Change the Implimentation of CSRMatrix to us SparseMatrixCSC (#101)

* This changes the implementation of CSRMatrix to include the additional value at the end of row_pointers that signifies the end of that row

Remove Depreciation  add sparse conversion

Small Fix

Change CSRMatrix to Adjoint{Sparse}}

Cleanup

Cleanup comments

Comment cleanup

cleanup

Changed Adjoint to Transpose

Rebase to no CI for julia v 0.6 (#1)

* Update appveyor.yml

remove testing for v0.6 add v1.1

* Update .travis.yml

drop testing for v0.6 add v1.1

* change require to julia 0.7

* This changes the implementation of CSRMatrix to include the additional value at the end of row_pointers that signifies the end of that row

* Remove Depreciation  add sparse conversion

* Small Fix

* Change CSRMatrix to Adjoint{Sparse}}

* Cleanup

* Cleanup comments

* Comment cleanup

* cleanup

* Changed Adjoint to Transpose

Remove commented lines
Fix Collect statement
drop v0.7

* spelling

src/constraints.jl

@@ -160,31 +160,29 @@ end
 """
     CSRMatrix{T}
 
-Matrix given in compressed sparse row (CSR) format.
-
-`CSRMatrix` is analgous to the structure in Julia's `SparseMatrixCSC` but with
-the rows and columns flipped. It contains three vectors:
- - `row_pointers` is a vector pointing to the start of each row in
-    `columns` and `coefficients`;
- - `columns` is a vector of column numbers; and
- - `coefficients` is a vector of corresponding nonzero values.
+Type alias for `Transpose{T,SparseMatrixCSC{T,Int}} where T`, which allows for the
+    efficient storage of compressed sparse row (CSR) sparse matrix
+
+Please use the following interface to access this data in case model is changed in future
+ - `row_pointers(mat)` returns that sparse row_pointer vector see description
+    which has a length of rows+1
+ - `colvals` this is the column version of `rowvals(SparseMatrixCSC)`
+ - `row_nonzeros` this is the equivilent to `nonzeros(SparseMatrixCSC)`
+"""
 
-The length of `row_pointers` is the number of rows in the matrix.
+const CSRMatrix{T} = Transpose{T,SparseMatrixCSC{T,Int}} where T
 
-This struct is not a subtype of `AbstractSparseMatrix` as it is intended to be a
-collection of the three vectors as they are required by solvers such as Gurobi.
-It is not intended to be used for general computation.
-"""
-struct CSRMatrix{T}
-    row_pointers::Vector{Int}
-    columns::Vector{Int}
-    coefficients::Vector{T}
-    function CSRMatrix{T}(row_pointers, columns, coefficients) where T
-        @assert length(columns) == length(coefficients)
-        new(row_pointers, columns, coefficients)
-    end
+function CSRMatrix{T}(row_pointers, columns, coefficients) where T
+    @assert length(columns) == length(coefficients)
+    @assert length(columns) + 1 == row_pointers[end]
+    transpose(SparseMatrixCSC{T,Int}(maximum(columns), length(row_pointers)-1, row_pointers, columns, coefficients))
 end
 
+#   Move access to an interface so that if we want to change type definition we can.
+colvals(mat::CSRMatrix) = rowvals(transpose(mat))
+row_pointers(mat::CSRMatrix) = transpose(mat).colptr  # This is the only way to get at colptrs without recreating it
+row_nonzeros(mat::CSRMatrix) = nonzeros(transpose(mat))
+
 #=
     Below we add constraints.
 =#

src/constraints/scalaraffine.jl

@@ -35,7 +35,7 @@ end
 function add_linear_constraint(model::LinQuadOptimizer, func::Linear, set::IV)
     columns = [get_column(model, term.variable_index) for term in func.terms]
     coefficients = [term.coefficient for term in func.terms]
-    A = CSRMatrix{Float64}([1], columns, coefficients)
+    A = CSRMatrix{Float64}([1, length(coefficients) + 1], columns, coefficients)
     add_ranged_constraints!(model, A, [set.lower], [set.upper])
 end
 
@@ -45,7 +45,7 @@ function add_linear_constraint(model::LinQuadOptimizer, func::Linear, sense, rhs
     end
     columns = [get_column(model, term.variable_index) for term in func.terms]
     coefficients = [term.coefficient for term in func.terms]
-    A = CSRMatrix{Float64}([1], columns, coefficients)
+    A = CSRMatrix{Float64}([1, length(coefficients) + 1], columns, coefficients)
     add_linear_constraints!(model, A, [sense], [rhs - func.constant])
 end
 
@@ -99,7 +99,7 @@ function functions_to_CSRMatrix(model::LinQuadOptimizer, functions::Vector{Linea
     # row (i - 1), storing the result in r[i]. Then we perform a cumsum on r,
     # storing the result back in r.
     num_rows = length(functions)
-    row_pointers = fill(0, num_rows)
+    row_pointers = fill(0, num_rows+1)
     row_pointers[1] = 1
     non_zero_index = 0
     for (row, func) in enumerate(functions)
@@ -117,6 +117,7 @@ function functions_to_CSRMatrix(model::LinQuadOptimizer, functions::Vector{Linea
         end
     end
     cumsum!(row_pointers, row_pointers)
+    row_pointers[end] = length(coefficients)+1
     return CSRMatrix{Float64}(row_pointers, columns, coefficients)
 end
 

src/constraints/vectoraffine.jl

@@ -41,7 +41,7 @@ function add_linear_constraint(model::LinQuadOptimizer, func::VecLin, sense::Cch
     # row (i - 1), storing the result in r[i]. Then we perform a cumsum on r,
     # storing the result back in r.
     num_rows = length(func.constants)
-    row_pointers = fill(0, num_rows)
+    row_pointers = fill(0, num_rows+1)
     row_pointers[1] = 1
     for term in func.terms
         row = term.output_index
@@ -53,7 +53,7 @@ function add_linear_constraint(model::LinQuadOptimizer, func::VecLin, sense::Cch
         end
     end
     cumsum!(row_pointers, row_pointers)
-
+    row_pointers[end]=length(coefficients)+1
     A = CSRMatrix{Float64}(row_pointers, columns, coefficients)
     add_linear_constraints!(model, A, fill(sense, num_rows), -func.constants)
 end

src/constraints/vectorofvariables.jl

@@ -21,7 +21,7 @@ function MOI.add_constraint(model::LinQuadOptimizer, func::VecVar, set::S) where
     rows = get_number_linear_constraints(model)
     num_vars = MOI.dimension(set)
     add_linear_constraints!(model,
-        CSRMatrix{Float64}(collect(1:num_vars),
+        CSRMatrix{Float64}(collect(1:num_vars+1),
                            get_column.(Ref(model), func.variables),
                            ones(num_vars)),
         fill(backend_type(model, set), num_vars),

src/mockoptimizer.jl

@@ -403,11 +403,10 @@ function LQOI.add_linear_constraints!(instance::MockLinQuadOptimizer, A::CSRMatr
     # quadind
     append!(instance.l_rows,addedrows)
 
-    rowvec, colvec, coefvec = A.row_pointers, A.columns, A.coefficients
+    rowvec, colvec, coefvec = row_pointers(A), colvals(A), row_nonzeros(A)
 
     rows = length(rhsvec)
     cols = size(instance.inner.A)[2]
-    push!(rowvec,length(colvec)+1)
 
     An = Array(SparseMatrixCSC(cols,rows,rowvec,colvec,coefvec)')
 
@@ -430,13 +429,10 @@ function LQOI.add_ranged_constraints!(instance::MockLinQuadOptimizer, A::CSRMatr
     # quadind
     append!(instance.l_rows,addedrows)
 
-    rowvec, colvec, coefvec = A.row_pointers, A.columns, A.coefficients
+    rowvec, colvec, coefvec = row_pointers(A), colvals(A), row_nonzeros(A)
     rows = length(lowerbound)
     cols = size(instance.inner.A)[2]
-    push!(rowvec,length(colvec)+1)
 
-    # An = Array(sparse(rowvec,colvec,coefvec,rows,cols))
-    # @show cols,rows,rowvec,colvec,coefvec
     An = Array(SparseMatrixCSC(cols,rows,rowvec,colvec,coefvec)')
 
     instance.inner.A = vcat(instance.inner.A,An)