SF.net SVN: matplotlib: [4003] trunk/py4science

[<jd...@us...>]

Revision: 4003
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=4003&view=rev
Author:   jdh2358
Date:     2007-10-25 11:16:03 -0700 (Thu, 25 Oct 2007)

Log Message:
-----------
added convolution example

Modified Paths:
--------------
    trunk/py4science/examples/fft_imdenoise.py
    trunk/py4science/examples/skel/glass_dots1_skel.py
    trunk/py4science/examples/stock_records.py
    trunk/py4science/workbook/files_etc.tex
    trunk/py4science/workbook/main.tex

Modified: trunk/py4science/examples/fft_imdenoise.py
===================================================================
--- trunk/py4science/examples/fft_imdenoise.py	2007-10-25 16:24:28 UTC (rev 4002)
+++ trunk/py4science/examples/fft_imdenoise.py	2007-10-25 18:16:03 UTC (rev 4003)
@@ -14,16 +14,18 @@
 
 def plot_spectrum(F, amplify=1000):
     """Normalise, amplify and plot an amplitude spectrum."""
-    M = mag_phase(F)[0]
+    M, Phase = mag_phase(F)
     M *= amplify/M.max()
     M[M > 1] = 1
-    
+
+    print M.shape, M.dtype
     P.imshow(M, P.cm.Blues)
 
 try:
     # Read in original image, convert to floating point for further
-    # manipulation
-    im = S.misc.pilutil.imread('data/moonlanding.jpg').astype(float)
+    # manipulation; imread returns a MxNx4 RGBA image.  Since the
+    # image is grayscale, just extrac the 1st channel
+    im = P.imread('data/moonlanding.png').astype(float)[:,:,0]
 except:
     print "Could not open image."
     sys.exit(-1)

Modified: trunk/py4science/examples/skel/glass_dots1_skel.py
===================================================================
--- trunk/py4science/examples/skel/glass_dots1_skel.py	2007-10-25 16:24:28 UTC (rev 4002)
+++ trunk/py4science/examples/skel/glass_dots1_skel.py	2007-10-25 18:16:03 UTC (rev 4003)
@@ -11,24 +11,19 @@
 from pylab import figure, show
 
 def csqrt(x):
-    """
-    sqrt func that handles returns sqrt(x)j for x<0
-    """
+    'sqrt func that handles returns sqrt(x)j for x<0'
     XXX
     
 def myeig(M):
     """
     compute eigen values and eigenvectors analytically
-
     Solve quadratic:
-
       lamba^2 - tau*lambda + Delta = 0
-
     where tau = trace(M) and Delta = Determinant(M)
-    
+
+    Return value is lambda1, lambda2
     """
     XXX
-    return lambda1, lambda2
     
 # 2000 random x,y points in the interval[-0.5 ... 0.5]
 X1 = XXX
@@ -39,10 +34,7 @@
 #name = 'center'
 #sx, sy, angle = XXX
 
-#name = 'stable focus'  # spiral
-#sx, sy, angle = XXX
-
-name= 'spiral'
+name = 'spiral'  #stable focus
 sx, sy, angle = XXX
 
 theta = angle * pi/180.  # the rotation in radians
@@ -62,16 +54,14 @@
 M = XXX
 
 # compute the eigenvalues using numpy linear algebra
-vals, vecs = XXX
-print 'numpy eigenvalues', vals
+print 'numpy eigenvalues', XXX
 
 # compare with the analytic values from myeig
-avals = myeig(M)
-print 'analytic eigenvalues', avals
+print 'analytic eigenvalues', myeig(M)
 
 # transform X1 by the matrix M
 X2 = XXX
 
-# plot the original x,y as green dots and the transformed x, y as red
+# plot the original X1 as green dots and the transformed X2 as red
 # dots
-show()
+XXX

Modified: trunk/py4science/examples/stock_records.py
===================================================================
--- trunk/py4science/examples/stock_records.py	2007-10-25 16:24:28 UTC (rev 4002)
+++ trunk/py4science/examples/stock_records.py	2007-10-25 18:16:03 UTC (rev 4003)
@@ -67,6 +67,6 @@
     print '%s: %1.1f%%'%(ticker, 100*g)
 
 
-p.savefig('fig/stock_records.png', dpi=100)
-p.savefig('fig/stock_records.eps')
+p.savefig('stock_records.png', dpi=100)
+p.savefig('stock_records.eps')
 p.show()

Modified: trunk/py4science/workbook/files_etc.tex
===================================================================
--- trunk/py4science/workbook/files_etc.tex	2007-10-25 16:24:28 UTC (rev 4002)
+++ trunk/py4science/workbook/files_etc.tex	2007-10-25 18:16:03 UTC (rev 4003)
@@ -204,7 +204,7 @@
 \par\end{center}
 
 
-\subsection{Loading and saving binary data}
+\section{Loading and saving binary data}
 \label{sec:binary_data}
 
 ASCII is bloated and slow for working with large arrays, and so binary

Modified: trunk/py4science/workbook/main.tex
===================================================================
--- trunk/py4science/workbook/main.tex	2007-10-25 16:24:28 UTC (rev 4002)
+++ trunk/py4science/workbook/main.tex	2007-10-25 18:16:03 UTC (rev 4003)
@@ -57,4 +57,11 @@
 \input{trapezoid.tex}
 
 \input{quad_newton.tex}
+
+\chapter{Linear algebra}
+\input{intro_linalg.tex}
+\input{glass_dots.tex}
+
+
+
 \end{document}


This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.