AnalysisFunctions.py 文件源码

def ReducedSpec(ar,ax=2,lenx=2*pi,leny=2*pi,lenz=2*pi):
   """
      ReducedSpec(ar,ax=2,lenx=2*pi,leny=2*pi,lenz=2*pi)

      Reduced spectrum of ar along axis ax

   """
   if len(ar) == 0:
      print 'No array provided! Exiting!'
      return
   ar=ar-np.mean(ar)
   nx=np.shape(ar)[0];kx=nf.fftshift(nf.fftfreq(nx))*nx*(2*pi/lenx)
   ny=np.shape(ar)[1];ky=nf.fftshift(nf.fftfreq(ny))*ny*(2*pi/leny)
   nz=np.shape(ar)[2];kz=nf.fftshift(nf.fftfreq(nz))*nz*(2*pi/lenz)

   if ax==0:
      # Both are one because after the first sum, the new array as dim=2
      # First sum along y, then along z
      ax1=1; ax2=1
      kk=kx; nn=nx
   elif ax==1:
      # First sum along x (0), then along z (1 for the new configuration)
      ax1=0; ax2=1
      kk=ky; nn=ny
   elif ax==2:
      # First sum along x (0), then along y (0 for the new configuration)
      ax1=0; ax2=0
      kk=kz; nn=nz

   far = nf.fftshift(nf.fftn(ar))/(nx*ny*nz); fftea=0.5*np.abs(far)**2
   ffteb=fftea.sum(axis=ax1).sum(axis=ax2)
   dk = kk[1]-kk[0]
   return kk[nn/2:],ffteb[nn/2:]/dk

##
## REDUCED SPECTRUM OF A VECTOR
##