Minor fixes.

Author: SebKrantz

examples/example02.jl

@@ -50,7 +50,7 @@ graph[:Lj][graph[:Lj] .== 0] .= 1e-6
     # second, in the nonconvex case (gamma>beta)
     param[:gamma] = 2 # change only gamma, keep other parameters
     res[2] = optimal_network(param, graph) # optimize by iterating on FOCs
-    res[3] = annealing(graph, res[2][:Ijk]) # improve with annealing, starting from previous result
+    res[3] = annealing(param, graph, res[2][:Ijk]) # improve with annealing, starting from previous result
 end
 
 # ==========

examples/paper_example02.jl

@@ -46,7 +46,7 @@ param[:gamma] = 2
 results[2] = optimal_network(param, graph)
 
 # Nonconvex - annealing
-results[3] = annealing(graph, results[2][:Ijk], perturbation_method = "rebranching")
+results[3] = annealing(param, graph, results[2][:Ijk], perturbation_method = "rebranching")
 
 welfare_increase = (results[3][:welfare] / results[2][:welfare]) ^ (1 / (param[:alpha] * (1 - param[:rho]))) # compute welfare increase in consumption equivalent
 

examples/paper_example03.jl

@@ -48,7 +48,7 @@ results[1] = optimal_network(param, graph)
 
 # Nonconvex
 param[:gamma] = 2
-results[2] = optimal_network(graph, I0 = results[1][:Ijk])
+results[2] = optimal_network(param, graph, I0 = results[1][:Ijk])
 
 # Plot results
 
@@ -59,7 +59,8 @@ for j in 1:2
     # Initialize an empty array to hold the subplots
     plots = Vector{Any}(undef, (1 + param[:N])) 
     # Plot network
-    plots[1] = plot_graph(graph, results[j][:Ijk], node_shades = results[j][:Lj], node_sizes = results[j][:Lj], node_sizes_scale = 40)
+    plots[1] = plot_graph(graph, results[j][:Ijk], node_shades = results[j][:Lj], 
+                          node_sizes = results[j][:Lj], node_sizes_scale = 40)
     title!(plots[1], "(a) Transport Network")
     # Plot goods flows
     for i in 1:param[:N]

examples/paper_example04.jl

@@ -3,11 +3,11 @@ using Random
 using Plots
 
 # Initialize parameters
-param = init_parameters(K = 100, labor_mobility = false)
+param = init_parameters(K = 100, rho = 0, labor_mobility = false)
 width, height = 13, 13
 
 # Create graph
-param, g0 = create_graph(param, width, height, type = "map")
+g0 = create_graph(param, width, height, type = "map")
 
 # Set fundamentals
 g0[:Zjn] = ones(g0[:J], 1) .* 1e-7  # matrix of productivity (not 0 to avoid numerical glitches)