Merge branch 'master' into develop

Project.toml

@@ -1,6 +1,6 @@
 name = "COBRA"
 uuid = "58298e0b-d05c-52ec-a210-0694647ebfc7"
-version = "0.4.2"
+version = "0.4.1"
 
 [deps]
 CPLEX = "a076750e-1247-5638-91d2-ce28b192dca0"

src/COBRA.jl

@@ -18,7 +18,7 @@ module COBRA
     # include the load file to load a model of .mat format
     import Pkg
     using SparseArrays, Distributed, LinearAlgebra
-    using MAT, JuMP
+    using MAT, MathOptInterface, JuMP
     using MATLAB
 
     include("checkSetup.jl")

src/distributedFBA.jl

@@ -75,7 +75,7 @@ function preFBA!(model, solver, optPercentage::Float64=0.0, osenseStr::String="m
 
         # solve the original LP problem
         status, objval, sol = solveCobraLP(model, solver)
-        
+
         if status == MathOptInterface.TerminationStatusCode(1)
             # retrieve the solution to the initial LP
             FBAobj = objval
@@ -124,7 +124,6 @@ function preFBA!(model, solver, optPercentage::Float64=0.0, osenseStr::String="m
     end
 
 end
-
 #-------------------------------------------------------------------------------------------
 """
     splitRange(model, rxnsList, nWorkers, strategy, printLevel)

src/solve.jl

@@ -6,6 +6,7 @@
 =#
 
 #-------------------------------------------------------------------------------------------
+
 """
     SolverConfig(name, handle)
 
@@ -22,6 +23,86 @@ mutable struct SolverConfig
 end
 
 #-------------------------------------------------------------------------------------------
+
+"""
+    buildlp(c, A, sense, b, l, u, solver)
+
+Function used to build a model using JuMP.
+
+# INPUTS
+
+- `c`:           The objective vector, always in the sense of minimization
+- `A`:           Constraint matrix
+- `sense`:       Vector of constraint sense characters '<', '=', and '>'
+- `b`:           Right-hand side vector
+- `l`:           Vector of lower bounds on the variables
+- `u`:           Vector of upper bounds on the variables
+- `solver`:      A `::SolverConfig` object that contains a valid `handle`to the solver
+
+# OUTPUTS
+
+- `model`:       An `::LPproblem` object that has been built using the JuMP.
+- `x`:           Primal solution vector
+
+# EXAMPLES
+
+```julia
+julia> model, x = buildlp(c, A, sense, b, l, u, solver)
+```
+
+"""
+
+function buildlp(c, A, sense, b, l, u, solver)
+    N = length(c)
+    model = Model(solver)
+    x = @variable(model, l[i] <= x[i=1:N] <= u[i])
+    @objective(model, Min, c' * x)
+    eq_rows, ge_rows, le_rows = sense .== '=', sense .== '>', sense .== '<'
+    @constraint(model, A[eq_rows, :] * x .== b[eq_rows])
+    @constraint(model, A[ge_rows, :] * x .>= b[ge_rows])
+    @constraint(model, A[le_rows, :] * x .<= b[le_rows])
+    return model, x
+end
+
+#-------------------------------------------------------------------------------------------
+
+"""
+    solvelp(model, x)
+
+Function used to solve a LPproblem using JuMP.
+
+# INPUTS
+
+- `model`:       An `::LPproblem` object that has been built using the JuMP.
+- `x`:           Primal solution vector
+
+# OUTPUTS
+
+- `status`:      Termination status
+- `objval`:      Optimal objective value
+- `sol`:         Primal solution vector
+
+# EXAMPLES
+
+```julia
+julia> status, objval, sol = solvelp(model, x)
+```
+
+"""
+
+function solvelp(model, x)
+    #println(x)
+    optimize!(model)
+    return (
+        status = termination_status(model),
+        objval = objective_value(model),
+        sol = value.(x)
+    )
+end
+
+#-------------------------------------------------------------------------------------------
+
+
 """
     buildlp(c, A, sense, b, l, u, solver)