Merge pull request #99 from mschauer/newversion

Newversion

Author: mschauer

scripts/diffbridge_bis.jl

@@ -18,6 +18,7 @@ end
 # This one could work for Boomerang 1d as well
 """
     move_forward!(τ, t, x, θ, B::Boomerang)
+
 Updates the position `x`, velocity `θ` and time `t` of the
 process after a time step equal to `τ` according to the deterministic
 dynamics of the `Boomerang` sampler which are the Hamiltonian
@@ -35,11 +36,12 @@ function move_forward!(τ, t, x, θ, B::Union{Boomerang, FactBoomerang})
 end
 
 """
-        reflect!(i, x, θ, F)
+        reflect!(i, ∇ϕx, x, θ, F)
 
-Reflection rule of sampler `F` at reflection time.
+Reflection rule of sampler `F` at reflection time, `∇ϕx`: inner product
+of `∇ϕ` and `x``. 
 `i`: coordinate which flips sign, `x`: position, `θ`: velocity (position
-not used for the `ZigZag` and `FactBoomerang`.)
+and inner product not used for the `ZigZag` and `FactBoomerang`.)
 """
 function reflect!(i, ∇ϕx::Number, x, θ, F::Union{ZigZag, FactBoomerang})
     θ[i] = -θ[i]
@@ -80,10 +82,10 @@ function move_forward(τ, t, x, θ, B::Boomerang1d)
 end
 
 """
-    reflect!(∇ϕx, θ, F::BouncyParticle, Boomerang)
+    reflect!(∇ϕx, x, θ, F::BouncyParticle, Boomerang)
 
 Reflection rule of sampler `F` at reflection time.
-x`: position, `θ`: velocity
+`x`: position, `θ`: velocity
 """
 function reflect!(∇ϕx, x, θ, F::BouncyParticle)
     θ .-= (2*dot(∇ϕx, θ)/normsq(F.L\∇ϕx))*(F.L'\(F.L\∇ϕx))

src/dynamics.jl

@@ -31,7 +31,7 @@ end
 
 
 """
-    λ(∇ϕ, i, x, θ, Z::FactBoomerang)
+    λ(∇ϕi, i, x, θ, Z::FactBoomerang)
 `i`th Poisson rate of the `FactBoomerang` sampler
 """
 function λ(∇ϕi, i, x, θ, B::FactBoomerang)
@@ -69,14 +69,6 @@ function adapt!(c, i, factor)
     c
 end
 
-"""
-    λ_bar(G, i, x, θ, c, Z)
-
-Computes the bounding rate `λ_bar` at position `x` and velocity `θ`.
-"""
-#λ_bar(G, i, x, θ, c, Z::ZigZag) = pos(ab(G, i, x, θ, c, Z)[1])
-#λ_bar(G, i, x, θ, c, Z::FactBoomerang) = pos(ab(G, i, x, θ, c, Z)[1])
-
 
 function event(i, t, x, θ, Z::Union{ZigZag,FactBoomerang,JointFlow})
     t, i, x[i], θ[i]

src/fact_samplers.jl

@@ -6,25 +6,7 @@ function ab(G, i, x, θ, C::LocalBound, ∇ϕi, vi, Z::ZigZag, args...)
 end
 #(idot(Z.Γ, i, x)  - idot(Z.Γ, i, Z.μ))'*θ[i]),  θ[i]'*idot(Z.Γ, i, θ)
 
-"""
-spdmp_inner!(rng, G, G1, G2, ∇ϕ, t, x, θ, Q, c, b, t_old, (acc, num),
-F::Union{ZigZag,FactBoomerang}, args...; factor=1.5, adapt=false, adaptscale=false)
-
-[Outdated]
-Inner loop of the factorised samplers: the factorised Boomerang algorithm and
-the Zig-Zag sampler. Given a dependency graph `G`, gradient `∇ϕ`,
-current position `x`, velocity `θ`, Queue of events `Q`, time `t`, tuning parameter `c`,
-terms of the affine bounds `a`,`b` and time when the upper bounds were computed `t_old`
 
-The sampler 1) extracts from the queue the first event time. 2) moves deterministically
-according to its dynamics until event time. 3) Evaluates whether the event
-time is a accepted reflection or refreshment time or shadow time. 4) If it is a
-reflection time, the velocity reflects according its reflection rule, if it is a
-refreshment time, the sampler updates the velocity from its prior distribution (Gaussian).
-In both cases, updates `Q` according to the dependency graph `G`. The sampler proceeds
-until the next accepted reflection time or refreshment time. `(num, acc)`
-incrementally counts how many event times occour and how many of those are real reflection times.
-"""
 function spdmp_inner!(rng, G, G2, ∇ϕ, t, x, θ, Q, c::LocalBound, (b, renew), t_old, (acc, num),
  F::Union{ZigZag,FactBoomerang,JointFlow}, args...; factor=1.5, adapt=false, adaptscale=false)
     n = length(x)

src/local.jl

@@ -70,25 +70,6 @@ sλ(∇ϕi, i, x, θ, Z::Union{ZigZag,FactBoomerang,JointFlow}) = λ(∇ϕi, i,
 sλ̄(abc, Δt) = pos(abc[1] + abc[2]*Δt)
 
 
-"""
-    spdmp_inner!(rng, G, G1, G2, ∇ϕ, t, x, θ, Q, c, b, t_old, (acc, num),
-F::Union{ZigZag,FactBoomerang}, args...; factor=1.5, adapt=false, adaptscale=false)
-
-[Outdated]
-Inner loop of the factorised samplers: the factorised Boomerang algorithm and
-the Zig-Zag sampler. Given a dependency graph `G`, gradient `∇ϕ`,
-current position `x`, velocity `θ`, Queue of events `Q`, time `t`, tuning parameter `c`,
-terms of the affine bounds `a`,`b` and time when the upper bounds were computed `t_old`
-
-The sampler 1) extracts from the queue the first event time. 2) moves deterministically
-according to its dynamics until event time. 3) Evaluates whether the event
-time is a accepted reflection or refreshment time or shadow time. 4) If it is a
-reflection time, the velocity reflects according its reflection rule, if it is a
-refreshment time, the sampler updates the velocity from its prior distribution (Gaussian).
-In both cases, updates `Q` according to the dependency graph `G`. The sampler proceeds
-until the next accepted reflection time or refreshment time. `(num, acc)`
-incrementally counts how many event times occour and how many of those are real reflection times.
-"""
 function spdmp_inner!(rng, G, G1, G2, ∇ϕ, t, x, θ, Q, c, b, t_old, (acc, num),
      F::Union{ZigZag,FactBoomerang}, args...; factor=1.5, adapt=false, adaptscale=false)
     n = length(x)

src/sfact.jl

@@ -13,7 +13,7 @@ struct FactTrace{FT,T,S,S2,R} <: Trace
 end
 
 """
-    FactTrace
+    PDMPTrace
 
 See [`Trace`](@ref).
 """

src/trace.jl

@@ -57,6 +57,7 @@ struct Boomerang{U, T, S, LT} <: ContinuousDynamics
     L::LT
 end
 Boomerang(Γ, μ, λ; ρ=0.0) = Boomerang(Γ, μ, λ, ρ, (cholesky(Symmetric(Γ)).L))
+
 """
     FactBoomerang(Γ, μ, λ) <: ContinuousDynamics