little changes, some first simulation-results

This commit is contained in:
Nicole Dresselhaus 2018-06-08 12:10:28 +02:00
parent e77cd02c21
commit 6d702f6b2f
Signed by: Drezil
GPG Key ID: 057D94F356F41E25
8 changed files with 2024 additions and 22 deletions

View File

@ -107,12 +107,16 @@ loop loopAmount ps env = loop' loopAmount 0 ps env
spc = meanAndVar `from` sumProducedCompounds $ cs
ndc = meanAndVar `from` numDistinctCompounds $ cs
fns = meanAndVar `from` id $ fs
cstats = meanAndVar `from` id <$> byProducts cs
cstats' = meanAndVar `from` id $ snd <$> cstats
when (curLoop `mod` printEvery == 0) $ liftIO $ do
printPopulation stringe (zip3 plants fs cs)
putStrLn $ "Population statistics (mean,variance):"
putStrLn $ "Amount of Components produced = " ++ (padded 50 . show $ spc)
putStrLn $ "Number of distinct Components = " ++ (padded 50 . show $ ndc)
putStrLn $ "Fitness = " ++ (padded 50 . show $ fns)
putStrLn $ show cstats
putStrLn $ show cstats'
hFlush stdout
threadDelay $ 10*1000 -- sleep x*1000ns (=x ~ ms)
tell $ show curLoop
@ -143,9 +147,12 @@ main = do
ds <- randoms <$> newStdGen
--probs <- randomRs (0.2,0.7) <$> newStdGen
let poisonedTree = poisonTree ds randomCompounds
poisonCompounds = foldMap (\(a,b) -> [(b,a) | a > 0.5]) poisonedTree
predators <- generatePredators 0.5 poisonedTree
--let env = exampleEnvironment (getTreeSize randomCompounds) (generateEnzymeFromTree randomCompounds) (zip predators probs) poisonCompounds
poisonCompounds = foldMap (\(a,b) -> [(b,a) | a > 0]) poisonedTree
predators <- generatePredators 0.0 poisonedTree
let poisonCompounds' = pruneCompounds poisonCompounds predators
pruneCompounds cs ps = filter ((`elem` usedPoisons) . fst) cs
where usedPoisons = concat $ irresistance <$> ps
--let env = exampleEnvironment (getTreeSize randomCompounds) (generateEnzymeFromTree randomCompounds) (zip predators probs) poisonCompounds'
(Just env) <- decodeStrict' <$> BS.readFile "environment2.json"
let emptyPlants = replicate (numPlants . settings $ env) emptyPlant
enzs <- randomRs (0,length (possibleEnzymes env) - 1) <$> newStdGen

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@ -506,28 +506,28 @@
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@ -536,19 +536,12 @@
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989
simulation_am.log Normal file
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964,8.868964250912363,6.448689836447363e-3,11.560000000000002,0.6864000000000005,0.2962029599987166,1.7769199849185793e-3
965,8.856452022890561,6.396633623894393e-3,11.36,0.2704000000000001,0.3006192180186791,1.8100746122657013e-3
966,8.863889681657234,5.173720392250497e-3,11.300000000000002,0.3299999999999999,0.3003866864218316,1.9807853969202745e-3
967,8.871703833807363,4.3277119243279715e-3,11.42,0.6436,0.30348903863923354,1.3527995654803201e-3
968,8.878090326750533,4.1480684964349136e-3,11.640000000000002,1.1103999999999998,0.2944731360957397,1.594559879043632e-3
969,8.88582908712033,4.797192641636354e-3,11.900000000000002,1.5699999999999994,0.2920907499386891,2.0248067848131985e-3
970,8.879079935434845,5.8630473496018645e-3,11.88,1.5055999999999998,0.2885689612702161,2.4694894327837304e-3
971,8.853964196003973,4.705955804350857e-3,11.58,1.3235999999999997,0.29502006739918823,2.3562584788732466e-3
972,8.861114079378545,5.9738690578408585e-3,11.799999999999997,1.4800000000000002,0.2957417602216308,2.0361374951965478e-3
973,8.851524666047911,6.935109476770597e-3,11.54,0.9283999999999996,0.3007697390721039,1.3582130020698753e-3
974,8.841778649454364,6.136113245212984e-3,11.420000000000005,0.6436000000000006,0.2980963687559264,1.5416799945357294e-3
975,8.840099586845076,6.31263058798506e-3,11.5,0.97,0.29637992890663134,1.3848436904981029e-3
976,8.856332850608371,8.500972544976068e-3,11.920000000000002,1.5935999999999995,0.2805502439815572,1.9361385552111767e-3
977,8.854210201123527,9.698390760276059e-3,11.98,1.6596000000000009,0.28287668783890674,2.25774021826987e-3
978,8.854997199142138,1.2300322701408961e-2,12.1,1.9299999999999997,0.27015722911355367,2.3026811966295265e-3
979,8.844761416979004,9.237542817771583e-3,11.82,1.3076000000000005,0.27588591489346426,1.8807389618971818e-3
980,8.837349333983449,5.500297461414885e-3,11.84,1.3344,0.2788969204364289,2.1643657903053525e-3
981,8.85766764535935,5.106752175537741e-3,12.04,1.3183999999999998,0.26598786704409066,2.1894655065881137e-3
982,8.837707739716643,1.2505460341906891e-2,11.74,1.1523999999999999,0.25784370344918145,2.6748616372165605e-3
983,8.838973977762857,8.191536019227664e-3,11.72,0.7615999999999998,0.25990613413048913,2.6118235102918835e-3
984,8.794356039184407,1.512818714811738e-2,11.56,1.2064000000000001,0.25753722824885394,2.869954587867897e-3
985,8.765282740808539,3.049693060063813e-2,11.5,2.4900000000000007,0.26433651045770695,2.2796090834373128e-3
986,8.788943818504315,2.0577953621333207e-2,11.8,1.76,0.277190911925863,2.1639025302111477e-3
987,8.768213568914934,3.187896117919605e-2,11.68,2.4576,0.27909075669701594,1.6792662224763796e-3
988,8.722872122625832,4.453760891506988e-2,11.3,2.6500000000000004,0.2743745872701072,3.1146252132025587e-3
989,8.746693804551548,4.1397517380513324e-2,11.22,2.2916,0.2924765289430965,1.9953679470195835e-3
990,8.78960449546432,3.428864357291173e-2,11.38,2.1556,0.29230553260553394,2.772121834374825e-3
991,8.828409542589096,1.8244841006956815e-2,11.840000000000002,2.2943999999999996,0.28437122017894234,2.8596579272559546e-3
992,8.840849048934384,1.7628057888263313e-2,11.999999999999998,2.92,0.28988667999901474,1.7986497286586994e-3
993,8.853025130521415,7.518474156529873e-3,11.96,1.9184000000000005,0.28936315371920646,2.0473000358445445e-3
994,8.853741428289096,7.770691286315561e-3,11.94,2.0563999999999996,0.3024558095341816,2.0037850560098796e-3
995,8.843209405020437,7.413813783944056e-3,11.699999999999998,1.0099999999999993,0.30168507505122083,2.3349103384734424e-3
996,8.853484936653405,5.781962598031919e-3,11.86,0.7203999999999998,0.2956502448409756,2.01773543087538e-3
997,8.889391764553105,7.235535992459629e-3,12.16,1.1743999999999999,0.2977090932150408,2.4480858868488825e-3
998,8.883112293073097,9.162618980270069e-3,12

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@ -216,14 +216,13 @@ fitness ps = do
return $ repeat 1
dieRate <- mapM (dieToPredators (zip appearingPredators popDefense)) products -- defeat predators with produced compounds
let sumEnzymes = sum . fmap (\(_,q,a) -> fromIntegral q*a) . genome <$> ps -- amount of enzymes * activation = resources "wasted"
staticCostOfEnzymes = (\x -> 1 - 0.02*x) <$> sumEnzymes -- static cost of creating enzymes
staticCostOfEnzymes = (*0.01) <$> sumEnzymes -- static cost of creating enzymes
nutrientsAvailable <- fmap snd <$> fromEnv soil
let nutrientsLeft = (\p -> [p ! i | i <- [0..fromEnum (maxBound :: Nutrient)]]) <$> products
nutrientRatio = minimum . zipWith (flip (/)) nutrientsAvailable <$> nutrientsLeft
costOfEnzymes = max 0 <$> zipWith (\s n -> s-n*0.1) staticCostOfEnzymes nutrientRatio -- cost to keep enzymes are static costs + amount of nutrient sucked out of the primary cycle
costOfEnzymes = max 0 <$> zipWith (\s n -> 1-(s+n*0.1)) staticCostOfEnzymes nutrientRatio -- cost to keep enzymes are static costs + amount of nutrient sucked out of the primary cycle
survivalRate = (1-) <$> dieRate
return $ zip (zipWith (*) survivalRate costOfEnzymes)
(products)
return $ zip (zipWith (*) survivalRate costOfEnzymes) products
produceCompounds :: Plant -> [(Nutrient, Amount)] -> World (Vector Amount)
produceCompounds (Plant genes _) substrate = do

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@ -4,10 +4,13 @@ module Evaluation
, sumCompounds
, from
, meanAndVar
, byCompound
, byProducts
) where
import Control.Foldl as F
import Numeric.LinearAlgebra as LA
import Data.List
import Environment
@ -18,9 +21,7 @@ eps = 0.01
sumProducedCompounds :: Functor f => f (LA.Vector Amount) -> f Amount
-- sumProducedCompounds :: [LA.Vector Amount] -> [Amount]
-- cut off numNutrients from the start of the vector and then sum.
sumProducedCompounds = fmap $ (\v -> sumElements . LA.subVector numNutrients (size v - numNutrients) $ v)
where
numNutrients = fromEnum (maxBound :: Nutrient) + 1 --enum starts at 0, subVector-indexing at 1
sumProducedCompounds = fmap sumElements . cutoffNutrients
-- | sum of all compounds
sumCompounds :: Functor f => f (LA.Vector Amount) -> f Amount
@ -42,3 +43,17 @@ from f w b = F.fold f (w b)
-- | helper to get mean and variance in a single pass.
meanAndVar :: F.Fold Amount (Amount,Amount)
meanAndVar = (,) <$> F.mean <*> F.variance
byProducts :: [LA.Vector Amount] -> [[Amount]]
byProducts = transpose . fmap toList . cutoffNutrients
byCompound :: [LA.Vector Amount] -> [[Amount]]
byCompound = transpose . fmap toList
-- | sum of produced compounds ignoring everything defined as 'Nutrient'.
cutoffNutrients :: Functor f => f (LA.Vector Amount) -> f (LA.Vector Amount)
-- sumProducedCompounds :: [LA.Vector Amount] -> [Amount]
-- cut off numNutrients from the start of the vector and then sum.
cutoffNutrients = fmap (\v -> LA.subVector numNutrients (size v - numNutrients) v)
where
numNutrients = fromEnum (maxBound :: Nutrient) + 1 --enum starts at 0, subVector-indexing at 1