[Numpy-discussion] help on fast slicing on a grid

frank wang f.yw@hotmail....
Fri Jan 30 12:58:21 CST 2009


I have created a test example for the question using for loop and hope someone can help me to get fast solution. My data set is about 2000000 data.
 
However, I have the problem to run the code, the Out[i]=cnstl[j] line gives me error says:
 
In [107]: Out[0]=cnstl[0]---------------------------------------------------------------------------TypeError                                 Traceback (most recent call last)
C:\Frank_share\qamslicer.py in <module>()----> 1      2      3      4      5
TypeError: can't convert complex to float; use abs(z)
In [108]: cnstl.dtypeOut[108]: dtype('complex128')
I do not know why that my data is complex128 already. Can anyone help to figure why?
 
Thanks
 
Frank
 
from numpy import *a = arange(-15,16,2)cnstl=a.reshape(16,1)+1j*acnstl=cnstl.reshape(256,1)
X = array([1.4 + 1j*2.7, -4.9 + 1j*8.3])
Out = array(X)error =array(X)for i in xrange(2):    for j in xrange(256):        a0 = real(X[i]) < (real(cnstl[j])+1)        a1 = real(X[i]) > (real(cnstl[j])-1)        a2 = imag(X[i]) > (imag(cnstl[j])-1)        a3 = imag(X[i]) < (imag(cnstl[j])+1) if (a0 & a1 & a2 &a3):            Out[i] = cnstl[j]            error[i] = X[i] - cnstl[j]

From: f.yw@hotmail.comTo: numpy-discussion@scipy.orgSubject: RE: [Numpy-discussion] help on fast slicing on a gridDate: Wed, 28 Jan 2009 23:28:47 -0700

Hi, Bob, Thanks for your help.  I am sorry for my type error. qam array is the X array in my example. cntl is a complex array contains the point (x,y) axises. I will try to make a workable example. Also I will try to find out the zeros_like function. However, I guess that zeros_like(X) will create an array the same size as X. It it is. Then the two line Out=X and error=X should be Out=zeros_like(X) and error=zeros(X). Also, can where command handel the logic command? aa = np.where((real(X)<real(cnstl[j])+1) & (real(X)>real(cnstl[j])-1) & (imag(X)<imag(cnstl[j])+1) & (imag(X)>imag(cnstl[j]-1)) For example, cntl[j]=3+1j*5, then the where command is the same as: aa = np.where((real(X)<4) & (real(X)>2 )& (imag(X)<6) & (imag(X)>4)) Thanks Frank> Date: Thu, 29 Jan 2009 00:15:48 -0600> From: robert.kern@gmail.com> To: numpy-discussion@scipy.org> Subject: Re: [Numpy-discussion] help on fast slicing on a grid> > On Thu, Jan 29, 2009 at 00:09, frank wang <f.yw@hotmail.com> wrote:> > Here is the for loop that I am think about. Also, I do not know whether the> > where commands can handle the complicated logic.> > The where command basically find the data in the square around the point> > cnstl[j].> > cnstl is a 2D array from your previous description.> > > Let the data array is qam with size N> > I don't see qam anywhere. Did you mean X?> > > Out = X> > error = X> > Don't you want something like zeros_like(X) for these?> > > for i in arange(N):> > for j in arange(L):> > aa = np.where((real(X)<real(cnstl[j])+1) &> > (real(X)>real(cnstl[j])-1) & (imag(X)<imag(cnstl[j])+1) &> > (imag(X)>imag(cnstl[j]-1))> > Out[aa]=cnstl[j]> > error[aa]=abs(X)**2 - abs(cnstl[j])**2> > I'm still confused. Can you show me a complete, working script with> possibly fake data?> > -- > Robert Kern> > "I have come to believe that the whole world is an enigma, a harmless> enigma that is made terrible by our own mad attempt to interpret it as> though it had an underlying truth."> -- Umberto Eco> _______________________________________________> Numpy-discussion mailing list> Numpy-discussion@scipy.org> http://projects.scipy.org/mailman/listinfo/numpy-discussion

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