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chemodiversity
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corrected many things according to specification that was agreed upon.

This commit is contained in:
Nicole Dresselhaus 2018-06-20 00:14:24 +02:00
parent 62db90d3d9
commit e758520c5c
Signed by: Drezil
GPG Key ID: AC88BB432537313A
8 changed files with 538 additions and 2046 deletions
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136
app/Main.hs
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@ -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

10
environment2.json
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@ -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": [

1
package.yaml
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@ -30,6 +30,7 @@ dependencies:
- foldl
- aeson
- bytestring
- optparse-applicative
library:
source-dirs: src

1191
simulation_am.log
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simulation_am.ods
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1201
simulation_no_am.log
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35
src/Environment.hs
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@ -112,9 +112,11 @@ instance FromJSON Predator
instance ToJSON Predator
-- | Settings to enable/disable parts of the simulation
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
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

10
src/Evaluation.hs
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@ -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