  By analysing models of the young massive cluster R136 in 30 Doradus, set-up
using the herewith introduced and publicly made available code McLuster, we
investigate and compare different methods for detecting and quantifying mass
segregation and substructure in non-seeing limited N-body data. For this
purpose we generate star cluster models with different degrees of mass
segregation and fractal substructure and analyse them. We quantify mass
segregation by measuring, from the projected 2d model data, the mass function
slope in radial annuli, by looking for colour gradients in radial colour
profiles, by measuring Allison's Lambda parameter, and by determining the local
stellar surface density around each star. We find that these methods for
quantifying mass segregation often produce ambiguous results. Most reliable for
detecting mass segregation is the mass function slope method, whereas the
colour gradient method is the least practical in an R136-like configuration.
The other two methods are more sensitive to low degrees of mass segregation but
are computationally much more demanding. We also discuss the effect of binaries
on these measures. Moreover, we quantify substructure by looking at the
projected radial stellar density profile, by comparing projected azimuthal
stellar density profiles, and by determining Cartwright & Whitworth's Q
parameter. We find that only high degrees of substructure affect the projected
radial density profile, whereas the projected azimuthal density profile is very
sensitive to substructure. The Q parameter is also sensitive to substructure
but its absolute value shows a dependence on the radial density gradient of the
cluster and is strongly influenced by binaries. (abridged)
