Re: [Numpy-discussion] Bug in the F distribution?

2009-07-06 Thread Alan Jackson
>On Fri, Jul 3, 2009 at 10:21 PM, Alan Jackson wrote: >> > >I don't see any problem here. If you can replicate your results, we >would need more information about the versions. > >Josef > >''' >>>> np.version.version >

Re: [Numpy-discussion] Bug in the F distribution?

2009-07-03 Thread Alan Jackson
I've tried the same scheme using R and it seems to give the right answers > quantile( rf(1000,10,10), .99) 99% 4.84548 > quantile( rf(1000,11,10), .99) 99% 4.770002 > quantile( rf(1000,11,11), .99) 99% 4.465655 > quantile( rf(1000,10,11), .99) 99% 4.539423

[Numpy-discussion] Bug in the F distribution?

2009-07-03 Thread Alan Jackson
I either found a bug in the F distribution, or I'm really messed up. >From a table I find dfnum dfden F(P<.01) 10 10 4.85 11 10 4.78 11 11 4.46 10 11 4.54 So let's calculate the same quantities using numpy... import scipy.stats as stats import numpy as np I

Re: [Numpy-discussion] PEP: named axis

2009-02-06 Thread Alan Jackson
On Thu, 05 Feb 2009 22:17:54 -0600 Travis Oliphant wrote: > Gael Varoquaux wrote: > > On Thu, Feb 05, 2009 at 05:08:49PM -0600, Travis E. Oliphant wrote: > > > >> I've been fairly quiet on this list for awhile due to work and family > >> schedule, but I think about how things can improve regu

Re: [Numpy-discussion] Please don't use google code for hosting

2009-01-16 Thread Alan Jackson
On Fri, 16 Jan 2009 19:24:56 -0500 "Kevin Jacobs " wrote: > On Fri, Jan 16, 2009 at 7:07 PM, Matthew Brett wrote: > > > So, please, if you are considering google code for hosting, consider > > other options. > > > > Seems odd that you'd post that from a gmail account. I do sympathize with > yo

Re: [Numpy-discussion] array gymnastics

2008-09-11 Thread Alan Jackson
gt; מאת: [EMAIL PROTECTED] בשם Brent Pedersen > נשלח: ו 12-ספטמבר-08 04:19 > אל: Discussion of Numerical Python > נושא: Re: [Numpy-discussion] array gymnastics > > On Thu, Sep 11, 2008 at 6:03 PM, Alan Jackson <[EMAIL PROTECTED]> wrote: > > There has got to be a

[Numpy-discussion] array gymnastics

2008-09-11 Thread Alan Jackson
There has got to be a simple way to do this, but I'm just not seeing it. >>> a = array([[1,2,3,4,5,6], [7,8,9,10,11,12]]) >>> b = array([21,22,23,24,25,26]) What I want to end up with is : c = array([[1,7,21], [2,8,22], .. [6,12,26]]) -- ---

Re: [Numpy-discussion] at my wits end over an error message...

2008-08-30 Thread Alan Jackson
Thanks. I'm still struggling with learning the idiom. Too much perl to unlearn. 8-) On Sat, 30 Aug 2008 23:10:10 -0400 Zachary Pincus <[EMAIL PROTECTED]> wrote: > Hi Alan, > > > Traceback (most recent call last): > > File "/usr/local/lib/python2.5/site-packages/enthought.traits-2.0.4- > > py2.

[Numpy-discussion] at my wits end over an error message...

2008-08-30 Thread Alan Jackson
I been beating myself up over this bit of code for far too long now - I know I must be missing something really simple, but what is it? TYPICALLY_UINT_COLUMNS = ['Track', 'Bin', 'code', 'horizon'] .. dtypes = [ ] for i in range(0, len(self.var_list)) : if TYPICALLY_

Re: [Numpy-discussion] Advice on converting iterator into array efficiently

2008-08-29 Thread Alan Jackson
I tested all three offered solutions : t = table[:] # convert to structured array collections = np.unique(t['collection']) for collection in collections: cond = t['collection'] == collection energy_this_collection = t['energy'][cond] -- energies = {} for ro

[Numpy-discussion] Advice on converting iterator into array efficiently

2008-08-28 Thread Alan Jackson
Looking for advice on a good way to handle this problem. I'm dealing with large tables (Gigabyte large). I would like to efficiently subset values from one column based on the values in another column, and get arrays out of the operation. For example, say I have 2 columns, "energy" and "collectio

[Numpy-discussion] Questions about some of the random functions

2008-08-15 Thread Alan Jackson
Just a question - I'm gradually working through the distributions for the documentation marathon and I realised that there is a whole nest of them named "standard-". For several (e.g., normal) they are just the regular distribution with all the parameters except size set to "standard" values.

Re: [Numpy-discussion] Switching to nose test framework (was: NumpyTest problem)

2008-06-13 Thread Alan Jackson
On Fri, 13 Jun 2008 15:21:11 +0200 Gael Varoquaux <[EMAIL PROTECTED]> wrote: > On Thu, Jun 12, 2008 at 02:51:51AM +0200, Stéfan van der Walt wrote: > > > Build instructions don't really belong in docstrings. Put it in the > > > README.txt or DEV_README.txt. > > > No, but running the tests is some