Robert Kern robert.kern at gmail.com writes:
On Wed, Sep 8, 2010 at 14:42, Chris Ball ceball at gmail.com wrote:
Robert Kern robert.kern at gmail.com writes:
...
a = numpy.array([1,2,3,4,5])
a.clip(2,None)
array([2, 2, 2, 2, 2], dtype=object)
I'm not sure why the returned array
On Thu, Sep 9, 2010 at 05:05, Chris Ball ceb...@gmail.com wrote:
Robert Kern robert.kern at gmail.com writes:
On Wed, Sep 8, 2010 at 14:42, Chris Ball ceball at gmail.com wrote:
Robert Kern robert.kern at gmail.com writes:
...
a = numpy.array([1,2,3,4,5])
a.clip(2,None)
array([2, 2,
Original Message
Subject:[Numpy-discussion] distutils
Date: Tue, 7 Sep 2010 12:12:58 -0700
From: Charles Doutriaux doutria...@llnl.gov
Reply-To: Discussion of Numerical Python numpy-discussion@scipy.org
To: Discussion of Numerical Python
On Tue, Sep 7, 2010 at 14:12, Charles Doutriaux doutria...@llnl.gov wrote:
Hi,
I'm using distutils to build extensions written in C.
I noticed that lately (it seems to be python 2.7 related) whenever I
touch 1 C file, ALL the C files are rebuilt.
Since I have a lot of C code, it takes a
Hi all,
NumPy currently makes extensive use of the DeprecationWarning
class to alert users when some feature is going to be withdrawn.
However, as of Python 2.7, the DeprecationWarning is silent by
default, see:
Yes, this is what I am computing. I am computing the pdf of a very high-
dimensional multivariate normal. Is there a specialized method to compute
this?
If you use cho_solve and cho_factor from scipy.linalg, you can proceed
like this:
cx = X - m
sqmahal =
Thu, 09 Sep 2010 18:18:29 +0200, Sturla Molden wrote:
[clip]
I hope the SciPy dev team can be persuaded to include a wrapper for
DTRTRS in the future. It is after all extremely useful for Mahalanobis
distances, and thus for any use of linear models in statistics.
I don't see reasons why not to
Clever and concise (and expect that it works), but isn't this less
efficient? Sorting is O(n*log(n)), while the code I gave is O(n).
Using argsort has the potential to use less memory, though.
On Tuesday, September 7, 2010, Zachary Pincus zachary.pin...@yale.edu wrote:
indices = argsort(a1)
Clever and concise (and expect that it works), but isn't this less
efficient? Sorting is O(n*log(n)), while the code I gave is O(n).
Using argsort has the potential to use less memory, though.
On Tuesday, September 7, 2010, Zachary Pincus zachary.pin...@yale.edu wrote:
indices = argsort(a1)
On Thu, Sep 9, 2010 at 15:59, Alexander Michael lxande...@gmail.com wrote:
Clever and concise (and expect that it works), but isn't this less
efficient? Sorting is O(n*log(n)), while the code I gave is O(n).
Using argsort has the potential to use less memory, though.
No, the code you gave is
I am looking for some reaally basic statistical tools. I have some
sample data, some sample weights for those measurements, and I want to
calculate a mean and a standard error of the mean.
Here are obvious places to look:
numpy
scipy.stats
statsmodels
It seems to me that numpy's mean and
Excerpts from cpblpublic's message of Thu Sep 09 22:22:05 -0400 2010:
I am looking for some reaally basic statistical tools. I have some
sample data, some sample weights for those measurements, and I want to
calculate a mean and a standard error of the mean.
Here are obvious places to look:
On Thu, Sep 9, 2010 at 10:22 PM, cpblpublic cpblpublic+nu...@gmail.com wrote:
I am looking for some reaally basic statistical tools. I have some
sample data, some sample weights for those measurements, and I want to
calculate a mean and a standard error of the mean.
Here are obvious places
Hello everyone,
My numpy based image processing toolbox has just had a new release: 0.5
New features are:
Distance transform
bwperim()
freeimage interface [borrowed and improved from scikits.image]
zernike moment computation
There were some fixes to the namespace (in particular,
On Thu, Sep 9, 2010 at 7:22 PM, cpblpublic cpblpublic+nu...@gmail.com wrote:
I am looking for some reaally basic statistical tools. I have some
sample data, some sample weights for those measurements, and I want to
calculate a mean and a standard error of the mean.
How about using a bootstrap?
On Thu, Sep 9, 2010 at 8:07 PM, Keith Goodman kwgood...@gmail.com wrote:
On Thu, Sep 9, 2010 at 7:22 PM, cpblpublic cpblpublic+nu...@gmail.com wrote:
I am looking for some reaally basic statistical tools. I have some
sample data, some sample weights for those measurements, and I want to
On Thu, Sep 9, 2010 at 11:32 PM, Keith Goodman kwgood...@gmail.com wrote:
On Thu, Sep 9, 2010 at 8:07 PM, Keith Goodman kwgood...@gmail.com wrote:
On Thu, Sep 9, 2010 at 7:22 PM, cpblpublic cpblpublic+nu...@gmail.com
wrote:
I am looking for some reaally basic statistical tools. I have some
I was, of course, just thinking of the incremental work of inverting
the initial argsort, but you are completely correct in pointing out
that the overall complexity is O(n*log(n)) either way. As it turns
out, both approaches run in the same amount of time for my problem.
Thanks,
Alex
On
On Thu, Sep 9, 2010 at 8:44 PM, josef.p...@gmail.com wrote:
On Thu, Sep 9, 2010 at 11:32 PM, Keith Goodman kwgood...@gmail.com wrote:
On Thu, Sep 9, 2010 at 8:07 PM, Keith Goodman kwgood...@gmail.com wrote:
On Thu, Sep 9, 2010 at 7:22 PM, cpblpublic cpblpublic+nu...@gmail.com
wrote:
I am
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