Hi all,
Where can I find some sophisticated examples for the usage
of numpy.genfromtxt ?
Nils
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A Tuesday 20 January 2009, Andrew Collette escrigué:
Hi Francesc,
Looks like a cool project! However, I'm not able to achieve the
advertised speed-ups. I wrote a simple script to try three
approaches to this kind of problem:
1) Native Python code (i.e. will try to do everything at once
On Mon, Jan 19, 2009 at 11:20 AM, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
Do you also know how the situation is with sourceforge/launchpad/trac...
and other popular hosting systems ?
Do they also have these restrictions ?
I've not noticed any problems with sourceforge, nor
Works much, much better with the current svn version. :) Numexpr now
outperforms everything except the simple technique, and then only
for small data sets.
Along the lines you mentioned I noticed that simply changing from a
shape of (100*100*100,) to (100, 100, 100) results in nearly a factor
of
Till I write some proper doc, you can check the examples in tests/
test_io (TestFromTxt suitcase)
On Jan 20, 2009, at 4:17 AM, Nils Wagner wrote:
Hi all,
Where can I find some sophisticated examples for the usage
of numpy.genfromtxt ?
Nils
Hello,
last year there has been a discussion on this on the OSGEO list about
the same issue.
You may check oggeo.discuss at Gmane or Nabble for it.
Kind regards,
Timmie
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On Mon, Jan 19, 2009 at 12:26, Tim Michelsen
timmichel...@gmx-topmail.de wrote:
Hello,
last year there has been a discussion on this on the OSGEO list about
the same issue.
You may check oggeo.discuss at Gmane or Nabble for it.
I must say that Wilfred L. Guerin's opinions on the subject were
I tried a little experiment, implementing some code in numpy (usually I
build modules in c++ to interface to python). Since these operations are
all large vectors, I hoped it would be reasonably efficient.
The code in question is simple. It is a model of an amplifier, modeled by
it's AM/AM
2009/1/20 Neal Becker ndbeck...@gmail.com:
I tried a little experiment, implementing some code in numpy (usually I
build modules in c++ to interface to python). Since these operations are
all large vectors, I hoped it would be reasonably efficient.
The code in question is simple. It is a
2009/1/20 Neal Becker ndbeck...@gmail.com:
I tried a little experiment, implementing some code in numpy (usually I
build modules in c++ to interface to python). Since these operations are
all large vectors, I hoped it would be reasonably efficient.
The code in question is simple. It is a
Robert Kern wrote:
2009/1/20 Neal Becker ndbeck...@gmail.com:
I tried a little experiment, implementing some code in numpy (usually I
build modules in c++ to interface to python). Since these operations are
all large vectors, I hoped it would be reasonably efficient.
The code in question
On Tue, Jan 20, 2009 at 20:44, Neal Becker ndbeck...@gmail.com wrote:
Robert Kern wrote:
2009/1/20 Neal Becker ndbeck...@gmail.com:
I tried a little experiment, implementing some code in numpy (usually I
build modules in c++ to interface to python). Since these operations are
all large
Robert Kern wrote:
2009/1/20 Neal Becker ndbeck...@gmail.com:
I tried a little experiment, implementing some code in numpy (usually I
build modules in c++ to interface to python). Since these operations are
all large vectors, I hoped it would be reasonably efficient.
The code in question
On Tue, Jan 20, 2009 at 20:57, Neal Becker ndbeck...@gmail.com wrote:
I see the problem. Thanks for the great profiler! You ought to make this
more widely known.
I'll be making a release shortly.
It seems the big chunks of time are used in data conversion between numpy
and my own vectors
On Tue, Jan 20, 2009 at 6:57 PM, Neal Becker ndbeck...@gmail.com wrote:
It seems the big chunks of time are used in data conversion between numpy
and my own vectors classes. Mine are wrappers around boost::ublas. The
conversion must be falling back on a very inefficient method since there is
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