update sigma in Parquet and addd docs

src/computational_graph/optimize.jl

@@ -1,12 +1,17 @@
 """
-    function optimize!(graphs::Union{Tuple,AbstractVector{<:AbstractGraph}}; verbose=0, normalize=nothing)
+    function optimize!(graphs::Union{Tuple,AbstractVector{<:AbstractGraph}}; level=0, verbose=0, normalize=nothing)
 
-    In-place optimization of given `graphs`. Removes duplicated leaves, merges chains, and merges linear combinations.
+    In-place optimization of given `graphs`. Removes duplicated nodes (when `level > 0`) or leaves, flattens chains, 
+    merges linear combinations, and removing zero-valued subgraphs.
 
 # Arguments:
 - `graphs`: A tuple or vector of graphs.
+- `level`: Optimization level (default: 0). A value greater than 0 triggers more extensive but slower optimization processes, such as removing duplicated nodes.
 - `verbose`: Level of verbosity (default: 0).
 - `normalize`: Optional function to normalize the graphs (default: nothing).
+
+# Returns
+- Returns the optimized graphs. If the input graphs is empty, it returns nothing.
 """
 function optimize!(graphs::Union{Tuple,AbstractVector{<:AbstractGraph}}; level=0, verbose=0, normalize=nothing)
     if isempty(graphs)
@@ -31,12 +36,14 @@ function optimize!(graphs::Union{Tuple,AbstractVector{<:AbstractGraph}}; level=0
 end
 
 """
-    function optimize(graphs::Union{Tuple,AbstractVector{<:AbstractGraph}}; verbose=0, normalize=nothing)
+    function optimize(graphs::Union{Tuple,AbstractVector{<:AbstractGraph}}; level=0, verbose=0, normalize=nothing)
 
-    Optimizes a copy of given `graphs`. Removes duplicated leaves, merges chains, and merges linear combinations.
+    Optimizes a copy of given `graphs`. Removes duplicated nodes (when `level > 0`) or leaves, flattens chains, 
+    merges linear combinations, and removing zero-valued subgraphs.
 
 # Arguments:
 - `graphs`: A tuple or vector of graphs.
+- `level`: Optimization level (default: 0). A value greater than 0 triggers more extensive but slower optimization processes, such as removing duplicated nodes.
 - `verbose`: Level of verbosity (default: 0).
 - `normalize`: Optional function to normalize the graphs (default: nothing).
 

src/computational_graph/tree_properties.jl

@@ -140,7 +140,6 @@ end
 """
 function count_leaves(g::G) where {G<:AbstractGraph}
     leaves = collect(Leaves(g))
-    sort!(leaves, by=x -> x.id)
     unique!(x -> x.id, leaves)
 
     return length(leaves)
@@ -151,7 +150,6 @@ function count_leaves(graphs::Vector{G}) where {G<:AbstractGraph}
     for g in graphs
         append!(leaves, collect(Leaves(g)))
     end
-    sort!(leaves, by=x -> x.id)
     unique!(x -> x.id, leaves)
 
     return length(leaves)

src/frontend/parquet/parquet.jl

@@ -213,12 +213,28 @@ include("filter.jl")
 include("to_graph.jl")
 
 const vertex4I_diags = Dict{Int,Vector{Graph}}()
+
+"""
+    initialize_vertex4I_diags(; filter=[NoHartree], spinPolarPara::Float64=0.0)
+
+    Initialize the vertex4I_diags dictionary with the diagrams of the 3- and 4-point fully-irreducible (Alli) vertex functions.
+
+# Parameters
+- `filter (optional)` : a list of filter conditions to select the diagrams. Default is `[NoHartree]`.
+- `spinPolarPara (optional)` : the spin-polarization parameter. Default is `0.0`.
+"""
 function initialize_vertex4I_diags(; filter=[NoHartree], spinPolarPara::Float64=0.0)
     dict_graphs = diagdictGV_ver4([(3, 0, 0), (4, 0, 0)], channels=[Alli], filter=filter, spinPolarPara=spinPolarPara)
     vertex4I_diags[3] = dict_graphs[(3, 0, 0)][1]
     vertex4I_diags[4] = dict_graphs[(4, 0, 0)][1]
 end
 
+"""
+    get_ver4I()
+
+    Retrieves the global dictionary `vertex4I_diags` that contains graph initialized by `initialize_vertex4I_diags`. 
+    This function is a getter that provides access to the stored graph data of the 3- and 4-point fully-irreducible (Alli) vertex functions.
+"""
 get_ver4I() = vertex4I_diags
 
 initialize_vertex4I_diags()

src/frontend/parquet/sigma.jl

@@ -106,7 +106,7 @@ function sigma(para::DiagPara, extK=getK(para.totalLoopNum, 1), subdiagram=false
                 # if compact
                 #     ver4 = ep_coupling(paraW; extK=legK, subdiagram=true, name=:W, blocks=blocks)
                 # else
-                ver4 = vertex4(paraW, legK, true; channels=[PHr,], blocks=blocks, blockstoplevel=ParquetBlocks(phi=[], Γ4=[PHr, PHEr, PPr]))
+                ver4 = vertex4(paraW, legK, true; channels=[PHr,], blocks=blocks, blockstoplevel=ParquetBlocks(phi=[], Γ4=[PHr, PHEr, PPr, Alli]))
                 # end
             end
             #transform extT coloum intwo extT for Σ and extT for G