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Better schema declarations for array attributes that don't scale with coordinate arrays #1894
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A quick grep shows three things in plotly.js that depend on
So seems not tightly coupled within plotly.js. Does changing the field type affect the backend processing? On principle though, I think it'd be nice if |
Hi - this issue has been sitting for a while, so as part of our effort to tidy up our public repositories I'm going to close it. If it's still a concern, we'd be grateful if you could open a new issue (with a short reproducible example if appropriate) so that we can add it to our stack. Cheers - @gvwilson |
See #1891 for context.
At the moment,
axis.tickvals
,axis.ticktext
,axis.categoryarray
,colorbar.tickvals
andcolorbar.ticktext
are listed asvalType: 'data_array'
. This is causing issues forcolorbar.tickvals
andcolorbar.ticktext
as routines that use the output ofPlotSchema.findArrayAttributes
are expecting those data arrays to scale with the coordinate arrays.So, as @alexcjohnson points out, maybe we should tag these uncorrelated data arrays in the schema (e.g.
colorbar.tickvals
would haveuncorrelatedArray: true
) - which would be a lot more robust than the solution in aa93123But perhaps, we should make these attributes something else then
valType: 'data_array'
instead. For plotly.js, setting those attributes tovalType: 'info_array'
withfreeLength: true
would work, but that might break a few things downstream (e.g. the plotly workspace).Somewhat related: we should also think about correlated arrays mean for trace with 2D coordinate arrays, so that we can eventually extend
filter
andsort
transform to 2D data.The text was updated successfully, but these errors were encountered: