Alice Invernizzi wrote: > > Dear all, > > I have an Hamletic doubt concerning the numpy array data type. > A general learned rule concerning the array usage in other high-level > programming languages is that array data-type are homogeneous datasets > of fixed dimension. > > Therefore, is not clear to me why in numpy the size of an array can be > changed (either with the 'returning-value' resize() function either with > the 'in-place' array method resize()). > More in detail, if the existence of the first function > ('returning-value') might make sense in array computing operation, the > existence of the 'in-place' method really make no sense for me. > > Would you please be so kind to give some explanation for the existence > of resize operator for numpy array? If array size can be change, > what are the real advantages of using numpy array instead of list object? > Thanks in avdance
Just to keep into the same line. import numpy a=numpy.arange(100.) a.shape = 10, 10 b = a * 1 # just to get a copy b.shape = 5, 2, 5, 5 b = (b.sum(axis=3)).sum(axis=1) In that way, on b I have a binned image of a. I would expect a.resize(5, 5) would have given something similar (perhaps there is already something to make a binning). In fact a.resize(5,5) is much closer to a crop than to a resize. I think the resize name is misleading and should be called crop, but that is just my view. Armando _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion