1 files changed, 10 insertions, 7 deletions

diff --git a/examples/pca2.hs b/examples/pca2.hs
index e7ea95f..892d382 100644
--- a/examples/pca2.hs
+++ b/examples/pca2.hs
@@ -1,5 +1,7 @@
 -- Improved PCA, including illustrative graphics
 
+{-# LANGUAGE FlexibleContexts #-}
+
 import Numeric.LinearAlgebra
 import Graphics.Plot
 import System.Directory(doesFileExist)
@@ -10,27 +12,27 @@ type Vec = Vector Double
 type Mat = Matrix Double
 
 -- Vector with the mean value of the columns of a matrix
-mean a = constant (recip . fromIntegral . rows $ a) (rows a) <> a
+mean a = konst (recip . fromIntegral . rows $ a) (rows a) <# a
 
 -- covariance matrix of a list of observations stored as rows
-cov x = (trans xc <> xc) / fromIntegral (rows x - 1)
+cov x = (mTm xc) -- / fromIntegral (rows x - 1)
     where xc = x - asRow (mean x)
 
 
 type Stat = (Vec, [Double], Mat)
 -- 1st and 2nd order statistics of a dataset (mean, eigenvalues and eigenvectors of cov)
 stat :: Mat -> Stat
-stat x = (m, toList s, trans v) where
+stat x = (m, toList s, tr v) where
     m = mean x
-    (s,v) = eigSH' (cov x)
+    (s,v) = eigSH (cov x)
 
 -- creates the compression and decompression functions from the desired reconstruction
 -- quality and the statistics of a data set
 pca :: Double -> Stat -> (Vec -> Vec , Vec -> Vec)
 pca prec (m,s,v) = (encode,decode)    
   where    
-    encode x = vp <> (x - m)
-    decode x = x <> vp + m
+    encode x = vp #> (x - m)
+    decode x = x <# vp + m
     vp = takeRows n v
     n = 1 + (length $ fst $ span (< (prec'*sum s)) $ cumSum s)
     cumSum = tail . scanl (+) 0.0
@@ -46,7 +48,7 @@ test :: Stat -> Double -> Vec -> IO ()
 test st prec x = do
     let (pe,pd) = pca prec st
     let y = pe x
-    print $ dim y
+    print $ size y
     shdigit (pd y)
 
 main = do
@@ -63,3 +65,4 @@ main = do
     let st = stat xs
     test st 0.90 x
     test st 0.50 x
+