Move thing that was unnecessarily moved, should make diff easier to read

Author: TorkelE

test/dsl/dsl_basics.jl

@@ -117,6 +117,17 @@ let
     @test rn == rn2
 end
 
+# Creates a reaction network using `eval` and internal function.
+let
+    ex = quote
+        (Ka, Depot --> Central)
+        (CL / Vc, Central --> 0)
+    end
+    # Line number nodes aren't ignored so have to be manually removed
+    Base.remove_linenums!(ex)
+    @test eval(Catalyst.make_reaction_system(ex)) isa ReactionSystem
+end
+
 # Miscellaneous interpolation tests. Unsure what they do here (not related to DSL).
 let
     rx = @reaction k*h, A + 2*B --> 3*C + D
@@ -131,17 +142,6 @@ let
     @test rx == Reaction(b+ex, [A,C], nothing, [2,1], nothing)
 end
 
-# Creates a reaction network using `eval` and internal function.
-let
-    ex = quote
-        (Ka, Depot --> Central)
-        (CL / Vc, Central --> 0)
-    end
-    # Line number nodes aren't ignored so have to be manually removed
-    Base.remove_linenums!(ex)
-    @test eval(Catalyst.make_reaction_system(ex)) isa ReactionSystem
-end
-
 ### Tests Reaction Metadata ###
 
 # Tests construction for various types of reaction metadata.

test/dsl/dsl_model_construction.jl

@@ -395,7 +395,7 @@ let
     @test isequal((@reaction k, 0 --> X), (@reaction k, 0 ⥟ X))
 end
 
-# Test that symbols with special mean, or that are forbidden, are handled properly.
+# Test that symbols with special meanings, or that are forbidden, are handled properly.
 let
     test_network = @reaction_network begin t * k, X --> ∅ end
     @test length(species(test_network)) == 1

test/model_simulation/simulate_SDEs.jl

@@ -131,8 +131,8 @@ let
             if nameof(rn_catalyst) != :rnc9
                 sprob_1 = SDEProblem(rn_catalyst, u0_1, (0.0, 1.0), ps_1)
                 sprob_2 = SDEProblem(rn_manual.f, rn_manual.g, u0_2, (0.0, 1.0), ps_2; noise_rate_prototype = rn_manual.nrp)
-                sol1 = solve(sprob_1, ImplicitEM(); seed = rand(rng, 100))
-                sol2 = solve(sprob_2, ImplicitEM(); seed = rand(rng, 100))
+                sol1 = solve(sprob_1, ImplicitEM(); seed = rand(rng, 1:100))
+                sol2 = solve(sprob_2, ImplicitEM(); seed = rand(rng, 1:100))
                 @test sol1[u0_sym] ≈ sol2.u
             end
         end
@@ -198,9 +198,9 @@ let
     sprob_1_2 = SDEProblem(noise_scaling_network_1, u0, (0.0, 1000.0), [:k1 => 2.0, :k2 => 0.66, :η1 => 2.0, :η2 => 0.2])
     sprob_1_3 = SDEProblem(noise_scaling_network_1, u0, (0.0, 1000.0), [:k1 => 2.0, :k2 => 0.66, :η1 => 0.2, :η2 => 0.2])
     for repeat in 1:5
-        sol_1_1 = solve(sprob_1_1, ImplicitEM(); saveat=1.0, seed = rand(rng, 100))
-        sol_1_2 = solve(sprob_1_2, ImplicitEM(); saveat=1.0, seed = rand(rng, 100))
-        sol_1_3 = solve(sprob_1_3, ImplicitEM(); saveat=1.0, seed = rand(rng, 100))
+        sol_1_1 = solve(sprob_1_1, ImplicitEM(); saveat=1.0, seed = rand(rng, 1:100))
+        sol_1_2 = solve(sprob_1_2, ImplicitEM(); saveat=1.0, seed = rand(rng, 1:100))
+        sol_1_3 = solve(sprob_1_3, ImplicitEM(); saveat=1.0, seed = rand(rng, 1:100))
         @test var(sol_1_1[:X1]) > var(sol_1_2[:X1]) > var(sol_1_3[:X1]) 
     end
 
@@ -214,9 +214,9 @@ let
     sprob_2_2 = SDEProblem(noise_scaling_network_2, u0, (0.0, 1000.0), [k1 => 2.0, k2 => 0.66, η[1] => 2.0, η[2] => 0.2])
     sprob_2_3 = SDEProblem(noise_scaling_network_2, u0, (0.0, 1000.0), [k1 => 2.0, k2 => 0.66, η[1] => 0.2, η[2] => 0.2])
     for repeat in 1:5
-        sol_2_1 = solve(sprob_2_1, ImplicitEM(); saveat=1.0, seed = rand(rng, 100))
-        sol_2_2 = solve(sprob_2_2, ImplicitEM(); saveat=1.0, seed = rand(rng, 100))
-        sol_2_3 = solve(sprob_2_3, ImplicitEM(); saveat=1.0, seed = rand(rng, 100))
+        sol_2_1 = solve(sprob_2_1, ImplicitEM(); saveat=1.0, seed = rand(rng, 1:100))
+        sol_2_2 = solve(sprob_2_2, ImplicitEM(); saveat=1.0, seed = rand(rng, 1:100))
+        sol_2_3 = solve(sprob_2_3, ImplicitEM(); saveat=1.0, seed = rand(rng, 1:100))
         @test var(sol_2_1[:X1]) > var(sol_2_2[:X1]) > var(sol_2_3[:X1]) 
     end
 end
@@ -274,7 +274,7 @@ let
     sprob = SDEProblem(noise_scaling_network, u0, (0.0, 1000.0), ps)
 
     for repeat in 1:5
-        sol = solve(sprob, ImplicitEM(); saveat=1.0, seed = rand(rng, 100))
+        sol = solve(sprob, ImplicitEM(); saveat=1.0, seed = rand(rng, 1:100))
         @test var(sol[:X1]) < var(sol[:X2]) 
         @test var(sol[:X1]) < var(sol[:X3]) 
     end
@@ -298,9 +298,9 @@ let
     u0 = [:X1 => 1000.0, :X2 => 1000.0, :X3 => 1000.0, :X4 => 1000.0, :X5 => 1000.0, :N1 => 3.0, :N3 => 0.33]
     ps = [:p => 1000.0, :d => 1.0, :η1 => 1.0, :η2 => 1.4, :η3 => 0.33, :η4 => 4.0]
     sprob = SDEProblem(noise_scaling_network, u0, (0.0, 1000.0), ps)
-    
+
     for repeat in 1:5
-        sol = solve(sprob, ImplicitEM(); saveat=1.0, adaptive=false, dt=0.1, seed = rand(rng, 100))
+        sol = solve(sprob, ImplicitEM(); saveat=1.0, adaptive=false, dt=0.1, seed = rand(rng, 1:100))
         @test var(sol[:X1]) > var(sol[:X2]) > var(sol[:X3]) > var(sol[:X4]) > var(sol[:X5])
     end
 end
@@ -356,7 +356,7 @@ let
         u0 = rnd_u0(no_param_network, rng; factor)
         sprob = SDEProblem(no_param_network, u0, (0.0, 1000.0))
         for repeat in 1:5
-            sol = solve(sprob, ImplicitEM(); seed = rand(rng, 100))
+            sol = solve(sprob, ImplicitEM(); seed = rand(rng, 1:100))
             @test mean(sol[:X1]) > mean(sol[:X2])
         end
     end