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speed up cycle prob calculation #54

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Jan 16, 2024
Merged

speed up cycle prob calculation #54

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17 changes: 14 additions & 3 deletions Source/ColorSummary.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -245,6 +245,7 @@ function join_table_cycle_likelihoods(g::DataGraph, color_hash, cycle_size::Int,
# start with a forward edge.
# detailed_edges::Set{Tuple{Int, Int, Int, Int, Vector{Bool}}} = Set()

println("Initializing Detailed Edges Dict: ", time())
# map start_node => vector of edges with that start node
detailed_edges::Dict{Int, Vector{Tuple{Int, Int, Int, Int, Vector{Bool}}}} = Dict(i => [] for i in vertices(g.graph))
for edge in edges(g.graph)
Expand All @@ -260,11 +261,16 @@ function join_table_cycle_likelihoods(g::DataGraph, color_hash, cycle_size::Int,
stored_paths::Dict{CyclePathAndColors, Float32} = Dict() # this stores summary info representing the path lengths that actually closed
# summary info = [c1, c2, [d]]

println("Initializing Cycle Path Calculation: ", time())
# initialize with size two data
# start up the "current joins" vector
updated_paths::Dict{Tuple{Int, Int, Int, Int, Vector{Bool}}, Float64} = Dict() # stores our progress as we repeatedly join
for edge_set in values(detailed_edges)
for edge in edge_set
vertex_sample = collect(keys(detailed_edges))
if length(vertex_sample) > max_partial_paths
vertex_sample = sample(collect(keys(detailed_edges)), max_partial_paths; replace=false)
end
for vertex in vertex_sample
for edge in detailed_edges[vertex]
summary_info = CyclePathAndColors(edge[5], (edge[3], edge[4]))
updated_paths[edge] = 1.0
stored_paths[summary_info] = get(stored_paths, summary_info, 0) + 1.0
Expand All @@ -274,8 +280,10 @@ function join_table_cycle_likelihoods(g::DataGraph, color_hash, cycle_size::Int,
end
end

println("Performing Cycle Path Calculation: ", time())
# for each cycle size...
for current_cycle_size in 2: cycle_size
println("Performing Cycle Size (", current_cycle_size, ") Calculation: ", time())
# new_paths stores the current detailed paths and their count
new_paths::Dict{Tuple{Int, Int, Int, Int, Vector{Bool}}, Float64} = Dict()
joined_path::Tuple{Int, Int, Int, Int, Vector{Bool}} = (0,0,0,0,[])
Expand All @@ -295,9 +303,12 @@ function join_table_cycle_likelihoods(g::DataGraph, color_hash, cycle_size::Int,
end
updated_paths = new_dict
end
random_numbers = rand(UInt32, 5)
for condensed_path in keys(updated_paths)
# first join/aggregate everything
sampled_edges = sample(detailed_edges[condensed_path[2]], 5)
num_neighbors = length(detailed_edges[condensed_path[2]])
sampled_edges = detailed_edges[condensed_path[2]][(random_numbers .% num_neighbors) .+ 1]
# sampled_edges = detailed_edges[condensed_path[2]]
for edge in sampled_edges
# [n1, n2, c1, c2, [d]]
joined_path = (condensed_path[1], edge[2], condensed_path[3], edge[4], cat(condensed_path[5], edge[5], dims=1))
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