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The Monte Carlo method is the most popular technique to perform radiativetransfer simulations in a general 3D geometry. The algorithms behind andacceleration techniques for Monte Carlo radiative transfer are discussedextensively in the literature, and many different Monte Carlo codes arepublicly available. On the contrary, the design of a suite of components thatcan be used for the distribution of sources and sinks in radiative transfercodes has received very little attention. The availability of such models, withdifferent degrees of complexity, has many benefits. For example, they can serveas toy models to test new physical ingredients, or as parameterised models forinverse radiative transfer fitting. For 3D Monte Carlo codes, this requiresalgorithms to efficiently generate random positions from 3D densitydistributions. We describe the design of a flexible suite of components for theMonte Carlo radiative transfer code SKIRT. The design is based on a combinationof basic building blocks (which can be either analytical toy models ornumerical models defined on grids or a set of particles) and the extensive useof decorators that combine and alter these building blocks to more complexstructures. For a number of decorators, e.g. those that add spiral structure orclumpiness, we provide a detailed description of the algorithms that can beused to generate random positions. Advantages of this decorator-based designinclude code transparency, the avoidance of code duplication, and an increasein code maintainability. Moreover, since decorators can be chained withoutproblems, very complex models can easily be constructed out of simple buildingblocks. Finally, based on a number of test simulations, we demonstrate that ourdesign using customised random position generators is superior to a simplerdesign based on a generic black-box random position generator.

SKIRT: the design of a suite of input models for Monte Carlo radiative transfer simulations