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From: Darren D. <dd...@co...> - 2004-10-04 16:26:21
|
> > 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 |
From: Todd M. <jm...@st...> - 2004-10-04 16:08:42
|
On Mon, 2004-10-04 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. > > > > > > > > ------------------------------------------------------- > > 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 > > > ------------------------------------------------------- > 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 -- |
From: Darren D. <dd...@co...> - 2004-10-04 15:03:32
|
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 |
From: <fcc...@fi...> - 2004-10-04 14:43:28
|
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 |
From: Jon P. <Jon...@no...> - 2004-10-04 09:28:13
|
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. |
From: Jean-Michel P. <jea...@ir...> - 2004-10-04 06:44:16
|
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 |
From: Darren D. <dd...@co...> - 2004-10-04 00:58:44
|
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 |