First of all, thank you for making napari - it’s become an instrumental piece of my image analysis workflow, and the fact that it’s so customisable makes the tool ever more amazing! So thanks again You’re enabling further cancer research
To the point; I currently use napari for viewing 2D image time series. In line with my idea of using napari for the curation of tracking data, I’ve added a matplotlib plot that represents the track length of each label, with label IDs on y axis & frame number in x axis. See below.
The main issue I have is that if I want to check the track for cell ID: 8, for example, the fact that I have two different colourmaps makes the whole process inefficient; because colours in plot & in the image are not the same, I have to hover on the labels layer rather randomly until I find the one of interest. In this case, cell 8 is red/pink in the plot but grey in the image.
How can generate a plot with the same colourmap as the label image? Is this possible?
Other things that I think would be nice to implement (plot-wise) but not sure how to:
- re-plot track lengths after some editing/curation; my idea here was calculate tracks & completely remove the widget (as I’m not sure if you can change the plot itself without removing it?) but the command
viewer.window.remove_dock_widget(mywidget)simply hides the plot-widget and doesn’t remove it. Any ideas?
- a vertical line showing current frame
- making the plot-widget responsive to user-clicks: clicking on a specific track on the plot would trigger a function that emphasizes the relevant label on the label_layer → this is only a dream though as I know it’s far fetched xD
Thanks in advance!