Redo weighted map (#30)

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Author: GiggleLiu

Project.toml

@@ -1,13 +1,13 @@
 name = "UnitDiskMapping"
 uuid = "1b61a8d9-79ed-4491-8266-ef37f39e1727"
 authors = ["QuEra Computing Inc."]
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 
 [compat]
-Graphs = "1.4"
+Graphs = "1.6"
 julia = "1"
 
 [extras]

README.md

@@ -86,15 +86,16 @@ The generic tensor network approach for solving MIS works best for graphs with s
 ```julia
 julia> using GraphTensorNetworks
 
-julia> gp = Independence(SimpleGraph(res.grid_graph); optimizer=TreeSA(ntrials=1, niters=10), simplifier=MergeGreedy());
+julia> gp = IndependentSet(SimpleGraph(res.grid_graph); optimizer=TreeSA(ntrials=1, niters=10), simplifier=MergeGreedy());
 
-julia> misconfig = solve(gp, "config max")[].c;
+julia> misconfig = solve(gp, SingleConfigMax())[].c.data
+10110001000110000111000001010101011000001111000001101010101010000101110100000010010101010101010001000000100111010000001001101000101010001110010001000101110100111010100010110100100110101010110100011100101010101010100011
 
 # create a grid mask as the solution, where occupied locations are marked as value 1.
 julia> c = zeros(Int, size(res.grid_graph.content));
 
 julia> for (i, loc) in enumerate(findall(!isempty, res.grid_graph.content))
-           c[loc] = misconfig.data[i]
+           c[loc] = misconfig[i]
        end
 
 julia> print_config(res, c)
@@ -131,7 +132,7 @@ julia> print_config(res, c)
 
 #### Step 3: solve the MIS solution back an MIS of the source graph
 ```julia
-julia> original_configs = map_configs_back(res, [c])
+julia> original_configs = map_configs_back(res, [misconfig])
 1-element Vector{Vector{Int64}}:
  [1, 0, 0, 1, 0, 0, 1, 1, 0, 0]
 
@@ -150,31 +151,74 @@ julia> w_res = map_graph(Weighted(), g, vertex_order=Branching());
 julia> println(w_res.grid_graph)
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+⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ● ⋅ ⋅ ⋅ ● ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ● ⋅ ⋅ 
+⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ● ⋅ ⋅ ○ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ○ ⋅ ⋅ 
+⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ● ● ⋅ ● ● ● ● ● ● ● ● ● ● ○ ⋅ ⋅ ⋅ 
+⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ● ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 
 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 
 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 
 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 
-⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
+⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 
+```
+
+Here, `▴` is a vertex having weight 3, `●` is a vertex having weight 2 and `○` is a vertex having weight 1.
+One can add some weights in range 0~1 by typing
+
+```julia
+julia> source_weights = 0.05:0.1:0.95
+0.05:0.1:0.95
+
+julia> mapped_weights = map_weights(w_res, source_weights)
+218-element Vector{Float64}:
+ 1.85
+ 2.0
+ 1.95
+ 2.0
+ 2.0
+ 2.0
+ 1.0
+ ⋮
+ 2.0
+ 2.0
+ 2.0
+ 2.0
+ 1.0
+ 2.0
+```
+
+One can easily check the correctness
+```julia
+julia> wr1 = solve(IndependentSet(g; weights=collect(source_weights)), SingleConfigMax())[]
+(2.2, ConfigSampler{10, 1, 1}(0100100110))ₜ
+
+julia> wr2 = solve(IndependentSet(SimpleGraph(w_res.grid_graph); weights=mapped_weights), SingleConfigMax())[].c.data
+(178.2, ConfigSampler{218, 1, 4}(10001110100000111000110101000100010110010010110010010001010101100010011001010000101000100010101010010100001001101100000110010001010101010001100000110110010010111011000001111000010110101011010010101010101010101010100101))ₜ
+
+julia> wr2.n - w_res.mis_overhead
+2.1999999999999886
+
+julia> map_configs_back(w_res, [wr2])
+1-element Vector{Vector{Int64}}:
+ [0, 1, 0, 0, 1, 0, 0, 1, 1, 0]
 ```
+
+Yep! We get exactly the same ground state.

examples/petersen.jl

@@ -15,8 +15,8 @@ G, tape = apply_gadgets!(copy(ug))
 locs = coordinates(G)
 
 using GraphTensorNetworks
-s1 = solve(Independence(g), "size max")
-s2 = solve(Independence(SimpleGraph(G)), "size max")
+s1 = solve(IndependentSet(g), SizeMax())
+s2 = solve(IndependentSet(SimpleGraph(G)), SizeMax())
 mis_overhead0 = 2 * nv(g) * (nv(g)-1) + nv(g)
 mis_overhead1 = sum(x->mis_overhead(x[1]), tape)
 s1[].n == s2[].n - mis_overhead0 - mis_overhead1

project/createmap.jl

@@ -2,7 +2,7 @@ using UnitDiskMapping, GraphTensorNetworks, Graphs
 
 function mapped_entry_to_compact(s::Pattern)
     locs, g, pins = mapped_graph(s)
-    a = solve(Independence(g; openvertices=pins), "size max")
+    a = solve(IndependentSet(g; openvertices=pins), SizeMax())
     b = mis_compactify!(copy(a))
     n = length(a)
     d = Dict{Int,Int}()  # the mapping from bad to good
@@ -27,7 +27,7 @@ end
 # from mapped graph bounary configuration to compact bounary configuration
 function source_entry_to_configs(s::Pattern)
     locs, g, pins = source_graph(s)
-    a = solve(Independence(g, openvertices=pins), "configs max")
+    a = solve(IndependentSet(g, openvertices=pins), ConfigsMax())
     d = Dict{Int,Vector{BitVector}}()  # the mapping from bad to good
     for i=1:length(a)
         d[i-1] = [BitVector(s) for s in a[i].c.data]
@@ -38,8 +38,8 @@ end
 function compute_mis_overhead(s)
     locs1, g1, pins1 = source_graph(s)
     locs2, g2, pins2 = mapped_graph(s)
-    m1 = mis_compactify!(solve(Independence(g1, openvertices=pins1), "size max"))
-    m2 = mis_compactify!(solve(Independence(g2, openvertices=pins2), "size max"))
+    m1 = mis_compactify!(solve(IndependentSet(g1, openvertices=pins1), SizeMax()))
+    m2 = mis_compactify!(solve(IndependentSet(g2, openvertices=pins2), SizeMax()))
     @assert nv(g1) == length(locs1) && nv(g2) == length(locs2)
     sig, diff = UnitDiskMapping.is_diff_by_const(GraphTensorNetworks.content.(m1), GraphTensorNetworks.content.(m2))
     @assert sig

project/map_config_back.jl

@@ -4,8 +4,8 @@ using GraphTensorNetworks, Graphs
 
 function all_configurations(p::Pattern)
     mlocs, mg, mpins = mapped_graph(p)
-    gp = Independence(mg, openvertices=mpins)
-    res = solve(gp, "configs max")
+    gp = IndependentSet(mg, openvertices=mpins)
+    res = solve(gp, ConfigsMax())
     configs = []
     for element in res
         for bs in element.c.data

src/mapping.jl

@@ -254,30 +254,42 @@ function center_location(tc::CopyLine; padding::Int)
 end
 function copyline_locations(tc::CopyLine; padding::Int)
     s = 4
+    nline = 0
     I, J = center_location(tc; padding=padding)
     locations = _weight_type(tc)[]
     # grow up
-    for i=I+s*(tc.vstart-tc.hslot)+1:I             # even number of nodes up
-        push!(locations, _weight2(tc, i, J))
+    start = I+s*(tc.vstart-tc.hslot)+1
+    if tc.vstart < tc.hslot
+        nline += 1
+    end
+    for i=I:-1:start             # even number of nodes up
+        push!(locations, _weighted(tc, i, J, 1+(i!=start)))   # half weight on last node
     end
     # grow down
-    for i=I:I+s*(tc.vstop-tc.hslot)-1              # even number of nodes down
+    stop = I+s*(tc.vstop-tc.hslot)-1
+    if tc.vstop > tc.hslot
+        nline += 1
+    end
+    for i=I:stop              # even number of nodes down
         if i == I
-            push!(locations, _weight2(tc, i+1, J+1))
+            push!(locations, _weighted(tc, i+1, J+1, 2))
         else
-            push!(locations, _weight2(tc, i, J))
+            push!(locations, _weighted(tc, i, J, 1+(i!=stop)))
         end
     end
     # grow right
-    for j=J+2:J+s*(tc.hstop-tc.vslot)-1            # even number of nodes right
-        push!(locations, _weight2(tc, I, j))
+    stop = J+s*(tc.hstop-tc.vslot)-1
+    if tc.hstop > tc.vslot
+        nline += 1
     end
-    push!(locations, _weight1(tc, I, J+1))                     # center node
+    for j=J+2:stop            # even number of nodes right
+        push!(locations, _weighted(tc, I, j, 1 + (j!=stop)))   # half weight on last node
+    end
+    push!(locations, _weighted(tc, I, J+1, nline))                     # center node
     return locations
 end
 _weight_type(::CopyLine{UnWeighted}) = SimpleNode{Int}
-_weight2(::CopyLine{UnWeighted}, i, j) = SimpleNode(i, j)
-_weight1(::CopyLine{UnWeighted}, i, j) = SimpleNode(i, j)
+_weighted(::CopyLine{UnWeighted}, i, j, w) = SimpleNode(i, j)
 
 export ugrid
 function ugrid(mode, g::SimpleGraph, vertex_order::AbstractVector{Int}; padding=2, nrow=nv(g))
@@ -342,9 +354,20 @@ end
 export mis_overhead_copylines
 function mis_overhead_copylines(ug::UGrid{WC,W}) where {WC,W}
     sum(ug.lines) do line
-        locs = copyline_locations(line; padding=ug.padding)
+        mis_overhead_copyline(line)
+    end
+end
+
+function mis_overhead_copyline(line::CopyLine{W}) where {W}
+    if W === Weighted
+        s = 4
+        return (line.hslot - line.vstart) * s +
+            (line.vstop - line.hslot) * s +
+            max((line.hstop - line.vslot) * s - 2, 0)
+    else
+        locs = copyline_locations(line; padding=2)
         @assert length(locs) % 2 == 1
-        W === Weighted ? length(locs)-1 : length(locs) ÷ 2
+        return length(locs) ÷ 2
     end
 end
 
@@ -360,20 +383,23 @@ end
 """
     map_graph([mode=Weighted(),] g::SimpleGraph; vertex_order=Branching(), ruleset=[...])
 
-Map a graph to a unit disk grid graph that being "equivalent" to the original graph.
+Map a graph to a unit disk grid graph that being "equivalent" to the original graph, and return a `MappingResult` instance.
 Here "equivalent" means a maximum independent set in the grid graph can be mapped back to
 a maximum independent set of the original graph in polynomial time.
 
+Positional Arguments
+-------------------------------------
+* `mode` is optional, it can be `Weighted()` (default) or `UnWeighted()`.
+* `g` is a graph instance, check the documentation of [`Graphs`](https://juliagraphs.org/Graphs.jl/dev/) for details.
 
-* `mode` is optional, it can be `Weighted()` (default) or `UnWeighted`.
+Keyword Arguments
+-------------------------------------
 * `vertex_order` specifies the order finding algorithm for vertices.
 Different vertex orders have different path width, i.e. different depth of mapped grid graph.
 It can be a vector or one of the following inputs
     * `Greedy()` fast but not optimal.
     * `Branching()` slow but optimal.
 * `ruleset` specifies and extra set of optimization patterns (not the crossing patterns).
-
-Returns a `MappingResult` instance.
 """
 function map_graph(g::SimpleGraph; vertex_order=Branching(), ruleset=default_simplifier_ruleset(UnWeighted()))
     map_graph(UnWeighted(), g; ruleset=ruleset, vertex_order=vertex_order)
@@ -388,7 +414,23 @@ function map_graph(mode, g::SimpleGraph; vertex_order=Branching(), ruleset=defau
     return MappingResult(ug, vcat(tape, tape2) , mis_overhead0 + mis_overhead1 + mis_overhead2)
 end
 
-map_configs_back(r::MappingResult{<:Cell}, configs::AbstractVector) = unapply_gadgets!(copy(r.grid_graph), r.mapping_history, copy.(configs))[2]
+"""
+    map_configs_back(res::MappingResult, configs::AbstractVector)
+
+Map MIS solutions for the mapped graph to a solution for the source graph.
+"""
+function map_configs_back(res::MappingResult, configs::AbstractVector)
+    cs = map(configs) do cfg
+        c = zeros(Int, size(res.grid_graph.content))
+        for (i, loc) in enumerate(findall(!isempty, res.grid_graph.content))
+            c[loc] = cfg[i]
+        end
+        c
+    end
+    return _map_configs_back(res, cs)
+end
+_map_configs_back(r::MappingResult{<:Cell}, configs::AbstractVector{<:AbstractMatrix}) = unapply_gadgets!(copy(r.grid_graph), r.mapping_history, copy.(configs))[2]
+
 default_simplifier_ruleset(::UnWeighted) = vcat([rotated_and_reflected(rule) for rule in simplifier_ruleset]...)
 default_simplifier_ruleset(::Weighted) = weighted.(default_simplifier_ruleset(UnWeighted()))