Merge pull request #484 from JuliaDataCubes/la/aog

aog documentation

docs/Project.toml

@@ -1,7 +1,7 @@
 [deps]
+AlgebraOfGraphics = "cbdf2221-f076-402e-a563-3d30da359d67"
 ArchGDAL = "c9ce4bd3-c3d5-55b8-8973-c0e20141b8c3"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
-Bonito = "824d6782-a2ef-11e9-3a09-e5662e0c26f8"
 CFTime = "179af706-886a-5703-950a-314cd64e0468"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
@@ -27,7 +27,6 @@ PlotUtils = "995b91a9-d308-5afd-9ec6-746e21dbc043"
 SkipNan = "aed68c70-c8b0-4309-8cd1-d392a74f991a"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 TimeSeries = "9e3dc215-6440-5c97-bce1-76c03772f85e"
-WGLMakie = "276b4fcb-3e11-5398-bf8b-a0c2d153d008"
 WeightedOnlineStats = "bbac0a1f-7c9d-5672-960b-c6ca726e5d5d"
 YAXArrayBase = "90b8fcef-0c2d-428d-9c56-5f86629e9d14"
 YAXArrays = "c21b50f5-aa40-41ea-b809-c0f5e47bfa5c"

docs/src/UserGuide/group.md

@@ -65,8 +65,11 @@ end
 ````
 :::
 
-> [!IMPORTANT]
-> In what follows, note how we are referencing the _time_ dimension via _YAX.time_. This approach is used to avoid name clashes with _time_ (_Time_) from **Base** (**Dates**). For convenience, we have defined the **Dimensions** _time_ and _Time_ in **YAXArrays.jl**, which are only accessible when explicitly called.
+::: info
+
+In what follows, note how we are referencing the time dimension via `YAX.time`. This approach is used to avoid name clashes with `time` (`Time`) from **Base** (**Dates**). For convenience, we have defined the **Dimensions** `time` and `Time` in **YAXArrays.jl**, which are only accessible when explicitly called.
+
+:::
 
 Now, we continue with the `groupby` operations as usual
 

docs/src/tutorials/plottingmaps.md

@@ -29,9 +29,9 @@ nothing # hide
 use lookup to get axis values
 
 ````@example plots
-lon = lookup(ct1_slice, :lon)
-lat = lookup(ct1_slice, :lat)
-data = ct1_slice.data[:,:];
+lon_d = lookup(ct1_slice, :lon)
+lat_d = lookup(ct1_slice, :lat)
+data_d = ct1_slice.data[:,:];
 nothing # hide
 ````
 
@@ -50,9 +50,9 @@ fig
 Some transformations
 
 ````@example plots
-δlon = (lon[2]-lon[1])/2
-nlon = lon .- 180 .+ δlon
-ndata = circshift(data, (192,1))
+δlon = (lon_d[2] - lon_d[1])/2
+nlon = lon_d .- 180 .+ δlon
+ndata = circshift(data_d, (192,1))
 nothing # hide
 ````
 
@@ -61,7 +61,7 @@ and add Coastlines with `GeoMakie.coastlines()`,
 ````@example plots
 fig = Figure(;size=(1200,600))
 ax = GeoAxis(fig[1,1])
-surface!(ax, nlon, lat, ndata; colormap = :seaborn_icefire_gradient, shading=false)
+surface!(ax, nlon, lat_d, ndata; colormap = :seaborn_icefire_gradient, shading=false)
 cl=lines!(ax, GeoMakie.coastlines(), color = :white, linewidth=0.85)
 translate!(cl, 0, 0, 1000)
 fig
@@ -71,20 +71,18 @@ fig
 ````@example plots
 fig = Figure(; size=(1200,600))
 ax = GeoAxis(fig[1,1]; dest = "+proj=moll")
-surface!(ax, nlon, lat, ndata; colormap = :seaborn_icefire_gradient, shading=false)
+surface!(ax, nlon, lat_d, ndata; colormap = :seaborn_icefire_gradient, shading=false)
 cl=lines!(ax, GeoMakie.coastlines(), color = :white, linewidth=0.85)
 translate!(cl, 0, 0, 1000)
 fig
 ````
 
 ## 3D sphere plot
 
-````julia
-using Bonito, WGLMakie
-Page(exportable=true, offline=true)
-
-WGLMakie.activate!()
-Makie.inline!(true) # Make sure to inline plots into Documenter output!
+````@example plots
+using GLMakie
+using GLMakie.GeometryBasics
+GLMakie.activate!()
 
 ds = replace(ndata, missing =>NaN)
 sphere = uv_normal_mesh(Tesselation(Sphere(Point3f(0), 1), 128))
@@ -98,4 +96,127 @@ rotate!(ax.scene, 2.5)
 fig
 ````
 
+## AlgebraOfGraphics.jl
+
+::: info
+
+From [DimensionalData docs](https://rafaqz.github.io/DimensionalData.jl/stable/plots#algebraofgraphics-jl) :
+
+**AlgebraOfGraphics.jl** is a high-level plotting library built on top of `Makie.jl` that provides a declarative algebra for creating complex visualizations, similar to **ggplot2**'s "grammar of graphics" in R. It allows you to construct plots using algebraic operations like `*` and `+`, making it easy to create sophisticated graphics with minimal code.
+
+:::
+
+
+````@example AoG
+using YAXArrays, Zarr, Dates
+using GLMakie
+using AlgebraOfGraphics
+using GLMakie.GeometryBasics
+GLMakie.activate!()
+````
+
+let's continue using the cmip6 dataset
+
+````@example AoG
+store ="gs://cmip6/CMIP6/ScenarioMIP/DKRZ/MPI-ESM1-2-HR/ssp585/r1i1p1f1/3hr/tas/gn/v20190710/"
+g = open_dataset(zopen(store, consolidated=true))
+c = g["tas"];
+nothing # hide
+````
+
+and let's focus on the first time step:
+
+````@example AoG
+dim_data = readcubedata(c[time=1]); # read into memory first!
+nothing # hide
+````
+
+and now plot
+
+````@example AoG
+data(dim_data) * mapping(:lon, :lat; color=:value) * visual(Scatter) |> draw
+````
+
+::: warning
+
+Note that we are using a `Scatter` type per point and not the `Heatmap` one. There are workarounds for this, albeit cumbersome, so for now, let's keep this simpler syntax in mind along with the current approach being used.
+
+:::
+
+set other attributes
+
+````@example AoG
+plt = data(dim_data) * mapping(:lon, :lat; color=:value)
+draw(plt * visual(Scatter, marker=:rect), scales(Color = (; colormap = :plasma));
+    axis = (width = 600, height = 400, limits=(0, 360, -90, 90)))
+````
+
+### Faceting
+
+For this let's consider more time steps from our dataset:
+
+````@example AoG
+using Dates
+dim_time = c[time=DateTime("2015-01-01") .. DateTime("2015-01-01T21:00:00")] # subset 7 t steps
+````
+
+````@example AoG
+dim_time = readcubedata(dim_time); # read into memory first!
+nothing # hide
+````
+
+````@example AoG
+plt = data(dim_time) * mapping(:lon, :lat; color = :value, layout = :time => nonnumeric)
+draw(plt * visual(Scatter, marker=:rect))
+````
+
+again, let's add some additional attributes
+
+````@example AoG
+plt = data(dim_time) * mapping(:lon, :lat; color = :value, layout = :time => nonnumeric)
+draw(plt * visual(Scatter, marker=:rect), scales(Color = (; colormap = :magma));
+    axis = (; limits=(0, 360, -90, 90)),
+    figure=(; size=(900,600)))
+````
+
+most [Makie plot functions](https://docs.makie.org/stable/reference/plots/overview) should work. See `lines` for example
+
+````@example AoG
+plt = data(dim_data[lon=50..100]) * mapping(:lat, :value => "tas"; color=:value => "tas")
+draw(plt * visual(Lines); figure=(; size=(650,400)))
+````
+
+or faceting them
+
+````@example AoG
+plt = data(dim_data[lon=50..59]) * mapping(:lat, :value => "tas"; color=:value => "tas",
+    layout = :lon => nonnumeric)
+draw(plt * visual(Lines); figure=(; size=(650,400)))
+````
+### Time series
+
+For this, let's load a little bit more of time steps
+
+````@example AoG
+dim_series = c[time=DateTime("2015-01-01") .. DateTime("2015-01-04"), lon = 150 .. 157, lat = 0..1] |> readcubedata
+````
+
+and plot
+
+````@example AoG
+plt = data(dim_series) * mapping(:time, :value => "tas"; color=:lon => nonnumeric)
+draw(plt * visual(ScatterLines), scales(Color = (; palette = :tableau_colorblind));
+    figure=(; size=(800,400)))
+````
+
+### Analysis
+
+Basic statistical [analysis](https://aog.makie.org/stable/generated/analyses/) can also be done, for example:
+
+````@example AoG
+specs = data(dim_data[lat=50..55]) * mapping(:lon, :value => "tas"; color=:lat => nonnumeric)
+specs *= (smooth() + visual(Scatter))
+draw(specs;  figure=(; size=(700,400)))
+````
 
+For more, visit [AlgebraOfGraphics.jl](https://aog.makie.org/stable/).