bluesky
WIP: Support slices like '3:10:mean(2)'
Closes #32
As proposed in #32, this will support:
- Reducing an N-dimensional array to an array of lower dimension by averaging over one or more dimensions. For example, average an image time series like
?slice=::mean - Downsamplig an N-dimensional array over some axes. For example, downsampling an image time series by a factor of 2 in x and y:
?slice=:,::mean(2),::mean(2)
The downsampling with employ local averaging as in https://scikit-image.org/docs/stable/api/skimage.transform.html#downscale-local-mean
Incidentally this removes the use of eval or client input, which I like. it was technically safe because it was guarded by regex, but it still made me nervous.
This would be extremely helpful for my igor Tiled client, where viewing downsampled images is really important - saving client memory and working with slower internet speeds. It also will allow for trivial data reduction for already resampled data. Essentially I will be able to construct a URL for users to pull valid 1D scattering curves from 2D datasets.
This related project shows another way to spell this which I think I like better:
Leave the slice syntax as is, taking standard numpy-style slices. Add an optional query parameter downsample_method. Its default value can be stride but it can accept other values mean, max, min….
https://google.github.io/tensorstore/driver/downsample/index.html
It occurred to me later downsample_method as implemented there assumes we are using the same downsample method for all axes, whereas the original approach we considered here, ?slice=:,::mean(2),::mean(2), supports a more general case of different downsample methods on different axes.
I suppose we could combine the two and support:
?downsample_method=mean # same on all axes
?downsample_method=mean,mean,max # different for each axis
but that creates a dependency with the value of slice that seems a bit odd...I might be back to preferring our original plan.