List of symbols and tunable flag

docs/src/tutorials/spectralDCM.jl

@@ -131,8 +131,15 @@ end
 A_prior = 0.01*randn(nr, nr)
 A_prior -= diagm(diag(A_prior))    # ensure diagonal dominance of matrix
 # Since we want to optimize these weights we turn them into symbolic parameters:
-# Add the symbolic weights to the edges and connect reegions.
-@parameters A[1:nr^2] = vec(A_prior) [tunable = true]
+# Add the symbolic weights to the edges and connect regions.
+A = []
+for (i, a) in enumerate(vec(A_prior))
+    symb = Symbol("A$(i)")
+    push!(A, only(@parameters $symb = a))
+end
+# With the function `untune!`` we can list indices of parameters whose tunable flag should be set to false.
+# For instance the first element in the second row:
+untune!(A, [4])
 for (i, idx) in enumerate(CartesianIndices(A_prior))
     if idx[1] == idx[2]
         add_edge!(g, regions[idx[1]] => regions[idx[2]]; :weight => -exp(A[i])/2)  # -exp(A[i])/2: treatement of diagonal elements in SPM12 to make diagonal dominance (see Gershgorin Theorem) more likely but it is not guaranteed

src/Neuroblox.jl

@@ -236,7 +236,7 @@ export system_from_graph, graph_delays
 export create_adjacency_edges!, adjmatrixfromdigraph
 export get_namespaced_sys, nameof
 export run_experiment!, run_trial!
-export addnontunableparams
+export addnontunableparams, untune!
 export get_weights, get_dynamic_states, get_idx_tagged_vars, get_eqidx_tagged_vars
 export BalloonModel,LeadField, boldsignal_endo_balloon
 export PINGNeuronExci, PINGNeuronInhib

src/blox/blox_utilities.jl

@@ -17,6 +17,12 @@ function paramscoping(;kwargs...)
     return paramlist
 end
 
+function untune!(parlist, nontunable)
+    for i in nontunable
+        parlist[i] = setmetadata(parlist[i], ModelingToolkit.VariableTunable, false)
+    end
+end
+
 get_HH_exci_neurons(n::HHNeuronExciBlox) = [n]
 get_HH_exci_neurons(n) = []
 

test/datafitting.jl

@@ -33,7 +33,12 @@ using MAT
     end
 
     # add symbolic weights
-    @parameters A[1:length(vars["pE"]["A"])] = vec(vars["pE"]["A"]) [tunable = true]
+    A = []
+    for (i, a) in enumerate(vec(vars["pE"]["A"]))
+        symb = Symbol("A$(i)")
+        push!(A, only(@parameters $symb = a))
+    end
+    untune!(A, [])   # list indices of parameters that should be set to tunable=false
     for (i, idx) in enumerate(CartesianIndices(vars["pE"]["A"]))
         if idx[1] == idx[2]
             add_edge!(g, regions[idx[1]], regions[idx[2]], :weight, -exp(A[i])/2)  # treatement of diagonal elements in SPM12, likely to avoid instabilities of the linear model