How does one calculate the empirical cumulative distribution (ecdf) of an image in Python?

I am trying to calculate the empirical cumulative distribution of images in Python. What is the best practice in doing so? And also I need the result to be stored in an array so that I can use it in further steps of my analysis.

I am using this function and I am not sure if it is the right way to do it:

`def ecdf(data):
    x = np.sort(data.flatten())
    n = x.size
    y = np.arange(1, n+1) / n
    return (x,y)`

Here is how I am doing this now and it works (for a grayscale image):

1. For normal Gaussian distribution:

def Ghist(image):
    '''compute eCDF of an image'''
    data_flatten = image.flatten()
    data_sort = np.sort(data_flatten)
    values, bins = np.histogram(data_sort, normed=True)

    return (bins, values)

2. For cumulative distribution:

def ecdf(image):
    '''compute eCDF of an image'''
    data_flatten = image.flatten()
    data_sort = np.sort(data_flatten)
    values, bins = np.histogram(data_sort, normed=True)
    data_cum = np.cumsum(values)
    
    return (bins, data_cum)