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This commit is contained in:
Nicole Dresselhaus 2018-05-23 13:13:20 +02:00
parent ee008ba920
commit 3dba2a478b
2 changed files with 6 additions and 6 deletions
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10
app/Main.hs
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@ -119,11 +119,11 @@ main = do
probs <- randomRs (0.2,0.7) <$> newStdGen
let emptyPlants = replicate 100 emptyPlant
poisonedTree = poisonTree ds randomCompounds
poisonCompounds = foldMap (\(a,b) -> if a > 0.5 then [(b,a)] else []) $ poisonedTree
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
printEnvironment env
writeFile "poison.twopi" $ generateDotFromPoisonTree "poison" 0.5 $ poisonedTree
writeFile "poison.twopi" $ generateDotFromPoisonTree "poison" 0.5 poisonedTree
putStr "\ESC[?1049h"
loop 200 emptyPlants env
putStrLn "Simulation ended. Press key to exit."
@ -143,14 +143,14 @@ generatePredators threshold t = do
ps <- mapM generatePredators' $ getSubTrees t
return $ filter ((/= []) . irresistance) $ concat ps -- filter out predators that are resistant to everything because this does not make sense in our model.
where
generatePredators' :: (EnzymeTree s (Double, Compound)) -> IO [Predator]
generatePredators' :: EnzymeTree s (Double, Compound) -> IO [Predator]
generatePredators' t = do -- not fully resistant to t, but fully resistant to everything in ts
let comps = foldMap (\(a,b) -> if a > threshold then [(a,b)] else []) t
let comps = foldMap (\(a,b) -> [(a,b) | a > threshold]) t
amount <- randomRIO (0,length comps + 1) :: IO Int
forM [1..amount] $ \_ -> do
impact <- randomRIO (0.2,0.7)
rands <- randoms <$> newStdGen
let unresists = foldMap (\((a,b),r) -> if r*2 < a then [b] else []) $ zip comps rands
let unresists = foldMap (\((a,b),r) -> [b | r*2 < a]) $ zip comps rands
return $ Predator unresists impact
printEnvironment :: Environment -> IO ()

2
src/Environment.hs
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@ -194,7 +194,7 @@ deterPredators cs = do
appearingPredators = fmap fst . filter (\((_,p),r) -> p > r) $ zip ps ds -- assign one probability to each predator, filter those who appear, throw random data away again.
-- appearingPredators is now a sublist of ps.
deter :: Predator -> Double
-- multiply (toxicity of t with 100% effectiveness at l| for all toxins t | and t not in p's irresistance-list)
-- multiply (toxicity of t with 100% effectiveness at l| for all toxins t; and t in p's irresistance-list)
deter p = product [1 - min 1 (cs ! fromEnum t / l) | (t,l) <- ts, t `elem` irresistance p]
-- multiply (probability of occurence * intensity of destruction / probability to deter predator | for all predators)
return $ product ([min 1 ((1-prob) * fitnessImpact p / deter p) | (p,prob) <- appearingPredators])