reordered inputs and improved style

Network.hs

@@ -18,7 +18,7 @@ module Network (
     Layer(..),
     newNetwork,
     output,
-    
+
     -- * Learning functions
     trainShuffled,
     trainNTimes,
@@ -39,19 +39,19 @@ module Network (
     loadNetwork
 ) where
 
-import Data.List.Split (chunksOf)
 import Data.List (foldl')
-import Data.Binary
+import Data.List.Split (chunksOf)
 import Data.Maybe (fromMaybe)
 import Text.Read (readMaybe)
+import Data.Binary
 
 import System.Directory
 import System.Random
 import Control.Monad (zipWithM, forM)
 import Data.Array.IO
 import Debug.Trace (trace)
-import Text.Regex.PCRE
 
+import Text.Regex.PCRE
 import Numeric.LinearAlgebra
 
 -- | The generic feedforward network type, a binary instance is implemented.
@@ -109,7 +109,8 @@ type Sample a = (Vector a, Vector a)
 -- | A list of 'Sample's
 type Samples a = [Sample a]
 
+-- | A simple synonym for the (,) operator, used to create samples very
+-- intuitively.
 (-->) :: Vector a -> Vector a -> Sample a
 (-->) = (,)
 
@@ -139,7 +140,7 @@ newNetwork layerSizes
         return $ Network lays
   where go :: Int -> Int -> IO (Layer Double)
         go inputSize outputSize = do
-            ws <- fmap (/ (sqrt $ fromIntegral inputSize)) (randn outputSize inputSize)
+            ws <- (/ (sqrt $ fromIntegral inputSize)) <$> randn outputSize inputSize
             seed <- randomIO
             let bs = randomVector seed Gaussian outputSize
             return $ Layer ws bs