[SciPy-user] How to Enable Delaunay Package

[Lorenzo Isella]

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())