[Numpy-discussion] Community Poll: numarray default underflow handling == "ignore" ?

Alexander Schmolck a.schmolck at gmx.net
Fri Nov 21 16:38:02 EST 2003


"Sebastian Haase" <haase at msg.ucsf.edu> writes:

> My vote would be '-1' ( if that means "I prefer ignore")
> I'm thinking of an INTERACTIVE platform - and so it would just "look nicer"
> without to many warnings.

Well, it's only a default so you could always deactivate it (for all
interactive sessions in your PYTHONSTARTUP if you wanted).

> 
> Actually on that note: I read some time ago about pythons default for
> printing floats:
> >>> 0.1
> 0.10000000000000001
> >>> print 0.1
> 0.1
> >>> repr(0.1)
> '0.10000000000000001'
> >>> str(.1)
> '0.1'
> 
> Does anyone here have an update on that ?



> What I am especially interested in is when I have a list of (floating point)
> (x,y) positions and
> then typing in the var-name and getting all these ugly numbers is still very
> frustration for me ;-)

You can customize python's interactive printing behavior any way you like (in
your PYTHONSTARTUP). Here is an example from my old ~/.pythonrc.py (nowadays I
almost exclusively use ipython).

import pprint
PRETTY_PRINT=1
_normal_displayhook = sys.displayhook
def _my_displayhook(object):
    if PRETTY_PRINT:
        # don't bore us with None
        if object is not None:
            pprint.pprint(object)
    else:
        _normal_displayhook(object)
sys.displayhook = _my_displayhook

You could add something to the above to achieve the floating point (or list)
formating you desire (``if type(object) is float:...).

Since I am a heavy interactive user and found the default floating formating
of arrays somewhat clumsy for interactive work, I also wrote some more
fanciful formatting code for my Numeric/numarray compatible matrix class that
amongst other things offers a number of formating options, including matlab
style. I found that this made my life much easier.

Thus:

>>> a
array([[-9.90000000e+01,  -9.72817182e+01,   0.00000000e+00,  -7.99144631e+01],
       [-4.54018500e+01,   4.84131591e+01,   3.03428793e+02,   9.96633158e+02],
       [2.88095799e+03,   8.00308393e+03,   2.19264658e+04,   5.97741417e+04]])
>>> m = matrix(a)
>>> m
matrix('''
1.0E+04 *

  -0.00990   -0.00973    0.00000   -0.00799
  -0.00454    0.00484    0.03034    0.09966
   0.28810    0.80031    2.19265    5.97741
''')
>>> m.show('long')
matrix('''
1.0E+04 *


Columns 0 through 3

  -0.009900000000000   -0.009728171817154    0.000000000000000
  -0.004540184996686    0.004841315910258    0.030342879349274
   0.288095798704173    0.800308392757538    2.192646579480672

Columns 3 through 4

  -0.007991446307681
   0.099663315842846
   5.977414171519782
''')
>>> m.show('+')
m.show('+')
matrix('''
-- -
-+++
++++
''')

etc.

Adapting this to e.g. format Numeric arrays similarly via the display hook
shouldn't be too hard, I can provide the code if you're interested.


'as





More information about the NumPy-Discussion mailing list