trial support of plotting in examples in docs

Author: MikaelSlevinsky

docs/Project.toml

@@ -1,7 +1,11 @@
 [deps]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 FastTransforms = "057dd010-8810-581a-b7be-e3fc3b93f78c"
+GR = "28b8d3ca-fb5f-59d9-8090-bfdbd6d07a71"
 Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
+PlotlyJS = "f0f68f2c-4968-5e81-91da-67840de0976a"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
 
 [compat]
 Documenter = "~0.24"

docs/make.jl

@@ -20,7 +20,7 @@ end
 
 makedocs(
             doctest = false,
-            format = Documenter.HTML(),
+            format = Documenter.HTML(assets = [asset("https://cdn.plot.ly/plotly-1.54.7.js")]),
             sitename = "FastTransforms.jl",
             authors = "Richard Mikael Slevinsky",
             pages = Any[

examples/disk.jl

@@ -19,13 +19,13 @@
 # For the storage pattern of the arrays, please consult the
 # [documentation](https://MikaelSlevinsky.github.io/FastTransforms).
 
-using FastTransforms, LinearAlgebra
+using FastTransforms, LinearAlgebra, Plots
 
 # Our function $f$ on the disk:
 f = (x,y) -> (x^2-y^2+1)/((x^2-y^2+1)^2+(2x*y+1)^2)
 
 # The Zernike polynomial degree:
-N = 5
+N = 20
 M = 4N-3
 
 # The radial grid:
@@ -37,6 +37,29 @@ r = [sinpi((N-n-0.5)/(2N)) for n in 0:N-1]
 # On the mapped tensor product grid, our function samples are:
 F = [f(r*cospi(θ), r*sinpi(θ)) for r in r, θ in θ]
 
+# We superpose the grid on top of a contour plot of $f$:
+X = [r*cospi(θ) for r in r, θ in θ]
+Y = [r*sinpi(θ) for r in r, θ in θ]
+
+# PyPlot
+pyplot()
+contourf(X, Y, F; levels=30, linewidth=2, xlabel="x", ylabel="y")
+scatter!(X, Y; legend=false, markercolor=:red, size=(600, 600))
+
+# bis
+scatter3d(vec(X), vec(Y), vec(0X); markersize=2.0, markercolor=:red, size=(600, 600))
+surface!(X, Y, F; legend=false, xlabel="x", ylabel="y")
+
+# PlotlyJS
+plotlyjs()
+scatter3d(vec(X), vec(Y), vec(0X); markersize=0.5, markercolor=:red, size=(600, 600))
+surface!(X, Y, F; legend=false, xlabel="x", ylabel="y")
+
+# GR
+gr()
+scatter3d(vec(X), vec(Y), vec(0X); markersize=0.5, markercolor=:red, size=(600, 600))
+surface!(vec(X), vec(Y), vec(F); legend=false, xlabel="x", ylabel="y")
+
 # We precompute a (generalized) Zernike--Chebyshev×Fourier plan:
 α, β = 0, 0
 P = plan_disk2cxf(F, α, β)
@@ -85,6 +108,29 @@ z = [sinpi((M-2m-1)/(2M)) for m in 0:M-1]
 # On the mapped tensor product grid, our function samples are:
 F = [f(x[n], w[n]*z) for n in 1:N, z in z]
 
+# We superpose the grid on top of a contour plot of $f$:
+X = [x for x in x, z in z]
+Y = [w*z for w in w, z in z]
+
+# PyPlot
+pyplot()
+contourf(X, Y, F; levels=30, linewidth=2, xlabel="x", ylabel="y")
+scatter!(X, Y; legend=false, markercolor=:green, size=(600, 600))
+
+# bis
+scatter3d(vec(X), vec(Y), vec(0X); markersize=2.0, markercolor=:green, size=(600, 600))
+surface!(X, Y, F; legend=false, xlabel="x", ylabel="y")
+
+# PlotlyJS
+plotlyjs()
+scatter3d(vec(X), vec(Y), vec(0X); markersize=0.5, markercolor=:green, size=(600, 600))
+surface!(X, Y, F; legend=false, xlabel="x", ylabel="y")
+
+# GR
+gr()
+scatter3d(vec(X), vec(Y), vec(0X); markersize=0.5, markercolor=:green, size=(600, 600))
+surface!(vec(X), vec(Y), vec(F); legend=false, xlabel="x", ylabel="y")
+
 # We precompute a Dunkl-Xu--Chebyshev plan:
 P = plan_rectdisk2cheb(F, β)