From 645f61724d96dccffda0f052cb0ddd4e789479bd Mon Sep 17 00:00:00 2001
From: Leonardo Robol <leo@robol.it>
Date: Sat, 13 Mar 2010 09:20:21 +0100
Subject: [PATCH] Piccole sporadiche modifiche.

---
 Filtering/Filtering.py |  3 +--
 Filtering/dwt          | 12 ++++++++----
 Slide/slide.tex        | 11 ++++++++++-
 3 files changed, 19 insertions(+), 7 deletions(-)

diff --git a/Filtering/Filtering.py b/Filtering/Filtering.py
index 0f8eb67..76e57f8 100644
--- a/Filtering/Filtering.py
+++ b/Filtering/Filtering.py
@@ -15,7 +15,7 @@ class AbstractFilter():
         overloaded from the specific filter class
         """
         pass
-               
+        
 
 class FIR(AbstractFilter):
 
@@ -121,7 +121,6 @@ class WaveletTransformedSignal():
         """
         Get the high frequency samples
         """
-
         try:
             ret = self.high_samples.pop ()
             return ret
diff --git a/Filtering/dwt b/Filtering/dwt
index 028fb1a..d3d26f8 100755
--- a/Filtering/dwt
+++ b/Filtering/dwt
@@ -15,7 +15,7 @@ def StartProgram():
 
 def EndProgram():
     """End banner"""
-    print ""
+    print "",
 
 def LoadingLibrariesStarted():
     """Loading libraries banner"""
@@ -107,9 +107,9 @@ class DWT():
             rebuilt = filterBank.Rebuild (wavelets)
             Output ("Rebuilt in %f seconds" % (time.time() - startingTime))
 
-            # Se la differenza in norma è più di 10^-6 possiamo preoccuparci. 
+            # Se la differenza in norma è più di 10^-8 possiamo preoccuparci. 
             a = norm(rebuilt - samples[0:len(rebuilt)])
-            if (a > 1E-6):
+            if (a > 1E-8):
                 Output ("Errore while reconstructing. Rebuilt samples differs from original ones")
                 Output ("||rebuilt - samples|| = %f" % a)
             else:
@@ -153,7 +153,7 @@ class DWT():
         scale = int(0.5 * scale)
         low = wavelets.GetLowSamples()
         data = low[:toPlot / scale]
-        print len(low), len(data), scale
+        
         axes = range(0, len(data) * scale, scale)
         
         plot(axes, data + offset)
@@ -179,6 +179,10 @@ class DWT():
 
 if __name__ == "__main__":
 
+    # Scegliamo cosa fare, a seconda delle opzioni di cui
+    # abbiamo fatto il parsing più in alto. 
+    # Partiamo. 
+
     if options.rebuild:
         DWT(filename = filename, action = 'rebuild', 
             filewrite = options.filewrite, depth = options.depth,
diff --git a/Slide/slide.tex b/Slide/slide.tex
index 307e5e5..9918958 100644
--- a/Slide/slide.tex
+++ b/Slide/slide.tex
@@ -235,6 +235,15 @@
 	Il filtro \textbf{amplifica ogni frequenza del segnale} di un coefficiente $H(\omega)$.
 \end{frame}
 
-
+\section{FilterBank}
+\subsection{Cos'è una filterbank}
+\begin{frame}
+	\frametitle{Haar filterbank}
+	Consideriamo i seguenti filtri:
+	\[
+	  h_0 = (\frac{1}{2}, \frac{1}{2}) \qquad h_1 = (\frac 1 2 , - \frac{1}{2}) \qquad
+	  f_0 = (\frac{1}{2}, \frac{1}{2}) \qquad f_1 = (-\frac 1 2 , \frac{1}{2})
+	\]
+\end{frame}
 
 \end{document}
-- 
2.1.4