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import Printf: @printf
function fullRun(niterations::Integer;
npop::Integer=300,
ncyclesperiteration::Integer=3000,
fractionReplaced::Float32=0.1f0,
verbosity::Integer=0,
topn::Integer=10
)
testConfiguration()
# 1. Start a population on every process
allPops = Future[]
# Set up a channel to send finished populations back to head node
channels = [RemoteChannel(1) for j=1:npopulations]
bestSubPops = [Population(1) for j=1:npopulations]
hallOfFame = HallOfFame()
frequencyComplexity = ones(Float32, actualMaxsize)
curmaxsize = 3
if warmupMaxsize == 0
curmaxsize = maxsize
end
for i=1:npopulations
future = @spawnat :any Population(npop, 3)
push!(allPops, future)
end
# # 2. Start the cycle on every process:
@sync for i=1:npopulations
@async allPops[i] = @spawnat :any run(fetch(allPops[i]), ncyclesperiteration, curmaxsize, copy(frequencyComplexity)/sum(frequencyComplexity), verbosity=verbosity)
end
if verbosity > 0
println("Started!")
end
cycles_complete = npopulations * niterations
if warmupMaxsize != 0
curmaxsize += 1
if curmaxsize > maxsize
curmaxsize = maxsize
end
end
last_print_time = time()
num_equations = 0.0
print_every_n_seconds = 5
equation_speed = Float32[]
for i=1:npopulations
# Start listening for each population to finish:
@async put!(channels[i], fetch(allPops[i]))
end
while cycles_complete > 0
@inbounds for i=1:npopulations
# Non-blocking check if a population is ready:
if isready(channels[i])
# Take the fetch operation from the channel since its ready
cur_pop = take!(channels[i])
bestSubPops[i] = bestSubPop(cur_pop, topn=topn)
#Try normal copy...
bestPops = Population([member for pop in bestSubPops for member in pop.members])
for member in cur_pop.members
size = countNodes(member.tree)
frequencyComplexity[size] += 1
if member.score < hallOfFame.members[size].score
hallOfFame.members[size] = deepcopy(member)
hallOfFame.exists[size] = true
end
end
# Dominating pareto curve - must be better than all simpler equations
dominating = PopMember[]
open(hofFile, "w") do io
println(io,"Complexity|MSE|Equation")
for size=1:actualMaxsize
if hallOfFame.exists[size]
member = hallOfFame.members[size]
if weighted
curMSE = MSE(evalTreeArray(member.tree), y, weights)
else
curMSE = MSE(evalTreeArray(member.tree), y)
end
numberSmallerAndBetter = 0
for i=1:(size-1)
if weighted
hofMSE = MSE(evalTreeArray(hallOfFame.members[i].tree), y, weights)
else
hofMSE = MSE(evalTreeArray(hallOfFame.members[i].tree), y)
end
if (hallOfFame.exists[size] && curMSE > hofMSE)
numberSmallerAndBetter += 1
end
end
betterThanAllSmaller = (numberSmallerAndBetter == 0)
if betterThanAllSmaller
println(io, "$size|$(curMSE)|$(stringTree(member.tree))")
push!(dominating, member)
end
end
end
end
cp(hofFile, hofFile*".bkup", force=true)
# Try normal copy otherwise.
if migration
for k in rand(1:npop, round(Integer, npop*fractionReplaced))
to_copy = rand(1:size(bestPops.members)[1])
cur_pop.members[k] = PopMember(
copyNode(bestPops.members[to_copy].tree),
bestPops.members[to_copy].score)
end
end
if hofMigration && size(dominating)[1] > 0
for k in rand(1:npop, round(Integer, npop*fractionReplacedHof))
# Copy in case one gets used twice
to_copy = rand(1:size(dominating)[1])
cur_pop.members[k] = PopMember(
copyNode(dominating[to_copy].tree)
)
end
end
@async begin
allPops[i] = @spawnat :any let
tmp_pop = run(cur_pop, ncyclesperiteration, curmaxsize, copy(frequencyComplexity)/sum(frequencyComplexity), verbosity=verbosity)
@inbounds @simd for j=1:tmp_pop.n
if rand() < 0.1
tmp_pop.members[j].tree = simplifyTree(tmp_pop.members[j].tree)
tmp_pop.members[j].tree = combineOperators(tmp_pop.members[j].tree)
if shouldOptimizeConstants
tmp_pop.members[j] = optimizeConstants(tmp_pop.members[j])
end
end
end
tmp_pop = finalizeScores(tmp_pop)
tmp_pop
end
put!(channels[i], fetch(allPops[i]))
end
cycles_complete -= 1
cycles_elapsed = npopulations * niterations - cycles_complete
if warmupMaxsize != 0 && cycles_elapsed % warmupMaxsize == 0
curmaxsize += 1
if curmaxsize > maxsize
curmaxsize = maxsize
end
end
num_equations += ncyclesperiteration * npop / 10.0
end
end
sleep(1e-3)
elapsed = time() - last_print_time
#Update if time has passed, and some new equations generated.
if elapsed > print_every_n_seconds && num_equations > 0.0
# Dominating pareto curve - must be better than all simpler equations
current_speed = num_equations/elapsed
average_over_m_measurements = 10 #for print_every...=5, this gives 50 second running average
push!(equation_speed, current_speed)
if length(equation_speed) > average_over_m_measurements
deleteat!(equation_speed, 1)
end
average_speed = sum(equation_speed)/length(equation_speed)
curMSE = baselineMSE
lastMSE = curMSE
lastComplexity = 0
if verbosity > 0
@printf("\n")
@printf("Cycles per second: %.3e\n", round(average_speed, sigdigits=3))
cycles_elapsed = npopulations * niterations - cycles_complete
@printf("Progress: %d / %d total iterations (%.3f%%)\n", cycles_elapsed, npopulations * niterations, 100.0*cycles_elapsed/(npopulations*niterations))
@printf("Hall of Fame:\n")
@printf("-----------------------------------------\n")
@printf("%-10s %-8s %-8s %-8s\n", "Complexity", "MSE", "Score", "Equation")
@printf("%-10d %-8.3e %-8.3e %-.f\n", 0, curMSE, 0f0, avgy)
end
for size=1:actualMaxsize
if hallOfFame.exists[size]
member = hallOfFame.members[size]
if weighted
curMSE = MSE(evalTreeArray(member.tree), y, weights)
else
curMSE = MSE(evalTreeArray(member.tree), y)
end
numberSmallerAndBetter = 0
for i=1:(size-1)
if weighted
hofMSE = MSE(evalTreeArray(hallOfFame.members[i].tree), y, weights)
else
hofMSE = MSE(evalTreeArray(hallOfFame.members[i].tree), y)
end
if (hallOfFame.exists[size] && curMSE > hofMSE)
numberSmallerAndBetter += 1
end
end
betterThanAllSmaller = (numberSmallerAndBetter == 0)
if betterThanAllSmaller
delta_c = size - lastComplexity
delta_l_mse = log(curMSE/lastMSE)
score = convert(Float32, -delta_l_mse/delta_c)
if verbosity > 0
@printf("%-10d %-8.3e %-8.3e %-s\n" , size, curMSE, score, stringTree(member.tree))
end
lastMSE = curMSE
lastComplexity = size
end
end
end
debug(verbosity, "")
last_print_time = time()
num_equations = 0.0
end
end
end
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