This is a script that can be run as:
python napari_colormaps_widget.py
It will launch a viewer with an example single channel image and add widget that permits extended colormap/LUT features. There will be 3 tabs:

1. Allows access to inverted ChrisLUTs by @cleterrier (https://github.com/cleterrier/ChrisLUTs)
2. Allows one to make a colormap by specifying a name, whether it should be inverted, and the end-point color.
3. Allows for importing of ImageJ .lut files (both ascii and binary) and applying them to layers in napari.

Note: inverted LUTs are not yet supported for multichannel images in napari. Also, when you apply a colormap to an image, it will persist in the napari colormaps menu for the duration of the viewer (even with the widget closed).

This is a module that can be imported, for example:

import napari_line_profile_widget as linepro

and then permits:

line_plot = linepro.profile_line(<insert name of napari viewer>) 

This will add a shape layer with a red line and widget at the bottom of the Napari window. The widget will display a plot of the pixel instensities along the red line, as you move the red line or change z- or t-stack slice. The top most image layer will be used for the intensity data and the x-axis of the plot should be consistent with any scale data provided to napari. If you close and open a new image, move the line/change slice to update. You can also get a nice figure (6"x3", 300 dpi) of the current viewer status and the line profile:

linepro.get_figure(line_plot, <insert name of napari viewer>)

If you don't want the viewer status and just want the plot, pass screenshot=False The figure can be saved, for example as PDF:

linepro.get_figure(line_plot, <insert name of napari viewer>, name="test_profile.pdf")

This is a module that can be imported, for example:

import napari_measure_widget as nmw

and then permits:

nmw.measure_shape(<insert name of napari viewer>)

This will add a shape layer to the napari window and create a widget to display a table of results. By default, the key m will be bound to measuring:

• length of lines drawn with line or path tools
• angle between path segments, for the case of a path of two segments (3 points)
• area of shapes drawn with rectangle, polygon, or ellipse tools The last drawn shape will be measured, unless a shape is selected. The keybind can be changed, by passing a different keybind as a string. For example, to set the keybind to z:

nm.measure_shape(<insert name of napari viewer>, keybind="z")

By default, existing keybinds will not be overwritten. To overwrite an existing keybind (for example, if re-opening the widget), you must pass overwrite=True. The measurements will be displayed in a table in the widget. Make sure there is an open, visible image layer, so that the measurements can take into account any scale and unit information.

This module can be imported, for example:

import napari_scripts.Browse_LIF_widget as BL

it then can be used to open Napari with a LIF browser widget:

viewer = BL.lif_widget()

This Napari viewer will have a empty widget on the right, where you can drag-and-drop a LIF. Make sure you drop it on the side panel, not the main/middle Napari canvas Using aicsimageio, the widget will import the LIF and prepare a list of scenes. Clicking on a scene should load the chosen scene as an image layer. Note: the Image will have all MTCZYX channels, to permit browsing all types of scenes. The returned viewer can be used for other manipulations, such listing the selected scenes: viewer.layers