diff --git a/BioInf/Keys.hs b/BioInf/Keys.hs new file mode 100644 --- /dev/null +++ b/BioInf/Keys.hs @@ -0,0 +1,246 @@ +{-# LANGUAGE PatternGuards #-} +{-# LANGUAGE TupleSections #-} + +-- | Transformation of predictions and known structures into keys. Keys are +-- used for linearization. +-- +-- NOTE READ THE BIG FAT KEYS WARNING +-- +-- TODO Generalize and move into its own library + +module BioInf.Keys where + +import Data.Vector.Unboxed as VU hiding ((++),concatMap,length,concat,null) +import qualified Data.Vector.Unboxed as VU +import Data.List as L +import qualified Data.Map as M + +import Biobase.Primary +import Biobase.Secondary +import Biobase.Secondary.Diagrams +import Data.PrimitiveArray +import Data.PrimitiveArray.Ix + +import BioInf.Params as P +import BioInf.Params.Import as P +import BioInf.Params.Export as P + + + +-- | A list of "named" parameters. + +paramsKeys = concat + [ L.map (HairpinLength . fst) . assocs . hairpinLength $ zeroParams + , L.map (HairpinClose . fst) . assocs . hairpinClose $ zeroParams + , L.map (Stem . fst) . assocs . stem $ zeroParams + , L.map (StemTriplet . fst) . assocs . stemTriplet $ zeroParams + , L.map (InteriorLength . fst) . assocs . interiorLength $ zeroParams + , L.map (InteriorAsym . fst) . assocs . interiorAsym $ zeroParams + , L.map (InteriorClose . fst) . assocs . interiorClose $ zeroParams + , L.map (BulgeLength . fst) . assocs . bulgeLength $ zeroParams + , L.map (BulgeTriplet . fst) . assocs . bulgeTriplet $ zeroParams + , L.map (BulgeClose . fst) . assocs . bulgeClose $ zeroParams + , L.map (MbClose . fst) . assocs . mbClose $ zeroParams + -- scalar values for multiloops + , [ MultiBranched, MultiHelix, MultiUnpaired ] + -- distance between pairs + , L.map (PairDistance . fst) . assocs . pairDistance $ zeroParams + , [ InterMolInit ] + ] + +-- | Uniquely tag each key +-- +-- NOTE BIG FAT WARNING: BE ABSOLUTELY SURE THAT ALL IMPORTS AND EXPORTS FOLLOW +-- THIS ORDERING EXACTLY, OTHERWISE KEYS WILL BE MAPPED TO WRONG POSITIONS +-- DURING LOOKUP AND VALUES END UP SOMEWHERE ELSE. + +data Keys + = HairpinLength Int + | HairpinClose (ExtPair,Nuc,Nuc) + | Stem (ExtPair,ExtPair) + | StemTriplet (ExtPair,ExtPair) + | InteriorLength Int + | InteriorAsym Int + | InteriorClose (ExtPair,Nuc,Nuc) + | BulgeLength Int + | BulgeTriplet (ExtPair,ExtPair) + | BulgeClose ExtPair + | MbClose (ExtPair,Nuc,Nuc) + | MultiBranched + | MultiHelix + | MultiUnpaired + | PairDistance Int + | InterMolInit + deriving (Read,Show,Eq,Ord) + +-- | Training data to feature vector + +featureVector :: String -> [ExtPairIdx] -> [Int] +featureVector inp xs = ys where + ys = L.map lookupFeatureIndex tr + tr = treeToFeatures inp $ ssTree (length inp) xs + +-- | transform feature to 0-based index + +lookupFeatureIndex :: Keys -> Int +lookupFeatureIndex k + | Just v <- k `M.lookup` kvs = v + | otherwise = error $ show ("key unknown: ", k) + where + +-- | Map param keys to thei Int-indices. + +kvs = M.fromList $ L.zip paramsKeys [0..] +{-# NOINLINE kvs #-} + +-- | And back from Int-indices to the keys. + +vks = M.fromList $ L.zip [0 ::Int ..] paramsKeys +{-# NOINLINE vks #-} + +-- | Takes a primary structure and secondary structure tree and produces a list +-- of keys. +-- +-- TODO Data.Traversable ?! +-- +-- TODO better handling of unknown features: we can have genuine errors +-- (pseudoknots) and uncoded features (e.g. hairpins of size > 30) + +treeToFeatures :: (MkPrimary a, Show a) => a -> SSTree ExtPairIdx t -> [Keys] +treeToFeatures inp = f where + pri = mkPrimary inp + swap23 (a,b,c) = (a,c,b) + vuIndex xs k = if k<0 || k>= VU.length xs then error (show (inp,k)) else xs VU.! k + n = VU.length pri -1 + -- Features for external loop + f (SSExt n _ xs) = concatMap f xs + -- Features for anything else + f (SSTree ((i,j),ijExt) _ xs) + + -- intermolecular init + | null xs + , let is = VU.length . VU.filter (==nIMI) . VU.take (j-i) . VU.drop i $ pri + , is > 0 + = L.replicate is InterMolInit + + -- hairpin + -- TODO relax the minima? + | null xs + , j-i-1<=P.maxLength + , j-i>=3 + = [ HairpinLength (j-i-1) + , HairpinClose (((nI,nJ),ijExt),nIp1,nJm1) +-- , PairDistance (j-i-1) + ] + + -- normal stem + | [SSTree ((k,l),klExt) _ _] <- xs + , let nK = pri `vuIndex` k; nL = pri `vuIndex` l + , i+1==k && j-1==l + = [ Stem (((nI,nJ),ijExt),((nL,nK),swap23 klExt)) +-- , PairDistance (j-i-1) + ] ++ concatMap f xs + {- + -- triplet stem (right nucleotide shared) + | [SSTree ((k,l),klExt) _ _] <- xs + , i+1==k && j==l + , let nK = pri `vuIndex` k + = [ StemTriplet ( ((nI,nJ),ijExt) + , ((nJ,nK),swap23 klExt) + ) +-- , PairDistance (j-i-1) + ] ++ concatMap f xs + -} + {- + -- triplet stem (left nucleotide shared) + | [SSTree ((k,l),klExt) _ _] <- xs + , i==k && j-1==l + , let nL = pri `vuIndex` l + = [ StemTriplet (((nI,nL),klExt),((nI,nJ),ijExt)) -- shared nuc first (nI), then 5' (nL) first +-- , PairDistance (j-i-1) + ] ++ concatMap f xs + -} + -- interior loops + | [SSTree ((k,l),klExt) _ _] <- xs + , let lenI = k-i-1; lenJ = j-l-1; len = lenI+lenJ + , lenI>=1 && lenJ>=1 && len<=P.maxLength + , let nL = pri `vuIndex` l; nK = pri `vuIndex` k; lkExt = swap23 klExt + , let nLm1 = pri `vuIndex` (l-1); nKp1 = pri `vuIndex` (k+1) + , let nLp1 = pri `vuIndex` (l+1); nKm1 = pri `vuIndex` (k-1) + = [ InteriorLength len + , InteriorAsym $ abs (lenI-lenJ) + , InteriorClose (((nI,nJ),ijExt),nIp1,nJm1) + , InteriorClose (((nL,nK),lkExt),nLp1,nKm1) +-- , PairDistance (j-i-1) + ] ++ concatMap f xs + -- normal bulge + | [SSTree ((k,l),klExt) _ _] <- xs + , let lenI = k-i-1; lenJ = j-l-1; len = max lenI lenJ + , lenI==0 && lenJ>0 || lenJ==0 && lenI>0 + , len<=P.maxLength + , let nK = pri `vuIndex` k; nL = pri `vuIndex` l; lkExt = swap23 klExt + = [ BulgeLength len + , BulgeClose ((nI,nJ),ijExt) + , BulgeClose ((nL,nK),lkExt) +-- , PairDistance (j-i-1) + ] ++ concatMap f xs + {- + -- bulge triplet (left) + | [SSTree ((k,l),klExt) _ _] <- xs + , let lenJ = j-l-1 + , i==k && lenJ>0 + , lenJ<=P.maxLength + , let nL = pri `vuIndex` l + = [ BulgeLength lenJ + , BulgeTriplet (((nI,nL),klExt),((nI,nJ),ijExt)) +-- , PairDistance (j-i-1) + ] ++ concatMap f xs + -} + {- + -- bulge triplet (right) + | [SSTree ((k,l),klExt) _ _] <- xs + , let lenI = k-i-1 + , j==l && lenI>0 + , lenI<=P.maxLength + , let nK = pri `vuIndex` k + = [ BulgeLength lenI + , BulgeTriplet (((nJ,nI),swap23 ijExt),((nJ,nK),swap23 klExt)) +-- , PairDistance (j-i-1) + ] ++ concatMap f xs + -} + -- close a multibranched loop + -- + -- TODO what about shared multibranched loops? (see sequence GCGGCACCGUCCGCUCAAACAAACGG in fr3d DB) + | length xs > 1 +-- = concatMap f xs + = [ MbClose (((nI,nJ),ijExt),nIp1,nJm1) +-- , PairDistance (j-i-1) + , MultiBranched + , MultiHelix + ] ++ concat + -- each inner part + [ [ MbClose (((nL,nK),lkExt),nLp1,nKm1) + , MultiHelix ] + | SSTree ((k,l),klExt) _ _ <- xs + , k>0 && l [ExtPairIdx] -> SSTree ExtPairIdx () +ssTree n xs = d2sTree . mkD2S . (n,) . L.filter okPairs $ xs where + okPairs ((i,j),_) = j-i>2 -- we only keep pairs which have at least to free nucleotides between them diff --git a/BioInf/Params.hs b/BioInf/Params.hs new file mode 100644 --- /dev/null +++ b/BioInf/Params.hs @@ -0,0 +1,105 @@ +{-# LANGUAGE TupleSections #-} + +-- | RNA-folding parameter space. +-- +-- TODO find better names for types, functions, and minima/maxima. + +module BioInf.Params where + +import Data.PrimitiveArray +import Data.PrimitiveArray.Ix + +import Biobase.Primary +import Biobase.Secondary + + + +-- | A (very) rich set of paramters. +-- +-- TODO 1xn interior loops should be tested (how often do they occur?) +-- +-- TODO external loop + +data Params = Params + { hairpinLength :: PaLength + , hairpinClose :: PaExtPairNN + , stem :: Pa2ExtPairs + , stemTriplet :: Pa2ExtPairs + , interiorLength :: PaLength + , interiorAsym :: PaLength + , interiorClose :: PaExtPairNN + , bulgeLength :: PaLength + , bulgeTriplet :: Pa2ExtPairs + , bulgeClose :: PaExtPair + , mbClose :: PaExtPairNN + , multiBranched :: Double + , multiHelix :: Double + , multiUnpaired :: Double + , pairDistance :: PaDistance + , interMolInit :: Double + } deriving (Read,Show) + +maxLength = 1000 :: Int +maxDistance = 1000 :: Int +minExtPair = ((nN,nN),(cis,wc,wc)) +maxExtPair = ((nT,nT),(trans,hoogsteen,hoogsteen)) +min2ExtPairs = (minExtPair,minExtPair) +max2ExtPairs = (maxExtPair,maxExtPair) +minExtPairNN = (minExtPair,nN,nN) +maxExtPairNN = (maxExtPair,nT,nT) +minTriplet = min2ExtPairs +maxTriplet = max2ExtPairs + +-- | A parameter set with all values set to zero. + +zeroParams = Params + { hairpinLength = zeroLength + , hairpinClose = zeroExtPairNN + , stem = zero2ExtPairs + , stemTriplet = zeroTriplet + , interiorLength = zeroLength + , interiorAsym = zeroLength + , interiorClose = zeroExtPairNN + , bulgeLength = zeroLength + , bulgeTriplet = zeroTriplet + , bulgeClose = zeroExtPair + , mbClose = zeroExtPairNN + , multiBranched = 0 + , multiHelix = 0 + , multiUnpaired = 0 + , pairDistance = zeroDistance + , interMolInit = 0 + } + +zeroLength = fromAssocs 0 maxLength 0 [] +zeroDistance = fromAssocs 0 maxDistance 0 [] +zeroExtPair = fromAssocs minExtPair maxExtPair 0 [] +zero2ExtPairs = fromAssocs min2ExtPairs max2ExtPairs 0 [] +zeroExtPairNN = fromAssocs minExtPairNN maxExtPairNN 0 [] +zeroTriplet = fromAssocs minTriplet maxTriplet 0 [] + + + +-- ** types + +-- | An array which encodes "length" information + +type PaLength = PrimArray Int Double + +-- | This is an experimental annotation for long-distance interactions + +type PaDistance = PrimArray Int Double + +-- | An array holding information for one extended pair. + +type PaExtPair = PrimArray ExtPair Double + +-- | An array holding information for two extended pairs, e.g. stems. + +type Pa2ExtPairs = PrimArray (ExtPair,ExtPair) Double + +-- | An array holding information for one extended pair and two unpaired +-- nucleotides, closes a loop. + +type PaExtPairNN = PrimArray (ExtPair,Nuc,Nuc) Double -- pair and two unpaired nucleotides, for hairpins, etc + diff --git a/BioInf/Params/Export.hs b/BioInf/Params/Export.hs new file mode 100644 --- /dev/null +++ b/BioInf/Params/Export.hs @@ -0,0 +1,33 @@ +{-# LANGUAGE RecordWildCards #-} + +-- | Exporting parameters is a bit more involved as we need the ability to +-- export into a database format as well as linearize to list form. + +module BioInf.Params.Export where + +import Data.PrimitiveArray as PA +import Data.PrimitiveArray.Ix as PA + +import BioInf.Params + + + +-- | Just a long list of doubles. + +toList :: Params -> [Double] +toList Params{..} = concat + [ PA.toList hairpinLength + , PA.toList hairpinClose + , PA.toList stem + , PA.toList stemTriplet + , PA.toList interiorLength + , PA.toList interiorAsym + , PA.toList interiorClose + , PA.toList bulgeLength + , PA.toList bulgeTriplet + , PA.toList bulgeClose + , PA.toList mbClose + , [multiBranched, multiHelix, multiUnpaired] + , PA.toList pairDistance + , [interMolInit] + ] diff --git a/BioInf/Params/Import.hs b/BioInf/Params/Import.hs new file mode 100644 --- /dev/null +++ b/BioInf/Params/Import.hs @@ -0,0 +1,73 @@ + +-- | Given a list of doubles with the /exact required length/ import into a +-- 'Params' structure. + +module BioInf.Params.Import where + +import Data.PrimitiveArray as PA +import Data.PrimitiveArray.Ix as PA +import Data.Ix (rangeSize) + +import BioInf.Params + + + +-- | Cast a list of values to parameters. +-- +-- NOTE This operation is rather fragile if there are layout changes. Consider +-- Repr for this. +-- +-- NOTE BIG FAT WARNING: BE ABSOLUTELY SURE THAT ALL IMPORTS AND EXPORTS FOLLOW +-- THIS ORDERING EXACTLY, OTHERWISE KEYS WILL BE MAPPED TO WRONG POSITIONS +-- DURING LOOKUP AND VALUES END UP SOMEWHERE ELSE. + +fromList :: [Double] -> Params +fromList xs = Params + { hairpinLength = PA.fromList 0 maxLength hpl + , hairpinClose = PA.fromList minExtPairNN maxExtPairNN hpc + , stem = PA.fromList min2ExtPairs max2ExtPairs sp + , stemTriplet = PA.fromList minTriplet maxTriplet tp + , interiorLength = PA.fromList 0 maxLength il + , interiorAsym = PA.fromList 0 maxLength ia + , interiorClose = PA.fromList minExtPairNN maxExtPairNN ip + , bulgeLength = PA.fromList 0 maxLength bl + , bulgeTriplet = PA.fromList minTriplet maxTriplet bt + , bulgeClose = PA.fromList minExtPair maxExtPair bu + , mbClose = PA.fromList minExtPairNN maxExtPairNN mbc + , multiBranched = head mbranched + , multiHelix = head mhelix + , multiUnpaired = head munpaired + , pairDistance = PA.fromList 0 maxDistance dst + , interMolInit = head intermol + } where + rsExtPair = rangeSize (minExtPair,maxExtPair) + rs2ExtPairs = rangeSize (min2ExtPairs,max2ExtPairs) + rsTriplet = rangeSize (minTriplet,maxTriplet) + rsExtPairNN = rangeSize (minExtPairNN,maxExtPairNN) + [hpl,hpc,sp,tp,il,ia,ip,bl,bt,bu,mbc,mbranched,mhelix,munpaired,dst,intermol] = splitXs + [ maxLength+1 -- hairpin length + , rsExtPairNN -- hairpin close + , rs2ExtPairs -- stem pair + , rsTriplet -- triplet pair + , maxLength+1 -- interior loop length + , maxLength+1 -- interior loop asymmetry + , rsExtPairNN -- interior pair + , maxLength+1 -- bulge length + , rsTriplet -- bulge triplet + , rsExtPair -- normal bulge with non-overlapping nucs + , rsExtPairNN -- multibranch pair + , 1 -- multibranched score + , 1 -- helix in multibranch score + , 1 -- unpaired nucleotide score in multibranch + , maxDistance+1 -- pair long distance + , 1 + ] + xs + +-- | split up a list accordings to given lengths + +splitXs :: [Int] -> [Double] -> [[Double]] +splitXs [k] xs + | length xs == k = [xs] + | otherwise = error "splitXs encountered wrong key length on last element" +splitXs (k:ks) xs = let (here,rest) = splitAt k xs in here : splitXs ks rest diff --git a/BioInf/PassiveAggressive.hs b/BioInf/PassiveAggressive.hs new file mode 100644 --- /dev/null +++ b/BioInf/PassiveAggressive.hs @@ -0,0 +1,110 @@ +{-# LANGUAGE RecordWildCards #-} + +-- | Passive-aggressive optimization. Mainly based on: +-- +-- Zakov, Shay and Goldberg, Yoav and Elhaded, Michael and Ziv-Ukelson, Michal +-- "Rich Parameterization Improves RNA Structure Prediction" +-- RECOMB 2011 +-- +-- and +-- +-- Crammer, Koby and (et al) +-- "Online Passive-Aggressive Algorithms" +-- Journal of Machine Learning Research (2006) +-- +-- TODO as always: move out of here and put in its own library + +module BioInf.PassiveAggressive where + +import qualified Data.Vector.Unboxed as VU +import Data.List as L +import Data.Set as S +import Control.Arrow +import Data.Map as M + +import Biobase.TrainingData +import BioInf.Keys + +import qualified BioInf.Params as P +import qualified BioInf.Params.Import as P +import qualified BioInf.Params.Export as P + +import Statistics.ConfusionMatrix +import Statistics.PerformanceMetrics + +import Data.PrimitiveArray as PA +import Data.PrimitiveArray.Ix + + + +-- | Default implementation of P/A. + +defaultPA :: Double -> P.Params -> TrainingData -> (P.Params,Double,Double,[(Int,Double)]) +defaultPA aggressiveness params td@TrainingData{..} +-- | kScore+0.02 < pScore = error $ show (pScore,kScore,pOnly,kOnly,tau,changes) +-- | pScore > kScore = error "foo" + | L.null $ pOnly++kOnly = (params,0,1,[]) + | sty >= 0.999 = (params,0,1,[]) +-- | otherwise = error $ show (pOnly,kOnly,kScore,pScore,tau,changes) + | otherwise = ( heck + , tau + , sty + , changes + ) + where + new1 = P.fromList . VU.toList $ VU.accum (\v pm -> v+pm) cur changes + new2 = P.fromList . VU.toList $ VU.accum (\v pm -> v+pm) (VU.fromList $ P.toList new1) [] + heck + | P.toList new1 == P.toList new2 = new1 + | otherwise = error "fuck" -- ignore this line ;-) (impressive, that you actually read this code!) + pFeatures = featureVector primary predicted + kFeatures = featureVector primary secondary + pOnly = pFeatures L.\\ kFeatures + kOnly = kFeatures L.\\ pFeatures + numChanges = genericLength $ pOnly ++ kOnly + cur = VU.fromList . P.toList $ params + pScore = sum . L.map (cur VU.!) $ pFeatures + kScore = sum . L.map (cur VU.!) $ kFeatures + pScore2 = sum . L.map (cur VU.!) $ pFeatures + kScore2 = sum . L.map (cur VU.!) $ kFeatures + tau + | abs ((kScore2 - pScore2) - (kScore-pScore)) > 0.1 + = error $ "abs: \n" ++ z + | val < 0 = error $ "val<0 \n" ++ z + | sty >= 0.999 = 0 + | otherwise = val -- 100 * val + where + val = min aggressiveness $ (kScore - pScore + sqrt (1-sty)) / (numChanges ^ 2) + z = show ( kScore,pScore,kScore - pScore + , kScore2,pScore2, kScore2 - pScore2 + ) ++ "\n" ++ primary ++ "\n" ++ (concat $ intersperse "\n" comments) ++ "\n" ++ + ( L.concatMap (\x -> show x ++ "\n") + $ L.map (fun &&& (cur VU.!)) kOnly ) ++ " <<<\n" ++ + ( L.concatMap (\x -> show x ++ "\n") + $ L.map (fun &&& (cur VU.!)) pOnly ) ++ " ALL\n" ++ + ( L.concatMap (\x -> show x ++ "\n") + $ L.map (fun &&& (cur VU.!)) pFeatures) + fun i = let lol = vks M.! i in (lol, fun2 lol) + fun2 hc@(HairpinClose k) = P.hairpinClose params PA.! k + fun2 hl@(HairpinLength l) = P.hairpinLength params PA.! l + fun2 _ = (-1) + sty = case fmeasure (mkConfusionMatrix td) of -- currently optimizing using F_1 + Left _ -> 1 + Right v -> v + changes = zip kOnly (repeat $ negate tau) ++ zip pOnly (repeat tau) + +-- | Pull in the statistical interface. From the confusion matrix, we +-- automagically get everything we need. +-- +-- NOTE Unfortunately, StatisticalMethods has heavy dependencies. + +instance MkConfusionMatrix TrainingData where + mkConfusionMatrix TrainingData{..} = ConfusionMatrix + { fn = Right . fromIntegral . S.size $ k `S.difference` p + , fp = Right . fromIntegral . S.size $ p `S.difference` k + , tn = Right . fromIntegral $ allPs - S.size (k `S.union` p) + , tp = Right . fromIntegral . S.size $ k `S.intersection` p + } where + k = S.fromList secondary + p = S.fromList predicted + allPs = ((length primary) * (length primary -1)) `div` 2 diff --git a/BioInf/RNAwolf.hs b/BioInf/RNAwolf.hs new file mode 100644 --- /dev/null +++ b/BioInf/RNAwolf.hs @@ -0,0 +1,265 @@ +{-# LANGUAGE BangPatterns #-} + +-- | The RNAwolf folding algorithm, version 1.9. We now have full stacking and +-- rich parameters everywhere. In general, most parameters closely follow what +-- we have for ViennaRNA 1.8 but with extended RNA secondary structures, +-- instead of canonicals only. Further refinements of the parameter system will +-- follow. +-- +-- TODO right now, 1-diagrams only, 2-diagrams come back in a few days. I want +-- to be sure that the full stacking approach does not introduce subtle bugs. +-- +-- TODO recast all fZZZ functions for folding to actually fuse on minimum/fZZZ. +-- +-- TODO VU.! -> VU.unsafeIndex +-- +-- TODO possibly very big TODO: is this being optimized? : fold $ g z where g z +-- = if z==True then [1..10] else []. If this is not optimized, we should +-- change all functions below in a way that allows optimization. (I dont think +-- fusion can fire on these objects...) +-- +-- TODO rewrite minimumVU to accept "Either" ctors and specialize on them. +-- "Left" to be used for strange errors, "Right" for correct streams + + + +module BioInf.RNAwolf + ( rnaWolf + , rnaWolfBacktrack + ) where + +import Control.Monad +import Control.Monad.ST +import qualified Data.Vector.Unboxed as VU +import Control.Arrow + +import Data.PrimitiveArray +import Data.PrimitiveArray.Ix +import Biobase.Primary +import Biobase.Secondary + +import BioInf.Params +import BioInf.RNAwolf.Types +import qualified BioInf.RNAwolf.Bulge as Bul +import qualified BioInf.RNAwolf.Extern as Ext +import qualified BioInf.RNAwolf.Hairpin as Hp +import qualified BioInf.RNAwolf.Interior as Int +import qualified BioInf.RNAwolf.Multibranched as Mul +import qualified BioInf.RNAwolf.Stem as Stem +import qualified BioInf.RNAwolf.TripletBulge as TrB +import qualified BioInf.RNAwolf.TripletStem as TrS + +import Debug.Trace + + + +-- * Folding + +-- | Wrapper around the state monad. + +rnaWolf :: Params -> Primary -> Tables +rnaWolf ps inp = {-# SCC "rnaWolf" #-} runST $ foldST ps inp + +-- | Folding magic. In principle, this is not more complicated than +-- Nussinov-style folding. + +foldST :: Params -> Primary -> ST s Tables +foldST ps inp = do + let n = VU.length inp -1 + let imi = map fst . filter ((==nIMI).snd) $ zip [0..] (VU.toList inp) + (eStemM,eStem) <- second EStem `fmap` mkExtTable n + (nStemM,nStem) <- second NStem `fmap` mkTable n + (nInteM,nInte) <- second NInte `fmap` mkTable n -- interior loop helper table + (nMultM,nMult) <- second NMult `fmap` mkTable n -- multibranched loop helper table + (nBulgM,nBulg) <- second NBulg `fmap` mkTable n -- bulge loop helper table + (nMbrM ,nMbr ) <- second NMbr `fmap` mkTable n + (nMbr1M,nMbr1) <- second NMbr1 `fmap` mkTable n + (nExtnM,nExtn) <- second NExtn `fmap` mkTableWith 0 n + (nBulgLoopM,nBulgLoop) <- second NBulgLoop `fmap` mkTable n + (nInteLoopM,nInteLoop) <- second NInteLoop `fmap` mkTable n -- interior loop helper table + (nMultLoopM,nMultLoop) <- second NMultLoop `fmap` mkTable n -- multibranched loop helper table + -- This version of the (i,j) pair generation walks along the diagonals. It is + -- required to calculate this way, as otherwise the shared nucleotide + -- variants will fail. + forM_ (mkIJ n) $ \(i,j) -> do + forM_ citr $ \ct -> forM_ wsh $ \eI -> forM_ wsh $ \eJ -> do + -- weak table (everything is weak) + let vHairpin = minimumVU $ Hp.fHairpin imi ps inp i j ct eI eJ + let vStem = minimumVU $ Stem.fStem ps inp eStem i j ct eI eJ + let vInterior = minimumVU $ Int.fInteriorOuter ps inp nInteLoop i j ct eI eJ + let vMlClose = minimumVU $ Mul.fMlClose ps inp nMultLoop i j ct eI eJ + let vBulge = minimumVU $ Bul.fBulgeOuter ps inp nBulgLoop i j ct eI eJ + writeM eStemM ((i,j),(ct,eI,eJ)) $ minimum [vHairpin,vStem,vInterior,vMlClose,vBulge] -- FIXME vTStem + -- fill stem table that ignores extended annotations + writeM nStemM (i,j) . minimumVU $ Stem.fNstem ps inp eStem i j + -- fill the inner interior table + writeM nInteM (i,j) . minimumVU $ Int.fInteriorInner ps inp eStem i j + -- fill the interior LOOP table (includes everything except the closing pair) + writeM nInteLoopM (i,j) . minimumVU $ Int.fInteriorLoop ps inp nInte i j + -- fill multibranch helper table + writeM nMultM (i,j) . minimumVU $ Mul.fMlHelix ps inp eStem i j + -- multibranched close helper table (should improve speed for MLs by 2x3x3) + writeM nMultLoopM (i,j) . minimumVU $ Mul.fMlLoop ps inp nMbr nMbr1 i j + -- fill bulge close helper table + writeM nBulgM (i,j) . minimumVU $ Bul.fBulgeInner ps inp eStem i j + -- fill bulge LOOP table + writeM nBulgLoopM (i,j) . minimumVU $ Bul.fBulgeLoop ps inp nBulg i j + -- one or more multibranched stems + let vUnpaired = minimumVU $ Mul.fUnpairedRight ps inp nMbr i j + let vStem = minimumVU $ Mul.fMlStem ps inp nMult i j + let vStems = minimumVU $ Mul.fMlStems ps inp nMbr nMult i j + writeM nMbrM (i,j) $ minimum [vUnpaired, vStem, vStems] + -- exactly one multibranched stem + let vUnpaired = minimumVU $ Mul.fUnpairedRight1 ps inp nMbr1 i j + let vStem = minimumVU $ Mul.fMl1Stem ps inp nMult i j + writeM nMbr1M (i,j) $ minimum [vUnpaired,vStem] + let j=n + forM_ [n-2,n-3..0] $ \i -> do + let unp = minimumVU $ Ext.fLeftUnpaired ps inp nExtn i j + let es = minimumVU $ Ext.fStem ps inp nStem i j + let esl = minimumVU $ Ext.fStems ps inp nStem nExtn i j + let one = minimumVU $ Ext.fOne ps inp i j + writeM nExtnM (i,j) $ minimum [unp,esl,es,one] + return ( eStem + , nStem + , nInte + , nInteLoop + , nBulg + , nBulgLoop + , nMult + , nMbr + , nMbr1 + , nMultLoop + , nExtn) + + + +-- * Backtracking + +-- | Given parameters, input, score band, and filled tables we can backtrack. +-- +-- NOTE the order in which backtracking for individual functions is performed, +-- is important. In case of ties in energy, the first result is taken. This +-- should be considered! +-- +-- [1] We consider unpaired stretches always first. This is kind of arbitrary. +-- +-- [2] extended stems always come last. This is because they can potentially +-- introduce many co-optimal structures before they are all discarded. +-- +-- TODO all the crap in comments are bug-fix backtracking options. + +rnaWolfBacktrack :: Params -> Primary -> Double -> Tables -> [([ExtPairIdx],Double)] +rnaWolfBacktrack ps inp delta ( estem@(EStem eStem) + , nstem@(NStem nStem) + , ninte@(NInte nInte) + , ninteloop@(NInteLoop nInteLoop) + , nbulg@(NBulg nBulg) + , nbulgloop@(NBulgLoop nBulgLoop) + , nmult@(NMult nMult) + , nmbr@(NMbr nMbr) + , nmbr1@(NMbr1 nMbr1) + , nmultloop@(NMultLoop nMultLoop) + , nextn@(NExtn nExtn) + ) + | otherwise = let finalScore = nExtn ! (0,n) + in filter ((<=0).snd) . map (second (\z -> finalScore + delta -z)) $ btE 0 n delta + where + btE i j d = -- trace (show ("btE",i,j,d)) $ + Ext.btOne ps inp nextn i j d ++ -- [1] + Ext.btLeftUnpaired ps inp nextn btE i j d ++ + Ext.btStem ps inp nextn nstem btNS i j d ++ + Ext.btStems ps inp nstem nextn btNS btE i j d + btNS i j d = + Stem.btNstem ps inp nstem estem btES i j d + btES :: Int -> Int -> CTisomerism -> Edge -> Edge -> Double -> [([ExtPairIdx],Double)] + btES i j ct eI eJ d = -- trace (show ("btES",i,j,ct,eI,eJ,d)) $ + Hp.btHairpin ps inp estem i j ct eI eJ d ++ + Int.btInteriorOuter ps inp estem ninteloop btILoop i j ct eI eJ d ++ + Bul.btBulgeOuter ps inp estem nbulgloop btBULoop i j ct eI eJ d ++ + Mul.btMlClose ps inp estem nmultloop btMultLoop i j ct eI eJ d ++ + Stem.btStem ps inp estem btES i j ct eI eJ d -- [2] + btILoop i j d = -- trace (show ("btILoop",i,j,d)) $ + Int.btInteriorLoop ps inp ninteloop ninte btIL i j d + btIL i j d = -- trace (show ("btIL",i,j,d)) $ + Int.btInteriorInner ps inp ninte estem btES i j d + btBULoop i j d = -- trace (show ("btBULoop",i,j,d)) $ + Bul.btBulgeLoop ps inp nbulgloop nbulg btBU i j d + btBU i j d = -- trace (show ("btBU",i,j,d)) $ + Bul.btBulgeInner ps inp nbulg estem btES i j d + btMH i j d = -- trace (show ("btMH",i,j,d)) $ + Mul.btMlHelix ps inp nmult estem btES i j d + btMultLoop i j d = + Mul.btMlLoop ps inp nmultloop nmbr nmbr1 btM btM1 i j d + btM i j d = {- trace (show ("btM",i,j,d)) $ -} + Mul.btUnpairedRight ps inp nmbr btM i j d ++ + Mul.btMlStem ps inp nmbr nmult btMH i j d ++ + Mul.btMlStems ps inp nmbr nmult btM btMH i j d + btM1 i j d = let ehere = nMbr1!(i,j) in + Mul.btUnpairedRight1 ps inp nmbr1 btM1 i j d ++ + Mul.btMl1Stem ps inp nmbr1 nmult btMH i j d + + newD d here next = d - (next - here) + testD d = d>=0 + n = VU.length inp -1 + epsilon = 0.001 + imi = map fst . filter ((==nIMI).snd) $ zip [0..] (VU.toList inp) + + + +-- * Helper functions + +-- | Given an unboxed vector with (index,value) elements, return the minimum +-- over the values. +-- +-- TODO with vector-0.7.2 / vector-0.8, rewrite using "snd . unzip" (or not, +-- see next todo) +-- +-- TODO http://trac.haskell.org/vector/ticket/51 + +minimumVU xs = VU.foldl' (\(!acc) (!k,!v) -> min acc v) 999999 xs +{-# INLINE minimumVU #-} + +-- | Create 2d-tables, initialized with "infinity" +-- +-- TODO use (infinity :: Energy) + +mkTable n = mkTableWith 9999999 n + +-- | Create 2d-tables, initialized with 'z' + +mkTableWith z n = do + tM <- fromAssocsM (0,0) (n,n) z [] + t <- unsafeFreezeM tM + return (tM,t) + +-- | 2d-tables with extended information. + +mkExtTable n = mkExtTableWith 9999999 n + +-- | 2d-tables with extended information. + +mkExtTableWith z n = do + tM <- fromAssocsM ((0,0),(cis,wc,wc)) ((n,n),(trans,hoogsteen,hoogsteen)) z [] + t <- unsafeFreezeM tM + return (tM,t) + +-- | Produces indices in correct diagonal order. +-- +-- TODO this is a stupid way to create the indices... + +mkIJ n = [ (i,j) | d <- [0..n], j<-[n,n-1..0], let i=j-d, j>=0, i>=0 ] + + + +-- * Types + + + + +-- * debugging + +trc k x = trace (show (k,x)) x +trc' k x = trace (show k) x +trci' c k x = if c then trace (show k) x else x + diff --git a/LICENSE b/LICENSE new file mode 100644 --- /dev/null +++ b/LICENSE @@ -0,0 +1,675 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. + diff --git a/RNAwolf.cabal b/RNAwolf.cabal new file mode 100644 --- /dev/null +++ b/RNAwolf.cabal @@ -0,0 +1,103 @@ +name: RNAwolf +version: 0.3.0.0 +author: Christian Hoener zu Siederdissen, Stephan H Bernhart, Peter F Stadler, Ivo L Hofacker +copyright: Christian Hoener zu Siederdissen, 2010-2011 +homepage: http://www.tbi.univie.ac.at/software/rnawolf/ +maintainer: choener@tbi.univie.ac.at +category: Bioinformatics +license: GPL-3 +license-file: LICENSE +build-type: Simple +stability: experimental +cabal-version: >= 1.6.0 +synopsis: + RNA folding with non-canonical basepairs and base-triplets. +description: + The algorithm implemented here-in provides extended RNA + secondary structure prediction. Each predicted nucleotide + pairing is extended with an annotation describing which of + three nucleotide edges is engaged in the pairing. In addition, + each nucleotide may be engaged in more than one pairing. + . + . + The algorithm is described in + . + Hoener zu Siederdissen C, Bernhart SH, Stadler PF, Hofacker IL, + . + "A Folding Algorithm for Extended RNA Secondary Structures", + . + Bioinformatics (2011) 27 (13), i129-136 + . + + . + . + Please note that "experimental" does mean experimental. We are + mostly concerned with determining a good set of (heuristic) + rules for run-time reduction currently. This version does + include stacking and is able to fold sequences of a few hundred + nucleotides in seconds. + . + Triplet calculations will come back with the next version (in a + few days). The recursions require a number of changes to keep + the runtimes down (as has been done for the extended loops + without triplets). + . + /We have recently split the Biohaskell libraries into smaller + individual libraries. In addition, stacking, intermediate + arrays, fusion and newtype-wrapping did require a number of + changes. Please send a mail, if you encounter strange behaviour + or bugs./ + +Flag llvm + description: build using llvm backend + default: False + +library + build-depends: + base >= 4 && < 5, + bytestring, + containers, + deepseq, + directory, + parallel, + random, + vector, + PrimitiveArray, + BiobaseXNA, + BiobaseTrainingData == 0.1.*, + StatisticalMethods + exposed-modules: + BioInf.Keys + BioInf.Params + BioInf.Params.Export + BioInf.Params.Import + BioInf.PassiveAggressive + BioInf.RNAwolf + ghc-options: + -O2 + if flag(llvm) + ghc-options: + -fllvm + +executable RNAwolfTrain + build-depends: + cmdargs == 0.7.* + main-is: + RNAwolfTrain.hs + ghc-options: + -O2 -rtsopts + if flag(llvm) + ghc-options: + -fllvm + +executable RNAwolf + build-depends: + cmdargs == 0.7.* + main-is: + RNAwolf.hs + ghc-options: + -O2 -rtsopts + if flag(llvm) + ghc-options: + -fllvm + diff --git a/RNAwolf.hs b/RNAwolf.hs new file mode 100644 --- /dev/null +++ b/RNAwolf.hs @@ -0,0 +1,86 @@ +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE DeriveDataTypeable #-} + +-- | RNAwolf extended secondary structure folding program. This is an extended +-- version of the algorithm first described in: + +-- Hoener zu Siederdissen, Christian and Bernhart, Stephan H. and Stadler, +-- Peter F. and Hofacker, Ivo L. +-- "A Folding Algorithm for Extended RNA Secondary Structures" +-- Bioinformatics, 2011 + +-- http://www.tbi.univie.ac.at/software/rnawolf/ + +module Main where + +import System.Console.CmdArgs +import Control.Monad +import Text.Printf + +import Biobase.Primary + +import BioInf.RNAwolf +import BioInf.RNAwolf.Types +import BioInf.Params as P + +import Data.PrimitiveArray + + + +main :: IO () +main = do + o@Options{..} <- cmdArgs options + when (null inDB) $ error "you need to give a database" + db <- fmap read $ readFile inDB + xs <- fmap lines $ getContents + mapM_ (foldLine o db) xs + return () + +foldLine :: Options -> Params -> String -> IO () +foldLine Options{..} p inp = do + let pri = mkPrimary inp + let ts = rnaWolf p pri + let bt = take coopt $ rnaWolfBacktrack p pri subopt ts + printX inp ts + putStrLn inp + forM_ bt $ \(pairs,score) -> do + printf "%s %7.4f\n" (simpleViewer inp pairs) score + forM_ pairs $ \((i,j),ext) -> do + printf " %4d %4d %s\n" i j (showX ext) + return () + +printX inp (_,_,_,_,_,_,_,_,_,_,NExtn n) = print $ n!(0,length inp -1) + +showX (ct,ei,ej) = show ct ++ show ei ++ show ej + +-- * options + +data Options = Options + { inDB :: FilePath + , subopt :: Double + , coopt :: Int + } deriving (Show,Data,Typeable) + +options = Options + { inDB = "" &= help "specify parameter database" + , subopt = 0.00001 &= help "calculate suboptimal in this range (returns all suboptimal results)" + , coopt = 1 &= help "how many co-optimal structures to return" + } + +-- | simple viewer... + +simpleViewer s xs = foldl f (replicate (length s) '.') xs where + f str ((i,j),_) = upd ')' j $ upd '(' i str + upd c k str + | l=='(' + && c=='(' + = pre ++ "<" ++ post + | l==')' + && c==')' + = pre ++ ">" ++ post + | l/='.' = pre ++ "X" ++ post + | otherwise = pre ++ [c] ++ post + where + pre = take k str + l = head $ drop k str + post = drop (k+1) str diff --git a/RNAwolfTrain.hs b/RNAwolfTrain.hs new file mode 100644 --- /dev/null +++ b/RNAwolfTrain.hs @@ -0,0 +1,231 @@ +{-# LANGUAGE BangPatterns #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE DeriveDataTypeable #-} + +-- | This program trains a parameter database for RNAwolf. The user has to take +-- care to only give appropriate training data to the optimizer. The most +-- important rule is to not give any pseudoknotted data. The small helper +-- program "MkTrainingData" should be able to take care of this. +-- "MkTrainingData" is part of BiobaseTrainingData. +-- +-- We currently train using an optimization scheme described in: +-- +-- Zakov, Shay and Goldberg, Yoav and Elhaded, Michael and Ziv-Ukelson, Michal +-- "Rich Parameterization Improves RNA Structure Prediction" +-- RECOMB 2011 +-- +-- NOTE It is likely that this we extended with other methods in the (near) +-- future, again. Especially the convex-optimization-based (even though the +-- Zakov et al. scheme is derived from cvx-methods) system seems promising. +-- Right now, this version simply is faster... +-- +-- TODO update the DB within IO to save creation / destruction of Params in +-- each iteration +-- +-- TODO re-allow co-folding + +module Main where + +import Control.Monad +import System.Console.CmdArgs +import Text.Printf +import Data.List +import Data.Function (on) +import System.Random +import Control.Applicative +import Data.Ord +import Control.Arrow +import qualified Data.Vector.Unboxed as VU +import qualified Data.Map as M + +import Biobase.Primary +import Biobase.TrainingData +import Biobase.TrainingData.Import +import Statistics.ConfusionMatrix +import Statistics.PerformanceMetrics +import Biobase.Secondary.Diagrams + +import BioInf.Params as P +import BioInf.Params.Export as P +import BioInf.Params.Import as P +import BioInf.RNAwolf +import BioInf.PassiveAggressive +import BioInf.Keys + + + +-- | Entry function + +main :: IO () +main = do + o@Options{..} <- cmdArgs options + when (null outDB) $ + error "please set --outdb" + when (null trainingData) $ + error "please give at least one training data file with --trainingdata" + -- read training data + xs <- id + . fmap (filter (\TrainingData{..} -> + True +-- length primary > 20 && + && all (/='&') primary -- no co-folding right now +-- length secondary > 5 -- at least 5 basepairs + ) + ) + . fmap (filter (lengthFlt maxLength)) + . fmap concat + $ mapM fromFile trainingData + -- read database or use zero-based parameters + dbIn <- maybe (return . P.fromList . map (+0.01) . P.toList $ P.zeroParams) (fmap read . readFile) inDB + -- dbOut <- foldM (foldTD $ length xs) dbIn $ zip xs [1..] + (dbOut,_) <- foldM (doIteration o xs) (dbIn,[]) [1..numIterations] + writeFile outDB $ show dbOut + +-- | length filter for training data + +lengthFlt l TrainingData{..} = maybe True (length primary <) l + +-- | iterations to go + +doIteration :: Options -> [TrainingData] -> (P.Params,[Double]) -> Int -> IO (P.Params,[Double]) +doIteration o@Options{..} xs' (!p,rhos) !k = do + xs <- return xs' -- shuffle xs' + when (Iteration `elem` verbose) $ do + putStrLn "\n======================================" + printf "# INFO iteration: %4d / %4d starting\n" + k + numIterations + putStrLn "======================================\n" + (newp,totalchange,rhosum,cooptimality) <- foldM (foldTD o $ length xs) (p,0,0,0) $ zip xs [1..] + let drctch = sum $ zipWith (\x y -> abs $ x-y) (P.toList p) (P.toList newp) + let rho = rhosum / genericLength xs + when (Iteration `elem` verbose) $ do + putStrLn "\n======================================" + printf "# INFO iteration: %4d / %4d ended\n" + k + numIterations + printf "# INFO sum tau: %7.2f, total change: %7.2f, avg.rho: %4.2f, avg.coopt: %5d\n" + totalchange + drctch + rho + (cooptimality `div` length xs) + putStr "# INFO history:" + zipWithM_ (printf " %4d %4.2f") [1::Int ..] $ rhos++[rho] + putStrLn "" + print $ sum $ map abs $ P.toList newp + print $ minimum $ P.toList newp + print $ maximum $ P.toList newp + putStrLn "======================================\n" + writeFile (printf "%04d.db" k) . show $ newp + return (newp,rhos++[rho]) + +-- | Fold one 'TrainingData', print some info and stuff + +foldTD :: Options -> Int -> (P.Params,Double,Double,Int) -> (TrainingData,Int) -> IO (P.Params,Double,Double,Int) +foldTD o@Options{..} total (!p,accChange,rhosum,cooptimality) (td@TrainingData{},k) = do + print $ length $ primary td + let pri = mkPrimary $ primary td + let tables = rnaWolf p pri + let bs' = let f x = td{predicted = x} in map (first f) . take (maybe 1 id maxLoss) $ rnaWolfBacktrack p pri 0.00001 tables + let bs = pure $ minimumBy (comparing (sensitivity . mkConfusionMatrix . fst)) bs' + case bs of + [(x,ddd)] -> do + let fV = featureVector (primary x) (predicted x) + let pVU = VU.fromList . P.toList $ p + let sss = map (pVU VU.!) fV + when (abs (ddd - sum sss) > 0.0001) $ do + printf "SCORE DIFFERENCE, backtracking score: %f, sum features: %f\n" ddd (sum sss) -- , " ", map (vks M.!) fV, " ", sss) + mapM_ print $ zip (map (vks M.!) fV) sss + print "You have found a bug, now write choener to have him fix it!" + let (newp,tau,rho,votes) = defaultPA aggressiveness p + $ x { comments = [ show ddd + , simpleViewer (primary x) $ secondary x + , simpleViewer (primary x) $ predicted x + , show $ predicted x + ] + } + when (Single `elem` verbose) $ do + printf "# INFO currently at: %4d / %4d (s-tau: %7.4f, rho: %5.2f, changes: %4d)\n" + k + total + (tau * genericLength votes) + rho + (length votes) + when (Detailed `elem` verbose) $ do + putStrLn $ take (length $ primary x) . concatMap show . concat . repeat $ [0..9] + putStrLn $ primary x + putStrLn $ simpleViewer (primary x) $ secondary x + putStrLn $ simpleViewer (primary x) $ predicted x + when (AllPairs `elem` verbose) $ do + mapM_ print $ predicted x + when (errorOnError && abs (ddd - sum sss) > 0.0001) $ error "error-ing out" + return (newp,accChange + tau * genericLength votes, rhosum+rho, cooptimality + length bs') + _ -> error $ "no prediction for: " ++ show td + +-- | simple viewer... + +simpleViewer s xs = foldl f (replicate (length s) '.') xs where + f str ((i,j),_) = upd ')' j $ upd '(' i str + upd c k str + | l=='(' + && c=='(' + = pre ++ "<" ++ post + | l==')' + && c==')' + = pre ++ ">" ++ post + | l/='.' = pre ++ "X" ++ post + | otherwise = pre ++ [c] ++ post + where + pre = take k str + l = head $ drop k str + post = drop (k+1) str + + + +-- ** program options + +data Options = Options + { inDB :: Maybe FilePath + , outDB :: FilePath + , trainingData :: [FilePath] + , maxLength :: Maybe Int + , numIterations :: Int + , verbose :: [Verbose] + , maxLoss :: Maybe Int + , aggressiveness :: Double + , errorOnError :: Bool + } deriving (Show,Data,Typeable) + +data Verbose + = Iteration + | Single + | Detailed + | AllPairs + deriving (Show,Data,Typeable,Eq) + +options = Options + { inDB = Nothing &= help "database from which to continue optimizing; if none is given, start from scratch" + , outDB = "" &= help "new database to write out" + , trainingData = [] &= help "training data elements to read" + , maxLength = Nothing &= help "[dev] only train using elements of length or less" + , numIterations = 50 &= help "how many optimizer iterations" + , verbose = [Iteration] &= help "select verbosity options: single, iteration, detailed (all switch on different verbosity options)" + , maxLoss = Nothing &= help "use maxLoss optimization instead of prediction-based, requires maximal number of instances to search for maxLoss (default: not used)" + , aggressiveness = 1 &= help "maximal tau for each round" + , errorOnError = False &= help "error out if an error is detected (default: false)" + } + + + +-- ** helper functions + +-- | simple shuffling of a list + +shuffle :: [a] -> IO [a] +shuffle [] = return [] +shuffle xs = do + r <- getStdRandom (randomR (0,length xs -1)) + let (hs,ts) = splitAt r xs + let y = head ts + ys <- shuffle $ hs ++ tail ts + return $ y : ys diff --git a/Setup.hs b/Setup.hs new file mode 100644 --- /dev/null +++ b/Setup.hs @@ -0,0 +1,2 @@ +import Distribution.Simple +main = defaultMain