Welcome to PyUblas’s documentation!

PyUblas solves one main difficulty of developing hybrid numerical codes in Python and C++: It integrates two major linear algebra libraries across the two languages, namely numpy and Boost.Ublas. In Python, you are working with native numpy arrays, whereas in C++, PyUblas lets you work with matrix and vector types immediately derived from and closely integrated with Ublas. And best of all: There’s no copying at the language boundary.

PyUblas is built using and meant to be used with Boost Python.

PyUblas also has its own web page.

Show me! I need examples!

Ok, here’s a simple sample extension:

#include <pyublas/numpy.hpp>

pyublas::numpy_vector<double> doublify(pyublas::numpy_vector<double> x)
  return 2*x;

  boost::python::def("doublify", doublify);

and some Python that uses it:

import numpy
import sample_ext
import pyublas # not explicitly used--but makes converters available

vec = numpy.ones((5,), dtype=float)
print vec
print sample_ext.doublify(vec)

and this is what gets printed:

[ 1.  1.  1.  1.  1.]
[ 2.  2.  2.  2.  2.]