[MATRIX-SIG] Fix to NumPy10

L. Busby busby@icf.llnl.gov
Fri, 6 Mar 98 13:09:01 PST

>Is there any files or pages having information (plans) on future
>development of NumPy? I'd like to to read what features are to be
>included in or excluded. That "TODO.TXT" file in distribution seems to
>be rather short :-), though Fortran direct support (at last) is a great

  TODO.TXT is all there is for now.  If it seems short to you, what
  else do you think should be there?  I'm sure many of us would like to
  read what features are to be included or excluded, but that's really
  what this mailing list is for.

>Look - another bug? (I use Win'95, Python 1.5, Numpy10)
>Maybe it is a supposed behaviour, but ...
>>>> r = arange(13)
>>>> r
>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])
>>>> ar=pow(10,r)
>### ar=10**r produce the same
>>>> ar
>array([1, 10, 100,1000, 10000,100000,
>         1000000, 10000000, 100000000, 1000000000,
>       1410065408, 1215752192, -727379968])
>How do you like it? I do not.
>never can be 10**10 =1410065408
>of course, 10.0**r gives "right" result.
>Andy K.

  When item 4 of TODO is finished, you'll be able to turn on a signal
  handler for SIGFPE and catch the overflow you observed above.  (Odd
  though it may seem, integer divide by zero and overflow will generate
  SIGFPE in most implementations.)  For the moment, it's neither a bug
  nor a feature.  Until Python itself was capable of handling SIGFPE,
  it was impossible to do much of anything about it in NumPy (unless
  you were willing to give up most of NumPy's speed advantage by
  checking all operands).

  Note that many of the functions in the Standard math library do check
  the domain and/or range of their arguments and/or results.  (And they
  will set errno to EDOM or ERANGE if an error occurs.) That's the
  difference between fast_umath and umath modules.  The first doesn't
  check the value of errno after each call to a library math function,
  the second does.  This will trap some errors, but not integer
  exponentiation, as you discovered.

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