Comments (7)
I think, you could define your own Makie.data_limits
as a work around for now!
E.g. like this:
function Makie.data_limits(p::ScaledImage)
edges = Point2f.(p[1][], p[2][]) # Get edges, pseudo code, needs to be 4 edges
scaled_points = # scale the points
return limits_from_transformed_points(scaled_points )
end
from makie.jl.
Hi @SimonDanisch, I was using the limits_from_transformed_points
function, but it seems to have disappeared in newer versions of Makie.jl. What would be the alternative to this function?
from makie.jl.
boundingbox(plot)
would be the best replacement.
from makie.jl.
Like this?
function Makie.data_limits(plot::ScaledImage)
return boundingbox(plot)
end
from makie.jl.
Most likely - but you may not need it at all in 0.21 with the changes to boundongbox computation
from makie.jl.
data_limits(plot) = boundingbox(plot)
goes against what data_limits is supposed to do and it will break when transform functions are involved. I would also consider this an Axis bug now
from makie.jl.
Actually this isn't even an issue right now. We're including model in an incorrect way atm (which I thought would be the same as pre 0.21), so for the opening example I do get the correct scaling. What's missing is the tight spacing that you get from Makie.needs_tight_limits(::ScaledImage) = true
, but that's expected.
Another issue you can run into atm is that the root plot's model matrix is considered here, not the ones of each children. so if you scale the image plot instead of the ScaledImage
it won't work.
from makie.jl.
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from makie.jl.