Evaluate KDE at given points.

        Prepares data according to whether sklearn or scipy
        KDE in use.

        :param log, dur, slope:
            Trapezoidal shape parameters.

def _density(self, logd, dur, slope):
        """
        Evaluate KDE at given points.

        Prepares data according to whether sklearn or scipy
        KDE in use.

        :param log, dur, slope:
            Trapezoidal shape parameters.
        """
        if self.sklearn_kde:
            #TODO: fix preprocessing
            pts = np.array([(logd - self.mean_logdepth)/self.std_logdepth,
                            (dur - self.mean_dur)/self.std_dur,
                            (slope - self.mean_slope)/self.std_slope])
            return self.kde.score_samples(pts)
        else:
            return self.kde(np.array([logd, dur, slope]))