Comments (3)
self.nufft_ob = tkbn.KbNufft(im_size=im_size, #grid_size=(256,256), ).to(self.dev),
is not syntatically correct python?
Not clear what you mean by "shutdown", but the warning is just a warning -- you can ignore, suppress, or fix (by replacing instances of np.complex
with complex
) without changing the computation.
from torchkbnufft.
As far as I can tell this is not used anywhere in the core package (but it is used in some examples).
https://github.com/mmuckley/torchkbnufft/search?q=np.complex
We should probably update the examples, but in your case @9B8DY6 it seems your self.dev
is np.complex
.
from torchkbnufft.
I solved this problem with filterwarning!
from torchkbnufft.
Related Issues (20)
- Thread allocation issues with batched density compensation HOT 11
- Basic KB-NUFFT Example HOT 6
- Failed for 3D non-Cartesian trajectory
- MriSenseNufft, AdjMriSenseNufft, AdjKbNufft, ToepSenseNufft removed
- Accuracy for numpoints = 2 - 7
- nonuniform discrete Fourier transform of type II HOT 4
- grid_size HOT 3
- Make compatible with latest PyTorch HOT 7
- data range changed after processing HOT 4
- KB-NUFFT hangs when used in PyTorch DataLoader with num_workers > 0 HOT 3
- Allow user control of threading
- Could you give an example of implementing a two-dimensional Fourier transform by use torchkbnufft?
- Performance vs FFT HOT 6
- Toeplitz Kernel has boundary artifacts HOT 9
- Support for NFFTs of real valued Arrays HOT 6
- Basic 1D case
- Batched input with varying size leads to TorchScript error HOT 2
- KbInterpAdjoint gives mismatch results? HOT 3
- Gradients w.r.t. coordinates in ktraj
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from torchkbnufft.