Improved error rates further on error_benchmark.jl

Author: shivin9

src/derivative_operators/convolutions.jl

@@ -37,13 +37,14 @@ function convolve_BC_left!(x_temp::AbstractVector{T}, x::AbstractVector{T}, A::D
     coeff   = A.coefficients
 
     _bpc = A.boundary_point_count
-
+    flag = false
     if stencil == []
         _bpc = A.boundary_point_count + 1
+        flag = true
     end
 
     for i in 1 : _bpc
-        if _bpc == 1
+        if flag == true
             cur_stencil = A.stencil_coefs
             slen = length(A.stencil_coefs)
         else
@@ -68,31 +69,34 @@ function convolve_BC_right!(x_temp::AbstractVector{T}, x::AbstractVector{T}, A::
     L       = A.boundary_stencil_length
 
     _bpc = A.boundary_point_count
+    flag = false
 
     if stencil == []
         _bpc = 1
+        flag = true
     end
 
     for i in 1 : _bpc
-        if _bpc == 1
+        # @show _bpc
+        if flag == true
             cur_stencil = A.stencil_coefs
             slen = length(A.stencil_coefs)
             L = A.stencil_length
         else
-            cur_stencil = stencil[i]
+            cur_stencil = stencil[end-i+1]
             slen = length(cur_stencil)
         end
 
         cur_coeff   = typeof(coeff)   <: AbstractVector ? coeff[i] : coeff isa Number ? coeff : true
         cur_stencil = use_winding(A) && cur_coeff < 0 ? reverse(cur_stencil) : cur_stencil
-        # cs = cur_stencil*(A.dx^A.derivative_order)
+        cs = cur_stencil*(A.dx^A.derivative_order)
         xtempi = zero(T)
         for idx in 1:slen
             # @show idx, N-L+idx, cs[idx], x[N-L+idx]
             xtempi += cur_coeff * cur_stencil[idx] * x[N-L+idx]
         end
         # @show xtempi*(1/(A.dx^A.derivative_order))
-        x_temp[end-_bpc+i] = xtempi
+        x_temp[end-i+1] = xtempi
     end
 end
 
@@ -130,13 +134,15 @@ function convolve_BC_left!(x_temp::AbstractVector{T}, _x::BoundaryPaddedVector,
     coeff   = A.coefficients
 
     _bpc = A.boundary_point_count
+    flag = false
 
     if stencil == []
         _bpc = 1
+        flag = true
     end
 
     for i in 1 : _bpc
-        if _bpc == 1
+        if flag == true
             cur_stencil = A.stencil_coefs
             slen = length(A.stencil_coefs)
         else
@@ -185,20 +191,22 @@ function convolve_BC_right!(x_temp::AbstractVector{T}, _x::BoundaryPaddedVector,
 
 
     _bpc = A.boundary_point_count
+    flag = false
 
     if stencil == []
         _bpc = 1
         L = A.stencil_length
+        flag = true
     end
 
     bc_start = N - _bpc + 1
 
     for i in 1 : _bpc
-        if _bpc == 1
+        if flag == true
             cur_stencil = A.stencil_coefs
             slen = length(A.stencil_coefs)
         else
-            cur_stencil = stencil[i]
+            cur_stencil = stencil[end-i+1]
             slen = length(cur_stencil)
         end
 
@@ -214,6 +222,6 @@ function convolve_BC_right!(x_temp::AbstractVector{T}, _x::BoundaryPaddedVector,
         #     xtempi += cur_coeff * cur_stencil[idx] * _x.u[end-L+idx+1]
         # end
 
-        x_temp[bc_start + i - 1] = xtempi
+        x_temp[N-i+1] = xtempi
     end
 end

test/bc_coeff_compositions.jl

@@ -6,8 +6,8 @@ function fourth_deriv_approx_stencil(N)
     A[1,1:8] = [3.5 -56/3 42.5 -54.0 251/6 -20.0 5.5 -2/3]
     A[2,1:8] = [2/3 -11/6 0.0 31/6 -22/3 4.5 -4/3 1/6]
 
-    A[N-1,N-5:end] = reverse([3.5 -56/3 42.5 -54.0 251/6 -20.0 5.5 -2/3], dims=2)
-    A[N,N-5:end] = reverse([2/3 -11/6 0.0 31/6 -22/3 4.5 -4/3 1/6], dims=2)
+    A[N-1,N-5:end] = reverse([2/3 -11/6 0.0 31/6 -22/3 4.5 -4/3 1/6], dims=2)
+    A[N,N-5:end] = reverse([3.5 -56/3 42.5 -54.0 251/6 -20.0 5.5 -2/3], dims=2)
 
     for i in 3:N-2
         A[i,i-2:i+4] = [-1/6 2.0 -13/2 28/3 -13/2 2.0 -1/6]

test/derivative_operators_interface.jl

@@ -1,14 +1,6 @@
 using SparseArrays, DiffEqOperators, LinearAlgebra, Random,
       Test, BandedMatrices, FillArrays
 
-function second_derivative_stencil(N)
-  A = zeros(N,N+2)
-  for i in 1:N, j in 1:N+2
-      (j-i==0 || j-i==2) && (A[i,j]=1)
-      j-i==1 && (A[i,j]=-2)
-  end
-  A
-end
 
 # Analytic solutions to higher order operators.
 # Do not modify unless you are completely certain of the changes.
@@ -39,7 +31,16 @@ function second_deriv_fourth_approx_stencil(N)
     return A
 end
 
+function second_derivative_stencil(N)
+  A = zeros(N,N+2)
+  for i in 1:N, j in 1:N+2
+      (j-i==0 || j-i==2) && (A[i,j]=1)
+      j-i==1 && (A[i,j]=-2)
+  end
+  A
+end
 
+# Broken?
 function convert_by_multiplication(::Type{Array}, A::AbstractDerivativeOperator{T}, N::Int=A.dimension) where T
     @assert N >= A.stencil_length # stencil must be able to fit in the matrix
     mat = zeros(T, (N, N+2))

test/differentiation_dimension.jl

@@ -4,8 +4,8 @@ function fourth_deriv_approx_stencil(N)
     A = zeros(N,N+2)
     A[1,1:8] = [3.5 -56/3 42.5 -54.0 251/6 -20.0 5.5 -2/3]
     A[2,1:8] = [2/3 -11/6 0.0 31/6 -22/3 4.5 -4/3 1/6]
-    A[N-1,N-5:end] = reverse([2/3 -11/6 0.0 31/6 -22/3 4.5 -4/3 1/6], dims=2)
-    A[N,N-5:end] = reverse([3.5 -56/3 42.5 -54.0 251/6 -20.0 5.5 -2/3], dims=2)
+    A[N-1,N-5:end] = reverse([3.5 -56/3 42.5 -54.0 251/6 -20.0 5.5 -2/3], dims=2)
+    A[N,N-5:end] = reverse([2/3 -11/6 0.0 31/6 -22/3 4.5 -4/3 1/6], dims=2)
     for i in 3:N-2
         A[i,i-2:i+4] = [-1/6 2.0 -13/2 28/3 -13/2 2.0 -1/6]
     end