Construct sparse matrix from LinearMap (#17)

* Construct sparse matrix from LinearMap

* Add tests

* Build CSC directly, improve tests

Author: samuelpowell

src/LinearMaps.jl

@@ -88,6 +88,31 @@ function Base.full(A::LinearMap)
     return mat
 end
 
+# sparse: create sparse matrix representtion of LinearMap
+function Base.sparse(A::LinearMap)
+    M, N = size(A)
+    T = eltype(A)
+    rowind = Int[]
+    nzval = T[]
+    colptr = Vector{Int}(N+1)
+    v = zeros(T, N)
+
+    for i = 1:N
+        v[i] = one(T)
+        Lv = A*v
+        js = find(Lv)
+        colptr[i] = length(nzval)+1
+        if length(js) > 0
+            append!(rowind, js)
+            append!(nzval, Lv[js])
+        end
+        v[i] = zero(T)
+    end
+    colptr[N+1] = length(nzval)+1
+    
+    return SparseMatrixCSC(M, N, colptr, rowind, nzval)
+end
+
 include("transpose.jl") # transposing linear maps
 include("linearcombination.jl") # defining linear combinations of linear maps
 include("composition.jl") # composition of linear maps

test/runtests.jl

@@ -36,6 +36,14 @@ M = LinearMap(A)
 @test full(M') == A'
 @test full(M.') == A.'
 
+# test sparse conversions
+@test sparse(M) == sparse(full(M))
+
+B = copy(A)
+B[rand(1:length(A), 30)] = 0.
+MS = LinearMap(B)
+@test sparse(MS) == sparse(full(MS))
+
 # test function map
 F = LinearMap(cumsum,2)
 @test full(F) == [1. 0.;1. 1.]