new file: src/pivot.jl

README.md

@@ -56,6 +56,8 @@ permkron(p,q) # kronecker product of list permutations, induced by m
 cyc_pow_perm(c,n) # nth power of c returned in array representation
 m=permtomat(p,flag) # permutation matrix, sparse if flag is true
 mattoperm(m) # array representation of permutation (abstract) matrix m
+ipiv2perm(v,[n]) # convert pivot vector to permutation in list form
+perm2piv(p) # convert p to pivot vector
 isperm(m) # true if matrix m is a permutation
 isperm(c) # true if c is a permutation
 Base.isperm(p) # already present in Base module

src/PermPlain.jl

@@ -731,5 +731,6 @@ cyclestring(xs...) = pprint_to_string(cycleprint, x...)
 
 
 include("matrixops.jl")
+include("pivot.jl")
 
 end # module Permplain

src/pivot.jl

@@ -0,0 +1,34 @@
+# Copied from linalg/lu.jl
+function ipiv2perm{T}(v::AbstractVector{T}, maxi::Integer)
+ p = T[1:maxi]
+ @inbounds for i in 1:length(v)
+ p[i], p[v[i]] = p[v[i]], p[i]
+ end
+ return p
+end
+
+function ipiv2perm{T}(v::AbstractVector{T})
+ ipiv2perm(v,length(v))
+end
+
+
+# A naive algorithm, maybe there exists a faster one.
+# Build the pivot while permuting 1:n. Make
+# inverse perm at the same time, so we know where to
+# find p[i]
+function perm2ipiv{T}(p::AbstractVector{T})
+ n = length(p)
+ m = [1:n]
+ v = similar(m)
+ x = copy(m)
+ @inbounds for i in 1:n
+ j = x[p[i]]
+ mi = m[i]
+ mj = m[j]
+ m[i],m[j] = mj,mi
+ v[i] = j
+ x[mj] = i
+ x[mi] = j
+ end
+ return v
+end

src/util.jl

@@ -1,3 +1,5 @@
+# turns out that this is not needed,
+# Julia has multiple parallel assignment
 macro swap!(p,q)
  return quote
  begin