diff --git a/src/analysis/fba.jl b/src/analysis/fba.jl
index 2e15bf838e2017034e8883ab35aa34d1df4d427a..363a868411976395d6b7ec840e12619b122264f3 100644
--- a/src/analysis/fba.jl
+++ b/src/analysis/fba.jl
@@ -71,8 +71,9 @@ function fba(
sense = MOI.MAX_SENSE,
)
# get core optimization problem
- cbm, v, mb, lbcons, ubcons = make_optimization_model(model, optimizer, sense = sense)
-
+ cbm = make_optimization_model(model, optimizer, sense = sense)
+ v = cbm[:x] # fluxes
+
# modify core optimization problem according to user specifications
if !isempty(solver_attributes) # set other attributes
for (k, val) in solver_attributes
@@ -83,7 +84,7 @@ function fba(
# set additional constraints
for (rxnid, con) in constraints
ind = model.reactions[findfirst(model.reactions, rxnid)]
- set_bound(ind, lbcons, ubcons; lb = con[1], ub = con[2])
+ set_bound(ind, cbm; lb = con[1], ub = con[2])
end
# if an objective function is supplied, modify the default objective
diff --git a/src/analysis/fva.jl b/src/analysis/fva.jl
index 0b38dc87179e3d82db28c96b2f5abcd4db8a0f6c..e1c5a575c1470b3341423f9d3095d1cd532efda9 100644
--- a/src/analysis/fva.jl
+++ b/src/analysis/fva.jl
@@ -37,14 +37,15 @@ function flux_variability_analysis(
throw(DomainError(reactions, "Index exceeds number of reactions."))
end
- (optimization_model, x0) = flux_balance_analysis(model, optimizer)
+ optimization_model = flux_balance_analysis(model, optimizer)
Z0 = COBREXA.JuMP.objective_value(optimization_model)
optimization_model = nothing # we won't need this one anymore, so free the memory
# store a JuMP optimization model at all workers
save_model = :(
begin
- optmodel, x = COBREXA.make_optimization_model($model, $optimizer)
+ optmodel = COBREXA.make_optimization_model($model, $optimizer)
+ x = optmodel[:x]
COBREXA._FVA_add_constraint(optmodel, $(objective(model)), x, $Z0, $gamma)
optmodel
end
@@ -140,7 +141,8 @@ function fva(
constraints = Dict{String,Tuple{Float64,Float64}}(),
sense = MOI.MAX_SENSE,
)
- cbm, v, mb, lbcons, ubcons = make_optimization_model(model, optimizer, sense = sense)
+ cbm = make_optimization_model(model, optimizer, sense = sense)
+ v = cbm[:x]
if !isempty(solver_attributes) # set other attributes
for (k, v) in solver_attributes
@@ -151,7 +153,7 @@ function fva(
# set additional constraints
for (rxnid, con) in constraints
ind = model.reactions[findfirst(model.reactions, rxnid)]
- set_bound(ind, lbcons, ubcons; lb = con[1], ub = con[2])
+ set_bound(ind, cbm; lb = con[1], ub = con[2])
end
# if an objective function is supplied, modify the default objective
diff --git a/src/analysis/pfba.jl b/src/analysis/pfba.jl
index 1e2afc4139a4494610cda97493d8da0643a5a941..8402d3f4da2052a72ddc9f9003a211a1d44c4047 100644
--- a/src/analysis/pfba.jl
+++ b/src/analysis/pfba.jl
@@ -33,16 +33,16 @@ function pfba(
if typeof(optimizer) <: AbstractArray # choose optimizer
- cbm, v, mb, lbcons, ubcons =
- make_optimization_model(model, optimizer[1], sense = sense)
+ cbm = make_optimization_model(model, optimizer[1], sense = sense)
+ v = cbm[:x]
if !isempty(solver_attributes["opt1"]) # set other attributes
for (k, v) in solver_attributes["opt1"]
set_optimizer_attribute(cbm, k, v)
end
end
else # singe optimizer
- cbm, v, mb, lbcons, ubcons =
- make_optimization_model(model, optimizer, sense = sense)
+ cbm = make_optimization_model(model, optimizer, sense = sense)
+ v = cbm[:x]
if !isempty(solver_attributes) # set other attributes
for (k, v) in solver_attributes
set_optimizer_attribute(cbm, k, v)
@@ -53,7 +53,7 @@ function pfba(
# set additional constraints
for (rxnid, con) in constraints
ind = model.reactions[findfirst(model.reactions, rxnid)]
- set_bound(ind, lbcons, ubcons; lb = con[1], ub = con[2])
+ set_bound(ind, cbm; lb = con[1], ub = con[2])
end
# check if default objective should be used
diff --git a/src/base/solver.jl b/src/base/solver.jl
index 178654463f73c57a05844438ca73c0cdf8674620..b8d16887170516b01d66a9bc8d4e31c08e5f8a66 100644
--- a/src/base/solver.jl
+++ b/src/base/solver.jl
@@ -13,11 +13,11 @@ function make_optimization_model(
optimization_model = COBREXA.JuMP.Model(optimizer)
@variable(optimization_model, x[i = 1:n])
@objective(optimization_model, sense, objective(model)' * x)
- mb = @constraint(optimization_model, mb, stoichiometry(model) * x .== balance(model)) # mass balance
- lbs = @constraint(optimization_model, lbs, xl .<= x) # lower bounds
- ubs = @constraint(optimization_model, ubs, x .<= xu) # upper bounds
+ @constraint(optimization_model, mb, stoichiometry(model) * x .== balance(model)) # mass balance
+ @constraint(optimization_model, lbs, xl .<= x) # lower bounds
+ @constraint(optimization_model, ubs, x .<= xu) # upper bounds
- return optimization_model, x, mb, lbs, ubs
+ return optimization_model
end
"""
@@ -28,8 +28,7 @@ function optimize_model(
optimizer;
sense = MOI.MIN_SENSE,
) where {LM<:MetabolicModel}
- optimization_model, x, _, _, _ =
- make_optimization_model(model, optimizer; sense = sense)
- COBREXA.JuMP.optimize!(optimization_model)
- return (optimization_model, x)
+ optimization_model = make_optimization_model(model, optimizer; sense = sense)
+ COBREXA.JuMP.optimize!(optimization_model)
+ return optimization_model
end
diff --git a/src/base/utilities.jl b/src/base/utilities.jl
index 6ea40a1767aae5e13e9b23f6a48d0c07c804d242..ac473dd5677cb0e740583539a7939ae4fabd251d 100644
--- a/src/base/utilities.jl
+++ b/src/base/utilities.jl
@@ -21,16 +21,16 @@ Base.copy(model::CoupledLinearModel) =
"""
- set_bound(index, ubconstaintref, lbconstaintref; ub=1000, lb=-1000)
+ set_bound(index, optimization_model; ub=1000, lb=-1000)
Helper function to set the bounds of variables.
The JuMP `set_normalized_rhs` function is a little confusing, so this function simplifies setting
-constraints. Just supply the constraint `index` and the bound objects (`ubconstaintref`, `lbconstaintref`) and they will be set to `ub` and `lb`.
+constraints. Just supply the constraint `index` and the model and they will be set to `ub` and `lb`.
"""
-function set_bound(vind, lbs, ubs; ub = 1000, lb = -1000)
+function set_bound(vind, opt_model; ub = 1000, lb = -1000)
if lb <= 0
- set_normalized_rhs(lbs[vind], abs(lb))
+ set_normalized_rhs(opt_model[:lbs][vind], abs(lb))
else
- set_normalized_rhs(lbs[vind], -abs(lb))
+ set_normalized_rhs(opt_model[:lbs][vind], -abs(lb))
end
- set_normalized_rhs(ubs[vind], ub)
+ set_normalized_rhs(opt_model[:ubs][vind], ub)
end