clean up

src/truncate.jl

@@ -83,6 +83,23 @@ function load_file(filename)
     end
 end
 
+"""
+$(TYPEDSIGNATURES)
+
+Truncate a clustered Hamiltonian based on 2-site belief propagation states.
+
+This function truncates a clustered Hamiltonian by considering 2-site belief propagation states and selecting the most probable states 
+to keep. It computes the beliefs for all 2-site combinations and selects the states that maximize the probability.
+
+# Arguments:
+- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labelled graph.
+- `beliefs::Dict`: A dictionary containing belief values for 2-site interactions.
+- `num_states::Int`: The maximum number of most probable states to keep.
+- `beta::Real (optional)`: The inverse temperature parameter (default is 1.0).
+
+# Returns:
+- `LabelledGraph{S, T}`: A truncated clustered Hamiltonian.
+"""
 function truncate_clustered_hamiltonian_2site_BP(
     cl_h::LabelledGraph{S, T}, 
     beliefs::Dict, 
@@ -158,50 +175,4 @@ function truncate_clustered_hamiltonian(cl_h, β, cs, result_folder, inst; tol=1
         cl_h = truncate_clustered_hamiltonian(cl_h, states)
     end
     cl_h
-end
-
-"""
-$(TYPEDSIGNATURES)
-
-Truncate a clustered Hamiltonian based on 2-site belief propagation states.
-
-This function truncates a clustered Hamiltonian by considering 2-site belief propagation states and selecting the most probable states 
-to keep. It computes the beliefs for all 2-site combinations and selects the states that maximize the probability.
-
-# Arguments:
-- `cl_h::LabelledGraph{S, T}`: The clustered Hamiltonian represented as a labelled graph.
-- `beliefs::Dict`: A dictionary containing belief values for 2-site interactions.
-- `num_states::Int`: The maximum number of most probable states to keep.
-- `beta::Real (optional)`: The inverse temperature parameter (default is 1.0).
-
-# Returns:
-- `LabelledGraph{S, T}`: A truncated clustered Hamiltonian.
-"""
-# function truncate_clustered_hamiltonian_2site_BP(
-#     cl_h::LabelledGraph{S, T}, 
-#     beliefs::Dict, 
-#     num_states::Int,
-#     result_folder::String = "results_folder",
-#     inst::String = "inst"; 
-#     beta=1.0
-#     ) where {S, T}
-#     states = Dict()
-
-#     saved_states = load_file(joinpath(result_folder, "$(inst).jld2"))
-#     if saved_states == nothing
-#         for node in vertices(cl_h)
-#             i, j, _ = node
-#             sx = has_vertex(cl_h, (i, j, 1)) ? length(get_prop(cl_h, (i, j, 1), :spectrum).energies) : 1
-#             E = beliefs[(i, j)]
-#             ind1, ind2 = select_numstate_best(E, sx, num_states)
-#             push!(states, (i, j, 1) => ind1)
-#             push!(states, (i, j, 2) => ind2)
-#         end
-#         path = joinpath(result_folder, "$(inst).jld2")
-#         save_object(string(path), states)
-#     else
-#         states = saved_states
-#     end
-#     truncate_clustered_hamiltonian(cl_h, states)
-# end
-
+end