Merge pull request #114 from opencobra/master

Compatibility of SRC and Test with MOI (#111)

Author: mtefagh

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/connect.jl

@@ -124,7 +124,7 @@ function createPool(localWorkers::Int, connectSSH::Bool=false, connectionFile::S
                 if printLevel > 0
                     println(" >> Connecting ", sshWorkers[i]["procs"], " workers on ", sshWorkers[i]["usernode"])
                 end
-
+                
                 try
                     if !(Sys.iswindows())
                         # try logging in quietly to defined node using SSH

src/distributedFBA.jl

@@ -95,7 +95,7 @@ function preFBA!(model, solver, optPercentage::Float64=0.0, osenseStr::String="m
         hasObjective = false
         fbaSol = NaN
     end
-
+    
     # add a condition if the LP has an extra condition based on the FBA solution
     if hasObjective
         if printLevel > 0
@@ -368,7 +368,7 @@ function loopFBA(m, x, c, rxnsList, nRxns::Int, rxnsOptMode=2 .+ zeros(Int, leng
         else
             performOptim = false
         end
-
+        
         if performOptim
 
             # Set the objective vector coefficients

src/load.jl

@@ -226,4 +226,4 @@ end
 loadModel(fileName, matrixAS::String="S", modelName::String="model", modelFields::Array{String,1}=["ub", "lb", "osense", "c", "b", "csense", "rxns", "mets"], printLevel::Int=1) = loadModel(fileName, modelName, printLevel)
 
 export loadModel
-#-------------------------------------------------------------------------------------------
+#-------------------------------------------------------------------------------------------

src/solve.jl

@@ -145,6 +145,128 @@ function linprog(c, A, sense, b, l, u, solver)
     )
 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, c
+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)
+    optimize!(model)
+    return (
+        status = termination_status(model),
+        objval = objective_value(model),
+        sol = value.(x)
+    )
+end
+
+#-------------------------------------------------------------------------------------------
+"""
+    linprog(c, A, sense, b, l, u, solver)
+
+Function used to build and solve a LPproblem 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
+
+- `status`:      Termination status
+- `objval`:      Optimal objective value
+- `sol`:         Primal solution vector
+
+# EXAMPLES
+
+```julia
+julia> status, objval, sol = linprog(c, A, sense, b, l, u, solver)
+```
+
+"""
+
+function linprog(c, A, sense, b, l, u, solver)
+    N = length(c)
+    model = Model(solver)
+    @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])
+    optimize!(model)
+    return (
+        status = termination_status(model),
+        objval = objective_value(model),
+        sol = value.(x)
+    )
+end
+
 #-------------------------------------------------------------------------------------------
 """
     buildCobraLP(model, solver)