Refactor variogram files

src/nesting.jl

@@ -26,51 +26,15 @@ end
 
 NestedVariogram(cs, γs) = NestedVariogram{typeof(cs),typeof(γs)}(cs, γs)
 
-(g::NestedVariogram)(h) = raw(sum(g.cs .* map(γ -> γ(h), g.γs)))
-(g::NestedVariogram)(u::Point, v::Point) = raw(sum(g.cs .* map(γ -> γ(u, v), g.γs)))
+isstationary(γ::NestedVariogram) = all(isstationary, γ.γs)
 
-sill(g::NestedVariogram) = raw(sum(g.cs .* map(sill, g.γs)))
-nugget(g::NestedVariogram) = raw(sum(g.cs .* map(nugget, g.γs)))
-Base.range(g::NestedVariogram) = maximum(range(γ) for γ in g.γs)
-isstationary(g::NestedVariogram) = all(isstationary, g.γs)
-isisotropic(g::NestedVariogram) = all(isisotropic, g.γs)
+isisotropic(γ::NestedVariogram) = all(isisotropic, γ.γs)
 
-# algebraic structure
-*(c, γ::Variogram) = NestedVariogram((c,), (γ,))
-*(c, γ::NestedVariogram) = NestedVariogram(map(x -> c .* x, γ.cs), γ.γs)
-+(γ₁::Variogram, γ₂::Variogram) = NestedVariogram((1, 1), (γ₁, γ₂))
-+(γ₁::NestedVariogram, γ₂::Variogram) = NestedVariogram((γ₁.cs..., 1), (γ₁.γs..., γ₂))
-+(γ₁::Variogram, γ₂::NestedVariogram) = NestedVariogram((1, γ₂.cs...), (γ₁, γ₂.γs...))
-+(γ₁::NestedVariogram, γ₂::NestedVariogram) = NestedVariogram((γ₁.cs..., γ₂.cs...), (γ₁.γs..., γ₂.γs...))
-
-"""
-    structures(γ)
+sill(γ::NestedVariogram) = raw(sum(γ.cs .* map(sill, γ.γs)))
 
-Return the individual structures of a (possibly nested)
-variogram as a tuple. The structures are the total nugget
-`cₒ`, and the coefficients (or contributions) `c[i]` for the
-remaining non-trivial structures `g[i]` after normalization
-(i.e. sill=1, nugget=0).
+nugget(γ::NestedVariogram) = raw(sum(γ.cs .* map(nugget, γ.γs)))
 
-## Examples
-
-```julia
-γ₁ = GaussianVariogram(nugget=1, sill=2)
-γ₂ = SphericalVariogram(nugget=2, sill=3)
-
-γ = 2γ₁ + 3γ₂
-
-cₒ, c, g = structures(γ)
-```
-"""
-function structures(γ::Variogram)
-  cₒ = nugget(γ)
-  c = sill(γ) - nugget(γ)
-  T = typeof(c)
-  γ = @set γ.sill = one(T)
-  γ = @set γ.nugget = zero(T)
-  cₒ, (c,), (γ,)
-end
+Base.range(γ::NestedVariogram) = maximum(range(g) for g in γ.γs)
 
 function structures(γ::NestedVariogram)
   ks, gs = γ.cs, γ.γs
@@ -93,6 +57,17 @@ function structures(γ::NestedVariogram)
   cₒ, cs, γs
 end
 
+(γ::NestedVariogram)(h) = raw(sum(γ.cs .* map(g -> g(h), γ.γs)))
+(γ::NestedVariogram)(u::Point, v::Point) = raw(sum(γ.cs .* map(g -> g(u, v), γ.γs)))
+
+# algebraic structure
+*(c, γ::Variogram) = NestedVariogram((c,), (γ,))
+*(c, γ::NestedVariogram) = NestedVariogram(map(x -> c .* x, γ.cs), γ.γs)
++(γ₁::Variogram, γ₂::Variogram) = NestedVariogram((1, 1), (γ₁, γ₂))
++(γ₁::NestedVariogram, γ₂::Variogram) = NestedVariogram((γ₁.cs..., 1), (γ₁.γs..., γ₂))
++(γ₁::Variogram, γ₂::NestedVariogram) = NestedVariogram((1, γ₂.cs...), (γ₁, γ₂.γs...))
++(γ₁::NestedVariogram, γ₂::NestedVariogram) = NestedVariogram((γ₁.cs..., γ₂.cs...), (γ₁.γs..., γ₂.γs...))
+
 # -----------
 # IO METHODS
 # -----------

src/variogram.jl

@@ -9,6 +9,27 @@ A theoretical variogram model (e.g. Gaussian variogram).
 """
 abstract type Variogram end
 
+"""
+    variotype(γ)
+
+Return the type constructor of the variogram `γ`.
+"""
+function variotype end
+
+"""
+    isstationary(γ)
+
+Check if variogram `γ` possesses the 2nd-order stationary property.
+"""
+isstationary(γ::Variogram) = isstationary(typeof(γ))
+
+"""
+    isisotropic(γ)
+
+Tells whether or not variogram `γ` is isotropic.
+"""
+isisotropic(γ::Variogram) = isisotropic(γ.ball)
+
 """
     sill(γ)
 
@@ -38,11 +59,33 @@ Return the maximum range of the variogram `γ`.
 Base.range(γ::Variogram) = maximum(radii(γ.ball))
 
 """
-    variotype(γ)
+    structures(γ)
 
-Return the type constructor of the variogram `γ`.
+Return the individual structures of a (possibly nested)
+variogram as a tuple. The structures are the total nugget
+`cₒ`, and the coefficients (or contributions) `c[i]` for the
+remaining non-trivial structures `g[i]` after normalization
+(i.e. sill=1, nugget=0).
+
+## Examples
+
+```julia
+γ₁ = GaussianVariogram(nugget=1, sill=2)
+γ₂ = SphericalVariogram(nugget=2, sill=3)
+
+γ = 2γ₁ + 3γ₂
+
+cₒ, c, g = structures(γ)
+```
 """
-function variotype end
+function structures(γ::Variogram)
+  cₒ = nugget(γ)
+  c = sill(γ) - nugget(γ)
+  T = typeof(c)
+  γ = @set γ.sill = one(T)
+  γ = @set γ.nugget = zero(T)
+  cₒ, (c,), (γ,)
+end
 
 """
     γ(u, v)
@@ -85,27 +128,6 @@ function (γ::Variogram)(U::Geometry, V::Geometry)
   mean(γ(u, v) for u in us, v in vs)
 end
 
-"""
-    returntype(γ, u, v)
-
-Return result type of γ(u, v).
-"""
-returntype(γ::Variogram, u, v) = typeof(γ(u, v))
-
-"""
-    isstationary(γ)
-
-Check if variogram `γ` possesses the 2nd-order stationary property.
-"""
-isstationary(γ::Variogram) = isstationary(typeof(γ))
-
-"""
-    isisotropic(γ)
-
-Tells whether or not variogram `γ` is isotropic.
-"""
-isisotropic(γ::Variogram) = isisotropic(γ.ball)
-
 """
     pairwise(γ, domain)
 
@@ -167,6 +189,23 @@ function pairwise!(Γ, γ::Variogram, domain₁, domain₂)
   Γ
 end
 
+"""
+    returntype(γ, u, v)
+
+Return type of γ(u, v).
+"""
+returntype(γ::Variogram, u, v) = typeof(γ(u, v))
+
+"""
+    scale(γ, s)
+
+Scale ranges of variogram `γ` with strictly positive scaling factor `s`.
+"""
+function scale(γ::Variogram, s::Real)
+  V = variotype(γ)
+  V(s * metricball(γ); sill=sill(γ), nugget=nugget(γ))
+end
+
 # -----------
 # IO METHODS
 # -----------