die Besprechung ergab fuer diese Gruppe:

• Trockenprogrammierung: insbesondere die Konsistenz von Bildkoordinaten von ASAR und Freibord-Footprint klären die Klasseneinteilungen von ASAR und Freibordhöhen vergleichen Frage "welche Statistik will man anwenden" beantworten

#Bisher erzeugtes Programm:

from pylab import * from scipy import * import time,calendar,os,pipes,struct,string import random import scipy.ndimage as ndi

nk=3 #number of classes ndim=[100,100] #dimension of ASAR image in pixels

fx0,fy0,fx2,fy2=[20.,100.,100.,10.] # freeboard coordinates from input file nf=11 #number of freeboard footprints fz_h=zeros(nf) #fz_h is the freeboard heights # produce a random array of freeboard heights for i in range(nf):

• fz_h[i]=random.random()*70

# the x,y positions of the freeboard footprints if fx2==fx0:

• fx=zeros(nf)+fx0 fy=linspace(0,ndim[1],nf)

else:

• teta=(fy2-fy0)/(fx2-fx0) fx=linspace(fx0,fx2,nf) fy=(fx-fx0)*teta+fy0

#produce a random matrix of ASAR image classes (in 3 classes)

a=zeros((ndim[0],ndim[1])) for i in range(ndim[0]):

• for j in range(ndim[1]):
  • a[i,j]=int(random.random()*(nk)+1)

#tranform from float to int

#A=ndimage.gaussian_filter(a,1)+0.5 #B=A.astype(int) B=a.astype(int)

#select the class of footprints from ASAR Image fz=zeros(nf) for i in range(nf):

• fz[i]=B[int(fx[i]-1),int(fy[i]-1)]

#calculation of mean and standard deviation of freeboard heights in each class mean=zeros(nk) std_kl=zeros(nk) for kl in (1,2,3):

• s=(fz==kl) fh_kl=fz_h[s] mean[kl-1]=fh_kl.sum()/fh_kl.shape[0] std_kl[kl-1]=std(fh_kl)

#plot mean and error bar kl=[1,2,3] bar(kl,mean,yerr=std_kl,ecolor='r',align='center')

#calculate correlation coefficient #corr=xcorr(fz,fz_h,normed=True)[1][nf]

figure() #plot ASAR image class together with freeboard heights x=arange(nf) bar(x,fz,align='center') ylim(0,6) ax=twinx() plot(x,fz_h,'r+-') xlim(-2,12)

#plot ASAR image with freeboard flight figure() plot(fx,fy,'r+-',linewidth=2) xlim(0,100) ylim(0,100) colorbar() imshow(B,origin='lower',interpolation=None) hold(True)

#figure() #imshow(a) show()