Hi,
I see the desire for stylistic improvement by removing the awkward
parens but your correction has incorrect grammar. One cannot have
arrays of Python, nor are Numpy objects a subset of Python
(because Python is not a set) -- both of which are what your sentence
technically states. I.e., the
page at our wiki for platform-specific details:
http://pydstool.sourceforge.net
Please use the bug tracker and user discussion list at Sourceforge to
report bugs or provide feedback. Code and documentation contributions
are always welcome.
Regards,
Rob Clewley
David,
I'm confused about your reply. I don't think Ruben was only asking why
you'd ever get non-zero error after the forward and inverse transform,
but why his implementation using lists gives zero error but using
arrays he gets something of order 1e-15.
On Mon, Apr 20, 2009 at 9:47 AM, David
On Mon, Apr 20, 2009 at 10:48 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Rob Clewley wrote:
David,
I'm confused about your reply. I don't think Ruben was only asking why
you'd ever get non-zero error after the forward and inverse transform,
but why his implementation using
(pydstool.sourceforge.net) is a multi-platform, open-source
environment offering a range of library tools and utilities for
research in dynamical systems modeling for scientists and engineers.
Please contact Dr. Rob Clewley (rclewley) at (@) the Department of
Mathematics, Georgia State University (gsu.edu
the tutorial
and wiki documentation, or to the code itself, please contact me.
-Rob Clewley
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On Thu, Nov 13, 2008 at 6:32 PM, Egor Zindy [EMAIL PROTECTED] wrote:
To get my head round the numpy.i interface for SWIG, I wrote some simple
examples and documented them as much as possible. The result is here:
Awesome. That will be very helpful to me, and I'm sure to others too.
I know some
Maybe we should focus on writing a decent 'deriv' function then. I
know Konrad Hinsen's Scientific had a derivatives package
(Scientific.Functions.Derivatives) that implemented automatic
differentiation:
http://en.wikipedia.org/wiki/Automatic_differentiation
That would be great, but
2008/10/29 Fernando Perez [EMAIL PROTECTED]:
I think it's fine to ask for functions that compute higher order
derivatives of n-d arrays: we already have diff(), which operates on a
single direction, and a hessian could make sense (with the caveats
David points out). But with higher order
In your experience, is this functionality enough to start a separate
package, or should we try to include it somewhere else? Otherwise we
could think of a new SciKit.
I confess to knowing no details about scikits so I don't know what the
difference really is between a new package and a
Hi Andrea,
I was wondering if someone had any suggestions/references/snippets
of code on how to find the minimum distance between 2 paths in 3D.
Basically, for every path, I have I series of points (x, y, z) and I
would like to know if there is a better way, other than comparing
point by
for model analysis
* Improved interface for legacy C and Fortran code (numerical
integrators) via some combination of SWIG, Scons, automake
* Overhaul of support for symbolic processing (probably by an
interface to SymPy)
For more details please contact Dr. Rob Clewley (rclewley) at (@) the
Department
IMO the Modular toolkit for Data Processing (MDP) has a fairly good
and straightforward PCA implementation, among other good tools:
mdp-toolkit.sourceforge.net/
I have no idea what apt-get is, though, so I don't know if this will
be helpful or not!
-Rob
On 21/06/07, Alex Torquato S. Carneiro
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