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Error plotting 1D dataset with Makie #412

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tomchor opened this issue Apr 11, 2023 · 7 comments
Closed

Error plotting 1D dataset with Makie #412

tomchor opened this issue Apr 11, 2023 · 7 comments

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@tomchor
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tomchor commented Apr 11, 2023 •
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In #389 I had thought a Makie recipe for 1D datasets was implemented, but at the moment it isn't working. For example the MWE used there:

using Downloads: download
url = "https://www.unidata.ucar.edu/software/netcdf/examples/tos_O1_2001-2002.nc";
filename = download(url, "tos_O1_2001-2002.nc");
A = Raster(filename)
lines(replace_missing(A[Y(Near(20.0)), Ti(1)], missingval=NaN)) # fails

Fails for me with

ERROR: MethodError: no method matching project(::StaticArraysCore.SMatrix{4, 4, Float32, 16}, ::Float32)
Closest candidates are:
  project(::StaticArraysCore.SMatrix{4, 4, Float32, 16}, ::Vec2, ::Point) at ~/.julia/packages/Makie/Iqcri/src/camera/projection_math.jl:300
  project(::StaticArraysCore.SMatrix{4, 4, Float32, 16}, ::T) where T<:(Union{Tuple{Vararg{T, N}}, StaticArraysCore.StaticArray{Tuple{N}, T, 1}} where {N, T}) at ~/.julia/packages/Makie/Iqcri/src/camera/projection_math.jl:294
  project(::StaticArraysCore.SMatrix{4, 4, Float32, 16}, ::T, ::Any) where T<:(Union{Tuple{Vararg{T, N}}, StaticArraysCore.StaticArray{Tuple{N}, T, 1}} where {N, T}) at ~/.julia/packages/Makie/Iqcri/src/camera/projection_math.jl:294
Stacktrace:
  [1] (::Makie.var"#756#757"{StaticArraysCore.SMatrix{4, 4, Float32, 16}, Symbol, typeof(identity)})(point::Float32)
    @ Makie ./none:0
  [2] iterate
    @ ./generator.jl:47 [inlined]
  [3] isempty
    @ ./essentials.jl:788 [inlined]
  [4] limits_from_transformed_points(points_iterator::Base.Generator{Vector{Float32}, Makie.var"#756#757"{StaticArraysCore.SMatrix{4, 4, Float32, 16}, Symbol, typeof(identity)}})
    @ Makie ~/.julia/packages/Makie/Iqcri/src/layouting/data_limits.jl:188
  [5] data_limits(plot::Lines{Tuple{Vector{Float32}, Tuple{Vector{Float64}}}})
    @ Makie ~/.julia/packages/Makie/Iqcri/src/layouting/data_limits.jl:171
  [6] (::Makie.var"#763#765"{Makie.var"#762#764", Base.RefValue{GeometryBasics.HyperRectangle{3, Float32}}})(plot::Lines{Tuple{Vector{Float32}, Tuple{Vector{Float64}}}})
    @ Makie ~/.julia/packages/Makie/Iqcri/src/layouting/data_limits.jl:198
  [7] foreach(f::Makie.var"#763#765"{Makie.var"#762#764", Base.RefValue{GeometryBasics.HyperRectangle{3, Float32}}}, itr::Vector{AbstractPlot})
    @ Base ./abstractarray.jl:2774
  [8] foreach_plot
    @ ~/.julia/packages/Makie/Iqcri/src/layouting/data_limits.jl:109 [inlined]
  [9] foreach_plot
    @ ~/.julia/packages/Makie/Iqcri/src/layouting/data_limits.jl:103 [inlined]
 [10] data_limits
    @ ~/.julia/packages/Makie/Iqcri/src/layouting/data_limits.jl:196 [inlined]
 [11] data_limits
    @ ~/.julia/packages/Makie/Iqcri/src/layouting/data_limits.jl:195 [inlined]
 [12] is2d
    @ ~/.julia/packages/Makie/Iqcri/src/scenes.jl:590 [inlined]
 [13] plot(P::Type{Lines}, args::Raster{Float32, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{Y{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}, EPSG, EPSG, Y{Colon}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{DateTime360Day, Vector{DateTime360Day}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{DateTime360Day}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}}}}, Vector{Float32}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}, Float32}; axis::NamedTuple{(), Tuple{}}, figure::NamedTuple{(), Tuple{}}, kw_attributes::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ Makie ~/.julia/packages/Makie/Iqcri/src/figureplotting.jl:49
 [14] plot
    @ ~/.julia/packages/Makie/Iqcri/src/figureplotting.jl:31 [inlined]
 [15] #lines#31
    @ ~/.julia/packages/MakieCore/6sckc/src/recipes.jl:34 [inlined]
 [16] lines(args::Raster{Float32, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{Y{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}, EPSG, EPSG, Y{Colon}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{DateTime360Day, Vector{DateTime360Day}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{DateTime360Day}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}}}}, Vector{Float32}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{String, Any}}, Float32})
    @ MakieCore ~/.julia/packages/MakieCore/6sckc/src/recipes.jl:33
 [17] top-level scope
    @ REPL[107]:1
 [18] top-level scope
    @ ~/.julia/packages/CUDA/BbliS/src/initialization.jl:52

and the same error appears anytime I need to plot any 1D dataset of my own.

Am I missing something here?

cc @asinghvi17

PS: I'm using Rasters v0.5.3
@rafaqz
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rafaqz commented Apr 21, 2023

I have no idea how these fallbacks work in Makie.jl

But this is more like something we should define in DimensionalData.jl recipes as it's not really a spatial problem but a general one.

@tomchor
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tomchor commented Apr 21, 2023

I agree, it's a general plotting issue, but it was at some point working in #389, no? That's why I posted it here.

Feel free to close this if you think it's not within the package scope to fix it here.

@rafaqz
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rafaqz commented Apr 21, 2023 •
edited
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I have no idea I thought that was mostly for heatmaps. @asinghvi17 ?

@tomchor
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tomchor commented May 4, 2023

@asinghvi17 was #433 supposed to fix this issue?

I ask because I'm still getting errors on main:

julia> using Rasters

julia> using GLMakie

julia> using Downloads: download

julia> url = "https://www.unidata.ucar.edu/software/netcdf/examples/tos_O1_2001-2002.nc";

julia> filename = download(url, "tos_O1_2001-2002.nc");

julia> A = Raster(filename)
[ Info: No `name` or `key` keyword provided, using first valid layer with name `:tos`
180×170×24 Raster{Union{Missing, Float32},3} tos with dimensions: 
  X Mapped{Float64} Float64[1.0, 3.0, …, 357.0, 359.0] ForwardOrdered Explicit Intervals crs: EPSG mappedcrs: EPSG,
  Y Mapped{Float64} Float64[-79.5, -78.5, …, 88.5, 89.5] ForwardOrdered Explicit Intervals crs: EPSG mappedcrs: EPSG,
  Ti Sampled{CFTime.DateTime360Day} CFTime.DateTime360Day[CFTime.DateTime360Day(2001-01-16T00:00:00), …, CFTime.DateTime360Day(2002-12-16T00:00:00)] ForwardOrdered Explicit Intervals
extent: Extent(X = (-0.0, 360.0), Y = (-80.0, 90.0), Ti = (CFTime.DateTime360Day(2001-01-01T00:00:00), CFTime.DateTime360Day(2003-01-01T00:00:00)))
missingval: missing
crs: EPSG:4326
mappedcrs: EPSG:4326
parent:
[:, :, 1]
        -79.5       -78.5       -77.5       -76.5       -75.5       -74.5       -73.5       …   81.5        82.5        83.5        84.5     85.5     86.5     87.5     88.5     89.5
   1.0     missing     missing     missing     missing     missing     missing     missing     271.42      271.419     271.42      271.422  271.426  271.43   271.437  271.445  271.459
   3.0     missing     missing     missing     missing     missing     missing     missing     271.42      271.419     271.42      271.422  271.426  271.431  271.438  271.445  271.459
   5.0     missing     missing     missing     missing     missing     missing     missing     271.42      271.418     271.42      271.422  271.425  271.431  271.438  271.445  271.459
   7.0     missing     missing     missing     missing     missing     missing     missing     271.42      271.417     271.419     271.421  271.425  271.431  271.439  271.446  271.459
   9.0     missing     missing     missing     missing     missing     missing     missing  …  271.419     271.415     271.418     271.421  271.425  271.431  271.439  271.446  271.459
  11.0     missing     missing     missing     missing     missing     missing     missing     271.415     271.414     271.417     271.421  271.424  271.431  271.44   271.447  271.459
  13.0     missing     missing     missing     missing     missing     missing     missing     271.411     271.411     271.417     271.421  271.424  271.431  271.44   271.447  271.459
  15.0     missing     missing     missing     missing     missing     missing     missing     271.409     271.41      271.416     271.421  271.424  271.432  271.441  271.447  271.459
  17.0     missing     missing     missing     missing     missing     missing     missing     271.409     271.409     271.416     271.422  271.424  271.432  271.441  271.448  271.459
  19.0     missing     missing     missing     missing     missing     missing     missing  …  271.408     271.408     271.417     271.422  271.425  271.433  271.441  271.448  271.459
  21.0     missing     missing     missing     missing     missing     missing     missing     271.406     271.408     271.417     271.422  271.426  271.433  271.442  271.449  271.459
  23.0     missing     missing     missing     missing     missing     missing     missing     271.405     271.408     271.417     271.422  271.428  271.434  271.443  271.449  271.459
  25.0     missing     missing     missing     missing     missing     missing     missing     271.404     271.408     271.416     271.421  271.429  271.434  271.443  271.45   271.459
  27.0     missing     missing     missing     missing     missing     missing     missing     271.405     271.407     271.416     271.421  271.43   271.435  271.444  271.45   271.459
  29.0     missing     missing     missing     missing     missing     missing     missing  …  271.404     271.407     271.416     271.421  271.431  271.437  271.445  271.451  271.459
  31.0     missing     missing     missing     missing     missing     missing     missing     271.401     271.406     271.416     271.421  271.432  271.438  271.446  271.451  271.459
   ⋮                                                      ⋮                                 ⋱                ⋮                                                  ⋮               
 329.0     missing     missing     missing  271.252     271.297     273.015     273.751           missing     missing     missing  271.43   271.427  271.428  271.435  271.445  271.459
 331.0     missing     missing     missing  271.26      271.305     273.014     273.877     …     missing     missing     missing  271.43   271.428  271.429  271.435  271.445  271.459
 333.0     missing     missing     missing     missing  271.305     272.948     274.052           missing     missing     missing  271.43   271.428  271.429  271.434  271.445  271.459
 335.0     missing     missing     missing     missing     missing  273.114     274.334           missing     missing  271.425     271.43   271.428  271.429  271.434  271.445  271.459
 337.0     missing     missing     missing     missing     missing  273.735     274.699           missing     missing  271.425     271.429  271.428  271.429  271.433  271.445  271.459
 339.0     missing     missing     missing     missing     missing     missing  274.972           missing     missing  271.425     271.428  271.428  271.429  271.433  271.445  271.459
 341.0     missing     missing     missing     missing     missing     missing  275.205     …     missing  271.422     271.425     271.427  271.428  271.429  271.433  271.445  271.459
 343.0     missing     missing     missing     missing     missing     missing     missing        missing  271.422     271.425     271.426  271.427  271.43   271.434  271.445  271.459
 345.0     missing     missing     missing     missing     missing     missing     missing     271.419     271.422     271.424     271.426  271.427  271.43   271.434  271.445  271.459
 347.0     missing     missing     missing     missing     missing     missing     missing     271.419     271.422     271.423     271.425  271.427  271.43   271.434  271.445  271.459
 349.0     missing     missing     missing     missing     missing     missing     missing     271.418     271.421     271.423     271.424  271.427  271.43   271.435  271.445  271.459
 351.0     missing     missing     missing     missing     missing     missing     missing  …  271.418     271.421     271.422     271.424  271.426  271.43   271.435  271.445  271.459
 353.0     missing     missing     missing     missing     missing     missing     missing     271.419     271.421     271.421     271.423  271.426  271.43   271.436  271.445  271.459
 355.0     missing     missing     missing     missing     missing     missing     missing     271.42      271.42      271.421     271.423  271.426  271.43   271.436  271.445  271.459
 357.0     missing     missing     missing     missing     missing     missing     missing     271.42      271.42      271.421     271.423  271.426  271.43   271.437  271.445  271.459
 359.0     missing     missing     missing     missing     missing     missing     missing     271.42      271.42      271.42      271.423  271.426  271.43   271.437  271.445  271.459
[and 23 more slices...]

julia> lines(replace_missing(A[Y(Near(20.0)), Ti(1)], missingval=NaN)) # fails
ERROR: `Makie.convert_arguments` for the plot type Lines{Tuple{Raster{Float64, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{Y{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, Y{Colon}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{CFTime.DateTime360Day, Vector{CFTime.DateTime360Day}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{CFTime.DateTime360Day}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}}}}, Vector{Float64}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, Float64}}} and its conversion trait PointBased() was unsuccessful.

The signature that could not be converted was:
::Raster{Float32, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{}, Vector{Float32}, Symbol, DimensionalData.Dimensions.LookupArrays.NoMetadata, Missing}

Makie needs to convert all plot input arguments to types that can be consumed by the backends (typically Arrays with Float32 elements).
You can define a method for `Makie.convert_arguments` (a type recipe) for these types or their supertypes to make this set of arguments convertible (See http://docs.makie.org/stable/documentation/recipes/index.html).

Alternatively, you can define `Makie.convert_single_argument` for single arguments which have types that are unknown to Makie but which can be converted to known types and fed back to the conversion pipeline.

Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:35
  [2] convert_arguments(T::Type{Lines{Tuple{Raster{Float64, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{Y{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, Y{Colon}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{CFTime.DateTime360Day, Vector{CFTime.DateTime360Day}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{CFTime.DateTime360Day}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}}}}, Vector{Float64}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, Float64}}}}, args::Raster{Float32, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{}, Vector{Float32}, Symbol, DimensionalData.Dimensions.LookupArrays.NoMetadata, Missing}; kw::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ Makie ~/.julia/packages/Makie/Iqcri/src/conversions.jl:17
  [3] convert_arguments(T::Type{Lines{Tuple{Raster{Float64, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{Y{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, Y{Colon}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{CFTime.DateTime360Day, Vector{CFTime.DateTime360Day}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{CFTime.DateTime360Day}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}}}}, Vector{Float64}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, Float64}}}}, args::Raster{Float32, 1, Tuple{X{Mapped{Float64, Vector{Float64}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Explicit{Matrix{Float64}}, DimensionalData.Dimensions.LookupArrays.Intervals{DimensionalData.Dimensions.LookupArrays.Center}, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDsource, Dict{String, Any}}, EPSG, EPSG, X{Colon}}}}, Tuple{}, Vector{Float32}, Symbol, DimensionalData.Dimensions.LookupArrays.NoMetadata, Missing})
    @ Makie ~/.julia/packages/Makie/Iqcri/src/conversions.jl:7

@rafaqz
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rafaqz commented May 4, 2023

Ah damn. We will have to set up proper CI with Makie to test all of this properly.

Its just a big overhead in the already long test time here to also compile e.g. CairoMakie.jl and make multiple plots in every CI run.

@asinghvi17
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Not necessarily...we could theoretically just test that the conversion pipelines are working. For this I'll install Rasters master and see what needs to be done...

@felixcremer
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This produces the following plot now and I think, that this can therefore be closed.
rasters_412

@rafaqz rafaqz closed this as completed Oct 25, 2023
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@rafaqz @tomchor @felixcremer @asinghvi17