clean up, organize and document
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Johannes Merl
199
lambda/src/LambdaDatasets/NurseryDataset.hs
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199
lambda/src/LambdaDatasets/NurseryDataset.hs
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{-# LANGUAGE DeriveGeneric #-}
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{-# LANGUAGE MultiParamTypeClasses #-}
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{-# LANGUAGE OverloadedStrings #-}
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{-# LANGUAGE TypeApplications #-}
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{-# LANGUAGE NoImplicitPrelude #-}
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module LambdaDatasets.NurseryDataset
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( module LambdaCalculus,
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module LambdaDatasets.NurseryDataset,
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module LambdaDatasets.NurseryData,
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module GA,
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)
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where
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import qualified Data.List.NonEmpty as NE
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import qualified Data.Map.Strict as Map
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import Data.Random
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import Data.Random.Distribution.Uniform
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import qualified Data.Text as T
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import Data.Tuple.Extra
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import GA
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import LambdaDatasets.NurseryData
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import LambdaCalculus
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import qualified Language.Haskell.Interpreter as Hint
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import qualified Language.Haskell.Interpreter.Unsafe as Hint
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import Protolude
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import Protolude.Error
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import System.Random.MWC (createSystemRandom)
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import qualified Type.Reflection as Ref
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import Utils
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lE :: LambdaEnviroment
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lE =
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LambdaEnviroment
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{ functions =
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Map.fromList
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[ -- Math
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-- Logic
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Bool -> Bool))), ["(&&)", "(||)"]),
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-- Ordered Enums
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((Ref.SomeTypeRep (Ref.TypeRep @(NurseryClass -> NurseryClass -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Parents -> Parents -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(HasNurs -> HasNurs -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Form -> Form -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Children -> Children -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Housing -> Housing -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Finance -> Finance -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Social -> Social -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Health -> Health -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
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-- Eq Enum
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-- Any Type
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Int -> Int -> Int))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> NurseryClass -> NurseryClass -> NurseryClass))), ["if'","if'","if'","if'","if'","if'","if'","if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Parents -> Parents -> Parents))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> HasNurs -> HasNurs -> HasNurs))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Form -> Form -> Form))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Children -> Children -> Children))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Housing -> Housing -> Housing))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Finance -> Finance -> Finance))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Social -> Social -> Social))), ["if'"]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Health -> Health -> Health))), ["if'"])
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],
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constants =
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Map.fromList
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[ ((Ref.SomeTypeRep (Ref.TypeRep @(Bool))), [(fmap show (uniform True False :: RVar Bool))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(NurseryClass))), [(fmap show (enumUniform NotRecommend SpecPriority))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Parents))), [(fmap show (enumUniform Usual GreatPret))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(HasNurs))), [(fmap show (enumUniform ProperNurs VeryCritNurs ))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Form))), [(fmap show (enumUniform CompleteFamilyForm FosterFamilyForm ))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Children))), [(fmap show (enumUniform OneChild MoreChilds ))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Housing))), [(fmap show (enumUniform ConvenientHousing CriticalHousing ))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Finance))), [(fmap show (enumUniform ConvenientFinance InconvFinance ))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Social))), [(fmap show (enumUniform NotProblematicSocial ProblematicSocial ))]),
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((Ref.SomeTypeRep (Ref.TypeRep @(Health))), [(fmap show (enumUniform NotRecommendHealth PriorityHealth ))])
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],
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targetType = (Ref.SomeTypeRep (Ref.TypeRep @(Parents -> HasNurs -> Form -> Children -> Housing -> Finance -> Social -> Health -> NurseryClass))),
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maxDepth = 8,
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weights =
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ExpressionWeights
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{ lambdaSpucker = 1,
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lambdaSchlucker = 2,
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symbol = 30,
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variable = 20,
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constant = 5
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}
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}
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trainingFraction :: R
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trainingFraction = (2/3)
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lEE :: LamdaExecutionEnv
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lEE =
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LamdaExecutionEnv
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{ -- For now these need to define all available functions and types. Generic functions can be used.
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imports = ["LambdaDatasets.NurseryDefinition"],
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training = True,
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trainingData =
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( map fst (takeFraktion trainingFraction nurseryTrainingData),
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map snd (takeFraktion trainingFraction nurseryTrainingData)
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),
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testData =
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( map fst (dropFraktion trainingFraction nurseryTrainingData),
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map snd (dropFraktion trainingFraction nurseryTrainingData)
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),
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exTargetType = (Ref.SomeTypeRep (Ref.TypeRep @(Parents -> HasNurs -> Form -> Children -> Housing -> Finance -> Social -> Health -> NurseryClass))),
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results = Map.empty
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}
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shuffledLEE :: IO LamdaExecutionEnv
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shuffledLEE = do
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mwc <- liftIO createSystemRandom
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let smpl = ((sampleFrom mwc) :: RVar a -> IO a)
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itD <- smpl $ shuffle nurseryTrainingData
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return
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LamdaExecutionEnv
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{ -- For now these need to define all available functions and types. Generic functions can be used.
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imports = ["LambdaDatasets.NurseryDefinition"],
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training = True,
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trainingData =
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( map fst (takeFraktion trainingFraction itD),
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map snd (takeFraktion trainingFraction itD)
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),
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testData =
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( map fst (dropFraktion trainingFraction itD),
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map snd (dropFraktion trainingFraction itD)
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),
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exTargetType = (Ref.SomeTypeRep (Ref.TypeRep @(Parents -> HasNurs -> Form -> Children -> Housing -> Finance -> Social -> Health -> NurseryClass))),
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results = Map.empty
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}
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data LamdaExecutionEnv = LamdaExecutionEnv
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{ -- For now these need to define all available functions and types. Generic functions can be used.
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imports :: [Text],
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training :: Bool,
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trainingData :: ([(Parents, HasNurs, Form, Children, Housing, Finance, Social, Health)], [NurseryClass]),
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testData :: ([(Parents, HasNurs, Form, Children, Housing, Finance, Social, Health)], [NurseryClass]),
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exTargetType :: TypeRep,
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-- todo: kindaHacky
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results :: Map TypeRequester FittnesRes
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}
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data FittnesRes = FittnesRes
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{ total :: R,
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fitnessTotal :: R,
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fitnessGeoMean :: R,
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fitnessMean :: R,
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accuracy :: R,
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biasSize :: R,
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totalSize :: N
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}
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deriving (Show)
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instance Fitness FittnesRes where
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getR = total
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instance Evaluator TypeRequester LamdaExecutionEnv FittnesRes where
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fitness' env tr = (results env) Map.! tr
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calc env pop = do
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let relevantResults = Map.filterWithKey (\k _ -> contains pop k) (results env)
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let toAdd = NE.filter (\k -> not (Map.member k relevantResults)) pop
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toInsert <- Hint.runInterpreter (evalResults env toAdd)
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let insertPair (key, val) m = Map.insert key val m
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let res = foldr insertPair relevantResults (fromRight (error ("To insert is " <> show toInsert)) toInsert)
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return env {results = res}
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dset :: LamdaExecutionEnv -> ([(Parents, HasNurs, Form, Children, Housing, Finance, Social, Health)], [NurseryClass])
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dset lEE = if training lEE then trainingData lEE else testData lEE
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evalResults :: LamdaExecutionEnv -> [TypeRequester] -> Hint.InterpreterT IO [(TypeRequester, FittnesRes)]
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evalResults ex trs = do
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Hint.setImports $ (map T.unpack (imports ex)) ++ ["Protolude"]
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Hint.unsafeSetGhcOption "-O2"
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let arrayOfFunctionText = map toLambdaExpressionS trs
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let textOfFunctionArray = "[" <> T.intercalate "," arrayOfFunctionText <> "]"
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result <- Hint.interpret (T.unpack (textOfFunctionArray)) (Hint.as :: [Parents -> HasNurs -> Form -> Children -> Housing -> Finance -> Social -> Health -> NurseryClass])
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return $ zipWith (evalResult ex) trs result
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evalResult :: LamdaExecutionEnv -> TypeRequester -> (Parents -> HasNurs -> Form -> Children -> Housing -> Finance -> Social -> Health -> NurseryClass) -> (TypeRequester, FittnesRes)
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evalResult ex tr result = ( tr,
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FittnesRes
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{ total = acc * 100 + (biasSmall - 1),
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fitnessTotal = fitness',
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fitnessMean = meanOfAccuricyPerClass resAndTarget,
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fitnessGeoMean = geomeanOfDistributionAccuracy resAndTarget,
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accuracy = acc,
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biasSize = biasSmall,
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totalSize = countTrsR tr
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}
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)
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where
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res = map (\(a, b, c, d, e, f, g, h) -> result a b c d e f g h) (fst (dset ex))
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resAndTarget = (zip (snd (dset ex)) res)
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acc = (foldr (\ts s -> if ((fst ts) == (snd ts)) then s + 1 else s) 0 resAndTarget) / fromIntegral (length resAndTarget)
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biasSmall = exp ((-(fromIntegral (countTrsR tr))) / 1000) -- 0 (schlecht) bis 1 (gut)
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fitness' = meanOfAccuricyPerClass resAndTarget
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score = fitness' + (biasSmall - 1)
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