diff --git a/app/Main.hs b/app/Main.hs index dd02bac..8d1ee79 100644 --- a/app/Main.hs +++ b/app/Main.hs @@ -4,17 +4,20 @@ module Main where import Text.Printf import Control.Monad.Reader -import Numeric.LinearAlgebra +import qualified Numeric.LinearAlgebra as LA import Data.List import System.Random import Control.Concurrent import Control.Parallel.Strategies -import Control.Monad.Writer +import Control.Monad.Writer (tell) import qualified Debug.Trace as Debug import qualified Control.Foldl as F import System.IO +import System.Environment import Data.Aeson import qualified Data.ByteString as BS +import Options.Applicative +import Data.Semigroup ((<>)) import ArbitraryEnzymeTree import Environment @@ -46,6 +49,8 @@ exampleEnvironment addedC es pred tox = , settings = Settings { automimicry = False , predatorsRandom = False , numPlants = 50 + , logEveryNIterations = 10 + , verbose = True } } @@ -91,20 +96,32 @@ loop loopAmount ps env = loop' loopAmount 0 ps env ) <$> possibleEnzymes (snd env) toxins :: [(Compound, Amount)] toxins = toxicCompounds (snd env) + printEverything = verbose.settings.snd $ env padded i str = take i $ str ++ repeat ' ' printEvery = 10 loop' :: Int -> Int -> [Plant] -> Simulation -> IO () loop' loopAmount curLoop plants s = unless (loopAmount+1 == curLoop) $ do - when (curLoop `mod` printEvery == 0) $ do + when (printEverything && curLoop `mod` printEvery == 0) $ do putStr "\ESC[2J\ESC[H" printEnvironment (snd env) putStrLn "" putStrLn $ "Generation " ++ show curLoop ++ " of " ++ show loopAmount ++ ":" newPlants <- simulate s $ do + when (curLoop == 0) $ + tell $ "num_iter" + ++ ",c_sum_mu,c_sum_sigma" + ++ ",c_d_mu,c_d_sigma" + ++ ",e_d_mu,e_d_sigma" + ++ ",fitness_mean,fitness_sigma" + ++ ",percent_toxic_mean,percent_toxic_sigma" + logIter <- fromEnv $ logEveryNIterations . settings (!fs,cs) <- unzip <$> fitness plants txns <- fmap (fromEnum . fst) <$> fromEnv toxicCompounds -- [Int] of id's of toxic compounds let fps = zip plants fs -- gives us plants & their fitness in a tuple sumFitness = sum fs + es = genomeToEnzymeAmount . genome <$> plants + genomeToEnzymeAmount :: Genome -> LA.Vector Double + genomeToEnzymeAmount g = LA.accum (LA.konst 0 (maxCompound . snd $ env)) (+) $ (\(e,q,a) -> ((fromEnum . fst . snd . synthesis $ e)-1,fromIntegral q*a)) <$> g -- $C_{\Sigma,mu}$: Durchschnittliche Menge an produzierten Stoffen -- $C_{\Sigma,sigma}$: Durchschnittliche Varianz an produzierten Stoffen (c_sum_mu, c_sum_sigma) = meanAndVar `from` sumProducedCompounds $ cs @@ -114,13 +131,22 @@ loop loopAmount ps env = loop' loopAmount 0 ps env -- wogegen Stoff B *im Schnitt* mit $0.5$ produziert wird, aber dies eine extreme -- Varianz auslöst) (c_i_mu,c_i_sigma) = unzip $ meanAndVar `from` id <$> byProducts cs - -- - $C_d$: Durchschnittliche Anzahl distinkter Produzierter Stoffe (sprich - -- nicht-endemisch, $#i | C_{i,\sigma} > \epsilon$ ) - isEndemic :: Vector Bool - isEndemic = fromList $ (> 0.01) <$> c_i_sigma - (c_d_mu, c_d_sigma) = meanAndVar `from` countWith isEndemic $ cs -- - $C_{\sigma,\{\mu/\sigma\}}$: Mittelwert/Varianz von $\C_{i,\sigma}$ (c_sigma_mu, c_sigma_sigma) = meanAndVar `from` id $ c_i_sigma + -- - $C_d$: Durchschnittliche Anzahl distinkter Produzierter Stoffe (sprich + -- nicht-endemisch, $#i | C_{i,\mu} < \epsilon$ ) + isNotEndemicCompound :: LA.Vector Bool + isNotEndemicCompound = LA.fromList $ (< 0.1) <$> c_i_mu + (c_d_mu, c_d_sigma) = meanAndVar `from` countWith isNotEndemicCompound (>0.1) $ cs + -- - $E_{i,\mu}$: Durchschnittliche Anzahl produzierbarer Komponenten (falls ausgangsstoff verfügbar) + -- - $E_{i,\sigma}$: Zusätzlich: Betrachtung der Varianz dieser Komponenten innerhalb der Population + -- analog zu $C_{i,\mu/\sigma}$ + (e_i_mu,e_i_sigma) = unzip $ meanAndVar `from` id <$> byCompound es + -- - $E_d$: Durchschnittliche Anzahl distinkter Produzierter Stoffe (sprich + -- nicht-endemisch, $#i | E_{i,\mu} < \epsilon$ ) + isNotEndemicEnzyme :: LA.Vector Bool + isNotEndemicEnzyme = LA.fromList $ (< 0.5) <$> e_i_mu + (e_d_mu, e_d_sigma) = meanAndVar `from` countWith isNotEndemicEnzyme (>0.5) $ es -- - $\mathbf{E}[C_{\Sigma,plant} - C_{\Sigma,mu}]$: Durchschnittliche Abweichung der produzierten -- Stoffe gegenüber dem Schnitt der Gesamtpopulation e_hash_plant = F.mean `from` numDistinctCompounds $ cs @@ -128,19 +154,23 @@ loop loopAmount ps env = loop' loopAmount 0 ps env fns = meanAndVar `from` id $ fs -- - $P_\{\mu,\sigma\}$ Mittelwert/Varianz der Anteile der Stoffe in Pflanze i, die giftig sind toxs = meanAndVar `from` percentagePoisonous txns $ cs - when (curLoop `mod` printEvery == 0) $ liftIO $ do - printPopulation (zip ((>0.01) <$> c_i_sigma) stringe) (zip3 plants fs cs) + when (printEverything && curLoop `mod` printEvery == 0) $ liftIO $ do + printPopulation isNotEndemicEnzyme stringe (zip3 plants fs cs) putStrLn $ "Population statistics (mean,variance):" - putStrLn $ "Amount of Components produced = " ++ (padded 50 . show $ (c_sum_mu,c_sum_sigma)) - putStrLn $ "Number of distinct Components = " ++ (padded 50 . show $ (c_d_mu, c_d_sigma)) - putStrLn $ "Fitness = " ++ (padded 50 . show $ fns) + putStrLn $ "Amount of Components produced = " ++ show (c_sum_mu,c_sum_sigma) + putStrLn $ "Number of distinct Components = " ++ show (c_d_mu, c_d_sigma) + putStrLn $ "Number of distinct Enzymes = " ++ show (e_d_mu, e_d_sigma) + putStrLn $ "Fitness = " ++ show fns + putStrLn $ "Percentage of toxins in Cmpnds= " ++ show toxs hFlush stdout threadDelay $ 10*1000 -- sleep x*1000ns (=x ~ ms) - tell $ show curLoop - ++ "," ++ show c_sum_mu ++ "," ++ show c_sum_sigma - ++ "," ++ show c_d_mu ++ "," ++ show c_d_sigma - ++ "," ++ show (fst fns) ++ "," ++ show (snd fns) - ++ "," ++ show (fst toxs) ++ "," ++ show (snd toxs) + when (curLoop `mod` logIter == 0) $ + tell $ show curLoop + ++ "," ++ show c_sum_mu ++ "," ++ show c_sum_sigma + ++ "," ++ show c_d_mu ++ "," ++ show c_d_sigma + ++ "," ++ show e_d_mu ++ "," ++ show e_d_sigma + ++ "," ++ show (fst fns) ++ "," ++ show (snd fns) + ++ "," ++ show (fst toxs) ++ "," ++ show (snd toxs) -- generate x new plants. np <- fromEnv (numPlants . settings) sequence . flip fmap [1..np] $ \_ -> do @@ -157,33 +187,68 @@ loop loopAmount ps env = loop' loopAmount 0 ps env haploMate parent loop' loopAmount (curLoop+1) newPlants s +data CLIOptions = CLIOptions + { environment :: Maybe FilePath + , logfile :: FilePath + } + +cliOptParser :: Parser CLIOptions +cliOptParser = CLIOptions + <$> optional (strOption + (long "environment" + <> short 'e' + <> metavar "ENV" + <> help "Environment to load" + )) + <*> option str + (long "logfile" + <> short 'l' + <> metavar "LOG" + <> showDefault + <> value "simulation.log" + <> help "Name for the logfile" + ) + +cliopts = info (cliOptParser <**> helper) + (fullDesc + <> progDesc "Simulation of Biological Systems" + <> header "Chemodiversity made easy ;)" + ) + + main :: IO () main = do + opts <- execParser cliopts hSetBuffering stdin NoBuffering - --hSetBuffering stdout NoBuffering + hSetBuffering stdout NoBuffering randomCompounds <- makeHead (Substrate PPM) <$> generateTreeFromList 30 (toEnum <$> [(maxCompoundWithoutGeneric+1)..] :: [Compound]) -- generate roughly x compounds ds <- randoms <$> newStdGen - --probs <- randomRs (0.2,0.7) <$> newStdGen + probs <- randomRs (0.2,0.7) <$> newStdGen let poisonedTree = poisonTree ds randomCompounds 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" + (Just env) <- case environment opts of + Nothing -> return . Just $ exampleEnvironment (getTreeSize randomCompounds) (generateEnzymeFromTree randomCompounds) (zip predators probs) poisonCompounds' + Just file -> do + putStrLn $ "reading environment: " ++ file + decodeStrict' <$> BS.readFile file let emptyPlants = replicate (numPlants . settings $ env) emptyPlant + printEverything = verbose.settings $ env enzs <- randomRs (0,length (possibleEnzymes env) - 1) <$> newStdGen let startPlants = randomGenome 1 enzs (possibleEnzymes env) emptyPlants - printEnvironment env - writeFile "poison.twopi" $ generateDotFromPoisonTree "poison" 0.5 poisonedTree + --writeFile "poison.twopi" $ generateDotFromPoisonTree "poison" 0.5 poisonedTree --writeFile "environment.json" . encode $ env - putStr "\ESC[?1049h" - logfile <- openFile "simulation.log" WriteMode - loop 2000 startPlants (logfile,env) - putStrLn "Simulation ended. Press key to exit." - _ <- getChar - putStr "\ESC[?1049l" + when printEverything $ putStr "\ESC[?1049h" + loghandle <- openFile (logfile opts) WriteMode + putStrLn $ "logging to: " ++ logfile opts + loop 2000 startPlants (loghandle,env) + when printEverything $ do + putStrLn "Simulation ended. Press key to exit." + _ <- getChar + putStr "\ESC[?1049l" randomGenome :: Int -> [Int] -> [Enzyme] -> [Plant] -> [Plant] randomGenome num inds enzs [] = [] @@ -221,8 +286,8 @@ printEnvironment (Environment soil pred metaIter maxComp toxic possEnz settings) putStrLn $ "Toxic: " ++ show toxic putStrLn $ "Settings: " ++ show settings -printPopulation :: [(Bool,(Enzyme,String))] -> [(Plant,Double,Vector Amount)] -> IO () -printPopulation es ps = do +printPopulation :: LA.Vector Bool -> [(Enzyme,String)] -> [(Plant,Double,LA.Vector Amount)] -> IO () +printPopulation endemic es ps = do let padded i str = take i $ str ++ repeat ' ' n = length ps fitnesses = (\(_,f,_) -> f) <$> ps @@ -231,8 +296,9 @@ printPopulation es ps = do putStr $ padded 50 ("Population: (fitness: mean " ++ padded 5 (show meanFitness) ++ ", max: " ++ padded 5 (show maxFitness) ++ ")") forM_ ps $ \(_,f,_) -> putStr (printColor (f/maxFitness) '█') putStrLn colorOff - forM_ es $ \(b,(e,s)) -> do - if b then putStr ">" else putStr " " + forM_ es $ \(e,s) -> do + let enzymeProductNum = fromEnum . fst . snd . synthesis $ e + if LA.toList endemic !! (enzymeProductNum - 1) then putStr ">" else putStr " " putStr s forM_ ps $ \(Plant g _,_,cs) -> do let curE = sum $ map (\(_,q,a) -> fromIntegral q*a) @@ -245,7 +311,7 @@ printPopulation es ps = do | x > 0.5 = 'o' | x > 0 = '.' | otherwise = '_' - amount = min 2 $ cs ! fromEnum (fst . snd . synthesis $ e) + amount = min 2 $ cs LA.! fromEnum (fst . snd . synthesis $ e) putStr $ printColor (amount/2) (plot curE) putStrLn colorOff diff --git a/environment2.json b/environment2.json index 2d4bed7..d7715c4 100644 --- a/environment2.json +++ b/environment2.json @@ -490,14 +490,16 @@ ] ], "settings": { - "automimicry": false, - "numPlants": 50, - "predatorsRandom": false + "automimicry": true, + "logEveryNIterations": 10, + "numPlants": 100, + "predatorsRandom": false, + "verbose": false }, "soil": [ [ [], - 10 + 20 ] ], "toxicCompounds": [ diff --git a/package.yaml b/package.yaml index f6e9b31..c2646e6 100644 --- a/package.yaml +++ b/package.yaml @@ -30,6 +30,7 @@ dependencies: - foldl - aeson - bytestring +- optparse-applicative library: source-dirs: src diff --git a/simulation_am.log b/simulation_am.log index ad702f4..07f47e7 100644 --- a/simulation_am.log +++ b/simulation_am.log @@ -1,989 +1,202 @@ -0,0.6939043552841977,2.527892084982486,1.1600000000000001,0.1344,1.6428011626920515e-2,8.480133218821758e-8 -1,0.7912651612268056,2.8583168948083646,1.1800000000000002,0.1476,1.6442663581355727e-2,9.509483504627635e-8 -2,0.7797667430372399,2.7699464804722727,1.18,0.14759999999999998,1.6444442780449084e-2,9.960201404494633e-8 -3,0.7793822983904451,2.7672293139135475,1.18,0.1476,1.6444505220466806e-2,9.638297581220594e-8 -4,0.6051967441525368,2.249920629370003,1.1399999999999997,0.1204,1.6401913730118168e-2,7.905167325094506e-8 -5,0.8651108991463277,2.993682894890368,1.2000000000000002,0.16,1.641693598635273e-2,9.460271034501287e-8 -6,0.6924334492943812,2.5172031898616716,1.1600000000000001,0.13440000000000005,1.6389387072817053e-2,8.585750666792748e-8 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numPlants :: Int -- ^ number of plants in starting population +data Settings = Settings { automimicry :: Bool -- ^ do we have automimicry-protection? + , predatorsRandom :: Bool -- ^ do predators always appear or according to their random distribution? + , numPlants :: Int -- ^ number of plants in starting population + , logEveryNIterations :: Int -- ^ log status every @loopNumber `mod` logEveryNIterations == 0@ + , verbose :: Bool -- ^ print visual statistics instead of just logging } deriving (Show, Eq, Generic) @@ -137,7 +139,7 @@ data Environment = -- Rest will get filled up with 'GenericEnzyme i' -- -- To find the 'maxCompound' without 'GenericEnzyme' use - -- 'maxComponent = fromEnum (maxBound :: Nutrient) + fromEnum (maxBound :: Component) + 1' + -- @maxComponent = fromEnum (maxBound :: Nutrient) + fromEnum (maxBound :: Component) + 1@ , toxicCompounds :: [(Compound,Amount)] -- ^ Compounds considered to be toxic in this environment. -- Kills 100% of Predators above Amount. @@ -149,7 +151,7 @@ data Environment = instance FromJSON Environment instance ToJSON Environment --- helper function. Allows for [0..maxCompoundWithoutGeneric] :: [Compound] with all non-generic Compounds +-- helper function. Allows for @[0..maxCompoundWithoutGeneric] :: [Compound]@ with all non-generic Compounds maxCompoundWithoutGeneric :: Int maxCompoundWithoutGeneric = fromEnum (maxBound :: Nutrient) + fromEnum (maxBound :: Component) + 1 @@ -274,7 +276,7 @@ haploMate (Plant genes abs) = do is <- randoms <$> newStdGen return $ zip ds is --generate some random infinite uniform distributed lists of doubles in [0,1) - r1 <- liftIO digen + r1 <- liftIO ((randoms <$> newStdGen) :: IO [Double]) r2 <- liftIO ((randoms <$> newStdGen) :: IO [Double]) r3 <- liftIO ((randoms <$> newStdGen) :: IO [Double]) r4 <- liftIO digen @@ -300,7 +302,7 @@ haploMate (Plant genes abs) = do duplicateGene :: [(Double,Int)] -> Genome -> Genome duplicateGene _ [] = [] - duplicateGene ((r,i):rs) g = if r < 0.05 then duplicateGene rs (stay ++ (e,q+1,a):stay') else g + duplicateGene ((r,i):rs) g = if r < 0.05 then duplicateGene rs (stay ++ (e,q,a):(e,1,a):stay') else g where (stay, (e,q,a):stay') = splitAt (i `mod` length g - 2) g @@ -311,14 +313,19 @@ haploMate (Plant genes abs) = do noiseActivation (r:rs) ((e,q,a):gs) = (e,q,max 0 $ min 1 $ a-0.01+0.02*r):noiseActivation rs gs noiseActivation _ [] = [] - mutateGene :: [(Double,Int)] -> [Int] -> Genome -> Genome + mutateGene :: [Double] -> [Int] -> Genome -> Genome mutateGene _ _ [] = [] - mutateGene ((r,i):rs) (s:ss) g = if r < 0.25 then mutateGene rs ss (stay ++ go' ++ stay') else g - where - (stay, go:stay') = splitAt (i `mod` length g - 2) g - go' = case go of - (e,1,a) -> [(enzymes !! s,1,a)] - (e,q,a) -> [(e,q-1,a),(enzymes !! s,1,a)] + mutateGene rs ss ((e,q,a):gs) = g' ++ mutateGene rs'' ss'' gs + where + -- take q randoms from rs/ss, replace numMuts (<= q) with the enzymes in ss + (rs',rs'') = splitAt q rs + (ss',ss'') = splitAt q ss + numMuts = length . filter (<0.01) $ rs' + newEnz = fmap ((\e' -> (e',1,a)).(enzymes!!).snd) + . filter ((<0.01).fst) + . zip rs' $ ss' + g' = if q == numMuts then newEnz + else (e,q-numMuts,a):newEnz return $ Plant genes' abs diff --git a/src/Evaluation.hs b/src/Evaluation.hs index 3da7a6a..0524ea0 100644 --- a/src/Evaluation.hs +++ b/src/Evaluation.hs @@ -38,11 +38,11 @@ numDistinctCompounds :: Functor f => f (LA.Vector Amount) -> f Amount --numDistinctCompounds :: [LA.Vector Amount] -> [Amount] numDistinctCompounds comps = sumElements . LA.cmap (\x -> if abs x < eps then 0 else 1) <$> comps -countWith :: Functor f => LA.Vector Bool -> f (LA.Vector Amount) -> f Amount -countWith toSelect = fmap $ sumElements . LA.zipVectorWith (\selected _ -> if selected then 1 else 0) toSelect --- apply selection to set data to 1 or 0 --- sum up 1 or 0s --- for all data +countWith :: Functor f => LA.Vector Bool -> (Amount -> Bool) -> f (LA.Vector Amount) -> f Amount +countWith toSelect filter = fmap $ sumElements . LA.zipVectorWith (\selected a -> if selected && filter a then 1 else 0) toSelect +-- apply selection & filter to set data to 1 or 0 +-- sum up 1 or 0s +-- for all data sumWith :: Functor f => LA.Vector Bool -> f (LA.Vector Amount) -> f Amount sumWith toSelect = fmap $ sumElements . LA.zipVectorWith (\selected d -> if selected then d else 0) toSelect