1 def load_img(filename):
   2     im=Image.open(filename)
   3     return resize(fromstring(im.tostring(),uint8),(im.size[1],im.size[0],3))

   1 from pylab import *
   2 
   3 def load_img(filename):
   4     im=Image.open(filename)
   5     return resize(fromstring(im.tostring(),uint8),(im.size[1],im.size[0],3))
   6 
   7 filename='AERONET_Hornsund.2009072.aqua.250m.jpg'
   8 
   9 a=load_img(filename)
  10 
  11 test=a[1500,500:1500,0]
  12 psd(test,NFFT=512,Fs=250,Fc=0,detrend=mlab.detrend_none,window=mlab.window_hanning, noverlap=0)
  13 
  14 show()

   1 from  scipy import *
   2 import Image
   3 def profmean(img,y1=0,ylen=5,x1=0,xlen=512):
   4     """
   5         
   6         
   7     """
   8     y2=y1+ylen
   9     xlist=range(x1,x1+xlen)
  10     #print xlist
  11     p=[]
  12     for x in xlist:
  13         p.append(a[y1:y2,x,0].mean())
  14     print p
  15     return p    
  16 
  17 def load_img(filename):
  18     im=Image.open(filename)
  19     return resize(fromstring(im.tostring(),uint8),(im.size[1],im.size[0],3))
  20     
  21 filename='AERONET_Hornsund.2009072.terra.250m.jpg'
  22 
  23 a=load_img(filename)
  24 
  25 print profmean(a)