Update examples

Project.toml

@@ -23,8 +23,10 @@ Symbolics = "7"
 julia = "1.10"
 
 [extras]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Ipopt", "Test"]
+test = ["CSV", "DataFrames", "Ipopt", "Test"]

README.md

@@ -23,9 +23,9 @@ An optimal reactor-separator-recycle process design problem originally presented
 A nonlinear kinetic parameter estimation problem originally described by [[5](#references)] is used to demonstrate the use of `register_odesystem` to formulate and solve an ODE system using [`Ipopt`](https://github.com/coin-or/ipopt) [[6](#references)].
 
 ## References
-1. Ma, Y., Gowda, S., Anantharaman, R., Laughman, C., Shah, V., and Rackauckas, C. ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling. (2022). DOI: [10.48550/arXiv.2103.05244)](https://doi.org/10.48550/arXiv.2103.05244)
+1. Ma, Y., Gowda, S., Anantharaman, R., Laughman, C., Shah, V., and Rackauckas, C. ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling. (2022). DOI: [10.48550/arXiv.2103.05244](https://doi.org/10.48550/arXiv.2103.05244)
 2. Lubin, M., Dowson, O., Dias Garcia, J., Huchette, J., Legat, B., and Vielma, J.P. JuMP 1.0: recent improvements to a modeling language for mathematical optimization. *Mathematical Programming Computation.* 15, 581-589 (2023). DOI: [10.1007/s12532-023-00239-3](https://doi.org/10.1007/s12532-023-00239-3)
 3. Kokossis, A.C. and Floudas, C.A. Synthesis of isothermal reactor-separator-recycle systems. *Chemical Engineering Science.* 46, 1361-1383 (1991). DOI: [10.1016/0009-2509(91)85063-4](https://doi.org/10.1016/0009-2509(91)85063-4)
-4. Wilhelm, M. E. and Stuber, M.D. EAGO.jl: easy advanced global optimization in Julia. *Optimization Methods and Software.* 37(2), 425-450 (2022). DOI: [10.1080/10556788.2020.1786566](https://doi.org/10.1080/10556788.2020.1786566)
+4. Wilhelm, M. E. and Stuber, M.D. EAGO.jl: easy advanced global optimization in Julia. *Optimization Methods & Software.* 37(2), 425-450 (2022). DOI: [10.1080/10556788.2020.1786566](https://doi.org/10.1080/10556788.2020.1786566)
 5. Taylor, J.W. Direct measurement and analysis of cyclohexadienyl oxidation. Ph.D. thesis, Massachusetts Institute of Technology. (2005). URL: http://hdl.handle.net/1721.1/33716
 6. Wächter, A. and Biegler, L.T. On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. *Mathematical Programming.* 106, 25-57 (2006). DOI: [10.1007/s10107-004-0559-y](https://doi.org/10.1007/s10107-004-0559-y)

examples/algebraic_model.jl

@@ -1,4 +1,7 @@
-using ModelingToolkit, JuMP, EAGO, EOptInterface
+using EAGO
+using EOptInterface
+using JuMP
+using ModelingToolkit
 using ModelingToolkit: t_nounits as t, D_nounits as D
 
 # Create algebraic ModelingToolkit system
@@ -163,14 +166,14 @@ xU = [100.0, 1.0, 1.0, 1.0, 100.0, 10.0]
 register_nlsystem(model, system, obj, [g1, g2])
 
 # Optimize model
-JuMP.optimize!(model)
+optimize!(model)
 
 # Display results
-println("Termination Status: $(JuMP.termination_status(model))")
-println("Primal Status: $(JuMP.primal_status(model))")
-println("Solve Time: $(round.(JuMP.solve_time(model), digits=5))")
-println("f^* = $(round(JuMP.objective_value(model), digits=5))")
-println("x* = $(round.(JuMP.value.(x), digits=3))")
+println("Termination Status: $(termination_status(model))")
+println("Primal Status: $(primal_status(model))")
+println("Solve Time: $(round.(solve_time(model), digits=5))")
+println("f^* = $(round(objective_value(model), digits=5))")
+println("x* = $(round.(value.(x), digits=3))")
 
 # Retrieve full-space solution
 full_solution(model, system)
@@ -191,9 +194,9 @@ xU = vcat(repeat([100.0, 1.0, 1.0, 1.0], 12), 100.0, 10.0)
 register_nlsystem(full_model, full_system, obj, [g1, g2])
 
 # Optimize model and retrieve results
-JuMP.optimize!(full_model)
-println("Termination Status: $(JuMP.termination_status(full_model))")
-println("Primal Status: $(JuMP.primal_status(full_model))")
-println("Solve Time: $(round.(JuMP.solve_time(full_model), digits=5))")
-println("f^* = $(round(JuMP.objective_value(full_model), digits=5))")
-println("x* = $(round.(JuMP.value.(x), digits=3))")
+optimize!(full_model)
+println("Termination Status: $(termination_status(full_model))")
+println("Primal Status: $(primal_status(full_model))")
+println("Solve Time: $(round.(solve_time(full_model), digits=5))")
+println("f^* = $(round(objective_value(full_model), digits=5))")
+println("x* = $(round.(value.(x), digits=3))")

examples/kinetic_intensity_data.csv

@@ -0,0 +1,202 @@
+time,intensity
+0,0
+0.01,66.0952
+0.02,104.762
+0.03,110.333
+0.04,114.905
+0.05,122.238
+0.06,125.429
+0.07,125.429
+0.08,123.476
+0.09,121.286
+0.1,118.857
+0.11,117.667
+0.12,116.143
+0.13,113.857
+0.14,111.571
+0.15,108.81
+0.16,105.952
+0.17,104.048
+0.18,102.048
+0.19,100.143
+0.2,98.5238
+0.21,96.2381
+0.22,94.381
+0.23,91.6667
+0.24,89.5714
+0.25,87.1429
+0.26,84.8571
+0.27,83.4286
+0.28,81.1905
+0.29,78.9048
+0.3,77.0476
+0.31,75.4762
+0.32,73.4762
+0.33,71.8095
+0.34,70.6667
+0.35,68.381
+0.36,67.3333
+0.37,65.0952
+0.38,63.7143
+0.39,62.0476
+0.4,60.8571
+0.41,59.619
+0.42,58.2857
+0.43,57.4762
+0.44,56.4762
+0.45,55.8095
+0.46,54.5238
+0.47,53
+0.48,51.8571
+0.49,50.4286
+0.5,49.381
+0.51,47.9524
+0.52,47.3714
+0.53,46.8952
+0.54,46.4857
+0.55,45.9048
+0.56,45.0762
+0.57,44.3238
+0.58,43.4143
+0.59,43.5429
+0.6,42.3619
+0.61,41.8381
+0.62,40.2381
+0.63,39.1286
+0.64,38.7857
+0.65,37.081
+0.66,36.9524
+0.67,36.581
+0.68,36.281
+0.69,35.3476
+0.7,34.8905
+0.71,34.1667
+0.72,33.6714
+0.73,32.9667
+0.74,31.8429
+0.75,31.5429
+0.76,31.1476
+0.77,30.9905
+0.78,29.9571
+0.79,29.1333
+0.8,28.7857
+0.81,28.4429
+0.82,28.3476
+0.83,27.5429
+0.84,27.4333
+0.85,27.6048
+0.86,27.1762
+0.87,27.2
+0.88,26.4333
+0.89,25.7619
+0.9,24.8095
+0.91,24.7429
+0.92,24.2857
+0.93,24.1714
+0.94,23.5667
+0.95,23.5476
+0.96,23.3952
+0.97,22.919
+0.98,22.3095
+0.99,21.8048
+1,21.2857
+1.01,21.2048
+1.02,20.8429
+1.03,20.4429
+1.04,20.0048
+1.05,19.9381
+1.06,19.5
+1.07,19.8667
+1.08,18.9333
+1.09,19.1381
+1.1,18.9619
+1.11,18.5476
+1.12,17.9048
+1.13,17.7571
+1.14,18.5333
+1.15,18.3762
+1.16,18.3571
+1.17,18.3286
+1.18,18.2762
+1.19,18.3952
+1.2,17.5952
+1.21,18.1524
+1.22,18.1952
+1.23,17.8476
+1.24,17.9095
+1.25,17.5048
+1.26,17.5
+1.27,15.9619
+1.28,16.2095
+1.29,16.181
+1.3,15.6952
+1.31,15.7095
+1.32,15.4619
+1.33,15.9476
+1.34,16
+1.35,16.1952
+1.36,16.1143
+1.37,15.7429
+1.38,15.5762
+1.39,15.7048
+1.4,15.8095
+1.41,15.6667
+1.42,14.9048
+1.43,14.5857
+1.44,14.7524
+1.45,14.7571
+1.46,14.9762
+1.47,14.5333
+1.48,14.5524
+1.49,14.0143
+1.5,13.6286
+1.51,13.4429
+1.52,13.4667
+1.53,13.319
+1.54,12.9333
+1.55,13.1238
+1.56,12.7476
+1.57,12.9333
+1.58,13.0714
+1.59,13.0714
+1.6,12.7619
+1.61,12.4238
+1.62,12.5143
+1.63,12.9143
+1.64,12.5714
+1.65,13.3667
+1.66,13.2286
+1.67,13.7905
+1.68,13.7571
+1.69,13.5905
+1.7,12.9667
+1.71,12.981
+1.72,12.8857
+1.73,12.919
+1.74,13.0143
+1.75,13.0095
+1.76,12.3857
+1.77,12.5571
+1.78,12.3429
+1.79,12.7571
+1.8,12.681
+1.81,12.5429
+1.82,12.1857
+1.83,12.7905
+1.84,12.5571
+1.85,12.8429
+1.86,12.5476
+1.87,12.5714
+1.88,12.3762
+1.89,11.9952
+1.9,11.4571
+1.91,11.3
+1.92,11.1524
+1.93,11.681
+1.94,11.619
+1.95,11.9048
+1.96,12
+1.97,12.0762
+1.98,11.9143
+1.99,11.7619
+2,11.5333