fastplotlib.ImageWidget#

class ImageWidget(data, window_funcs=None, frame_apply=None, figure_shape=None, names=None, figure_kwargs=None, histogram_widget=True, rgb=None, cmap='plasma', graphic_kwargs=None)[source]#

A high-level widget for navigating through image stacks. It is a thin wrapper around an NDWidget, one add_nd_image per array, with sliders for the “t” (time) and “z” dimensions shared across every image stack.

Allowed dimension orders for each image stack, where the optional (c) is an RGB(A) channel of size 3 or 4:

n_dims	dims order
2	“xy(c)”
3	“txy(c)”
4	“tzxy(c)”

Parameters:

data (np.ndarray | list[np.ndarray]) – array-like or a list of array-like, one image stack per subplot
window_funcs (dict[str, tuple[Callable, int]], optional) – Rolling window functions along the “t” and/or “z” dims, {dim: (func, window_size)}, ex: {"t": (np.mean, 11)}. func must take an axis kwarg, window_size is in frames.
frame_apply (Callable | dict[int, Callable], optional) – Function(s) applied to each array’s slice before it is displayed. A single callable is applied to every subplot, a {array_index: callable} dict applies per-array. Applied after window_funcs.
figure_shape (tuple[int, int], optional) – manually provide the [n_rows, n_cols] shape for the figure, otherwise it is estimated
names (list[str], optional) – names for the subplots
figure_kwargs (dict, optional) – passed to the underlying ImguiFigure
histogram_widget (bool, default True) – make a histogram colorbar for each subplot to interactively set vmin, vmax
rgb (bool | list[bool], optional) – whether each array is RGB(A), i.e. the last dim is a channel of size 3 or 4
cmap (str, default "plasma") – colormap for the image graphics
graphic_kwargs (dict, optional) – passed to each ImageGraphic