I’m under the impression something in the comparative visualization is not working as intended, but I tested with 5.6.0, 5.8.1, and the latest nightly (5.8.1-1454-gf84473df96), so maybe I’m just not doing it properly.
Shortly said, the “visibility” option of the comparative view makes the given dataset either visible in every layout or in none of them based on the value (0 or 1) of the last cell (bottom right) of the visibility table.
So, if I actually want to have different datasets displayed in different layouts, I use the threshold filter with the “Range (1)” variable. Doing that I’m able to show and hide datasets in each of the comparative view layouts as I wish.
Indeed, visibility was not intended to controllable across views the way you’re wanting. Using another filter to achieve the same, as you do is perhaps a reasonable workaround.
Hello @utkarsh.ayachit,
I’m having the same problem but can’t do this workaround because I’m working with raster.
I want to display 2 different rasters in the comparative view but I’m enable choose which data put in separated comparative views.
I have the same impression that @Louis, it seems that “comparative view” mode have been built in order to do that task but it’s not working.
Thanks in advance, Frank
I am having a similar issue. I am also very new to ParaView, so I could be missing something basic. Plus, it takes an incredibly long time to render with every simple change I make and I don’t see anywhere to wait and “apply” changes all at once, so troubleshooting is a bit painful!
I have 4 models I would like to compare, each clipped at the same value. So, the clip filter for each is the same, but operates on a different dataset (*side question below). In comparative view I have added each clip as a parameter and put a 1 in the visibility matrix below. However, the image in each view is identical (when I view them individually in “layout 1” they are different):
Client Information:
Version: 5.11.0-RC1
VTK Version: 9.2.20220823
Qt Version: 5.15.2
vtkIdType size: 64bits
Embedded Python: On
Python Library Path: C:\Program Files\ParaView 5.11.0\bin\lib
Python Library Version: 3.9.13 (tags/v3.9.13:6de2ca5, May 17 2022, 16:36:42) [MSC v.1929 64 bit (AMD64)]
Python Numpy Support: On
Python Numpy Path: C:\Program Files\ParaView 5.11.0\bin\Lib\site-packages\numpy
Python Numpy Version: 1.21.1
Python Matplotlib Support: On
Python Matplotlib Path: C:\Program Files\ParaView 5.11.0\bin\Lib\site-packages\matplotlib
Python Matplotlib Version: 3.2.1
Python Testing: Off
MPI Enabled: Off
ParaView Build ID: superbuild 5d77dcfd71ab85235799c921f55ebb69e8b72630 (!1015)
Disable Registry: Off
Test Directory:
Data Directory:
SMP Backend: TBB
SMP Max Number of Threads: 40
OpenGL Vendor: NVIDIA Corporation
OpenGL Version: 3.2.0 NVIDIA 451.48
OpenGL Renderer: Quadro RTX 4000/PCIe/SSE2
Accelerated filters overrides available: No
Connection Information:
Remote Connection: No
*side question: I am under the impression I am applying a separate clip filter to each model data set. However, when I update one it seems to apply to all the others, but it seems sporadic. For example, when I change the color map in “Clip4” it applies to “Clip3”, “Clip2”, and “Clip1”. Also, when I change the parameter/value to be colored it changes for all other “Clip” filters. But occasionally the value to be colored changes back to “Solid Color” rather than what I had previously chosen
Based on the pipeline tree, I thought they were each applied to a different data set independently. How are they linked? Can I un-link them?
I don’t think you want to use Comparative View for your case. If you have four different models that you simply want to compare in 4 views: do the following instead:
split the main render view into 4 using the split buttons
link cameras between all views
now show each dataset in each of the views as you want.
Alternatively, there’s a meta-file that you can setup to which you provide the 4 datasets as the datasets defining the parameter sweep. I am not fully aware of that capability. cc-ing a few folks who’d have better insight on the meta-file approach: @berkgeveci, @danlipsa
