def prop_samples(self,prop,return_values=True,conf=0.683):
        """Returns samples of given property, based on MCMC sampling

        :param prop:
            Name of desired property.  Must be column of ``self.samples``.

        :param return_values: (optional)
            If ``True`` (default), then also return (median, lo_err, hi_err)
            corresponding to desired credible interval.

        :param conf: (optional)
            Desired quantile for credible interval.  Default = 0.683.

        :return:
            :class:`np.ndarray` of desired samples

        :return: 
            Optionally also return summary statistics (median, lo_err, hi_err),
            if ``returns_values == True`` (this is default behavior)
        
        """
        samples = self.samples[prop].values
        
        if return_values:
            sorted = np.sort(samples)
            med = np.median(samples)
            n = len(samples)
            lo_ind = int(n*(0.5 - conf/2))
            hi_ind = int(n*(0.5 + conf/2))
            lo = med - sorted[lo_ind]
            hi = sorted[hi_ind] - med
            return samples, (med,lo,hi)
        else:
            return samples