Charles R Harris wrote:
Matrix rank has nothing to do with numpy rank. Numpy rank is simply the number of indices required to address an element of an ndarray. I always thought a better name for the Numpy rank would be dimensionality, but like everything else one gets used to the numpy jargon, it only needs to be defined someplace for what it is.
"numpy rank" derives from "tensor rank" rather than "matrix rank". It's not *wrong*, but as with many things in mathematics, the term is overloaded and can be confusing. "dimensionality" is no better. A "three-dimensional array" might be [1, 2, 3], not [[[1]]]. http://mathworld.wolfram.com/TensorRank.html -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco