Fixes for Julia 0.5

- FormalPowerSeries tests take into account indexing changes in 0.5
- blasfunc in 0.4 is now @blasfunc in 0.5
- replace 1:length(v) with eachindex(v) in for loops

Author: jiahao

src/FormalPowerSeries.jl

@@ -22,7 +22,7 @@ type FormalPowerSeries{Coefficients}
   FormalPowerSeries{Coefficients}(c::Dict{BigInt, Coefficients}) = new(c)
   function FormalPowerSeries{Coefficients}(v::Vector{Coefficients})
     c=Dict{BigInt, Coefficients}()
-    for i=1:length(v)
+    for i in eachindex(v)
       if v[i] != 0
         c[i-1] = v[i] #Note this off by 1 - allows constant term c[0] to be set
       end
@@ -37,10 +37,10 @@ zero{T}(P::FormalPowerSeries{T}) = FormalPowerSeries(T[])
 one{T}(P::FormalPowerSeries{T}) = FormalPowerSeries(T[1])
 
 #Return truncated vector with c[i] = P[n[i]]
-function tovector{T,Index<:Integer}(P::FormalPowerSeries{T}, n :: AbstractVector{Index})
+function tovector{T,Index<:Integer}(P::FormalPowerSeries{T}, n::AbstractVector{Index})
   nn = length(n)
   c = zeros(nn)
-  for (k,v) in P.c, i=1:nn
+  for (k,v) in P.c, i in eachindex(n)
       n[i]==k && (c[i]=v)
   end
   c

src/HaarMeasure.jl

@@ -65,19 +65,31 @@ end
 #Zyczkowski and Kus, Random unitary matrices, J. Phys. A: Math. Gen. 27,
 #4235–4245 (1994).
 
-### Stewarts algorithm for n^2 orthogonal random matrix
 using Base.LinAlg: BlasInt
 for (s, elty) in (("dlarfg_", Float64),
                   ("zlarfg_", Complex128))
-    @eval begin
-        function larfg!(n::Int, α::Ptr{$elty}, x::Ptr{$elty}, incx::Int, τ::Ptr{$elty})
-            ccall(($(Base.blasfunc(s)), Base.liblapack_name), Void,
-                (Ptr{BlasInt}, Ptr{$elty}, Ptr{$elty}, Ptr{BlasInt}, Ptr{$elty}),
-                &n, α, x, &incx, τ)
+    if Base.VERSION < v"0.5-"
+	@eval begin
+            function larfg!(n::Int, α::Ptr{$elty}, x::Ptr{$elty}, incx::Int, τ::Ptr{$elty})
+		ccall(($(Base.blasfunc(s)), Base.liblapack_name), Void,
+		    (Ptr{BlasInt}, Ptr{$elty}, Ptr{$elty}, Ptr{BlasInt}, Ptr{$elty}),
+                    &n, α, x, &incx, τ)
+            end
+        end
+    else
+	@eval begin
+            function larfg!(n::Int, α::Ptr{$elty}, x::Ptr{$elty}, incx::Int, τ::Ptr{$elty})
+		ccall(($(Base.@blasfunc(s)), Base.liblapack_name), Void,
+		    (Ptr{BlasInt}, Ptr{$elty}, Ptr{$elty}, Ptr{BlasInt}, Ptr{$elty}),
+                    &n, α, x, &incx, τ)
+            end
         end
     end
 end
 
+"""
+Stewarts algorithm for n^2 orthogonal random matrix
+"""
 function Stewart(::Type{Float64}, n)
     τ = Array(Float64, n)
     H = randn(n, n)

test/FormalPowerSeries.jl

@@ -1,6 +1,8 @@
 using RandomMatrices
 using Base.Test
 
+srand(4)
+
 # Excursions in formal power series (fps)
 MaxSeriesSize=8
 MaxRange = 20
@@ -49,7 +51,11 @@ end
 #of the original series
 #Force reciprocal to exist
 X.c[0] = 1
-discrepancy = (norm(inv(float(MatrixForm(X,c)))[1, :]'[:, 1] - tovector(reciprocal(X, c), 0:c-1)))
+discrepancy = if Base.VERSION < v"0.5-"
+    (norm(inv(float(MatrixForm(X,c)))[1, :]'[:, 1] - tovector(reciprocal(X, c), 0:c-1)))
+else
+    (norm(inv(float(MatrixForm(X,c)))[1, :][:, 1] - tovector(reciprocal(X, c), 0:c-1)))
+end
 tol = c*√eps()
 if discrepancy > tol
     error(string("Error ", discrepancy, " exceeds tolerance ", tol))