NaN's and infs

from the numpy list:
> numarray allows one to customize how errors are handled. You can
> choose:
>
> 1) to silently ignore all errors.
> 2) print a warning message (default)
> 3) raise an exception.
>
> One may separately set one of these three behaviors for each of
> the 4 ieee categories of floating point errors, namely
>
> 1) invalid results (i.e., NaNs)
> 2) divide by zeros (Infs)
> 3) overflows
> 4) underflows

now try this:
from numarray import *
1./arange(10)
Warning: Encountered divide by zero(s) in divide
array([ inf, 1.00000000e+000, 5.00000000e-001,
         3.33333333e-001, 2.50000000e-001, 2.00000000e-001,
         1.66666667e-001, 1.42857143e-001, 1.25000000e-001,
         1.11111111e-001])

there is the inf!!

Thank you Flavio,

I had tried the test you just suggested, and only got the warning message. I
incorrectly assumed that the result had not been returned. Now I see that it
was returned:

from numarray import *
a=1./arange(10) #displays error
print a # displays a with the inf

Thanks again,

Darren