On 25. aug. 2011, at 23.49, David Warde-Farley wrote:
On 2011-08-25, at 2:42 PM, Chris.Barker wrote:
On 8/24/11 9:22 AM, Anthony Scopatz wrote:
You can use Python pickling, if you do *not* have a requirement for:
I can't recall why, but it seem pickling of numpy arrays has been
On 25.08.2011, at 8:42PM, Chris.Barker wrote:
On 8/24/11 9:22 AM, Anthony Scopatz wrote:
You can use Python pickling, if you do *not* have a requirement for:
I can't recall why, but it seem pickling of numpy arrays has been
fragile and not very performant.
Hmm, the pure Python version
Hi,
as the subject says, the array_* comparison functions currently do not operate
on structured/record arrays. Pull request
https://github.com/numpy/numpy/pull/146
implements these comparisons.
There are two commits, differing in their interpretation whether two
arrays with different field
On 8/26/11 5:04 AM, Derek Homeier wrote:
Hmm, the pure Python version might be, but, I've used cPickle for a long time
and never noted any stability problems.
well, here is the NEP:
https://github.com/numpy/numpy/blob/master/doc/neps/npy-format.txt
It addresses the why's and hows of the
On Fri, Aug 26, 2011 at 07:04, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 25.08.2011, at 8:42PM, Chris.Barker wrote:
On 8/24/11 9:22 AM, Anthony Scopatz wrote:
You can use Python pickling, if you do *not* have a requirement for:
I can't recall why, but it seem pickling
Hello All,
I am trying to identify columns of a matrix that are perfectly collinear. It
is not that difficult to identify when two columns are identical are have zero
variance, but I do not know how to ID when the culprit is of a higher order.
i.e. columns 1 + 2 + 3 = column 4.
On Fri, Aug 26, 2011 at 1:10 PM, Mark Janikas mjani...@esri.com wrote:
Hello All,
I am trying to identify columns of a matrix that are perfectly collinear.
It is not that difficult to identify when two columns are identical are have
zero variance, but I do not know how to ID when the
I actually use the VIF when the design matrix can be inverted I do it the
quick and dirty way as opposed to the step regression:
1. Calc the correlation coefficient of the matrix (w/o the intercept)
2. Return the diagonal of the inversion of the correlation matrix in step 1.
Again, the
I wonder if my last statement is essentially the only answer... which I wanted
to avoid...
Should I just use combinations of the columns and try and construct the
corrcoef() (then ID whether NaNs are present), or use the condition number to
ID the singularity? I just wanted to avoid the
On Fri, Aug 26, 2011 at 7:41 PM, Mark Janikas mjani...@esri.com wrote:
I wonder if my last statement is essentially the only answer... which I
wanted to avoid...
Should I just use combinations of the columns and try and construct the
corrcoef() (then ID whether NaNs are present), or use the
On Fri, Aug 26, 2011 at 11:41 AM, Mark Janikas mjani...@esri.com wrote:
I wonder if my last statement is essentially the only answer... which I
wanted to avoid...
Should I just use combinations of the columns and try and construct the
corrcoef() (then ID whether NaNs are present), or use the
On Fri, Aug 26, 2011 at 1:41 PM, Mark Janikas mjani...@esri.com wrote:
I wonder if my last statement is essentially the only answer... which I
wanted to avoid...
Should I just use combinations of the columns and try and construct the
corrcoef() (then ID whether NaNs are present), or use the
Charles! That looks like it could be a winner! It looks like you always
choose the last column of the U matrix and ID the columns that have the same
values? It works when I add extra columns as well! BTW, sorry for my lack of
knowledge... but what was the point of the dot multiply at the
Regarding ufuncs and NA's, all the mechanics of handling NA from a
ufunc are in the PyUFunc_FromFuncAndData function, right? So the ufunc
creation docs don't have to be updated to include NA's?
-Chris JS
On Wed, Aug 24, 2011 at 7:08 PM, Mark Wiebe mwwi...@gmail.com wrote:
I've added C-API
On Fri, Aug 26, 2011 at 12:38 PM, Mark Janikas mjani...@esri.com wrote:
Charles! That looks like it could be a winner! It looks like you always
choose the last column of the U matrix and ID the columns that have the same
values? It works when I add extra columns as well! BTW, sorry for my
On Fri, Aug 26, 2011 at 11:47 AM, Christopher Jordan-Squire cjord...@uw.edu
wrote:
Regarding ufuncs and NA's, all the mechanics of handling NA from a
ufunc are in the PyUFunc_FromFuncAndData function, right? So the ufunc
creation docs don't have to be updated to include NA's?
That's
On Fri, Aug 26, 2011 at 2:57 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Fri, Aug 26, 2011 at 12:38 PM, Mark Janikas mjani...@esri.com wrote:
Charles! That looks like it could be a winner! It looks like you always
choose the last column of the U matrix and ID the columns that
On Thu, Aug 25, 2011 at 2:10 PM, Paul Menzel
paulepan...@users.sourceforge.net wrote:
is there an easy way to also save the indexes of an array (columns, rows
or both) when outputting it to a text file. For saving an array to a
file I only found `savetxt()` [1] which does not seem to have such
On Thu, Aug 25, 2011 at 2:23 PM, srean srean.l...@gmail.com wrote:
Hi,
I would like to know a bit about how the installation process works. Could
you point me to a resource. In particular I want to know how the site.cfg
configuration works. Is it numpy/scipy specific or is it standard with
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