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Commit a36f397c authored by St. Elmo's avatar St. Elmo
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implement suggestions

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src/io/matlab_reader.jl → src/io/m_reader.jl
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src/io/matlab_writer.jl → src/io/m_writer.jl
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src/types/cobraModel.jl → src/types/metabolicModel.jl
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test/analysis/fba.jl
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......@@ -38,3 +38,55 @@
# rxns = reactions(cp)
# @test all([fluxesDict[rxns[i]] == sol[i] for i in eachindex(rxns)])
end
@testset "Flux balance analysis with CobraModel" begin
model = read_model(
Downloads.download(
"http://bigg.ucsd.edu/static/models/e_coli_core.json",
joinpath("data", "e_coli_core.json"),
),
)
@test length(model.reactions) == 95 # read in correctly
# FBA
biomass = findfirst(model.reactions, "BIOMASS_Ecoli_core_w_GAM")
cons = Dict("EX_glc__D_e" => (-12.0, -12.0))
optimizer = Tulip.Optimizer # quiet by default
sol = fba(model, optimizer; objective_func = biomass, constraints = cons)
pfl = findfirst(model.reactions, "PFL")
solmulti = fba(model, optimizer; objective_func = [biomass, pfl], weights = [0.8, 0.2]) # classic flux balance analysis
flux_vec = [sol[rxn.id] for rxn in model.reactions]
sol_mapped = map_fluxes(flux_vec, model)
@test isapprox(sol_mapped["BIOMASS_Ecoli_core_w_GAM"], 1.0572509997013568, atol = 1e-6)
@test isapprox(sol["BIOMASS_Ecoli_core_w_GAM"], 1.0572509997013568, atol = 1e-6)
@test !isempty(solmulti)
sol = fba(model, optimizer; objective_func = biomass)
# atom tracker
atom_fluxes = atom_exchange(sol, model)
@test isapprox(atom_fluxes["C"], -37.1902, atol = 1e-3)
# exchange trackers
consuming, producing = exchange_reactions(sol; verbose = false)
@test isapprox(consuming["EX_nh4_e"], -4.76532, atol = 1e-3)
# metabolite trackers
consuming, producing = metabolite_fluxes(sol, model)
@test isapprox(consuming["atp_c"]["PFK"], -7.47738, atol = 1e-3)
@test isapprox(producing["atp_c"]["PYK"], 1.75818, atol = 1e-3)
# set bounds
cbm, v, mb, lbs, ubs = makeOptimizationModel(model, optimizer)
glucose_index = model[findfirst(model.reactions, "EX_glc__D_e")]
o2_index = model[findfirst(model.reactions, "EX_o2_e")]
atpm_index = model[findfirst(model.reactions, "ATPM")]
set_bound(glucose_index, lbs, ubs; ub = -1.0, lb = -1.0)
@test normalized_rhs(ubs[glucose_index]) == -1.0
@test normalized_rhs(lbs[glucose_index]) == 1.0
set_bound(o2_index, lbs, ubs; ub = 1.0, lb = 1.0)
@test normalized_rhs(ubs[o2_index]) == 1.0
@test normalized_rhs(lbs[o2_index]) == -1.0
end
test/analysis/fba2.jl deleted 100644 → 0
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@testset "Flux balance analysis with CobraModel" begin
model = read_model(
Downloads.download(
"http://bigg.ucsd.edu/static/models/e_coli_core.json",
joinpath("data", "e_coli_core.json"),
),
)
@test length(model.reactions) == 95 # read in correctly
# FBA
biomass = findfirst(model.reactions, "BIOMASS_Ecoli_core_w_GAM")
cons = Dict("EX_glc__D_e" => (-12.0, -12.0))
optimizer = Tulip.Optimizer # quiet by default
sol = fba(model, optimizer; objective_func = biomass, constraints = cons)
pfl = findfirst(model.reactions, "PFL")
solmulti = fba(model, optimizer; objective_func = [biomass, pfl], weights = [0.8, 0.2]) # classic flux balance analysis
flux_vec = [sol[rxn.id] for rxn in model.reactions]
sol_mapped = map_fluxes(flux_vec, model)
@test isapprox(sol_mapped["BIOMASS_Ecoli_core_w_GAM"], 1.0572509997013568, atol = 1e-6)
@test isapprox(sol["BIOMASS_Ecoli_core_w_GAM"], 1.0572509997013568, atol = 1e-6)
@test !isempty(solmulti)
sol = fba(model, optimizer; objective_func = biomass)
# atom tracker
atom_fluxes = atom_exchange(sol, model)
@test isapprox(atom_fluxes["C"], -37.1902, atol = 1e-3)
# exchange trackers
consuming, producing = exchange_reactions(sol; verbose = false)
@test isapprox(consuming["EX_nh4_e"], -4.76532, atol = 1e-3)
# metabolite trackers
consuming, producing = metabolite_fluxes(sol, model)
@test isapprox(consuming["atp_c"]["PFK"], -7.47738, atol = 1e-3)
@test isapprox(producing["atp_c"]["PYK"], 1.75818, atol = 1e-3)
# set bounds
cbm, v, mb, lbs, ubs = makeOptimizationModel(model, optimizer)
glucose_index = model[findfirst(model.reactions, "EX_glc__D_e")]
o2_index = model[findfirst(model.reactions, "EX_o2_e")]
atpm_index = model[findfirst(model.reactions, "ATPM")]
set_bound(glucose_index, lbs, ubs; ub = -1.0, lb = -1.0)
@test normalized_rhs(ubs[glucose_index]) == -1.0
@test normalized_rhs(lbs[glucose_index]) == 1.0
set_bound(o2_index, lbs, ubs; ub = 1.0, lb = 1.0)
@test normalized_rhs(ubs[o2_index]) == 1.0
@test normalized_rhs(lbs[o2_index]) == -1.0
end
test/analysis/fva.jl
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......@@ -59,3 +59,36 @@ end
]
rmprocs(pids)
end
@testset "Flux variability analysis with CobraModel" begin
model = read_model(
Downloads.download(
"http://bigg.ucsd.edu/static/models/e_coli_core.json",
joinpath("data", "e_coli_core.json"),
),
)
@test length(model.reactions) == 95 # read in correctly
biomass = findfirst(model.reactions, "BIOMASS_Ecoli_core_w_GAM")
pfl = findfirst(model.reactions, "PFL")
# FVA
optimizer = Tulip.Optimizer
atts = Dict("IPM_IterationsLimit" => 500)
cons = Dict("EX_glc__D_e" => (-10.0, -10.0))
fva_max, fva_min =
fva(model, optimizer; objective_func = biomass, solver_attributes = atts)
fva_max2, fva_min2 = fva(
model,
optimizer;
objective_func = [biomass, pfl],
weights = [0.5, 0.5],
constraints = cons,
)
@testset "FVA" begin
@test isapprox(fva_max["PDH"]["PDH"], 9.338922420065819, atol = 1e-6)
@test isapprox(fva_min["PDH"]["PDH"], 9.270274952732315, atol = 1e-6)
@test !isempty(fva_max2)
@test !isempty(fva_min2)
end
end
test/analysis/fva2.jl deleted 100644 → 0
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@testset "Flux variability analysis with CobraModel" begin
model = read_model(
Downloads.download(
"http://bigg.ucsd.edu/static/models/e_coli_core.json",
joinpath("data", "e_coli_core.json"),
),
)
@test length(model.reactions) == 95 # read in correctly
biomass = findfirst(model.reactions, "BIOMASS_Ecoli_core_w_GAM")
pfl = findfirst(model.reactions, "PFL")
# FVA
optimizer = Tulip.Optimizer
atts = Dict("IPM_IterationsLimit" => 500)
cons = Dict("EX_glc__D_e" => (-10.0, -10.0))
fva_max, fva_min =
fva(model, optimizer; objective_func = biomass, solver_attributes = atts)
fva_max2, fva_min2 = fva(
model,
optimizer;
objective_func = [biomass, pfl],
weights = [0.5, 0.5],
constraints = cons,
)
@testset "FVA" begin
@test isapprox(fva_max["PDH"]["PDH"], 9.338922420065819, atol = 1e-6)
@test isapprox(fva_min["PDH"]["PDH"], 9.270274952732315, atol = 1e-6)
@test !isempty(fva_max2)
@test !isempty(fva_min2)
end
end
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