fix unnecessary logging

Project.toml

@@ -67,6 +67,7 @@ DomainSets = "5b8099bc-c8ec-5219-889f-1d9e522a28bf"
 Graphviz_jll = "3c863552-8265-54e4-a6dc-903eb78fde85"
 HomotopyContinuation = "f213a82b-91d6-5c5d-acf7-10f1c761b327"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
@@ -83,4 +84,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [targets]
-test = ["BifurcationKit", "DiffEqCallbacks", "DomainSets", "Graphviz_jll", "HomotopyContinuation", "NonlinearSolve", "OrdinaryDiffEq", "Plots", "Random", "SafeTestsets", "SciMLBase", "SciMLNLSolve", "StableRNGs", "Statistics", "SteadyStateDiffEq", "StochasticDiffEq", "StructuralIdentifiability", "Test", "Unitful"]
+test = ["BifurcationKit", "DiffEqCallbacks", "DomainSets", "Graphviz_jll", "HomotopyContinuation", "Logging", "NonlinearSolve", "OrdinaryDiffEq", "Plots", "Random", "SafeTestsets", "SciMLBase", "SciMLNLSolve", "StableRNGs", "Statistics", "SteadyStateDiffEq", "StochasticDiffEq", "StructuralIdentifiability", "Test", "Unitful"]

test/extensions/structural_identifiability.jl

@@ -37,9 +37,9 @@ let
 
     # Identifiability analysis for Catalyst converted to StructuralIdentifiability.jl model.
     si_catalyst_ode = make_si_ode(goodwind_oscillator_catalyst; measured_quantities = [:M])
-    gi_2 = assess_identifiability(si_catalyst_ode)
-    li_2 = assess_local_identifiability(si_catalyst_ode)
-    ifs_2 = find_identifiable_functions(si_catalyst_ode)
+    gi_2 = assess_identifiability(si_catalyst_ode; loglevel)
+    li_2 = assess_local_identifiability(si_catalyst_ode; loglevel)
+    ifs_2 = find_identifiable_functions(si_catalyst_ode; loglevel)
 
     # Identifiability analysis for StructuralIdentifiability.jl model (declare this overwrites e.g. X2 variable etc.).
     goodwind_oscillator_si = @ODEmodel(
@@ -264,14 +264,14 @@ let
         k1, x1 --> x2
     end
     # Measure the source
-    id_report = assess_identifiability(rs, measured_quantities = [:x1])
+    id_report = assess_identifiability(rs; measured_quantities = [:x1], loglevel)
     @test sym_dict(id_report) == Dict(
         :x1 => :globally,
         :x2 => :nonidentifiable,
         :k1 => :globally
     )
     # Measure the target instead
-    id_report = assess_identifiability(rs, measured_quantities = [:x2])
+    id_report = assess_identifiability(rs; measured_quantities = [:x2], loglevel)
     @test sym_dict(id_report) == Dict(
         :x1 => :globally,
         :x2 => :globally,
@@ -303,13 +303,13 @@ let
         1, x1 --> x2
         1, x2 --> x3
     end
-    id_report = assess_identifiability(rs, measured_quantities = [:x3])
+    id_report = assess_identifiability(rs; measured_quantities = [:x3], loglevel)
     @test sym_dict(id_report) == Dict(
         :x1 => :globally,
         :x2 => :globally,
         :x3 => :globally,
     )
-    @test length(find_identifiable_functions(rs, measured_quantities = [:x3])) == 1
+    @test length(find_identifiable_functions(rs; measured_quantities = [:x3], loglevel)) == 1
 end
 
 

test/miscellaneous_tests/stability_computation.jl

@@ -29,7 +29,7 @@ let
               :d => 0.5 + rand(rng))
 
         # Computes stability using various jacobian options.
-        sss = hc_steady_states(rn, ps; show_progress=false)
+        sss = hc_steady_states(rn, ps; show_progress = false)
         stabs_1 = [steady_state_stability(ss, rn, ps) for ss in sss]
         stabs_2 = [steady_state_stability(ss, rn, ps; ss_jac = ss_jac) for ss in sss]
 
@@ -71,7 +71,7 @@ let
     ps_3 = [rn.k1 => 8.0, rn.k2 => 2.0, rn.k3 => 1.0, rn.k4 => 1.5, rn.kD1 => 0.5, rn.kD2 => 4.0]
 
     # Computes stability using various input forms, and checks that the output is correct. 
-    sss = hc_steady_states(rn, ps_1; u0 = u0_1, show_progress=false)
+    sss = hc_steady_states(rn, ps_1; u0 = u0_1, show_progress = false)
     for u0 in [u0_1, u0_2, u0_3, u0_4], ps in [ps_1, ps_2, ps_3]
         stab_1 =  [steady_state_stability(ss, rn, ps) for ss in sss]
         ss_jac = steady_state_jac(rn; u0 = u0)