[SciPy-user] How to Enable Delaunay Package

Dominik Szczerba domi@vision.ee.ethz...
Tue Jun 26 17:35:20 CDT 2007


Go the the VTK online documentation, there is plenty of python examples.
- Dominik

Gabriel Gellner wrote:
> Could you give a quick example?
> I would love to have a second way of doing this. . .
> 
> Gabriel
> 
> On Tue, Jun 26, 2007 at 10:05:23PM +0200, Dominik Szczerba wrote:
>> I use VTK for this purpose (there are python bindings).
>> - Dominik
>>
>> Lorenzo Isella wrote:
>>> Dear All,
>>> I am posting this after a discussion originated on the matplotlib 
>>> mailing list.
>>> Fundamentally, I need to plot data on irregular (i.e. non equi-spaced 
>>> rectangular) grids.
>>> I finally was recommended to look at the Delaunay package (see approach2 
>>> at the link:  
>>>
>>> http://scipy.org/Cookbook/Matplotlib/Gridding_irregularly_spaced_data
>>> ).
>>>
>>> The problem is that the approach:
>>>
>>> from scipy.sandbox.delaunay import *
>>>
>>> does not work (the system does not find the requested module).
>>>
>>> Now, I am running Debian testing on my box and I have Python2.3,2.4,2.5 
>>> installed beside SciPy as taken from the standard repositories.
>>> Under /usr/lib/python2.4/site-packages/scipy/sandbox I have the file 
>>> setup.py which I copy and paste at the end of the email.
>>> I try uncommenting the line dealing with Delaunay, but that did not help 
>>> me out (probably it is useful only if I am rebuilding SciPy, which I 
>>> would like to avoid).
>>> Anyone has experienced the same problem or has any suggestions?
>>> I am really in need to get this working in order to be able to perform 
>>> some non-trivial data plotting with matplotlib.
>>> Many thanks
>>>
>>> Lorenzo
>>>
>>>
>>>
>>>
>>> import os
>>>
>>> def configuration(parent_package='',top_path=None):
>>>     from numpy.distutils.misc_util import Configuration
>>>     config = Configuration('sandbox',parent_package,top_path)
>>>
>>>     sandbox_packages = []
>>>     try:
>>>         sandbox_file = open(os.path.join(config.package_path,
>>>                                          'enabled_packages.txt'), 'rU')
>>>     except IOError:
>>>         pass
>>>     else:
>>>         for line in sandbox_file:
>>>             p = line.strip()
>>>             if line.startswith('#'):
>>>                 continue
>>>             sandbox_packages.append(p)
>>>         sandbox_file.close()
>>>
>>>     for p in sandbox_packages:
>>>         config.add_subpackage(p)
>>>
>>>     # All subpackages should be commented out in the version
>>>     # committed to the repository. This prevents build problems
>>>     # for people who are not actively working with these
>>>     # potentially unstable packages.
>>>
>>>     # You can put a list of modules you want to always enable in the
>>>     # file 'enabled_packages.txt' in this directory (you'll have to 
>>> create it).
>>>     # Since this isn't under version control, it's less likely you'll
>>>     # check it in and screw other people up :-)
>>>
>>>     # An example package:
>>>     #config.add_subpackage('exmplpackage')
>>>
>>>     # Monte Carlo package
>>>     #config.add_subpackage('montecarlo')
>>>
>>>     # PySparse fork with NumPy compatibility
>>>     #config.add_subpackage('pysparse')
>>>
>>>     # Robert Kern's corner:
>>>     #config.add_subpackage('rkern')
>>>
>>>     # ODRPACK
>>>     #config.add_subpackage('odr')
>>>
>>>     # Delaunay triangulation and Natural Neighbor interpolation
>>>     config.add_subpackage('delaunay')
>>>
>>>     # Gist-based plotting library for X11
>>>     #config.add_subpackage('xplt')
>>>
>>>     # elementwise numerical expressions
>>>     #config.add_subpackage('numexpr')
>>>
>>>     # Statistical models
>>>     #config.add_subpackage('models')
>>>
>>>     # Adaptation of Scientific.IO (2.4.9) to use NumPy
>>>     #config.add_subpackage('netcdf')
>>>
>>>     # Finite Difference Formulae package
>>>     #config.add_subpackage('fdfpack')
>>>
>>>     # Package with useful constants and unit-conversions defined
>>>     #config.add_subpackage('constants')
>>>
>>>     # Interpolating between sparse samples
>>>     #config.add_subpackage('buildgrid')
>>>
>>>     # Package for Support Vector Machine
>>>     #config.add_subpackage('svm')
>>>
>>>     # Package for Gaussian Mixture Models
>>>     #config.add_subpackage('pyem')
>>>
>>>     # David Cournapeau's corner: autocorrelation, lpc, lpc residual
>>>     #config.add_subpackage('cdavid')
>>>
>>>     # New spline package (based on scipy.interpolate)
>>>     #config.add_subpackage('spline')
>>>
>>>     return config
>>>
>>> if __name__ == '__main__':
>>>     from numpy.distutils.core import setup
>>>     setup(**configuration(top_path='').todict())
>>>
>>>
>>>
>>>
>>> _______________________________________________
>>> SciPy-user mailing list
>>> SciPy-user@scipy.org
>>> http://projects.scipy.org/mailman/listinfo/scipy-user
>> -- 
>> Dominik Szczerba, Ph.D.
>> Computer Vision Lab CH-8092 Zurich
>> http://www.vision.ee.ethz.ch/~domi
>> _______________________________________________
>> SciPy-user mailing list
>> SciPy-user@scipy.org
>> http://projects.scipy.org/mailman/listinfo/scipy-user
> _______________________________________________
> SciPy-user mailing list
> SciPy-user@scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user

-- 
Dominik Szczerba, Ph.D.
Computer Vision Lab CH-8092 Zurich
http://www.vision.ee.ethz.ch/~domi


More information about the SciPy-user mailing list