From 3f5bf5985d3da0e4d01cd9c126cb781cb6fc28ef Mon Sep 17 00:00:00 2001
From: Alberto Ruiz <aruiz@um.es>
Date: Wed, 3 Feb 2010 17:53:51 +0000
Subject: updated examples, removed Util module

---
 examples/pca2.hs | 28 +++++++++++++---------------
 1 file changed, 13 insertions(+), 15 deletions(-)

(limited to 'examples/pca2.hs')

diff --git a/examples/pca2.hs b/examples/pca2.hs
index 8c20370..c38857c 100644
--- a/examples/pca2.hs
+++ b/examples/pca2.hs
@@ -9,33 +9,31 @@ import Control.Monad(when)
 type Vec = Vector Double
 type Mat = Matrix Double
 
-sumColumns m = constant 1 (rows m) <> m
+-- Vector with the mean value of the columns of a matrix
+mean a = constant (recip . fromIntegral . rows $ a) (rows a) <> a
 
--- Vector with the mean value of the columns of a Mat
-mean x = sumColumns x / fromIntegral (rows x)
+-- covariance matrix of a list of observations stored as rows
+cov x = (trans xc <> xc) / fromIntegral (rows x - 1)
+    where xc = x - asRow (mean x)
 
--- covariance matrix of a list of observations as rows of a matrix
-cov x = (trans xc <> xc) / fromIntegral (rows x -1) 
-    where xc = center x
-          center m = m - constant 1 (rows m) `outer` mean m
 
 type Stat = (Vec, [Double], Mat)
--- 1st and 2nd order statistics of a dataset (mean, eigenvalues and eigenvectors of cov)  
+-- 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, trans 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 
+-- 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
-    vp = takeRows n v    
+    vp = takeRows n v
     n = 1 + (length $ fst $ span (< (prec'*sum s)) $ cumSum s)
-    cumSum = tail . scanl (+) 0.0     
+    cumSum = tail . scanl (+) 0.0
     prec' = if prec <=0.0 || prec >= 1.0
                 then error "the precision in pca must be 0<prec<1"
                 else prec
@@ -49,7 +47,7 @@ test st prec x = do
     let (pe,pd) = pca prec st
     let y = pe x
     print $ dim y
-    shdigit (pd y)    
+    shdigit (pd y)
 
 main = do
     ok <- doesFileExist ("mnist.txt")
@@ -58,7 +56,7 @@ main = do
         system("wget -nv http://dis.um.es/~alberto/material/sp/mnist.txt.gz")
         system("gunzip mnist.txt.gz")
         return ()
-    m <- fromFile "mnist.txt" (5000,785)
+    m <- loadMatrix "mnist.txt"
     let xs = takeColumns (cols m -1) m
     let x = toRows xs !! 4  -- an arbitrary test vector
     shdigit x
-- 
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