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@ -60,11 +60,14 @@ library
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, HushGP.PushTests.IntTests
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, HushGP.PushTests.GenericTests
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, HushGP.PushTests.UtilTests
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, HushGP.PushTests.GP.Selection
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, HushGP.GP
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, HushGP.GP.PushArgs
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, HushGP.GP.Variation
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, HushGP.GP.Downsample
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, HushGP.GP.PushData
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, HushGP.GP.Selection
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, HushGP.GP.Individual
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, HushGP.Problems.IntegerRegression
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, HushGP.Tools.Metrics
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7
TODO.md
7
TODO.md
@ -6,6 +6,7 @@
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- [X] Implement all functions as seen in propeller
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- [X] Implement all functions as seen in the specification
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- [ ] Implement Linear Algebra functions as specified in the previous papers
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- [ ] These are in a separate branch, just need merging now
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- [X] Add a function to sort a vector forward and backwards
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- [X] Disambiguate isEmpty and stackIsEmpty
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- [X] Rename Logical to Bool
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@ -18,6 +19,7 @@
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- [X] Move utility functions to their own file
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- [ ] Make add/sub/mult/div/mod instructions generic
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- [ ] Use template haskell to (mostly) generate functions from generic ones (Split files based on the arity of their functions)
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- [ ] Add more special functions like sqrt, pow
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## PushGP TODO
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- [X] Implement a Plushy genome translator
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@ -31,10 +33,11 @@
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- [ ] Need to make genomes serializable (Check pysh json files)
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- [ ] Add Memory
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- [ ] Add history stack(s), like a call stack
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- [ ] Implement interpreter options (could probably just place this into a map)
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- [ ] Implement interpreter options (PushArgs would work well)
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- Should probably place this in a separate file
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- [ ] Implement different forms of downsampling
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- [X] Implement different forms of downsampling
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- [ ] Implement concurrent execution of creating random plushies and evaluating individuals
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- [X] Devise a good way to implement ERCs
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- [ ] Implement random simplification of genomes
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- [ ] Find a way to multi-thread this
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- [ ] Look at using `uniformShuffleList` over System.Random.Shuffle
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@ -11,6 +11,7 @@ import HushGP.GP.PushArgs
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import HushGP.GP.PushData
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import HushGP.GP.Variation
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import HushGP.Genome
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import HushGP.GP.Individual
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-- import Debug.Trace (trace, traceStack)
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@ -4,12 +4,12 @@ import System.Random.Shuffle
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import System.Random
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import Data.List
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import Data.Maybe
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import HushGP.Genome
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import HushGP.Utility
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import HushGP.GP.PushData
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import HushGP.GP.PushArgs
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import HushGP.Tools.Metrics
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import HushGP.Instructions.Utility
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import HushGP.GP.Individual
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-- |Sets the index of the passed training data.
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assignIndicesToData :: [PushData] -> [PushData]
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24
src/HushGP/GP/Individual.hs
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24
src/HushGP/GP/Individual.hs
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@ -0,0 +1,24 @@
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module HushGP.GP.Individual where
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import HushGP.State
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-- | The structure for an individual containing the genome, the totalFitness, and
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-- the individual fitness cases for lexicase.
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data Individual = Individual
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{ plushy :: [Gene],
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totalFitness :: Maybe Double,
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fitnessCases :: Maybe [Double]
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}
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deriving (Show, Eq)
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instance Ord Individual where
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ind0 <= ind1 = totalFitness ind0 <= totalFitness ind1
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-- | Extracts the fitnessCases from an Individual. Errors if the field is empty.
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extractFitnessCases :: Individual -> [Double]
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extractFitnessCases Individual {fitnessCases = Nothing} = error "Error: fitnessCases is empty!"
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extractFitnessCases Individual {fitnessCases = Just xs} = xs
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extractTotalFitness :: Individual -> Double
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extractTotalFitness Individual {totalFitness = Nothing} = error "Error: totalFitness is empty!"
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extractTotalFitness Individual {totalFitness = Just x} = x
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@ -3,6 +3,7 @@ module HushGP.GP.PushArgs where
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import HushGP.State
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import HushGP.Instructions
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import HushGP.GP.PushData
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import HushGP.GP.Individual
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import Data.Map qualified as Map
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-- | The structure holding the arguments for the various aspects
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@ -96,7 +97,11 @@ data PushArgs = PushArgs
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epsilons :: Maybe [Double],
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-- | Used with the CaseMaxminAuto downsampling strategy. Tells downsampling to stop when
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-- the maximum minimum distance is too far away.
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caseDelta :: Double
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caseDelta :: Double,
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-- | Used in lexicase selection. If initialCases is present will use those before randomly
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-- selecting from the population for initial cases. Can raise a value into the IO monad using
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-- `pure @IO`
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initialCases :: Maybe [Int]
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}
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-- | The default values for which all runs of Hush derive
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@ -143,5 +148,6 @@ defaultPushArgs = PushArgs {
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umadRate = 0.1,
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variation = Map.fromList [("umad", 1.0)],
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epsilons = Nothing,
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caseDelta = 0
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caseDelta = 0,
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initialCases = Nothing
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}
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32
src/HushGP/GP/Selection.hs
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32
src/HushGP/GP/Selection.hs
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@ -0,0 +1,32 @@
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module HushGP.GP.Selection where
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import Data.List
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import System.Random
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import System.Random.Shuffle
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import HushGP.GP.PushArgs
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import HushGP.GP.Individual
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-- | Tournament selection based off tournament size from PushArgs and a population.
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-- Takes the individual with the lowest total error in the tournament.
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tournamentSelection :: PushArgs -> [Individual] -> IO Individual
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tournamentSelection PushArgs{tournamentSize = tSize} pop = do
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shuffledPop <- shuffle' pop (length pop) <$> initStdGen
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let tournSet = take tSize shuffledPop
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pure $ minimum tournSet
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-- |Selects an individual from the population using lexicase selection.
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-- Lexicase parent selection filters the population by considering one random training case at a time,
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-- eliminating any individuals with errors for the current case that are worse than the best error in the selection pool,
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-- until a single individual remains. This is the top level function.
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lexicaseSelection :: PushArgs -> [Individual] -> IO Individual
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lexicaseSelection PushArgs{initialCases = iCases} pop = do
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startCases <- maybe (shuffle' [0..lehp] lehp <$> initStdGen) (pure @IO) iCases
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undefined
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where
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lehp :: Int -- length of the extracted fitness cases of the head of the passed population.
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lehp = length $ extractFitnessCases $
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case uncons pop of
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Just (x, _) -> x
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_ -> error "Error: Population in lexicaseSelection cannot be empty!"
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-- lexicaseSelection' ::
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@ -1,7 +1,7 @@
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module HushGP.GP.Variation where
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import HushGP.Genome
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import HushGP.GP.PushArgs
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import HushGP.GP.Individual
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newIndividual :: PushArgs -> [Individual] -> Individual
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newIndividual = error "Implement this later"
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@ -7,31 +7,11 @@ import HushGP.GP.PushArgs
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import HushGP.Instructions.Opens
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import HushGP.State
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import HushGP.Utility
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import HushGP.GP.Individual
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-- import HushGP.Instructions
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-- import Debug.Trace
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-- | The structure for an individual containing the genome, the totalFitness, and
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-- the individual fitness cases for lexicase.
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data Individual = Individual
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{ plushy :: [Gene],
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totalFitness :: Maybe Double,
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fitnessCases :: Maybe [Double]
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}
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deriving (Show, Eq)
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instance Ord Individual where
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ind0 <= ind1 = totalFitness ind0 <= totalFitness ind1
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-- | Extracts the fitnessCases from an Individual. Errors if the field is empty.
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extractFitnessCases :: Individual -> [Double]
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extractFitnessCases Individual {fitnessCases = Nothing} = error "Error: fitnessCases is empty!"
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extractFitnessCases Individual {fitnessCases = Just xs} = xs
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extractTotalFitness :: Individual -> Double
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extractTotalFitness Individual {totalFitness = Nothing} = error "Error: totalFitness is empty!"
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extractTotalFitness Individual {totalFitness = Just x} = x
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-- | Makes a random individual based on the variables in a passed PushArgs.
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makeRandomIndividual :: PushArgs -> IO Individual
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makeRandomIndividual pushArgs = do
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22
src/HushGP/PushTests/GP/Selection.hs
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22
src/HushGP/PushTests/GP/Selection.hs
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@ -0,0 +1,22 @@
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module HushGP.PushTests.GP.Selection where
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import Data.List
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import HushGP.GP.Individual
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import HushGP.State
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import HushGP.Utility
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-- | One of the steps in the lexicase selection process for selecting initial survivors.
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tempFunc0 :: [[Individual]]
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tempFunc0 = groupBy (\x y -> fitnessCases x == fitnessCases y) testInds
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-- \| Another step forward in the lexicase selection process.
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survivors :: IO [Individual]
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survivors = mapM randElem tempFunc0
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-- | A list of individuals used for testing.
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testInds :: [Individual]
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testInds =
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[ Individual{plushy = [Close], totalFitness = Just 1000, fitnessCases = Just [500,500]}
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, Individual{plushy = [Close], totalFitness = Just 1000, fitnessCases = Just [400,600]}
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, Individual{plushy = [Close], totalFitness = Just 900, fitnessCases = Just [500,400]}
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]
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@ -23,3 +23,7 @@ mapIndexed = mapIndexed' 0
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mapIndexed' :: Int -> (Int -> a -> b) -> [a] -> [b]
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mapIndexed' _ _ [] = []
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mapIndexed' count f (x : xs) = f count x : mapIndexed' (count + 1) f xs
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-- | Returns a random element from a passed list. No generator required.
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randElem :: [a] -> IO a
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randElem xs = (xs !!) . fst . uniformR (0, length xs - 1) <$> initStdGen
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