Implement Fisher Yates algorithm

Author: kayvank

src/DataFrame/Operations/Permutation.hs

@@ -9,16 +9,17 @@ import qualified Data.List as L
 import qualified Data.Text as T
 import qualified Data.Vector as V
 import qualified Data.Vector.Unboxed as VU
+import qualified Data.Vector.Unboxed.Mutable as VUM
 
 import Control.Exception (throw)
+import Control.Monad.ST (runST)
 import DataFrame.Errors (DataFrameException (..))
-import DataFrame.Internal.Column
+import DataFrame.Internal.Column (Columnable, atIndicesStable)
 import DataFrame.Internal.DataFrame (DataFrame (..))
-import DataFrame.Internal.Expression
-import DataFrame.Internal.Row
-import DataFrame.Operations.Core
-import System.Random
-import System.Random.Shuffle (shuffle')
+import DataFrame.Internal.Expression (Expr (Col))
+import DataFrame.Internal.Row (sortedIndexes', toRowVector)
+import DataFrame.Operations.Core (columnNames, dimensions)
+import System.Random (Random (randomR), RandomGen)
 
 -- | Sort order taken as a parameter by the 'sortBy' function.
 data SortOrder where
@@ -76,4 +77,17 @@ shuffle pureGen df =
         df{columns = V.map (atIndicesStable indexes) (columns df)}
 
 shuffledIndices :: (RandomGen g) => g -> Int -> VU.Vector Int
-shuffledIndices pureGen k = VU.fromList (shuffle' [0 .. (k - 1)] k pureGen)
+shuffledIndices pureGen k = shuffleVec pureGen (VU.fromList [0 .. (k - 1)])
+  where
+    shuffleVec :: (RandomGen g) => g -> VU.Vector Int -> VU.Vector Int
+    shuffleVec g v = runST $ do
+        vm <- VU.thaw v
+        let (n, nGen) = randomR (0, (k - 1)) g
+        go vm n nGen
+        VU.unsafeFreeze vm
+
+    go v (-1) _ = pure ()
+    go v 0 _ = pure ()
+    go v maxInd gen =
+        let (n, nextGen) = randomR (0, maxInd) gen
+         in VUM.swap v 0 n *> go (VUM.tail v) (maxInd - 1) nextGen