def _interpolate_coefficients(self, alpha):
        """Interpolate coefficients by calculating the weighted average of coefficient vectors corresponding to
        neighbors of alpha in the list of alphas constructed during training."""
        exact = False
        coef_idx = None
        for i, val in enumerate(self.alphas_):
            if val > alpha:
                coef_idx = i
            elif alpha - val < numpy.finfo(numpy.float).eps:
                coef_idx = i
                exact = True
                break

        if coef_idx is None:
            coef = self.coef_[:, 0]
        elif exact or coef_idx == len(self.alphas_) - 1:
            coef = self.coef_[:, coef_idx]
        else:
            # interpolate between coefficients
            a1 = self.alphas_[coef_idx + 1]
            a2 = self.alphas_[coef_idx]
            frac = (alpha - a1) / (a2 - a1)
            coef = frac * self.coef_[:, coef_idx] + (1.0 - frac) * self.coef_[:, coef_idx + 1]

        return coef
Interpolate coefficients by calculating the weighted average of coefficient vectors corresponding to
        neighbors of alpha in the list of alphas constructed during training.