plfit/plfit.py
def most_likely_alpha(data, xmin, alpharange=(1.5,3.5), n_alpha=201):
    """
    Return the most likely alpha for the data given an xmin
    """
    alpha_vector = np.linspace(alpharange[0],alpharange[1],n_alpha)
    return alpha_vector[discrete_max_likelihood_arg(data, xmin,
                                                    alpharange=alpharange,
                                                    n_alpha=n_alpha)]
def most_likely_alpha(data, xmin, alpharange=(1.5,3.5), n_alpha=201):
    alpha_vector = np.linspace(alpharange[0],alpharange[1],n_alpha)
    return alpha_vector[discrete_max_likelihood_arg(data, xmin,
                                                    alpharange=alpharange,
                                                    n_alpha=n_alpha)]
def most_likely_alpha ( data , xmin , alpharange = ( 1.5 , 3.5 ) , n_alpha = 201 ) : alpha_vector = np . linspace ( alpharange [ 0 ] , alpharange [ 1 ] , n_alpha ) return alpha_vector [ discrete_max_likelihood_arg ( data , xmin , alpharange = alpharange , n_alpha = n_alpha ) ]
Return the most likely alpha for the data given an xmin
Return the most likely alpha for the data given an xmin