Decide on python/napari teaching style

[K-Meech]

Definition of done

We need to decide how much we focus on directly manipulating images with python (numpy / scikit-image) vs only using the napari user interface + plugins. We could:

• Use the napari bundled app, install plugins via app + do everything via the GUI (easy installation, but no python access)
• Use Jupyter notebooks, install napari + plugins via conda/python + mostly use plugins for analysis
• Use Jupyter notebooks, install napari + plugins via conda/python + mostly use numpy/scikit-image for analysis, with napari for visualisation

Another combination?

• Install napari + plugins via conda/python; Intro to images (numpy/Napari), Visualisation with Napari (GUI pixel values, ...), and a mix of Jupyter for data analysis from saved data (rather than direct interaction with Napari from Jupyter).

[davecash75]

@K-Meech If helpful, here are some previous attempts around talking about images: https://github.com/HealthBioscienceIDEAS/software_carpentry_september_2022/tree/main A few different branches are ahead of this one and might be relevant.

[K-Meech]

Just to add another option here - we could also use napari directly (installed via conda) + do any numpy/scikit-image calls directly from its built-in python console. This would save us having to introduce Jupyter notebooks and swapping back and forth between Jupyter and napari.

[davecash75]

Given that we already have the heavy documentation on sandpaper, this seems like a really nice approach to me.

[K-Meech]

I'm going to close this issue, as we've decided on using Napari directly + doing any python calls in its built-in console