update

Author: AFeuerpfeil

src/AbstractWavefunctionMC.jl

@@ -34,7 +34,7 @@ function Carlo.init!(mc::AbstractWavefunctionMC{N}, ctx::MCContext, params::Abst
     mc_state = state(mc)
     N_active, dynamic_pos = dynamic_positions(mc)
 
-    mc_state[:] = coordinate_projector(mc).(rand(ctx.rng, distribution(mc), N))
+    mc_state[:] = [coordinate_projector(mc)(rand(ctx.rng, distribution(mc))) for _ in 1:N]
 
     mc_state.logdensity = logdensity(wavefunction(mc), position(mc_state).buffer)
     mc_state.num_accepts = 0
@@ -62,7 +62,7 @@ end
 
 function _update_coordinates(ctx::MCContext, dynamic_pos, bare_position, d, coordinate_trafo, coordinate_proj, wavefunc::T, buffer::X, mc_state) where {T<:AbstractWavefunction, X<:Buffer}
     @inbounds for dim in dynamic_pos
-        x_new = coordinate_proj(bare_position[dim] + rand(ctx.rng, d))
+        x_new = coordinate_proj(bare_position[dim] .+ rand(ctx.rng, d))
         x_new_transformed = coordinate_trafo(x_new)
 
         logα = delta_logdensity(wavefunc, x_new_transformed, buffer.buffer, dim)

src/WavefunctionMC.jl

@@ -52,11 +52,24 @@ function WavefunctionMC(params::AbstractDict)
     N = inputlength(wavefunction)
     sigma_dist = get(params, :sigma_distribution, 0.3)
     distribution = get(params, :distribution, S <: Complex ? ComplexNormal(0, sigma_dist) : Normal(0, sigma_dist))
-    position = coordinate_proj.(100 * rand(distribution, N))
+    position = [coordinate_proj(100 * rand(distribution)) for _ in 1:N]
 
     observables = get(params, :observables, NoObservables())
     dynamic_pos = get(params, :dynamic_positions, (N, 1:N))
-    return WavefunctionMC{N}(State(position, 0.0, coordinate_transf), distribution, coordinate_proj, wavefunction, observables; adapt_interval = div(get(params, :thermalization, 10_000), 10), dynamic_positions = dynamic_pos)
+
+    adapt_interval = get(params, :adapt_interval,div(get(params, :thermalization, 10_000), 10))
+    coordinate_update = get(params, :coordinate_update, CoordinateUpdate())
+    target_accept = get(params, :target_accept, optimal_acceptance_rate(coordinate_update))
+    adaptive = get(params, :adaptive, true)
+    active_during_run = get(params, :active_during_run, false)
+    update_distribution = get(params, :update_distribution, (d, adjustment) -> begin
+        sigma_new = d.σ * Base.exp(-adjustment)
+        return typeof(d)(d.μ, sigma_new)
+    end)
+    adaptor = adaptive ? AcceptanceAdapter(; acceptance_rate = target_accept, adapt_interval = adapt_interval, update_distribution = update_distribution, active_during_run = active_during_run) : NoAcceptanceAdapter()
+
+
+    return WavefunctionMC{N}(State(position, 0.0, coordinate_transf), distribution, coordinate_proj, wavefunction, observables; dynamic_positions = dynamic_pos, adaptor = adaptor, coordinate_update = coordinate_update)
 end
 
 function Carlo.write_checkpoint(mc::WavefunctionMC, out::HDF5.Group)

src/buffer/buffer.jl

@@ -18,7 +18,7 @@ Base.length(b::Buffer) = length(parent(b))
 Base.@propagate_inbounds Base.getindex(b::Buffer, i) = getindex(parent(b), i)
 Base.firstindex(b::Buffer) = firstindex(parent(b))
 Base.lastindex(b::Buffer) = lastindex(parent(b))
-Base.@propagate_inbounds Base.setindex!(b::Buffer, v, i) = (parent(b)[i] = b.map(v))
+Base.@propagate_inbounds Base.setindex!(b::Buffer, v, i) = (parent(b)[i] = b.map.(v))
 
 function Buffer(def::T, size; map::G = Base.identity) where {T, G}
     return Buffer{T, AbstractVector{T}, G}(fill(def, size), map)