Compute graphs

.editorconfig

@@ -0,0 +1,2 @@
+[*.jl]
+indent_size = 2

.gitignore

@@ -26,3 +26,4 @@ docs/site/
 # committed for packages, but should be committed for applications that require a static
 # environment.
 Manifest.toml
+/coverage/

DEC/Project.toml

@@ -0,0 +1,31 @@
+name = "DEC"
+uuid = "e670b126-1168-4583-bd0f-29deacb39f6a"
+authors = ["Owen Lynch <[email protected]>"]
+version = "0.1.0"
+
+[deps]
+CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
+Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
+CombinatorialSpaces = "b1c52339-7909-45ad-8b6a-6e388f7c67f2"
+Crayons = "a8cc5b0e-0ffa-5ad4-8c14-923d3ee1735f"
+Decapodes = "679ab3ea-c928-4fe6-8d59-fd451142d391"
+GeometryBasics = "5c1252a2-5f33-56bf-86c9-59e7332b4326"
+MLStyle = "d8e11817-5142-5d16-987a-aa16d5891078"
+Metatheory = "e9d8d322-4543-424a-9be4-0cc815abe26c"
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
+StructEquality = "6ec83bb0-ed9f-11e9-3b4c-2b04cb4e219c"
+
+[compat]
+CairoMakie = "0.12.5"
+Colors = "0.12.11"
+CombinatorialSpaces = "0.6.7"
+Crayons = "4.1.1"
+Decapodes = "0.5.5"
+GeometryBasics = "0.4.11"
+MLStyle = "0.4.17"
+OrdinaryDiffEq = "6.86.0"
+Random = "1.11.0"
+Reexport = "1.2.2"
+StructEquality = "2.1.0"

DEC/src/DEC.jl

@@ -0,0 +1,20 @@
+module DEC
+using MLStyle
+using Reexport
+using StructEquality
+import Metatheory
+using Metatheory: EGraph, EGraphs, Id, VECEXPR_FLAG_ISCALL, VECEXPR_FLAG_ISTREE, VECEXPR_META_LENGTH
+import Metatheory: extract!
+
+import Base: +, -
+import Base: *
+
+include("HashColor.jl")
+include("Signature.jl")
+include("Roe.jl")
+include("SSAExtract.jl")
+include("Luke.jl")
+
+@reexport using .SSAExtract
+
+end # module DEC

DEC/src/HashColor.jl

@@ -0,0 +1,32 @@
+module HashColor
+export hashcolor, hashcrayon
+
+using Colors
+using Random
+using Crayons
+
+randunif(rng, range) = rand(rng) * (range[2] - range[1]) + range[1]
+
+"""
+Returns a Color generated randomly by hashing `x`.
+
+This uses the LCHuv space to sample uniformly across the human visual spectrum.
+"""
+function hashcolor(x; lightnessrange=(0.,100.), chromarange=(0.,100.), huerange=(0.,360.))
+  h = hash(x)
+  rng = MersenneTwister(h)
+  l = randunif(rng, lightnessrange)
+  c = randunif(rng, chromarange)
+  h = randunif(rng, huerange)
+  LCHuv{Float64}(l, c, h)
+end
+
+"""
+Returns a Crayon with foreground color given by `hashcolor`
+"""
+function hashcrayon(x; lightnessrange=(0.,100.), chromarange=(0.,100.), huerange=(0.,360.))
+  c = hashcolor(x; lightnessrange, chromarange, huerange)
+  Crayon(foreground=RGB24(RGB{Float64}(c)).color)
+end
+
+end

DEC/src/Luke.jl

@@ -0,0 +1,75 @@
+import Decapodes
+using StructEquality
+
+@struct_hash_equal struct TypedApplication
+    fn::Function
+    sorts::Vector{Sort}
+end
+
+const TA = TypedApplication
+
+function Base.show(io::IOBuffer, ta::TA)
+  print(io, Expr(:call, ta.fn, ta.sorts...))
+end
+
+function precompute_matrices(sd, hodge)::Dict{TypedApplication, Any}
+    Dict{TypedApplication, Any}(
+        # Regular Hodge Stars
+        TA(★, Sort[PrimalForm(0)]) => Decapodes.dec_mat_hodge(0, sd, hodge),
+        TA(★, Sort[PrimalForm(1)]) => Decapodes.dec_mat_hodge(1, sd, hodge),
+        TA(★, Sort[PrimalForm(2)]) => Decapodes.dec_mat_hodge(2, sd, hodge),
+
+        # Inverse Hodge Stars
+        TA(★, Sort[DualForm(0)]) => Decapodes.dec_mat_inverse_hodge(1, sd, hodge), # why is this 1???
+        TA(★, Sort[DualForm(1)]) => Decapodes.dec_pair_inv_hodge(Val{1}, sd, hodge), # Special since Geo is a solver
+        TA(★, Sort[DualForm(2)]) => Decapodes.dec_mat_inverse_hodge(0, sd, hodge),
+
+        # Differentials
+        TA(d, Sort[PrimalForm(0)]) => Decapodes.dec_mat_differential(0, sd),
+        TA(d, Sort[PrimalForm(1)]) => Decapodes.dec_mat_differential(1, sd),
+
+        # Dual Differentials
+        TA(d, Sort[DualForm(0)]) => Decapodes.dec_mat_dual_differential(0, sd),
+        TA(d, Sort[DualForm(1)]) => Decapodes.dec_mat_dual_differential(1, sd),
+
+        # Wedge Products
+        TA(∧, Sort[PrimalForm(0), PrimalForm(1)]) => Decapodes.dec_pair_wedge_product(Tuple{0,1}, sd),
+        TA(∧, Sort[PrimalForm(1), PrimalForm(0)]) => Decapodes.dec_pair_wedge_product(Tuple{1,0}, sd),
+        TA(∧, Sort[PrimalForm(0), PrimalForm(2)]) => Decapodes.dec_pair_wedge_product(Tuple{0,2}, sd),
+        TA(∧, Sort[PrimalForm(2), PrimalForm(0)]) => Decapodes.dec_pair_wedge_product(Tuple{2,0}, sd),
+        TA(∧, Sort[PrimalForm(1), PrimalForm(1)]) => Decapodes.dec_pair_wedge_product(Tuple{1,1}, sd),
+
+        # Primal-Dual Wedge Products
+        TA(∧, Sort[PrimalForm(1), DualForm(1)]) => Decapodes.dec_wedge_product_pd(Tuple{1,1}, sd),
+        TA(∧, Sort[PrimalForm(0), DualForm(1)]) => Decapodes.dec_wedge_product_pd(Tuple{0,1}, sd),
+        TA(∧, Sort[PrimalForm(1), DualForm(1)]) => Decapodes.dec_wedge_product_dp(Tuple{1,1}, sd),
+        TA(∧, Sort[PrimalForm(1), DualForm(0)]) => Decapodes.dec_wedge_product_dp(Tuple{1,0}, sd),
+
+        # Dual-Dual Wedge Products
+        # TA(∧, Sort[DualForm(1), DualForm(1)]) => Decapodes.dec_wedge_product_dd(Tuple{1,1}, sd),
+        TA(∧, Sort[DualForm(1), DualForm(0)]) => Decapodes.dec_wedge_product_dd(Tuple{1,0}, sd),
+        TA(∧, Sort[DualForm(0), DualForm(1)]) => Decapodes.dec_wedge_product_dd(Tuple{0,1}, sd),
+
+        # # Dual-Dual Interior Products
+        # :ι₁₁ => interior_product_dd(Tuple{1,1}, sd)
+        # :ι₁₂ => interior_product_dd(Tuple{1,2}, sd)
+
+        # # Dual-Dual Lie Derivatives
+        # :ℒ₁ => ℒ_dd(Tuple{1,1}, sd)
+
+        # # Dual Laplacians
+        # :Δᵈ₀ => Δᵈ(Val{0},sd)
+        # :Δᵈ₁ => Δᵈ(Val{1},sd)
+
+        # # Musical Isomorphisms
+        # :♯ => Decapodes.dec_♯_p(sd)
+        # :♯ᵈ => Decapodes.dec_♯_d(sd)
+
+        # :♭ => Decapodes.dec_♭(sd)
+
+        # # Averaging Operator
+        # :avg₀₁ => Decapodes.dec_avg₀₁(sd)
+
+        # :neg => x -> -1 .* x
+    )
+end

DEC/src/OperatorStorage.jl

@@ -0,0 +1,4 @@
+struct OperatorStorage
+    hodge::Tuple{}
+end
+