Attackers in intervals now also work.

TODO.md

@@ -20,13 +20,13 @@
 - $\mathbf{E}[C_{plant} - C_#]$: Durchschnittliche Abweichung der produzierten
   Stoffe gegenüber dem Schnitt der Gesamtpopulation
 - Anteile der Stoffe, die giftig sind
-
+- $#Plants$ die Angreifer X abwehren könnten
 
 ## Messung
 
 - Ermitteln der Metriken für alle $x$ Generationen
 - Stabilisieren sich die Metriken bei identischem Aufbau konsistent?
-- $#Plants$ die Angreifer X abwehren könnten
+  - Ja, $\pm$ Random-Effekt
 
 ## Zu untersuchende Parameter
 

app/Main.hs

@@ -16,6 +16,7 @@ import System.IO
 import System.Environment
 import Data.Aeson
 import qualified Data.ByteString as BS
+import qualified Data.ByteString.Lazy as LBS
 import Options.Applicative
 import Data.Semigroup ((<>))
 
@@ -47,10 +48,9 @@ exampleEnvironment addedC es pred tox =
     , toxicCompounds = tox --[(Produced FPP,0.1)] ++ tox
     , possibleEnzymes = es -- [pps,fpps] ++ es
     , settings = Settings { automimicry = False
-                          , predatorsRandom = False
+                          , predatorBehaviour = AttackInterval 10
                           , numPlants = 50
                           , logEveryNIterations = 10
-                          , verbose = True
                           }
     }
 
@@ -83,8 +83,8 @@ exampleEnvironment addedC es pred tox =
 -- Running the simulation
 -- ----------------------
 
-loop :: Int -> [Plant] -> Simulation -> IO ()
+loop :: Int -> [Plant] -> Simulation -> CLIOptions -> IO ()
-loop loopAmount ps env = loop' loopAmount 0 ps env
+loop loopAmount ps env opts = loop' loopAmount 0 ps env
 
   where
     -- cache enzyme colorful-strings
@@ -96,7 +96,7 @@ loop loopAmount ps env = loop' loopAmount 0 ps env
              ) <$> possibleEnzymes (snd env)
     toxins :: [(Compound, Amount)]
     toxins = toxicCompounds (snd env)
-    printEverything = verbose.settings.snd $ env
+    printEverything = verbose opts
     padded i str = take i $ str ++ repeat ' '
     printEvery = 10
     loop' :: Int -> Int -> [Plant] -> Simulation -> IO ()
@@ -107,15 +107,19 @@ loop loopAmount ps env = loop' loopAmount 0 ps env
         putStrLn ""
         putStrLn $ "Generation " ++ show curLoop ++ " of " ++ show loopAmount ++ ":"
       newPlants <- simulate s $ do
-          when (curLoop == 0) $
+          when (curLoop == 0) $ do
+            preds <- length <$> fromEnv predators
+                --- generates "pred1,pred2,pred3,.....predN"
+            let additionalHeader = intercalate "," $ ("pred"++).show <$> [1..preds]
             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"
+                 ++ "," ++ additionalHeader
           logIter <- fromEnv $ logEveryNIterations . settings
-          (!fs,cs) <- unzip <$> fitness plants
+          (!fs,cs) <- unzip <$> fitness curLoop 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
@@ -164,13 +168,17 @@ loop loopAmount ps env = loop' loopAmount 0 ps env
             putStrLn $ "Percentage of toxins in Cmpnds= " ++ show toxs
             hFlush stdout
             threadDelay $ 10*1000 -- sleep x*1000ns (=x ~ ms)
-          when (curLoop `mod` logIter == 0) $ 
+          when (curLoop `mod` logIter == 0) $ do
+            preds <- fmap fst <$> fromEnv predators
+            let numPlantsCanRepel = (\ir -> sum $ (\p -> if sum ((p LA.!) <$> ir) > 0 then 1 else 0) <$> cs) . fmap fromEnum . irresistance <$> preds
+                addedData = intercalate "," $ show <$> numPlantsCanRepel
             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)
+                 ++  ","  ++  addedData
           -- generate x new plants.
           np <- fromEnv (numPlants . settings)
           sequence . flip fmap [1..np] $ \_ -> do
@@ -190,6 +198,7 @@ loop loopAmount ps env = loop' loopAmount 0 ps env
 data CLIOptions = CLIOptions
     { environment :: Maybe FilePath
     , logfile     :: FilePath
+    , verbose     :: Bool
     }
 
 cliOptParser :: Parser CLIOptions
@@ -208,6 +217,11 @@ cliOptParser = CLIOptions
         <> value "simulation.log"
         <> help "Name for the logfile"
         )
+    <*> switch
+        (long "verbose"
+        <> short 'v'
+        <> help "show 'gui' during process"
+        )
 
 cliopts = info (cliOptParser <**> helper)
                 (fullDesc
@@ -236,15 +250,15 @@ main = do
                     putStrLn $ "reading environment: " ++ file
                     decodeStrict' <$> BS.readFile file
   let emptyPlants      = replicate (numPlants . settings $ env) emptyPlant
-      printEverything  = verbose.settings $ env
+      printEverything  = verbose opts
   enzs <- randomRs (0,length (possibleEnzymes env) - 1) <$> newStdGen
   let startPlants      = randomGenome 1 enzs (possibleEnzymes env) emptyPlants
   --writeFile "poison.twopi" $ generateDotFromPoisonTree "poison" 0.5 poisonedTree
-  --writeFile "environment.json" . encode $ env
+  LBS.writeFile "environment.json" . encode $ env
   when printEverything $ putStr "\ESC[?1049h"
   loghandle <- openFile (logfile opts) WriteMode
   putStrLn $ "logging to: " ++ logfile opts
-  loop 2000 startPlants (loghandle,env)
+  loop 2000 startPlants (loghandle,env) opts
   hClose loghandle
   when printEverything $ do
     putStrLn "Simulation ended. Press key to exit."

environment2.json

@@ -429,7 +429,7 @@
                 "fitnessImpact": 0.4901681711436634,
                 "irresistance": [
                     {
-                        "contents": 27,
+                        "contents": 26,
                         "tag": "GenericCompound"
                     }
                 ],
@@ -493,8 +493,10 @@
         "automimicry": false,
         "logEveryNIterations": 10,
         "numPlants": 100,
-        "predatorsRandom": false,
+        "predatorBehaviour": {
-        "verbose": false
+            "contents": 10,
+            "tag": "AttackInterval"
+        }
     },
     "soil": [
         [

src/Environment.hs

@@ -111,12 +111,19 @@ data Predator = Predator { irresistance    :: [Compound]
 instance FromJSON Predator
 instance ToJSON Predator
 
+data PredatorBehaviour = AlwaysAttack
+                       | AttackRandom
+                       | AttackInterval Int
+                       deriving (Show, Eq, Generic)
+
+instance FromJSON PredatorBehaviour
+instance ToJSON PredatorBehaviour
+
 -- | 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?
+                         , predatorBehaviour :: PredatorBehaviour    -- ^ 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)
 
@@ -199,19 +206,20 @@ instance Eq Plant where
 
 type Fitness = Double
 
-fitness :: [Plant] -> World [(Fitness, Vector Amount)]
+fitness :: Int -> [Plant] -> World [(Fitness, Vector Amount)]
-fitness ps = do
+fitness iter ps = do
   nutrients <- mapM absorbNutrients ps           -- absorb soil
   products <- sequenceA $ zipWith produceCompounds ps nutrients -- produce compounds
   ds <- liftIO $ randoms <$> newStdGen
   preds <- fromEnv predators
-  randPred <- fromEnv (predatorsRandom . settings)
+  predB <- fromEnv (predatorBehaviour . settings)
   let
-     appearingPredators = if randPred then
+     appearingPredators = case predB of
-                            fmap (fst . fst) . filter (\((_,p),r) -> p > r) $ zip preds ds -- assign one probability to each predator, filter those who appear, throw random data away again.
+                            AttackRandom -> fmap (fst . fst) . filter (\((_,p),r) -> p > r) $ zip preds ds -- assign one probability to each predator, filter those who appear, throw random data away again.
                                                                                                            -- appearingPredators is now a sublist of preds without the probability.
-                          else
+                            AttackInterval lngth -> fmap fst . filter (\(_,p) -> iter `mod` floor (fromIntegral lngth / p) < lngth) $ preds
-                            fst <$> preds -- else just forget about probabilities
+                                                                                                           -- attacker appears for length lngth iterations averaging out at p over longer timespans.
+                            AlwaysAttack -> fst <$> preds -- else just forget about probabilities
   automimicry <- fromEnv (automimicry . settings)
   popDefense <- if automimicry then
                    forM appearingPredators $ \p -> do
@@ -310,7 +318,7 @@ haploMate (Plant genes abs) = do
                                             (stay, (e,q,a):stay') = splitAt (i `mod` length g - 2) g
 
     addGene :: [Double] -> [Int] -> Genome -> Genome
-    addGene (r:rs) (s:ss) g = if r < 0.005 then (enzymes !! s,1,1):g else g
+    addGene (r:rs) (s:ss) g = if r < 0.005 then (enzymes !! s,1,0.5):g else g
 
     noiseActivation :: [Double] -> Genome -> Genome
     noiseActivation (r:rs) ((e,q,a):gs) = (e,q,max 0 $ min 1 $ a-0.01+0.02*r):noiseActivation rs gs