visualize_with_fourier#
- radionets.plotting.visualization.visualize_with_fourier(i: int, img_input: tensor, img_pred: tensor, img_truth: tensor, amp_phase: bool, out_path: Path, plot_format: str = 'png', return_fig: bool = False, kwargs: list[dict] | None = None)[source]#
Visualizes how the target variables are displayed in fourier space.
- Parameters:
- iint
Current index given form the loop
- img_input
torch.tensor() Current input image as a
array()ortensor()with shape [M, N]- img_pred
torch.tensor() Current prediction image as a
array()ortensor()with shape [M, N]- img_truth
torch.tensor() Current true image as a
array()ortensor()with shape [M, N]- amp_phasebool
Whether the image contains real/imaginary information or amplitude/phase information.
- out_pathstr which contains the output path
Output path of the figure. Skipped if
return_figis set toTrue.- plot_formatstr, optional
Output file format. Default: png
- return_figbool, optional
Whether to return the
figure()object instead of saving the figure to a file. Default:False- **kwargslist[dict] or None, optional
Additional list of dictionaries with keyword arguments for each subplot. Default:
None
- Returns:
- fig
figure() Figure object if
return_figis set toTrue.
- fig