Class Fourier

monai/transforms/utils.py:1876–1923

Helper class storing Fourier mappings

class Fourier:
    """
    Helper class storing Fourier mappings
    """

    @staticmethod
    def shift_fourier(x: NdarrayOrTensor, spatial_dims: int, as_contiguous: bool = False) -> NdarrayOrTensor:
        """
        Applies fourier transform and shifts the zero-frequency component to the
        center of the spectrum. Only the spatial dimensions get transformed.

        Args:
            x: Image to transform.
            spatial_dims: Number of spatial dimensions.
            as_contiguous: Whether to convert the cached NumPy array or PyTorch tensor to be contiguous.

        Returns
            k: K-space data.
        """
        dims = tuple(range(-spatial_dims, 0))
        k: NdarrayOrTensor
        if isinstance(x, torch.Tensor):
            k = torch.fft.fftshift(torch.fft.fftn(x, dim=dims), dim=dims)
        else:
            k = np.fft.fftshift(np.fft.fftn(x, axes=dims), axes=dims)
        return ascontiguousarray(k) if as_contiguous else k

    @staticmethod
    def inv_shift_fourier(k: NdarrayOrTensor, spatial_dims: int, as_contiguous: bool = False) -> NdarrayOrTensor:
        """
        Applies inverse shift and fourier transform. Only the spatial
        dimensions are transformed.

        Args:
            k: K-space data.
            spatial_dims: Number of spatial dimensions.
            as_contiguous: Whether to convert the cached NumPy array or PyTorch tensor to be contiguous.

        Returns:
            x: Tensor in image space.
        """
        dims = tuple(range(-spatial_dims, 0))
        out: NdarrayOrTensor
        if isinstance(k, torch.Tensor):
            out = torch.fft.ifftn(torch.fft.ifftshift(k, dim=dims), dim=dims, norm="backward").real
        else:
            out = np.fft.ifftn(np.fft.ifftshift(k, axes=dims), axes=dims).real
        return ascontiguousarray(out) if as_contiguous else out


def get_number_image_type_conversions(transform: Compose, test_data: Any, key: Hashable | None = None) -> int: