANGLE_STRIPS 2 14 6 0 3 1 4 2 5 6 3 6 4 7 5 8 POINT_DATA 9 SCALARS nodal float LOOKUP_TABLE default 0.0 0.1 0.0 0.3 0.6 0.3 0.8 1.0 0.8
在表面上渲染轮廓可以很简单:
from mayavi import mlab source = mlab.pipeline.open('test.vtk') lines = mlab.pipeline.contour_surface(source) mlab.show()
或者我们可以有点发烧友:
from mayavi import mlab # Make a figure with a black background fig = mlab.figure(bgcolor=(0,0,0)) # Also see methods like: fig.scene.z_plus_view(), etc fig.scene.camera.azimuth(215) source = mlab.pipeline.open('test.vtk') # Show the surface, colored by the scalars surf = mlab.pipeline.surface(source) # Draw contours of the scalars on the surface lines = mlab.pipeline.contour_surface(source) mlab.show()