brsa.py 文件源码

def _bin_exp(self, n_bin, scale=1.0):
        """ Calculate the bin locations to approximate exponential distribution.
            It breaks the cumulative probability of exponential distribution
            into n_bin equal bins, each covering 1 / n_bin probability. Then it
            calculates the center of mass in each bins and returns the
            centers of mass. So, it approximates the exponential distribution
            with n_bin of Delta function weighted by 1 / n_bin, at the
            locations of these centers of mass.
        Parameters:
        -----------
        n_bin: int
            The number of bins to approximate the exponential distribution
        scale: float, default: 1.0
            The scale parameter of the exponential distribution, defined in
            the same way as scipy.stats. It does not influence the ratios
            between the bins, but just controls the spacing between the bins.
            So generally users should not change its default.
        Returns:
        --------
        bins: numpy array of size [n_bin,]
            The centers of mass for each segment of the
            exponential distribution.
        """
        boundaries = np.flip(scipy.stats.expon.isf(
            np.linspace(0, 1, n_bin + 1),
            scale=scale), axis=0)
        bins = np.empty(n_bin)
        for i in np.arange(n_bin):
            bins[i] = utils.center_mass_exp(
                (boundaries[i], boundaries[i + 1]), scale=scale)
        return bins