matplotlib-users Mailing List for matplotlib

>
> 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

On Mon, 2004年10月04日 at 10:43, Flávio Codeço Coelho wrote:
> On Monday 04 October 2004 09:27, Jon Peirce wrote:
> > On my AMD64 (using pre-compiled version as packaged by enthought) I get
> >
> > the expected results from RandomArray under Numeric ie:
> > >>> from RandomArray import *
> > >>> normal(2,2,10)
> >
> > array([-0.43560529, 2.67296922, 0.84804749, 4.26332831, 0.64425385,
> > 3.43939352,
> > 4.07021809, 3.6235764 , 2.93580639, 1.81101392])
> >
> > Jon
> 
> Jon,
> 
> was you pre compiled Numeric compile for amd64 or for x86?
> 
> I think this is a result of the compilation .
> 
> Flavio
Pearu Peterson, the guy who does f2py for SciPy, also commented
recently on num...@li... that he had found and fixed
this problem in Numeric for SciPy. He posted a patch which I also
applied to Numeric on Source Forge; that is still unreleased. The
contents of the patch were already in numarray.random_array.
Todd
> > >Message: 3
> > >From: =?iso-8859-1?q?Fl=E1vio_Code=E7o_Coelho?= <fcc...@fi...>
> > >Organization: PROCC-Fiocruz
> > >To: mat...@li...
> > >Date: Fri, 1 Oct 2004 17:06:10 +0000
> > >Subject: [Matplotlib-users] warning: Numeric and amd64
> > >
> > >Hi,
> > >
> > >look at this:
> > >>>>>>> from RandomArray import *
> > >>>>>>>
> > >>>>>>>
> > >>>>>>>
> > >>>>>>>
> > >>>>>>>
> > >>>>>>> normal(2,2,10)
> > >
> > > array([ 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.])
> > >
> > >This is Numeric 23.1 compiled on my AMD64!!! I ran the same tests on a
> > > 32bit P4 and it ran fine.
> > >Has anyone else seen this before?
> > >
> > >For those that didn't understand, the normal function as called above, is
> > >supposed to give me ten samples form a normal distribution with mean = 2
> > > and standard deviation = 2
> > >
> > >luckily:
> > >>>>>>> from numarray.random_array import *
> > >>>>>>>
> > >>>>>>>
> > >>>>>>>
> > >>>>>>>
> > >>>>>>>
> > >>>>>>> normal(2,2,10)
> > >
> > >array([-0.04525638, 4.31467819, -0.17468357, 5.29377031, 0.84202135,
> > > 5.29593539, 4.69651532, 1.61354655, 1.10839236, 1.7743317 ])
> > >
> > >If anybody still needed a reason for switching to numarray, there you go!
> > >
> > >I anybody here subscribes the numeric or numarray mailing lists (i.e. if
> > > they even exist) could you please forward this message to them?
> > >
> > >Flavio
> >
> > This message has been scanned but we cannot guarantee that it and any
> > attachments are free from viruses or other damaging content: you are
> > advised to perform your own checks. Email communications with the
> > University of Nottingham may be monitored as permitted by UK legislation.
> >
> >
> >
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> 
> 
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-- 

On Monday 04 October 2004 10:38 am, you wrote:
> On Monday 04 October 2004 00:58, Darren Dale wrote:
> > Would somebody kindly direct me to some information on how to deal with
> > dividing by zero? I am getting ValueError: math domain error, is there
> > anything I can do to return an inf instead?
> >
> > Thanks,
> >
> > Darren
>
> If you can't avoid the division by zero, you can handle the exception:
>
> try:
> a = x/0
> except ValueError:
> pass # or some other outcome (a = 'inf')
>
> as far as I know python does not have a representation for infinity. (if I
> am wrong, somebody please correct me)
There are some special representations that can be imported, for example
from numarray.ieeespecial import inf
However, My simulations require HEAVY array mathematics, so I dont have an 
opportunity to test for exceptions.
Darren

On Monday 04 October 2004 09:27, Jon Peirce wrote:
> On my AMD64 (using pre-compiled version as packaged by enthought) I get
>
> the expected results from RandomArray under Numeric ie:
> >>> from RandomArray import *
> >>> normal(2,2,10)
>
> array([-0.43560529, 2.67296922, 0.84804749, 4.26332831, 0.64425385,
> 3.43939352,
> 4.07021809, 3.6235764 , 2.93580639, 1.81101392])
>
> Jon
Jon,
was you pre compiled Numeric compile for amd64 or for x86?
I think this is a result of the compilation .
Flavio
>
> >Message: 3
> >From: =?iso-8859-1?q?Fl=E1vio_Code=E7o_Coelho?= <fcc...@fi...>
> >Organization: PROCC-Fiocruz
> >To: mat...@li...
> >Date: Fri, 1 Oct 2004 17:06:10 +0000
> >Subject: [Matplotlib-users] warning: Numeric and amd64
> >
> >Hi,
> >
> >look at this:
> >>>>>>> from RandomArray import *
> >>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>>> normal(2,2,10)
> >
> > array([ 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.])
> >
> >This is Numeric 23.1 compiled on my AMD64!!! I ran the same tests on a
> > 32bit P4 and it ran fine.
> >Has anyone else seen this before?
> >
> >For those that didn't understand, the normal function as called above, is
> >supposed to give me ten samples form a normal distribution with mean = 2
> > and standard deviation = 2
> >
> >luckily:
> >>>>>>> from numarray.random_array import *
> >>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>>> normal(2,2,10)
> >
> >array([-0.04525638, 4.31467819, -0.17468357, 5.29377031, 0.84202135,
> > 5.29593539, 4.69651532, 1.61354655, 1.10839236, 1.7743317 ])
> >
> >If anybody still needed a reason for switching to numarray, there you go!
> >
> >I anybody here subscribes the numeric or numarray mailing lists (i.e. if
> > they even exist) could you please forward this message to them?
> >
> >Flavio
>
> This message has been scanned but we cannot guarantee that it and any
> attachments are free from viruses or other damaging content: you are
> advised to perform your own checks. Email communications with the
> University of Nottingham may be monitored as permitted by UK legislation.
>
>
>
> -------------------------------------------------------
> This SF.net email is sponsored by: IT Product Guide on ITManagersJournal
> Use IT products in your business? Tell us what you think of them. Give us
> Your Opinions, Get Free ThinkGeek Gift Certificates! Click to find out more
> http://productguide.itmanagersjournal.com/guidepromo.tmpl
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

On my AMD64 (using pre-compiled version as packaged by enthought) I get 
the expected results from RandomArray under Numeric ie:
 >>> from RandomArray import *
 >>> normal(2,2,10)
array([-0.43560529, 2.67296922, 0.84804749, 4.26332831, 0.64425385, 
3.43939352,
 4.07021809, 3.6235764 , 2.93580639, 1.81101392])
Jon
>Message: 3
>From: =?iso-8859-1?q?Fl=E1vio_Code=E7o_Coelho?= <fcc...@fi...>
>Organization: PROCC-Fiocruz
>To: mat...@li...
>Date: Fri, 1 Oct 2004 17:06:10 +0000
>Subject: [Matplotlib-users] warning: Numeric and amd64
>
>Hi,
>
>look at this:
>
> 
>
>>>>>>> from RandomArray import *
>>>> 
>>>>
>
> 
>
>>>>>>> normal(2,2,10)
>>>> 
>>>>
> array([ 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.])
>
>This is Numeric 23.1 compiled on my AMD64!!! I ran the same tests on a 32bit 
>P4 and it ran fine.
>Has anyone else seen this before?
>
>For those that didn't understand, the normal function as called above, is 
>supposed to give me ten samples form a normal distribution with mean = 2 and 
>standard deviation = 2
>
>luckily:
>
> 
>
>>>>>>> from numarray.random_array import *
>>>> 
>>>>
>
> 
>
>>>>>>> normal(2,2,10)
>>>> 
>>>>
>array([-0.04525638, 4.31467819, -0.17468357, 5.29377031, 0.84202135,
> 5.29593539, 4.69651532, 1.61354655, 1.10839236, 1.7743317 ])
>
>If anybody still needed a reason for switching to numarray, there you go!
>
>I anybody here subscribes the numeric or numarray mailing lists (i.e. if they 
>even exist) could you please forward this message to them?
>
>Flavio
>
This message has been scanned but we cannot guarantee that it and any
attachments are free from viruses or other damaging content: you are
advised to perform your own checks. Email communications with the
University of Nottingham may be monitored as permitted by UK legislation.

Ok. Now suppose you write an application that runs a set of algorithms 
not known in advance. These algorithms may or may not create figures 
depending on what they perform; they may also encounter difficulties 
(e.g. not enough input data) so that none of them is finally able to 
create a figure. As this is always better to dissociate code pieces the 
more as possible, I'd prefer not to use a global variable to trace 
figure creation. So is there a way to know that no figure was created?
Regards.
JM.
jdh...@ac... wrote:
> Jean-Michel> It seems that show() hangs if no figure has been
> Jean-Michel> created before calling (under matplotlib 0.62.4). Am
> Jean-Michel> I wrong or is it an unexpected use of show() ?
> 
> show should be the last line of your script. It is expected to hang.
> It starts the GUI mainloop after which all processing is done in the
> GUI event handling (unless you are using threading).
> 
> See http://matplotlib.sf.net/faq.html#SHOW
> 
> JDH

Would somebody kindly direct me to some information on how to deal with 
dividing by zero? I am getting ValueError: math domain error, is there 
anything I can do to return an inf instead?
Thanks,
Darren