1. A method of establishing a hierarchial library of spectra, each spectrum corresponding to point-by-point representations of characteristics of a known sample, each spectrum being different from all other spectra, comprising the steps of: (a) converting each spectrum into a vector in n-dimensional hyperspace corresponding to the point-by-point representations of a different known sample; (b) determining mathematical angles, as determinitive of similarity, between all of the vectors; (c) selecting a first vector which is closest to a mean of the vectors and hence represents a center of population of the vectors; (d) selecting a second vector which is most dissimilar to the first vector and represents a local center of population; (e) separating the vectors into first and second groups of vectors that are most similar to the selected first and second vectors; (f) for each group of vectors, excluding each previously selected vector representing a center of population and selecting one new vector that represents a local center of population and another vector that is most dissimilar to the one vector and which represents a local center of population of vectors; (g) separating the vectors of each group into pairs of subgroups according to their similarity to the centers of population vectors of step (f); (h) associating the center of population vector for each group of vectors for each subgroup of vectors; and (i) repeating steps (f), (g), and (h) for each successive subgroup until all vectors have been selected as centers of population.