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Changes to swap rule and to acc_tuner #26

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Changes to swap rule and to acc_tuner #26

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1a9e207
Changes to dist_fun and acc_tuners
edoardociscato Aug 18, 2018
45b79e5
missing s
edoardociscato Aug 18, 2018
0e82520
Add vector acc_tuners to examples
edoardociscato Aug 18, 2018
183e604
Merge pull request #1 from floswald/master
edoardociscato Sep 11, 2018
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12 changes: 6 additions & 6 deletions src/mopt/AlgoBGP.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -369,7 +369,7 @@ mutable struct MAlgoBGP <: MAlgo
anim :: Plots.Animation
dist_fun :: Function

function MAlgoBGP(m::MProb,opts=Dict("N"=>3,"maxiter"=>100,"maxtemp"=> 2,"coverage"=>0.125,"sigma_update_steps"=>10,"sigma_adjust_by"=>0.01,"smpl_iters"=>1000,"parallel"=>false,"maxdists"=>[0.5 for i in 1:3],"acc_tuner"=>2.0))
function MAlgoBGP(m::MProb,opts=Dict("N"=>3,"maxiter"=>100,"maxtemp"=> 2,"coverage"=>0.125,"sigma_update_steps"=>10,"sigma_adjust_by"=>0.01,"smpl_iters"=>1000,"parallel"=>false,"maxdists"=>[0.0 for i in 1:3],"acc_tuners"=>[2.0 for i in 1:3]))

init_sd = OrderedDict{Symbol,Float64}()
if opts["N"] > 1
Expand All @@ -388,17 +388,17 @@ mutable struct MAlgoBGP <: MAlgo
# @assert init_sd[k] == b / quantile(Normal(),0.975)
init_sd[k] = b / quantile(Normal(),0.975)
end
BGPChains = BGPChain[BGPChain(i,opts["maxiter"],m,collect(values(init_sd)) .* temps[i],get(opts,"sigma_update_steps",10),get(opts,"sigma_adjust_by",0.01),get(opts,"smpl_iters",1000),get(opts,"maxdists",[0.5 for j in 1:opts["N"]])[i],get(opts,"acc_tuner",2.0)) for i in 1:opts["N"]]
BGPChains = BGPChain[BGPChain(i,opts["maxiter"],m,collect(values(init_sd)) .* temps[i],get(opts,"sigma_update_steps",10),get(opts,"sigma_adjust_by",0.01),get(opts,"smpl_iters",1000),get(opts,"maxdists",[0.0 for j in 1:opts["N"]])[i],get(opts,"acc_tuners",[2.0 for j in 1:opts["N"]])[i]) for i in 1:opts["N"]]
else
temps = [1.0]
for (k,v) in m.params_to_sample
b = (v[:ub]-v[:lb])*opts["coverage"]
init_sd[k] = b / quantile(Normal(),0.975)
end
# println(init_sd)
BGPChains = BGPChain[BGPChain(1,opts["maxiter"],m,collect(values(init_sd)) .* temps[1],get(opts,"sigma_update_steps",10),get(opts,"sigma_adjust_by",0.01),get(opts,"smpl_iters",1000),get(opts,"maxdists",[0.5 for j in 1:opts["N"]])[1],get(opts,"acc_tuner",2.0)) ]
BGPChains = BGPChain[BGPChain(1,opts["maxiter"],m,collect(values(init_sd)) .* temps[1],get(opts,"sigma_update_steps",10),get(opts,"sigma_adjust_by",0.01),get(opts,"smpl_iters",1000),get(opts,"maxdists",[0.0 for j in 1:opts["N"]])[1],get(opts,"acc_tuners",[2.0 for j in 1:opts["N"]])[1]) ]
end
return new(m,opts,0,BGPChains, Animation(),abs)
return new(m,opts,0,BGPChains, Animation(),-)
end
end

Expand Down Expand Up @@ -536,8 +536,8 @@ function exchangeMoves!(algo::MAlgoBGP)
# BGP version
# exchange i with j if rho(S(z_j),S(data)) < epsilon_i
@debug(logger,"Exchanging $i with $j? Distance is $(algo.dist_fun(evj.value - evi.value))")
@debug(logger,"Exchange: $(algo.dist_fun(evj.value - evi.value) < algo["maxdists"][i])")
if algo.dist_fun(evj.value - evi.value) < algo["maxdists"][i]
@debug(logger,"Exchange: $(algo.dist_fun(evj.value, evi.value) < algo["maxdists"][i])")
if algo.dist_fun(evj.value, evi.value) < algo["maxdists"][i]
swap_ev_ij!(algo,i,j)
end
end
Expand Down
6 changes: 3 additions & 3 deletions src/mopt/Examples.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ function parallelNormal(niter=200)
"parallel"=>true,
"maxdists"=>[0.05 for i in 1:nchains],
"mixprob"=>0.3,
"acc_tuner"=>12.0,
"acc_tuners"=>[12.0 for i in 1:nchains],
"animate"=>false)

# plot slices of objective function
Expand Down Expand Up @@ -90,7 +90,7 @@ function serialNormal(niter=200)
"parallel"=>false,
"maxdists"=>[0.05 for i in 1:nchains],
"mixprob"=>0.3,
"acc_tuner"=>12.0,
"acc_tuners"=>[0.05 for i in 1:nchains],
"animate"=>false)

# plot slices of objective function
Expand Down Expand Up @@ -135,7 +135,7 @@ function BGP_example()
"coverage"=>0.005, # i.e. this gives you a 95% CI about the current parameter on chain number 1.
"maxdists"=>linspace(0.025, 2,nchains),
"mixprob"=>0.3,
"acc_tuner"=>12.0,
"acc_tuners"=>[0.05 for i in 1:nchains],
"animate"=>false)
# setup the BGP algorithm
MA = MAlgoBGP(mprob,opts)
Expand Down