proc_3dgal.py 文件源码

def fspecialgauss2D(shape=(3,3),sigma=0.5):
    """
    2D gaussian mask - should give the same result as MATLAB's
    fspecial('gaussian',[shape],[sigma])
    """
    m,n = [(ss-1.)/2. for ss in shape]
    y,x = np.ogrid[-m:m+1,-n:n+1]
    h = np.exp( -(x*x + y*y) / (2.*sigma*sigma) )
 ## The statement below determines the machine
 ## epsilon - if gaussian is smaller than that
 ## set to 0.
    h[ h < np.finfo(h.dtype).eps*h.max() ] = 0
    sumh = h.sum()
 ## This notation states that it takes the input
 ## h and then it divides by the sum and returns h 
    if sumh != 0:
        h /= sumh
    return h