remove csparse functions

The functions and tests for these function have been moved to the
package SuiteSparse.jl in the JuliaSparse organization.

Author: KristofferC

LICENSE.md

@@ -65,7 +65,6 @@ their own licenses:
 The following components of Julia's standard library have separate licenses:
 
 - base/fftw.jl (see [FFTW](http://fftw.org/doc/License-and-Copyright.html))
-- base/sparse/csparse.jl (LGPL-2.1+)
 - base/linalg/umfpack.jl (see [SUITESPARSE](http://faculty.cse.tamu.edu/davis/suitesparse.html))
 - base/linalg/cholmod.jl (see [SUITESPARSE](http://faculty.cse.tamu.edu/davis/suitesparse.html))
 

base/sparse.jl

@@ -36,7 +36,6 @@ export AbstractSparseArray, AbstractSparseMatrix, AbstractSparseVector,
 include("sparse/abstractsparse.jl")
 include("sparse/sparsematrix.jl")
 include("sparse/sparsevector.jl")
-include("sparse/csparse.jl")
 
 include("sparse/linalg.jl")
 if Base.USE_GPL_LIBS
@@ -45,4 +44,37 @@ if Base.USE_GPL_LIBS
     include("sparse/spqr.jl")
 end
 
+# point users to SuiteSparse
+const SUITESPARSE_END_ERR_SRING = string(" has been moved to the package SuiteSparse.jl.\n",
+          "Run Pkg.add(\"SuiteSparse\") to install SuiteSparse on Julia v0.5-")
+
+"""
+    etree(A[, post])
+Compute the elimination tree of a symmetric sparse matrix `A` from `triu(A)`
+and, optionally, its post-ordering permutation.
+
+Note: This function has been moved to the SuiteSparse.jl package.
+"""
+etree{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, postorder::Bool) =
+    error("etree(A[, post])", SUITESPARSE_END_ERR_SRING)
+etree(A::SparseMatrixCSC) = etree(A, false)
+
+ereach{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, k::Integer, parent::Vector{Ti}) =
+    error("ereach(A, k, parent)", SUITESPARSE_END_ERR_SRING)
+
+csc_permute{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, pinv::Vector{Ti}, q::Vector{Ti})=
+    error("csc_permute(A, pinv, q)", SUITESPARSE_END_ERR_SRING)
+
+"""
+    symperm(A, p)
+Return the symmetric permutation of `A`, which is `A[p,p]`. `A` should be
+symmetric, sparse, and only contain nonzeros in the upper triangular part of the
+matrix is stored. This algorithm ignores the lower triangular part of the
+matrix. Only the upper triangular part of the result is returned.
+
+Note: This function has been moved to the SuiteSparse.jl package.
+"""
+symperm{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, pinv::Vector{Ti}) =
+    error("symperm(A, pinv)", SuiteSparse_END_ERR_SRING)
+
 end

base/sparse/csparse.jl

@@ -34,7 +34,6 @@ const skipfiles = [
     # files to check - already copyright
     # see: https://github.com/JuliaLang/julia/pull/11073#issuecomment-98099389
     "../base/special/trig.jl",
-    "../base/sparse/csparse.jl",
     "../base/linalg/givens.jl",
     #
     "../src/abi_llvm.cpp",

contrib/add_license_to_files.jl

@@ -227,7 +227,7 @@ Constructors
 
    .. Docstring generated from Julia source
 
-   Create an array with the same data as the given array, but with different dimensions. An implementation for a particular type of array may choose whether the data is copied or shared.
+   Create an array with the same data as the given array, but with different dimensions.
 
 .. function:: similar(array, [element_type=eltype(array)], [dims=size(array)])
 
@@ -971,12 +971,16 @@ dense counterparts. The following functions are specific to sparse arrays.
 
    Compute the elimination tree of a symmetric sparse matrix ``A`` from ``triu(A)`` and, optionally, its post-ordering permutation.
 
+   Note: This function has been moved to the SuiteSparse.jl package.
+
 .. function:: symperm(A, p)
 
    .. Docstring generated from Julia source
 
    Return the symmetric permutation of ``A``\ , which is ``A[p,p]``\ . ``A`` should be symmetric, sparse, and only contain nonzeros in the upper triangular part of the matrix is stored. This algorithm ignores the lower triangular part of the matrix. Only the upper triangular part of the result is returned.
 
+   Note: This function has been moved to the SuiteSparse.jl package.
+
 .. function:: nonzeros(A)
 
    .. Docstring generated from Julia source

doc/stdlib/arrays.rst

@@ -343,20 +343,6 @@ end
 @test full(spdiagm((ones(2), ones(2)), (0, -1), 3, 3)) ==
                        [1.0  0.0  0.0; 1.0  1.0  0.0;  0.0  1.0  0.0]
 
-# elimination tree
-## upper triangle of the pattern test matrix from Figure 4.2 of
-## "Direct Methods for Sparse Linear Systems" by Tim Davis, SIAM, 2006
-rowval = Int32[1,2,2,3,4,5,1,4,6,1,7,2,5,8,6,9,3,4,6,8,10,3,5,7,8,10,11]
-colval = Int32[1,2,3,3,4,5,6,6,6,7,7,8,8,8,9,9,10,10,10,10,10,11,11,11,11,11,11]
-A = sparse(rowval, colval, ones(length(rowval)))
-p = etree(A)
-P,post = etree(A, true)
-@test P == p
-@test P == Int32[6,3,8,6,8,7,9,10,10,11,0]
-@test post == Int32[2,3,5,8,1,4,6,7,9,10,11]
-@test isperm(post)
-
-
 # issue #4986, reinterpret
 sfe22 = speye(Float64, 2)
 mfe22 = eye(Float64, 2)
@@ -1019,13 +1005,9 @@ A = sparse(tril(rand(5,5)))
 @test istril(A)
 @test !istril(sparse(ones(5,5)))
 
-# symperm
-srand(1234321)
-A = triu(sprand(10,10,0.2))       # symperm operates on upper triangle
-perm = randperm(10)
-@test symperm(A,perm).colptr == [1,1,2,4,5,5,6,8,8,9,10]
-
 # droptol
+srand(1234321)
+A = triu(sprand(10,10,0.2))
 @test Base.droptol!(A,0.01).colptr == [1,1,1,2,2,3,4,6,6,7,9]
 @test isequal(Base.droptol!(sparse([1], [1], [1]), 1), SparseMatrixCSC(1,1,Int[1,1],Int[],Int[]))
 
@@ -1224,12 +1206,6 @@ if Base.USE_GPL_LIBS
 end
 @test_throws DimensionMismatch Base.SparseArrays.normestinv(sprand(3,5,.9))
 
-# csc_permute
-A = sprand(10,10,0.2)
-p = randperm(10)
-q = randperm(10)
-@test Base.SparseArrays.csc_permute(A, invperm(p), q) == full(A)[p, q]
-
 # issue #13008
 @test_throws ArgumentError sparse(collect(1:100), collect(1:100), fill(5,100), 5, 5)
 @test_throws ArgumentError sparse(Int[], collect(1:5), collect(1:5))