  In the study of computer codes, filling space as uniformly as possible is
important to describe the complexity of the investigated phenomenon. However,
this property is not conserved by reducing the dimension. Some numeric
experiment designs are conceived in this sense as Latin hypercubes or
orthogonal arrays, but they consider only the projections onto the axes or the
coordinate planes. In this article we introduce a statistic which allows
studying the good distribution of points according to all 1-dimensional
projections. By angularly scanning the domain, we obtain a radar type
representation, allowing the uniformity defects of a design to be identified
with respect to its projections onto straight lines. The advantages of this new
tool are demonstrated on usual examples of space-filling designs (SFD) and a
global statistic independent of the angle of rotation is studied.
