zorro_util.py 文件源码

def histClim( imData, cutoff = 0.01, bins_ = 512 ):
    '''Compute display range based on a confidence interval-style, from a histogram
    (i.e. ignore the 'cutoff' proportion lowest/highest value pixels)'''

    if( cutoff <= 0.0 ):
        return imData.min(), imData.max()
    # compute image histogram
    hh, bins_ = imHist(imData, bins_)
    hh = hh.astype( 'float' )

    # number of pixels
    Npx = np.sum(hh)
    hh_csum = np.cumsum( hh )

    # Find indices where hh_csum is < and > Npx*cutoff
    try:
        i_forward = np.argwhere( hh_csum < Npx*(1.0 - cutoff) )[-1][0]
        i_backward = np.argwhere( hh_csum > Npx*cutoff )[0][0]
    except IndexError:
        print( "histClim failed, returning confidence interval instead" )
        from scipy.special import erfinv

        sigma = np.sqrt(2) * erfinv( 1.0 - cutoff )
        return ciClim( imData, sigma )

    clim =  np.array( [bins_[i_backward], bins_[i_forward]] )
    if clim[0] > clim[1]:
        clim = np.array( [clim[1], clim[0]] )
    return clim