How to Enable Delaunay Package
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())
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
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
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).
VTK can do a Delaunay triangularization, but it will not do the natural neighbor interpolation, which is what the OP is ultimately trying to do. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco
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
Since there is now an unstable branch of the eggs repository, would it be entirely unreasonable to suggest to provide eggs for the sandboxed modules? Actually, it might make sense, since its so easy to update these... -jelle
jelle wrote:
Since there is now an unstable branch of the eggs repository, would it be entirely unreasonable to suggest to provide eggs for the sandboxed modules?
Whose egg repository?
Actually, it might make sense, since its so easy to update these...
Not as long as scipy is a monolithic package, no. Better to move the independent sandboxed packages out to scikits so they can each be installed by themselves. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco
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?
You will have to rebuild. Follow the instructions here:
# 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 :-)
-- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco
participants (5)
-
Dominik Szczerba -
Gabriel Gellner -
jelle -
Lorenzo Isella -
Robert Kern