From 30ee1d3526af8892e8e1c22e29f9d7be14881eba Mon Sep 17 00:00:00 2001 From: rgommers Date: Sun, 13 Mar 2011 17:10:36 +0800 Subject: DOC: update 1.6.0 release notes. Add headers for items to still be filled in. --- doc/release/1.6.0-notes.rst | 46 +++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 44 insertions(+), 2 deletions(-) (limited to 'doc/release') diff --git a/doc/release/1.6.0-notes.rst b/doc/release/1.6.0-notes.rst index 774b611e1..fdc020572 100644 --- a/doc/release/1.6.0-notes.rst +++ b/doc/release/1.6.0-notes.rst @@ -1,3 +1,6 @@ +Note: NumPy 1.6.0 is not yet released. + + ========================= NumPy 1.6.0 Release Notes ========================= @@ -29,8 +32,20 @@ the data type ``numpy.half``. Within Python, the type behaves similarly to half-float API. -Einstein summation convention evaluation function -------------------------------------------------- +New iterator +------------ + + + + +Legendre polynomials in ``numpy.polynomial`` +-------------------------------------------- + + + + +Fortran assumed shape array support in ``numpy.f2py`` +----------------------------------------------------- @@ -44,11 +59,38 @@ flat indices, applying boundary modes to the coordinates. ``numpy.slogdet`` : Compute the sign and (natural) logarithm of the determinant of an array. +``numpy.einsum`` : Evaluate the Einstein summation convention. Using the +Einstein summation convention, many common multi-dimensional array operations +can be represented in a simple fashion. This function provides a way compute +such summations. The best way to understand this function is to try the +examples below, which show how many common NumPy functions can be implemented +as calls to ``numpy.einsum``. + Changes ======= +Changes and improvements in the numpy core +------------------------------------------ + + + + +``numpy.distutils`` +------------------- + +Several new compilers are supported for building Numpy: the Portland Group +Fortran compiler on OS X, the PathScale compiler suite and the 64-bit Intel C +compiler on Linux. + + +``numpy.testing`` +----------------- + +The testing framework gained ``numpy.testing.assert_allclose``, which provides +a more convenient way to compare floating point arrays than +`assert_almost_equal`, `assert_approx_equal` and `assert_array_almost_equal`. Removed features -- cgit v1.2.1