The subdivision of a geologic map into structural domains involves the location of regions in which the rock fabric has certain geometrical characteristics; typically, foliation data should share a common axis. The location of such domains involves working interactively with map and equal-area projections of the data set, a tedious and often subjective process. Eigenvector methods can quantify this type of analysis. A set of four eigenvalue-based indexes assists in discriminating among fabric distributions, particularly between strong and weak cylindrical distributions. These indexes form the basis of a triangular diagram for distinguishing among point, girdle, random, and cylindrical fabrics. A domain search proceeds by subdividing the data set and attempting to maximize the total cylindricity, or other characteristic. The method has been applied to a set of foliation data from a fold nappe in the Western Gneiss Region of the Norwegian Caledonides. The resulting domains define a late fold that refolds the recumbent nappe. Lineation and fold-axis data from the area support the results of the domain search. This method may be valuable in other areas of complex geometry.