Add new example that defines a custom materian and saves the output

.gitignore

@@ -10,4 +10,5 @@ Manifest.toml
 .DS_Store
 *.gif
 *.png
-docs/node_modules
+docs/node_modules
+*.npy

docs/Project.toml

@@ -14,11 +14,12 @@ Krang = "54806c32-d51a-438d-8447-e0041be2fbfb"
 Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
 MeshIO = "7269a6da-0436-5bbc-96c2-40638cbb6118"
+NPZ = "15e1cf62-19b3-5cfa-8e77-841668bca605"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [compat]
-Enzyme = "0.13"
+Enzyme = "0.13"

docs/make.jl

@@ -48,7 +48,6 @@ makedocs(;
         ],
         "api.md",
     ],
-    checkdocs=:none
 )
 
 deploydocs(;

docs/src/api.md

@@ -72,7 +72,6 @@ Krang.Mesh
 Krang.MeshGeometry
 Krang.ElectronSynchrotronPowerLawIntensity
 Krang.ElectronSynchrotronPowerLawPolarization
-Krang.UnionGeometry
 ```
 
 ### Pixel Related Functions

examples/Project.toml

@@ -12,6 +12,7 @@ JacobiElliptic = "2a8b799e-c098-4961-872a-356c768d184c"
 KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
 Krang = "54806c32-d51a-438d-8447-e0041be2fbfb"
 Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
+NPZ = "15e1cf62-19b3-5cfa-8e77-841668bca605"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"

examples/custom-material-example.jl

@@ -0,0 +1,84 @@
+# # Defining a Custom Material and Saving Output
+# We will define a redshift material for raytracing, and export the raytraced quantities to a .npy file.
+
+using Krang
+
+# Materials should be functors (i.e. types with callable objects).
+# Our material will raytrace the redshifts associated with a zero angular momentum observer (ZAMO) on a cone for a given sub-image.
+# If the cone is self obscuring, then only the redshift on the side that is closest to the observer will be raytraced.
+struct ZAMORedshifts{T} <: Krang.AbstractMaterial
+    n::Int
+    rmin::T
+    rmax::T
+end
+
+# Define the function for the material. 
+# This functor will take in a pixel and a geometry and return the redshift associated with a given sub image.
+# You must include the relevant physics in the functor definition. 
+# Here we will include redshift effects associated with a zero angular momentum observer (ZAMO).
+function (m::ZAMORedshifts)(pix::Krang.AbstractPixel, geometry::Krang.ConeGeometry{T,A}) where {T,A}
+
+    observation = zero(T)
+    α,β = Krang.screen_coordinate(pix)
+
+    θs = geometry.opening_angle
+    isindir = false
+    for _ in 1:2 
+        isindir ⊻= true
+        rs, νr, νθ, _, issuccess = emission_radius(pix, geometry.opening_angle, isindir, m.n)
+        if issuccess && m.rmin ≤ rs < m.rmax
+            ηtemp = η(metric, α, β, θo)
+            λtemp = λ(metric, α, θo)
+            curr_p_bl_d = p_bl_d(metric, rs, θs, ηtemp, λtemp, νr, νθ)
+
+            curr_p_bl_u = metric_uu(metric, rs, θs) * curr_p_bl_d
+            p_zamo_u = jac_zamo_u_bl_d(metric, rs, θs) * curr_p_bl_u
+            redshift = inv(p_zamo_u[1])
+
+            observation = max(redshift, eps(T))^(T(3))
+        end
+    end
+    return observation
+end
+
+# We will use a $0.94$ spin Kerr black hole viewed by an asymptotic observer at an inclination angle of $θo=17^\circ$. 
+# The emission to be raytraced is 
+metric = Krang.Kerr(0.99);
+θo = 17 * π / 180;
+ρmax = 15.0;
+rmin = Krang.horizon(metric); # minimum radius to truncate cone
+rmax = 10.0; # maximum radius to truncate cone
+n = 1; # sub-image to raytrace
+
+# Let's create a camera with a resolution of 400x400 pixels and our mesh.
+camera = Krang.IntensityCamera(metric, θo, -ρmax, ρmax, -ρmax, ρmax, 400);
+mesh = Krang.Mesh(Krang.ConeGeometry((75 * π / 180)), ZAMORedshifts(n, rmin, rmax))
+scene = Krang.Scene((mesh,))
+
+# Finally, we will render the scene with the camera and plot the redshifts.
+redshifts = render(camera, scene)
+
+import CairoMakie as CMk
+
+theme = CMk.Theme(
+    Axis = (
+        xticksvisible = false, 
+        xticklabelsvisible = false,
+        yticksvisible = false,
+        yticklabelsvisible = false,
+        ),
+)
+
+CMk.set_theme!(CMk.merge!(theme, CMk.theme_latexfonts()))
+
+fig = CMk.Figure(resolution=(700, 700));
+ax = CMk.Axis(fig[1, 1], title="Redshifts", titlesize=20, aspect=1)
+hm = CMk.heatmap!(ax, redshifts, colormap=:afmhot)
+CMk.Colorbar(fig[1, 2], hm, label="Redshifts", labelsize=20)
+CMk.save("redshifts.png", fig)
+
+# ![redshifts](redshifts.png)
+
+# Saving the redshifts to a .npy file
+using NPZ
+npzwrite("redshifts_n1.npy", redshifts)

examples/polarization-example.jl

@@ -63,9 +63,10 @@ geometry2 = Krang.ConeGeometry((π-θs))
 # We will create two meshes, one for each geometry anc create a scene with both meshes.
 mesh1 = Krang.Mesh(geometry1, material1)
 mesh2 = Krang.Mesh(geometry2, material2)
-scene = Krang.Scene((mesh1, mesh2))
 
 # Finally, we will render the scene with the camera and plot the Stokes parameters.
+
+scene = Krang.Scene((mesh1, mesh2))
 stokesvals = render(camera, scene)
 
 fig = Figure(resolution=(700, 700));
@@ -80,4 +81,4 @@ fig
 
 save("polarization_example.png", fig)
 
-# ![image](polarization_example.png)
+# ![polarization of emission model](polarization_example.png)