deepmr.fft.plan_toeplitz_nufft#
- deepmr.fft.plan_toeplitz_nufft(coord, shape, basis=None, dcf=None, width=4, device='cpu')[source]#
Compute spatio-temporal kernel for fast self-adjoint operation.
- Parameters:
coord (torch.Tensor) – K-space coordinates of shape
(ncontrasts, nviews, nsamples, ndims)
. Coordinates must be normalized between(-0.5 * shape[i], 0.5 * shape[i])
, withi = (z, y, x)
.shape (int | Iterable[int]) – Oversampled grid size of shape
(ndim,)
. If scalar, isotropic matrix is assumed.basis (torch.Tensor, optional) – Low rank subspace projection operator of shape
(ncontrasts, ncoeffs)
; can beNone
. The default isNone
.dcf (torch.Tensor, optional) – Density compensation function of shape
(ncontrasts, nviews, nsamples)
. The default is a tensor of1.0
.width (int | Iterable[int], optional) – Interpolation kernel full-width of shape
(ndim,)
. If scalar, isotropic kernel is assumed. The default is3
.device (str, optional) – Computational device (
cpu
orcuda:n
, withn=0, 1,...nGPUs
). The default iscpu
.
- Returns:
toeplitz_kernel – Structure containing Toeplitz kernel (i.e., Fourier transform of system tPSF).
- Return type:
GramMatrix