Distribution element trees (DETs) enable the estimation of probability densities based on (possibly large) datasets. Moreover, DETs can be used for random number generation or smooth bootstrapping both in unconditional and conditional modes. In the latter mode, information about certain probability-space components is taken into account when sampling the remaining probability-space components. For details see http://dx.doi.org/10.1007/s11222-017-9751-9 or http://arxiv.org/abs/1610.00345 and http://dx.doi.org/10.1080/10618600.2018.1482768 or http://arxiv.org/abs/1711.04632