RuntimeError: ffi_prep_cif_var failed when calling richardson_lucy_nc but not when calling richardson_lucy (python) #34
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How big is your image? My first thought is that you might be running out of memory (the non-circulant version uses more memory). If you are running out of memory you could try the dask version. Here is an example as to how to use the dask version https://github.com/clij/clij2-fft/blob/master/python/tests/test_richardson_lucy_dask.py. If not a memory problem let me and I'll look into it further. |
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Hi, Thanks very much for the quick response! Not so sure it is a memory issue, as I the test image is very small (14,500,500), psf (31,47,47) and the gpu's we run have 80G of memory. I also tried it with a small array of np.ones of dimension (100, 100, 24) with psf (24, 24, 12) with the same result. See log below: |
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Thanks for the additional feedback. I changed the interface to convcorr3d a few months ago and somehow did not update the Linux libs. I think I've fixed it, but let me know. Update clij2-fft, confirm that you have version 0.27 and try again. Once you get it going I'd be interested to hear if the non-circulant version makes a difference for your image. I noticed your PSF size in z is longer than the image size. Is that correct? The non-circulant version should be able to handle that, however I haven't done a lot of testing with that scenario. What type of instrument are you using and how did you create the PSF? |
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Hi, Thanks for your very quick fix, it solves the issue, but I am now getting another error using v0.27 when calling the nc version: Is this some kind of broken reference? I installed v0.27 through pip. The image I get out seems to have a constant value for all pixels. The circulant version seems to work still. I also get this issue when I use the array of 1's. Some off topic context:
Some context of what we are hoping to do that are maybe a bit of topic (and maybe better moved to image sc?), please don't feel obligated to go through this, but as I am still learning about deconvolution, some expert advice would be welcome! We are in a situtation where we run image aquistiaiton in high throughput on small cells (5 to 15um) which are not in a clean monolayer, so are a little limeted in how many z-planes we can aquire while keeping things manageble computationally (every plane can add about 500gb). We are planning to up the number of z-planes a bit in future experiments, but we will likely always have some edges in the z axis. Having experimented a bit however, in this non ideal senario where we have 0.5 / 0.6 plane spacing with 14-16 planes and some strong edges as we started the aquistion 0.5um up, the standard RL seems to work suprisingly well with suprsingly minimal artefacts, at least using the clij2 implementation (Below an example of the nuclei before and after). I didn't have much luck with redlionfish, as that gave strong artefacts, even with padding zeroes to the image. However if you feel in this senerio where we will have cells with strong edges, attempting decon is not sensible, please let us know! If it would be better to capture more of the cell by increasing our z-spacing to lets say 0.6 or 0.7 (slightly over the Nyquist threshold of 0.5) but then we capture more of the cells, and have fewer edges, that would also be helpfull.
With the gamma at 0.2 to illustrate where the non-zero signal is: With the gamma at 1: Before: After 100 iterations: Detaills PSF generation: |
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Your images from circulant RL actually pretty good, so not sure the non-circulant version will help you much. That being said I'd still like to figure out why it isn't working for you. If you are able to post a sample of an image and one of your PSFs I can troubleshoot further. Either here or on ImageSC. |
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This issue has been mentioned on Image.sc Forum. There might be relevant details there: https://forum.image.sc/t/issues-with-python-version-of-clij2-richardson-lucy-nc/101300/1 |
Hi,
I am running into a runtime error during calling the non circular RL from python version, where it throws RuntimeError: ffi_prep_cif_var failed
The circular version richardson_lucy() does seem to work fine and produces quite good results. Any advice on if this could be a data issue (psf / data in wrong format) or a install issue would be appreciated as I'd like to test the nc version as I have some strong edges in my data.
I tried a bit of googling and looking at the source, and it seems like its an error between the python - C interaction but it goes a bit above my head.
Running on Ubuntu 22.04.4 with version python 3.10.0, clij2-fft 0.26, pyopencl 2024.2.7 and cuda 12.1 (full package list below).
EDIT:
I have tried running with np.ones to rule out an issue with my image / psfs following from: https://github.com/clij/clij2-fft/blob/master/python/interactive%20tests/test_richardson_lucy.py
It still gives the same issue
Package versions in my environment:
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