SciPy is a scientific package that includes tools for Fourier transforms, optimization, linear algebra, image and signal processing, as well as statistics and ODE solvers.
It is a library depending on NumPy that provides fast and convenient N-dimensional array manipulation.
SciPy and NumPy run on all popular operating systems, they are free and very easy to install.
Requirements:
· Numpy
· Python 2.4 or later
What's New in This Release: [ read full changelog ]
New features:
· ``scipy.spatial`` improvements
· cKDTree feature-complete
· Cython version of KDTree, cKDTree, is now feature-complete.Most operations
· (construction, query, query_ball_point, query_pairs, count_neighbors and
· sparse_distance_matrix) are between 200 and 1000 times faster in cKDTree than
· in KDTree.With very minor caveats, cKDTree has exactly the same interface as
· KDTree, and can be used as a drop-in replacement.
Voronoi diagrams and convex hulls:
· `scipy.spatial` now contains functionality for computing Voronoi
· diagrams and convex hulls using the Qhull library. (Delaunay
· triangulation was available since Scipy 0.9.0.)
Delaunay improvements:
· It's now possible to pass in custom Qhull options in Delaunay
· triangulation. Coplanar points are now also recorded, if present.
· Incremental construction of Delaunay triangulations is now also
· possible.
Spectral estimators (``scipy.signal``):
· The functions ``scipy.signal.periodogram`` and ``scipy.signal.welch`` were
· added, providing DFT-ba...