Introduce perturbation factor

eureqa.jl

@@ -208,7 +208,7 @@ function mutateConstant(
     end
 
     bottom = 0.1f0
-    maxChange = T + 1.0f0 + bottom
+    maxChange = perturbationFactor * T + 1.0f0 + bottom
     factor = maxChange^Float32(rand())
     makeConstBigger = rand() > 0.5
 
@@ -490,10 +490,7 @@ end
 
 # Go through one simulated annealing mutation cycle
 #  exp(-delta/T) defines probability of accepting a change
-function iterate(
-        tree::Node, T::Float32;
-        annealing::Bool=true
-    )::Node
+function iterate(tree::Node, T::Float32)::Node
     prev = tree
     tree = copyNode(tree)
 
@@ -592,13 +589,9 @@ function bestSubPop(pop::Population; topn::Integer=10)::Population
 end
 
 # Mutate the best sampled member of the population
-function iterateSample(
-        pop::Population, T::Float32;
-        annealing::Bool=true)::PopMember
+function iterateSample(pop::Population, T::Float32)::PopMember
     allstar = bestOfSample(pop)
-    new = iterate(
-        allstar.tree, T,
-        annealing=annealing)
+    new = iterate(allstar.tree, T)
     allstar.tree = new
     allstar.score = scoreFunc(new)
     allstar.birth = getTime()
@@ -607,11 +600,9 @@ end
 
 # Pass through the population several times, replacing the oldest
 # with the fittest of a small subsample
-function regEvolCycle(
-    pop::Population, T::Float32;
-    annealing::Bool=true)::Population
+function regEvolCycle(pop::Population, T::Float32)::Population
     for i=1:round(Integer, pop.n/ns)
-        baby = iterateSample(pop, T, annealing=annealing)
+        baby = iterateSample(pop, T)
         #printTree(baby.tree)
         oldest = argmin([pop.members[member].birth for member=1:pop.n])
         pop.members[oldest] = baby
@@ -623,17 +614,16 @@ end
 # printing the fittest equation every 10% through
 function run(
         pop::Population,
-        ncycles::Integer,
-        annealing::Bool=false;
+        ncycles::Integer;
         verbosity::Integer=0
         )::Population
 
     allT = LinRange(1.0f0, 0.0f0, ncycles)
     for iT in 1:size(allT)[1]
         if annealing
-            pop = regEvolCycle(pop, allT[iT], annealing=true)
+            pop = regEvolCycle(pop, allT[iT])
         else
-            pop = regEvolCycle(pop, 1.0f0, annealing=true)
+            pop = regEvolCycle(pop, 1.0f0)
         end
 
         if verbosity > 0 && (iT % verbosity == 0)
@@ -721,7 +711,6 @@ end
 
 function fullRun(niterations::Integer;
                 npop::Integer=300,
-                annealing::Bool=true,
                 ncyclesperiteration::Integer=3000,
                 fractionReplaced::Float32=0.1f0,
                 verbosity::Integer=0,
@@ -738,7 +727,7 @@ function fullRun(niterations::Integer;
     for k=1:niterations
         # Spawn threads to run indepdent evolutions, then gather them
         @inbounds Threads.@threads for i=1:nthreads
-            allPops[i] = run(allPops[i], ncyclesperiteration, annealing, verbosity=verbosity)
+            allPops[i] = run(allPops[i], ncyclesperiteration, verbosity=verbosity)
             bestSubPops[i] = bestSubPop(allPops[i], topn=topn)
             for j=1:bestSubPops[i].n
                 bestSubPops[i].members[j].tree = simplifyTree(bestSubPops[i].members[j].tree)

eureqa.py

@@ -21,6 +21,7 @@ default_weightDoNothing =          1
 default_result =                   1
 default_topn =                    10
 default_parsimony =              0.0
+default_perturbationFactor =     1.0
 
 
 def eureqa(X=None, y=None, threads=4,
@@ -46,6 +47,7 @@ def eureqa(X=None, y=None, threads=4,
             weightMutateOperator=default_weightMutateOperator,
             weightRandomize=default_weightRandomize,
             weightSimplify=default_weightSimplify,
+            perturbationFactor=default_perturbationFactor,
             timeout=None,
             equation_file='hall_of_fame.csv',
             test='simple1',
@@ -138,6 +140,8 @@ const fractionReplacedHof = {fractionReplacedHof}f0
 const shouldOptimizeConstants = {'true' if shouldOptimizeConstants else 'false'}
 const hofFile = "{equation_file}"
 const nthreads = {threads:d}
+const perturbationFactor = {perturbationFactor:f}f0
+const annealing = {"true" if annealing else "false"}
 const mutationWeights = [
     {weightMutateConstant:f},
     {weightMutateOperator:f},
@@ -175,7 +179,7 @@ const y = convert(Array{Float32, 1}, """f"{y_str})""""
         'julia -O3',
         f'--threads {threads}',
         '-e',
-        f'\'include(".hyperparams_{rand_string}.jl"); include(".dataset_{rand_string}.jl"); include("eureqa.jl"); fullRun({niterations:d}, npop={npop:d}, annealing={"true" if annealing else "false"}, ncyclesperiteration={ncyclesperiteration:d}, fractionReplaced={fractionReplaced:f}f0, verbosity=round(Int32, {verbosity:f}), topn={topn:d})\'',
+        f'\'include(".hyperparams_{rand_string}.jl"); include(".dataset_{rand_string}.jl"); include("eureqa.jl"); fullRun({niterations:d}, npop={npop:d}, ncyclesperiteration={ncyclesperiteration:d}, fractionReplaced={fractionReplaced:f}f0, verbosity=round(Int32, {verbosity:f}), topn={topn:d})\'',
         ]
     if timeout is not None:
         command = [f'timeout {timeout}'] + command
@@ -203,6 +207,7 @@ if __name__ == "__main__":
     parser.add_argument("--npop", type=int, default=int(default_npop), help="Number of members per population")
     parser.add_argument("--ncyclesperiteration", type=int, default=10000, help="Number of evolutionary cycles per migration")
     parser.add_argument("--topn", type=int, default=int(default_topn), help="How many best species to distribute from each population")
+    parser.add_argument("--perturbationFactor", type=float, default=default_perturbationFactor)
     parser.add_argument("--fractionReplacedHof", type=float, default=default_fractionReplacedHof, help="Fraction of population to replace with hall of fame")
     parser.add_argument("--fractionReplaced", type=float, default=default_fractionReplaced, help="Fraction of population to replace with best from other populations")
     parser.add_argument("--weightAddNode", type=float, default=default_weightAddNode)

hyperparamopt.py

@@ -38,7 +38,7 @@ def run_trial(args):
         args[key] = int(args[key])
 
 
-    total_steps = 20*100*5000
+    total_steps = 10*100*1000
     niterations = args['niterations']
     npop = args['npop']
     if niterations == 0 or npop == 0: 
@@ -57,7 +57,7 @@ def run_trial(args):
 
     args['weightDoNothing'] = 1.0
 
-    maxTime = 3*60
+    maxTime = 30
     ntrials = 2
     equation_file = f'.hall_of_fame_{np.random.rand():f}.csv'
 
@@ -73,13 +73,13 @@ def run_trial(args):
     print(f"Starting", str(args))
     try:
         trials = []
-        for i in range(1, 6):
+        for i in range(3, 6):
             print(f"Starting test {i}")
             for j in range(ntrials):
                 print(f"Starting trial {j}")
                 trial = eureqa.eureqa(
                     test=f"simple{i}",
-                    threads=8,
+                    threads=4,
                     binary_operators=["plus", "mult", "pow", "div"],
                     unary_operators=["cos", "exp", "sin", "loga", "abs"],
                     equation_file=equation_file,
@@ -114,6 +114,7 @@ space = {
     'alpha': hp.lognormal('alpha', np.log(10.0), 1.0),
     'fractionReplacedHof': hp.lognormal('fractionReplacedHof', np.log(0.1), 1.0),
     'fractionReplaced': hp.lognormal('fractionReplaced', np.log(0.1), 1.0),
+    'perturbationFactor': hp.lognormal('perturbationFactor', np.log(1.0), 1.0),
     'weightMutateConstant': hp.lognormal('weightMutateConstant', np.log(4.0), 1.0),
     'weightMutateOperator': hp.lognormal('weightMutateOperator', np.log(0.5), 1.0),
     'weightAddNode': hp.lognormal('weightAddNode', np.log(0.5), 1.0),