def xzImage ( self, zscale ):
    zdim,ydim,xdim = self.data.shape[1:]
    if self.data.dtype == np.uint8:  
      outimage = Image.frombuffer ( 'L', (xdim,zdim), self.data[0,:,0,:].flatten(), 'raw', 'L', 0, 1)
    else:
      outimage = Image.frombuffer ( 'I;16', (xdim,zdim), self.data[0,:,0,:].flatten(), 'raw', 'I;16', 0, 1)
      outimage = outimage.point(lambda i:i*(1./256)).convert('L')
    
    return  outimage.resize ( [xdim, int(zdim*zscale)] )
Computes the covariance matrix for each Gaussian kernel using
dataset/ETHPy150Open neurodata/ndstore/ocpca/timecube.py/TimeCube16.xzImage--crossover with--dataset/ETHPy150Open scipy/scipy/scipy/stats/kde.py/gaussian_kde._compute_covariance