Peter Brown comments

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                                            Peter Brown

Add option to export tracks overlayed on max-z projection for 3D time series data

Presumably this can be achieved by editing a few lines in `CaptureOverlayAction.java` ... easier said than done I'm sure

icons do not show up when starting napari with plugin from command line

Here is the output from `napari.sys_info()` ``` napari: 0.4.12 Platform: Windows-10-10.0.19041-SP0\nPython: 3.9.9 | packaged by conda-forge | (main, Dec 20 2021, 02:36:06) [MSC v.1929 64 bit (AMD64)] Qt: 5.12.9 PyQt5:...

icons do not show up when starting napari with plugin from command line

I updated napari, but this did not affect the behavior `napari.sys_info()` ``` napari: 0.4.13 Platform: Windows-10-10.0.19041-SP0 Python: 3.9.9 | packaged by conda-forge | (main, Dec 20 2021, 02:36:06) [MSC v.1929...

icons do not show up when starting napari with plugin from command line

I also verified this issue does not have anything to do with this plugin ... I get the same behavior with the `naprij` plugin. So I will open this issue...

icons do not show up when starting napari with plugin from command line

https://github.com/napari/napari/issues/4004

Proposal: Aim for an independent pymmcore-widgets package, use it here

@tlambert03 I think this would be great and could be very helpful for our use case. Maybe it is useful if I comment on what we are doing in the...

Proposal: Aim for an independent pymmcore-widgets package, use it here

@tlambert03 thanks for the suggestions! Right now my python devices do not have any notion of events, but that might be useful. Especially if I find myself in a situation...

Pixel oversampling when nxy is even produces asymmetric PSF

@tlambert03 - no worries, and yes just a suggestion for modification/improvement. This is an issue that took me a long time to track down, and still seems like unexpected behavior....

Error in PyDAQmx setup command: use_2to3 is invalid

I had the same issue, and this resolved the problem for me

feat: more efficient proximal total variation operator

@dpshepherd since it doesn't add any new dependencies and we don't have that many proximal operators, I am fine if it lives in `optimize.py`. And we can collapse `shrinkage()` and...