Hello all, On my (older) version of numpy (1.0.4.dev3896), I found several oddities in the handling of assignment of long-integer values to integer arrays:
In : numpy.array([2**31], dtype=numpy.int8) ------------------------------------------------------------------------ --- ValueError Traceback (most recent call last) /Users/zpincus/<ipython console> ValueError: setting an array element with a sequence. While this might be reasonable to be an error condition, the precise error raised seems not quite right! But not all overflow errors are caught in this way: In : numpy.array([2**31-1], dtype=numpy.int8) Out: array([-1], dtype=int8) As above, numpy is quite happy allowing overflows; it just breaks when doing a python long-int to int conversion. The conversion from numpy-long-int to int does the "right thing" though (if by "right thing" you mean "allows silent overflow", which is a matter of discussion elsewhere right now...): In : numpy.array(numpy.array([2**31], dtype=numpy.int64), dtype=numpy.int8) Out: array([0], dtype=int8) At least on item assignment, the overflow exception is less odd: In : a = numpy.empty(shape=(1,), dtype=numpy.int8) In : a[0] = 2**31 ------------------------------------------------------------------------ --- OverflowError Traceback (most recent call last) /Users/zpincus/<ipython console> OverflowError: long int too large to convert to int Things work right with array element assignment: In : a[0] = numpy.array([2**31], dtype=numpy.int64)[0] But break again with array scalars, and with the strange ValueError again! In : a[0] = numpy.array(2**31, dtype=numpy.int64) ------------------------------------------------------------------------ --- ValueError Traceback (most recent call last) /Users/zpincus/<ipython console> ValueError: setting an array element with a sequence. Note that non-long-int-to-int array scalar conversions work: In : a[0] = numpy.array(2**31-1, dtype=numpy.int64) Is this still the case for the current version of numpy? Best, Zach _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
