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Project.toml

@@ -4,6 +4,7 @@ authors = ["Christoph Ortner <[email protected]> and contributors"]
 version = "0.0.1"
 
 [deps]
+ACE = "3e8ccfd2-c8b0-11ea-32f1-f3a5990fd77a"
 ACEbase = "14bae519-eb20-449c-a949-9c58ed33163e"
 ACEcore = "44c1e890-45d1-48ea-94d6-c2ea5b573f71"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
@@ -15,15 +16,14 @@ Polynomials4ML = "03c4bcba-a943-47e9-bfa1-b1661fc2974f"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 
 [compat]
+ACEbase = "0.2"
 ACEcore = "0.0.1"
 BenchmarkTools = "1"
 ForwardDiff = "0.10"
+JSON = "0.21"
 ObjectPools = "0.0.2"
-Polynomials4ML = "0.0.2"
 julia = "1"
-JSON = "0.21"
-ACEbase = "0.2"
-
+Polynomials4ML = "0.0.6"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

examples/backup/bflow-v-1trans.jl

@@ -0,0 +1,20 @@
+using ACE
+using Polynomials4ML
+using ACEpsi
+
+const ↑, ↓, ∅ = '↑','↓','∅'
+
+Nel = 8
+Σ = vcat(rand([↑],Int(ceil(Nel/2))),rand([↓],Nel - Int(ceil(Nel/2))))
+trans = λ("r -> 2/pi * atan(r)")
+MaxDeg = [4, 4]
+polys = Polynomials4ML.legendre_basis(maximum(MaxDeg))
+U = ACEpsi.BFwf(Nel, polys; ν=length(MaxDeg), totdeg = maximum(MaxDeg), trans = trans,sd_admissible = bb -> (length(bb) == 0 || all([bb[i][1] <= MaxDeg[length(bb)] for i = 1:length(bb)])))
+
+X = rand(Nel)
+ACEpsi.evaluate(U,X,Σ)
+ACEpsi.gradient(U,X,Σ)
+
+
+
+

examples/backup/bflow-v-mtrans.jl

@@ -0,0 +1,22 @@
+using ACE
+using Polynomials4ML
+using ACEpsi
+
+const ↑, ↓, ∅ = '↑','↓','∅'
+
+Nel = 8
+Σ = vcat(rand([↑],Int(ceil(Nel/2))),rand([↓],Nel - Int(ceil(Nel/2))))
+
+pos = [-70.,-50.,-30.,-10.,10.,30.,50.,70.]
+trans = [λ("r -> atan(r+70.0)"),λ("r -> atan(r+50.0)"),λ("r -> atan(r+30.0)"),λ("r -> atan(r+10.0)"),λ("r -> atan(r-10.0)"),λ("r -> atan(r-30.0)"),λ("r -> atan(r-50.0)"),λ("r -> atan(r-70.0)")]
+tpos = reduce(vcat,pos)
+pos = reduce(vcat,pos)
+M = length(pos)
+MaxDeg = [6, 6, 6]
+
+polys = Polynomials4ML.legendre_basis(maximum(MaxDeg))
+wf = ACEpsi.BFwf(Nel, polys, x -> sqrt(1+x^2); pos = pos, tpos = tpos, ν=length(MaxDeg[1]), totdeg = maximum(MaxDeg), trans = trans,sd_admissible = bb -> (length(bb) == 0 || all([bb[i][1] <= MaxDeg[length(bb)] for i = 1:length(bb)])))
+
+X = rand(Nel)
+ACEpsi.evaluate(U,X,Σ)
+ACEpsi.gradient(U,X,Σ)

profile/profile_bflow.jl

@@ -0,0 +1,47 @@
+using Polynomials4ML, ACEcore, ACEpsi, ACEbase, Printf
+using ACEpsi: BFwf, gradient, evaluate, laplacian 
+using LinearAlgebra
+using BenchmarkTools
+
+##
+
+N = 8
+Σ = vcat(rand([↑],Int(ceil(N/2))),rand([↓],N - Int(ceil(N/2))))
+
+pos = [-70.,-50.,-30.,-10.,10.,30.,50.,70.]
+trans = [λ("r -> atan(r+70.0)"),λ("r -> atan(r+50.0)"),λ("r -> atan(r+30.0)"),λ("r -> atan(r+10.0)"),λ("r -> atan(r-10.0)"),λ("r -> atan(r-30.0)"),λ("r -> atan(r-50.0)"),λ("r -> atan(r-70.0)")]
+tpos = reduce(vcat,pos)
+pos = reduce(vcat,pos)
+M = length(pos)
+MaxDeg = [6, 6, 6]
+
+polys = Polynomials4ML.legendre_basis(maximum(MaxDeg))
+wf = BFwf(N, polys, x -> sqrt(1+x^2); pos = pos, tpos = tpos, ν=length(MaxDeg[1]), totdeg = maximum(MaxDeg), trans = trans,sd_admissible = bb -> (length(bb) == 0 || all([bb[i][1] <= MaxDeg[length(bb)] for i = 1:length(bb)])))
+
+##
+
+X = 2 * rand(Nel) .- 1
+Σ = rand([↑, ↓], Nel)
+wf(X, Σ)
+gradient(wf, X, Σ)
+laplacian(wf, X, Σ)
+
+## 
+
+@info("evaluate")
+@btime wf($X, Σ)
+
+@info("gradient")
+@btime gradient($wf, $X, $Σ)
+
+@info("laplacian")
+@btime laplacian($wf, $X, $Σ)
+
+
+##
+
+# @profview let wf=wf, X=X
+#    for nrun = 1:50_000 
+#       laplacian(wf, X)
+#    end
+# end

profile/profile_bflow1.jl → profile/profile_bflows.jl

@@ -1,34 +1,35 @@
-
-
 using Polynomials4ML, ACEcore, ACEpsi, ACEbase, Printf
 using ACEpsi: BFwf, gradient, evaluate, laplacian 
 using LinearAlgebra
 using BenchmarkTools
 
 ##
 
-Nel = 10
-polys = legendre_basis(15)
+const ↑, ↓, ∅ = '↑','↓','∅'
+Nel = 8
+polys = legendre_basis(6)
 wf = BFwf(Nel, polys; ν=3)
 
 
 ##
 
 X = 2 * rand(Nel) .- 1
-wf(X)
-gradient(wf, X)
-laplacian(wf, X)
+Σ = rand([↑, ↓], Nel)
+wf(X, Σ)
+gradient(wf, X, Σ)
+laplacian(wf, X, Σ)
 
 ## 
 
 @info("evaluate")
-@btime $wf($X)
+@btime wf($X, Σ)
 
 @info("gradient")
-@btime gradient($wf, $X)
+@btime gradient($wf, $X, $Σ)
 
 @info("laplacian")
-@btime laplacian($wf, $X)
+@btime laplacian($wf, $X, $Σ)
+
 
 ##
 

src/ACEpsi.jl

@@ -2,5 +2,6 @@ module ACEpsi
 
 include("bflow.jl")
 include("envelope.jl")
+include("bflow-mts.jl")
 
 end