Use a weighting metric that isn't based on app. spectral radius

Author: ranjanan

src/multilevel.jl

@@ -88,7 +88,7 @@ function solve{T}(ml::MultiLevel, b::Vector{T},
         push!(residuals, T(norm(b - A * x)))
     end
 
-    @show residuals
+    # @show residuals
     if log
         return x, residuals
     else

src/smoother.jl

@@ -100,11 +100,13 @@ end
 
 struct DiagonalWeighting
 end
+struct LocalWeighting
+end
 
 function smooth_prolongator(j::JacobiProlongation,
                                         A, T, S, B,
                                         degree = 1,
-                                        weighting = DiagonalWeighting())
+                                        weighting = LocalWeighting())
     D_inv_S = weight(weighting, A, j.ω)
     P = T
     for i = 1:degree
@@ -120,6 +122,13 @@ function weight(::DiagonalWeighting, S, ω)
     # (ω) * D_inv_S
 end
 
+function weight(::LocalWeighting, S, ω)
+    D = abs.(S) * ones(size(S, 1))
+    D_inv = 1 ./ D[find(D)]
+    D_inv_S = scale_rows(S, D_inv)
+    eltype(S)(ω) * D_inv_S
+end
+
 #approximate_spectral_radius(A) =
 #    eigs(A, maxiter = 15, tol = 0.01, ritzvec = false)[1][1] |> real