{-# LANGUAGE RecordWildCards #-}

module Environment where


import Data.Functor        ((<$>))
import Control.Applicative ((<*>))
import Control.Monad       (forM_)
import Control.Monad.Reader
import Data.List           (permutations, subsequences)
import Numeric.LinearAlgebra

type Probability = Double
type Quantity = Int
type Activation = Double
type Amount = Double

-- | Nutrients are the basis for any reaction and are found in the environment of the plant.
data Nutrient = Sulfur
              | Phosphor
              | Nitrate
              | Photosynthesis
     deriving (Show, Enum, Bounded, Eq)

-- | Fixed, non-generic Components
data Component = PP
               | FPP
     deriving (Show, Enum, Bounded, Eq)

-- | Compounds are either direct nutrients, already processed components or GenericEnzymes
data Compound = Substrate Nutrient
              | Produced Component
              | GenericEnzyme Int
     deriving (Show, Eq)

instance Enum Compound where
  toEnum x
    | x <= maxS            = Substrate . toEnum $ x
    | x - (maxS+1) <= maxP = Produced . toEnum $ x - (maxS + 1)
    | otherwise            = GenericEnzyme $ x - (maxS + 1) - (maxP + 1)
    where
      maxS = fromEnum (maxBound :: Nutrient)
      maxP = fromEnum (maxBound :: Component)

  fromEnum (Substrate x)     = fromEnum x
  fromEnum (Produced x)      = fromEnum x + maxS + 1
    where
      maxS = fromEnum (maxBound :: Nutrient)
  fromEnum (GenericEnzyme x) = x + maxS + maxP + 2
    where
      maxS = fromEnum (maxBound :: Nutrient)
      maxP = fromEnum (maxBound :: Component)



-- | Enzymes are the main reaction-driver behind synthesis of intricate compounds.
--   
--   They are assumed to be reversible.
data Enzyme = Enzyme
       { enzymeName            :: String
         -- ^ Name of the Enzyme.
       , substrateRequirements :: [(Compound,Amount)]
         -- ^ needed for reaction to take place
       , synthesis             :: ((Compound,Amount),(Compound,Amount))
         -- ^ given x in amount -a, this will produce y in amount b
       , dominance             :: Maybe Amount
         -- ^ in case of competition for nutrients this denotes the priority
         --   Nothing = max possible
       }
       deriving (Show, Eq)

-- | conviniently make an Enzyme using 1 of the first compund to produce 1 of the second
makeSimpleEnzyme :: Compound -> Compound -> Enzyme
makeSimpleEnzyme a b = Enzyme (show a ++ " -> " ++ show b) [] ((a,-1),(b,1)) Nothing

--Example "enzymes" could be:

pps :: Enzyme -- uses Phosphor from Substrate to produce PP
pps = Enzyme "PPS" [(Substrate Phosphor,1)] ((Substrate Phosphor,(-1)),(Produced PP,1)) Nothing

fpps :: Enzyme -- PP -> FPP
fpps = makeSimpleEnzyme (Produced PP) (Produced FPP)

-- Evironment
-- ----------

-- | In the environment we have predators that impact the fitness of our plants and
--   may be resistant to some compounds the plant produces. They can also differ in
--   their intensity.
data Predator = Predator { resistance    :: [Compound]
                           -- ^ list of components this predator is resistant to
                         , fitnessImpact :: Amount
                           -- ^ impact on the fitness of a plant
                           --   (~ agressiveness of the herbivore)
                         } deriving (Show, Eq)

-- Exemplatory:

greenfly :: Predator         -- 20% of plants die to greenfly, but the fly is
greenfly = Predator [] 0.2   -- killed by any toxic Component

-- The environment itself is just the soil and the predators. Extensions would be possible.

data Environment =
     Environment
   { soil      :: [(Nutrient, Amount)]
     -- ^ soil is a list of nutrients available to the plant.
   , predators :: [(Predator, Probability)]
     -- ^ Predators with the probability of appearance in this generation.
   , metabolismIteration :: Int
     -- ^ Number of iterations for producing compounds
   , maxCompound :: Int
     -- ^ Number of possible Compounds
     --   'maxCompound' should be greater than #Nutrient + #Products.
     --   Rest will get filled up with 'GenericEnzyme i'
     --
     --   To find the 'maxCompound' without 'GenericEnzyme' use
     --   'maxComponent = fromEnum (maxBound :: Nutrient) + fromEnum (maxBound :: Component) + 1'
   , toxicCompounds :: [Compound]
     -- ^ Compounds considered to be toxic in this environment.
   } deriving (Show, Eq)

-- helper function. Allows for [0..maxCompoundWithoutGeneric] :: [Compound] with all non-generic Compounds
maxCompoundWithoutGeneric :: Int
maxCompoundWithoutGeneric = fromEnum (maxBound :: Nutrient) + fromEnum (maxBound :: Component) + 1

-- Example:

exampleEnvironment :: Environment
exampleEnvironment =
  Environment
    { soil = [ (Nitrate, 2)
             , (Phosphor, 3)
             , (Photosynthesis, 10)
             ]
    , predators = [ (greenfly, 0.1) ]
    , metabolismIteration = 100
    , maxCompound = maxCompoundWithoutGeneric
    , toxicCompounds = [Produced FPP]
    }

type World a = ReaderT Environment IO a

-- Plants
-- ------

-- Plants consist of a Genome responsible for creation of the PSM and also an
-- external state how many nutrients and compounds are currently inside the plant.

type Genome = [(Enzyme, Quantity, Activation)]

data Plant = Plant
     { genome            :: Genome
       -- ^ the genetic characteristic of the plant
     , absorbNutrients   :: World [(Nutrient,Amount)]
       -- ^ the capability to absorb nutrients given an environment
     }
instance Show Plant where
  show p = "Plant with Genome " ++ show (genome p)
instance Eq Plant where
  a == b = genome a == genome b

-- | The following example yields in the example-environment this population:
--
--   >>> printPopulation [pps, fpps] plants
--   Population:
--   PPS     ______oöö+++______oöö+++____________oöö+++oöö+++
--   FPPS    ____________oöö+++oöö+++______oöö+++______oöö+++
plants :: [Plant]
plants = (\g -> Plant g defaultAbsorption) <$> genomes
 where
   enzymes = [pps, fpps]
   quantity = [1,2] :: [Quantity]
   activation = [0.7, 0.9, 1]

   genomes = do
     e <- permutations enzymes
     e' <- subsequences e
     q <- quantity
     a <- activation
     return $ (,,) <$> e' <*> [q] <*> [a]

   defaultAbsorption = soil <$> ask >>= return . fmap ( limit Phosphor 2
                                                      . limit Nitrate 1
                                                      . limit Sulfur 0
                                                      )
   -- custom absorbtion with helper-function:
   limit :: Nutrient -> Amount -> (Nutrient, Amount) -> (Nutrient, Amount)
   limit n a (n', a')
     | n == n'   = (n, min a a') -- if we should limit, then we do ;)
     | otherwise = (n', a')

-- Fitness
-- -------

-- The fitness-measure is central for the generation of offspring and the
-- simulation. It evaluates the probability for passing on genes given a plant in
-- an environment.

type Fitness = Double

fitness :: Plant -> World Fitness
fitness p = do
  nutrients <- absorbNutrients p           -- absorb soil
  products <- produceCompounds p nutrients -- produce compounds
  survivalRate <- deterPredators products  -- defeat predators with produced compounds
  return survivalRate
  -- can also be written as, but above is more clear.
  -- fitness p = absorbNutrients p >>= produceCompounds p >>= deterPredators

produceCompounds :: Plant -> [(Nutrient, Amount)] -> World (Vector Amount)
produceCompounds (Plant genes _) substrate = do
  numIter <- metabolismIteration <$> ask
  numCompounds <- maxCompound <$> ask
  let
    initialAmount = assoc (numCompounds+1) 0 ((\(n,a) -> (fromEnum $ Substrate n,a)) <$> substrate)
    enzymes = (\(e,q,a) -> (synthesis e,(fromIntegral q)*a)) <$> genes -- [(((Component,Amount),(Component,Amount)),q*a)], Amount got * by quantity & activation
    positions = concat $ (\(((i,ia),(o,oa)),f) -> [((fromEnum i,fromEnum i),2*f*ia),((fromEnum o,fromEnum i),oa),((fromEnum i,fromEnum o),f*oa)]) <$> enzymes -- [((row,column),amount)]
    mat = accum (konst 0 (numCompounds+1,numCompounds+1)) (+) positions --accumulate all entries into one matrix.
    -- mat is now the rate of change in u'(t) = A u(t)
    (l,v) = eig (ident (numCompounds+1) + ((*0.01) `cmap` mat)) -- use u(t+1) = u(t) + A u(t) = (E + A) u(t) for iteration
    final = (realPart `cmap` (v <> ((^numIter) `cmap` diag l) <> (tr v))) #> initialAmount -- (E + A)^numIter * t_0 for numIter iterations.
  return final


deterPredators :: Vector Amount -> World Probability
deterPredators cs = do
   ps <- predators <$> ask
   ts <- toxicCompounds <$> ask
   let
     deter :: Predator -> Bool
         -- if any (amount of toxin t > 0| for all toxins t | t not in p's resistance-list)
     deter p = or [cs ! (fromEnum t) > 0 | t <- ts,           not (t `elem` resistance p)]
         -- multipy   (probability of occurence * intensity of destruction| for all predators, if not deterred by toxins
   return . product $ [prob*fitnessImpact p                               | (p,prob) <- ps,    not $ deter p]

-- Mating & Creation of diversity
-- ------------------------------

-- Running the simulation
-- ----------------------




main = do
  putStrLn "Environment:"
  print exampleEnvironment
  putStrLn "Example population:"
  printPopulation [pps, fpps] plants
  fitness <- runReaderT (sequence $ (\a -> do p <- absorbNutrients a >>= produceCompounds a; (,) p <$> deterPredators p) <$> plants) exampleEnvironment
  mapM_ print fitness

-- Utility Functions
-- -----------------

getAmountOf :: Compound -> [(Compound, Amount)] -> Amount
getAmountOf c = sum . fmap snd . filter ((== c) . fst)

printPopulation :: [Enzyme] -> [Plant] -> IO ()
printPopulation es ps = do
  let padded i str = take i $ str ++ repeat ' '
  putStrLn "Population:"
  forM_ es $ \e -> do
    putStr $ padded 8 (show e)
    forM_ ps $ \(Plant g _) -> do
      let curE = sum $ map (\(_,q,a) -> (fromIntegral q)*a) 
                     . filter (\(e',_,_) -> e == e')
                     $ g
          plot x
           | x > 2     = "O"
           | x > 1     = "+"
           | x > 0.7   = "ö"
           | x > 0.5   = "o"
           | x > 0     = "."
           | otherwise = "_"
      putStr (plot curE)
    putStrLn ""