Comments (2)
Next step would be to understand a bit better how AXIS_indices
works; how the axis dataset is structured and mapped; how to deal with various uses/misuses of AXIS_indices
; etc. The feature seems very broad, so we need to define the scope a bit better.
from h5web.
I've renamed this issue to focus on the underlying use case, which is basically to support stacks of scatter plots.
For context, currently, the following code is used to decide that an NXdata
group supports the NX Scatter
visualization:
axisDatasets.length === 2 && axisDatasets.every((d) => d && hasNumDims(d, 1))
... which basically means that the @axes
attribute must declare exactly two 1D datasets (e.g. ["X", "Y"]
where both X
and Y
have only one dimension).
This works great for simple 1D cases (cf. /nexus_entry/scatter
in demo) but the complexity increases drastically when dealing with nD signals and axes. This is what the AXIS_indices
convention was trying to address, but it doesn't help viewers like H5Web understand how the data is really meant to be plotted.
Where we go from here is still an open question. We considered relaxing the condition above to cover more strictly defined cases, but this would add yet another implicit convention, which does not seem like the right way forward.
@loichuder (and others) suggested introducing an attribute called SILX_scatter
(in line with the existing SILX_style
attribute) to allow describing scatter plots explicitly, which could take the following shape:
{
"x": "A0", // dataset to use as X coordinates
"y": "A1", // dataset to use as Y coordinates
"slice": [0] // dimension(s) on which the user should be able to slice
}
from h5web.
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