import numpy as np
'''
    source repository: https://github.com/oliviaguest/gini.git
'''
def gini(array):
    """Calculate the Gini coefficient of a numpy array."""
    # based on bottom eq:
    # http://www.statsdirect.com/help/generatedimages/equations/equation154.svg
    # from:
    # http://www.statsdirect.com/help/default.htm#nonparametric_methods/gini.htm
    # All values are treated equally, arrays must be 1d:
    array = np.array([float(i) for i in array])
    # array = array.flatten()
    if np.amin(array) < 0:
        # Values cannot be negative:
        array -= np.amin(array)
    # Values cannot be 0:
    array += 0.0000001
    # Values must be sorted:
    array = np.sort(array)
    # Index per array element:
    index = np.arange(1,array.shape[0]+1)
    # Number of array elements:
    n = array.shape[0]
    # Gini coefficient:
    return ((np.sum((2 * index - n  - 1) * array)) / (n * np.sum(array)))


if __name__ == '__main__':
    # print gini(np.array([1.0,0,0]))
    print(gini(np.array([0.1,0.5,0.2,0.1])))