diff --git a/app/Main.hs b/app/Main.hs
--- a/app/Main.hs
+++ b/app/Main.hs
@@ -16,8 +16,8 @@
 import qualified Data.IntMap as IM (IntMap, fromList, insert, lookup, map, mapWithKey, traverseWithKey, foldlWithKey, foldrWithKey)
 -- exceptions
 import Control.Monad.Catch (MonadThrow(..))
--- mnist-idx-conduit
-import Data.IDX.Conduit (sourceIdxSparse, sBufSize, sNzComponents)
+-- -- mnist-idx-conduit
+-- import Data.IDX.Conduit (sourceIdxSparse, sBufSize, sNzComponents)
 -- splitmix-distributions
 import System.Random.SplitMix.Distributions (Gen, GenT, sample, sampleT, bernoulli, normal)
 -- transformers
@@ -27,7 +27,7 @@
 import qualified Data.Vector as V (Vector, toList, fromList, replicate, zip)
 
 import Control.Monad (replicateM)
-import Data.RPTree (knn, candidates, Embed(..), Inner(..), RPTree, RPForest, leaves, SVector, fromListSv, DVector, fromListDv, dense, writeCsv, forest, dataSource, sparse, normal2, normalSparse2, datS, datD)
+import Data.RPTree (knn, candidates, Embed(..), Inner(..), RPTree, RPForest, SVector, fromListSv, DVector, fromListDv, dense, writeCsv, forest, dataSource, sparse, normal2, normalSparse2, datS, datD)
 -- import Data.RPTree.Internal.Testing (datS, datD)
 
 main :: IO ()
diff --git a/bench/time/Main.hs b/bench/time/Main.hs
--- a/bench/time/Main.hs
+++ b/bench/time/Main.hs
@@ -19,8 +19,8 @@
 import Control.DeepSeq (NFData(..), force)
 -- exceptions
 import Control.Monad.Catch (MonadThrow(..))
--- mnist-idx-conduit
-import Data.IDX.Conduit (sourceIdxSparse, sBufSize, sNzComponents)
+-- -- mnist-idx-conduit
+-- import Data.IDX.Conduit (sourceIdxSparse, sBufSize, sNzComponents)
 -- splitmix-distributions
 import System.Random.SplitMix.Distributions (GenT, sampleT, sample, samples)
 
@@ -31,8 +31,7 @@
 import qualified Data.Vector as V (Vector, replicateM, fromList)
 import qualified Data.Vector.Unboxed as VU (Unbox, Vector, map)
 
-import Data.RPTree (tree, forest, recallWith, knn, fromVectorSv, fromListSv, RPForest, RPTree, SVector, Inner(..), normalSparse2, liftC, Embed(..))
-import Data.RPTree.Internal.Testing (BenchConfig(..), randSeed, datD, datS)
+import Data.RPTree (forest, recallWith, knn, fromVectorSv, fromListSv, RPForest, RPTree, SVector, Inner(..), normalSparse2, liftC, Embed(..), BenchConfig(..), randSeed, datD, datS)
 
 main :: IO ()
 main = do -- putStrLn "hello!"
@@ -113,16 +112,16 @@
 --       let q = sample 1234 $ normalSparse2 nzData d
 --       pure $! recallWith metricL2 tt k q
 
-mnist :: MonadResource m =>
-         FilePath -- path to uncompressed MNIST IDX data file
-      -> Int -- number of data items
-      -> C.ConduitT a (Embed SVector Double ()) m ()
-mnist fp n = C.takeExactly n src
-  where
-    src = sourceIdxSparse fp .|
-          C.map (\r -> fromVectorSv (sBufSize r) (VU.map f $ sNzComponents r)) .|
-          C.map (\r -> Embed r ())
-    f (i, x) = (i, toUnitRange x)
+-- mnist :: MonadResource m =>
+--          FilePath -- path to uncompressed MNIST IDX data file
+--       -> Int -- number of data items
+--       -> C.ConduitT a (Embed SVector Double ()) m ()
+-- mnist fp n = C.takeExactly n src
+--   where
+--     src = sourceIdxSparse fp .|
+--           C.map (\r -> fromVectorSv (sBufSize r) (VU.map f $ sNzComponents r)) .|
+--           C.map (\r -> Embed r ())
+--     f (i, x) = (i, toUnitRange x)
 
 toUnitRange :: Word8 -> Double
 toUnitRange w8 = fromIntegral w8 / 255
@@ -161,28 +160,6 @@
       x <- sampleT seed $ growForest s cfg src
       pure $ force x
 
-
-
--- treeBench :: (Monad m, Inner SVector v) =>
---              C.ConduitT () (v Double) m ()
---           -> (m (RPTree Double (V.Vector (v Double))) -> IO c)
---           -> Int
---           -> BenchConfig
---           -> IO (c, Double)
-treeBench src go n cfg = benchmark n setup (const $ pure ()) go
-      where
-        setup = do
-          s <- randSeed
-          -- let src' = C.transPipe lift src
-          pure $ growTree s cfg src
-
--- growTree :: (Monad m, Inner SVector v) =>
---             Word64
---          -> BenchConfig
---          -> C.ConduitT () (v Double) m ()
---          -> m (RPTree Double (V.Vector (v Double)))
-growTree seed (BenchConfig _ maxd minl _ chunksize pnz pdim _ _) =
-  tree seed maxd minl chunksize pnz pdim
 
 -- growForest :: (Monad m, Inner SVector v) =>
 --               Word64
diff --git a/rp-tree.cabal b/rp-tree.cabal
--- a/rp-tree.cabal
+++ b/rp-tree.cabal
@@ -1,5 +1,5 @@
 name:                rp-tree
-version:             0.3.2
+version:             0.3.3
 synopsis:            Random projection trees
 description:         Random projection trees for approximate nearest neighbor search in high-dimensional vector spaces
                      .
@@ -77,7 +77,7 @@
                      , conduit
                      , deepseq >= 1.4.4.0
                      , exceptions
-                     , mnist-idx-conduit
+                     -- , mnist-idx-conduit
                      , mtl
                      , rp-tree
                      , splitmix >= 0.1.0.3
@@ -94,7 +94,7 @@
                      , conduit
                      , containers
                      , exceptions
-                     , mnist-idx-conduit
+                     -- , mnist-idx-conduit
                      , rp-tree
                      , splitmix
                      , splitmix-distributions
diff --git a/src/Data/RPTree.hs b/src/Data/RPTree.hs
--- a/src/Data/RPTree.hs
+++ b/src/Data/RPTree.hs
@@ -59,7 +59,7 @@
   -- * Validation
   , recallWith
   -- * Access
-  , levels, points, leaves, candidates
+  , levels, points, candidates
   -- * Types
   , Embed(..)
   -- ** RPTree
@@ -128,7 +128,7 @@
 
 import Data.RPTree.Conduit (tree, forest, dataSource, liftC)
 import Data.RPTree.Gen (sparse, dense, normal2, normalSparse2)
-import Data.RPTree.Internal (RPTree(..), RPForest, RPT(..), Embed(..), levels, points, leaves, RT(..), Inner(..), Scale(..), scaleS, scaleD, (/.), innerDD, innerSD, innerSS, metricSSL2, metricSDL2, SVector(..), fromListSv, fromVectorSv, DVector(..), fromListDv, fromVectorDv, partitionAtMedian, Margin, getMargin, sortByVG, serialiseRPForest, deserialiseRPForest)
+import Data.RPTree.Internal (RPTree(..), RPForest, RPT(..), Embed(..), levels, points, Inner(..), Scale(..), scaleS, scaleD, (/.), innerDD, innerSD, innerSS, metricSSL2, metricSDL2, SVector(..), fromListSv, fromVectorSv, DVector(..), fromListDv, fromVectorDv, partitionAtMedian, Margin, getMargin, sortByVG, serialiseRPForest, deserialiseRPForest)
 import Data.RPTree.Internal.Testing (BenchConfig(..), randSeed, datS, datD)
 import Data.RPTree.Draw (draw, writeCsv)
 
diff --git a/src/Data/RPTree/Internal.hs b/src/Data/RPTree/Internal.hs
--- a/src/Data/RPTree/Internal.hs
+++ b/src/Data/RPTree/Internal.hs
@@ -9,7 +9,7 @@
 {-# language LambdaCase #-}
 {-# language MultiParamTypeClasses #-}
 {-# language GeneralizedNewtypeDeriving #-}
-{-# language TemplateHaskell #-}
+-- {-# language TemplateHaskell #-}
 {-# LANGUAGE BangPatterns        #-}
 {-# options_ghc -Wno-unused-imports #-}
 module Data.RPTree.Internal where
@@ -33,9 +33,9 @@
 import qualified Data.IntMap.Strict as IM (IntMap, fromList)
 -- deepseq
 import Control.DeepSeq (NFData(..))
--- microlens
-import Lens.Micro (Traversal', (.~), (^..), folded)
-import Lens.Micro.TH (makeLensesFor, makeLensesWith, lensRules, generateSignatures)
+-- -- microlens
+-- import Lens.Micro (Traversal', (.~), (^..), folded)
+-- import Lens.Micro.TH (makeLensesFor, makeLensesWith, lensRules, generateSignatures)
 -- mtl
 import Control.Monad.State (MonadState(..), modify)
 -- serialise
@@ -91,8 +91,16 @@
   show (SV n vv) = unwords ["SV", show n, show (VU.toList vv)]
 instance NFData (SVector a)
 
+-- | (Unsafe) Pack a 'SVector' from its vector dimension and components
+--
+-- Note : the relevant invariants are not checked :
+--
+-- * vector components are _assumed_ to be in increasing order
+--
+-- * vector dimension is larger than any component index
 fromListSv :: VU.Unbox a => Int -> [(Int, a)] -> SVector a
 fromListSv n ll = SV n $ VU.fromList ll
+
 -- | (Unsafe) Pack a 'SVector' from its vector dimension and components
 --
 -- Note : the relevant invariants are not checked :
@@ -119,17 +127,7 @@
 toListDv :: (VU.Unbox a) => DVector a -> [a]
 toListDv (DV v) = VU.toList v
 
--- | Internal
---
--- one projection vector per node (like @annoy@)
-data RT v d a =
-  RBin !d !(v d) !(RT v d a) !(RT v d a)
-  | RTip { _rData :: !a } deriving (Eq, Show, Generic, Functor, Foldable, Traversable)
-makeLensesFor [("_rData", "rData")] ''RT
-instance (NFData (v d), NFData d, NFData a) => NFData (RT v d a)
 
-
-
 -- | Internal
 --
 -- one projection vector per tree level (as suggested in https://www.cs.helsinki.fi/u/ttonteri/pub/bigdata2016.pdf )
@@ -142,7 +140,7 @@
   | Tip { _rpData :: !a }
   deriving (Eq, Show, Generic, Functor, Foldable, Traversable)
 instance (Serialise a, Serialise d) => Serialise (RPT d a)
-makeLensesFor [("_rpData", "rpData")] ''RPT
+-- makeLensesFor [("_rpData", "rpData")] ''RPT
 instance (NFData v, NFData a) => NFData (RPT v a)
 
 -- | Random projection trees
@@ -157,7 +155,7 @@
   , _rpTree :: !(RPT d a)
                          } deriving (Eq, Show, Functor, Foldable, Traversable, Generic)
 instance (Serialise d, Serialise a, VU.Unbox d) => Serialise (RPTree d a)
-makeLensesFor [("_rpTree", "rpTree")] ''RPTree
+-- makeLensesFor [("_rpTree", "rpTree")] ''RPTree
 instance (NFData a, NFData d) => NFData (RPTree d a)
 
 -- | A random projection forest is an ordered set of 'RPTree's
@@ -179,12 +177,12 @@
   Left e -> Left (show e)
   Right xs -> Right $ IM.fromList $ zip [0 ..] xs
 
-rpTreeData :: Traversal' (RPTree d a) a
-rpTreeData = rpTree . rpData
+-- rpTreeData :: Traversal' (RPTree d a) a
+-- rpTreeData = rpTree . rpData
 
--- | All data buckets stored at the leaves of the tree
-leaves :: RPTree d a -> [a]
-leaves = (^.. rpTreeData)
+-- -- | All data buckets stored at the leaves of the tree
+-- leaves :: RPTree d a -> [a]
+-- leaves = (^.. rpTreeData)
 
 -- | Number of tree levels
 levels :: RPTree d a -> Int