I am pleased to announce the availability of NumPy 1.5.0. This is the first NumPy release to include support for Python 3, as well as for Python 2.7.
Binaries, sources, documentation and release notes can be found at https://sourceforge.net/projects/numpy/files/. Thank you to everyone who contributed to this release. Enjoy, the Numpy developers ========================= NumPy 1.5.0 Release Notes ========================= Highlights ========== Python 3 compatibility ---------------------- This is the first NumPy release which is compatible with Python 3. Support for Python 3 and Python 2 is done from a single code base. Extensive notes on changes can be found at `<http://projects.scipy.org/numpy/browser/trunk/doc/Py3K.txt>`_. Note that the Numpy testing framework relies on nose, which does not have a Python 3 compatible release yet. A working Python 3 branch of nose can be found at `<http://bitbucket.org/jpellerin/nose3/>`_ however. Porting of SciPy to Python 3 is expected to be completed soon. :pep:`3118` compatibility ------------------------- The new buffer protocol described by PEP 3118 is fully supported in this version of Numpy. On Python versions >= 2.6 Numpy arrays expose the buffer interface, and array(), asarray() and other functions accept new-style buffers as input. New features ============ Warning on casting complex to real ---------------------------------- Numpy now emits a `numpy.ComplexWarning` when a complex number is cast into a real number. For example: >>> x = np.array([1,2,3]) >>> x[:2] = np.array([1+2j, 1-2j]) ComplexWarning: Casting complex values to real discards the imaginary part The cast indeed discards the imaginary part, and this may not be the intended behavior in all cases, hence the warning. This warning can be turned off in the standard way: >>> import warnings >>> warnings.simplefilter("ignore", np.ComplexWarning) Dot method for ndarrays ----------------------- Ndarrays now have the dot product also as a method, which allows writing chains of matrix products as >>> a.dot(b).dot(c) instead of the longer alternative >>> np.dot(a, np.dot(b, c)) linalg.slogdet function ----------------------- The slogdet function returns the sign and logarithm of the determinant of a matrix. Because the determinant may involve the product of many small/large values, the result is often more accurate than that obtained by simple multiplication. new header ---------- The new header file ndarraytypes.h contains the symbols from ndarrayobject.h that do not depend on the PY_ARRAY_UNIQUE_SYMBOL and NO_IMPORT/_ARRAY macros. Broadly, these symbols are types, typedefs, and enumerations; the array function calls are left in ndarrayobject.h. This allows users to include array-related types and enumerations without needing to concern themselves with the macro expansions and their side- effects. Changes ======= polynomial.polynomial --------------------- * The polyint and polyder functions now check that the specified number integrations or derivations is a non-negative integer. The number 0 is a valid value for both functions. * A degree method has been added to the Polynomial class. * A trimdeg method has been added to the Polynomial class. It operates like truncate except that the argument is the desired degree of the result, not the number of coefficients. * Polynomial.fit now uses None as the default domain for the fit. The default Polynomial domain can be specified by using [] as the domain value. * Weights can be used in both polyfit and Polynomial.fit * A linspace method has been added to the Polynomial class to ease plotting. * The polymulx function was added. polynomial.chebyshev -------------------- * The chebint and chebder functions now check that the specified number integrations or derivations is a non-negative integer. The number 0 is a valid value for both functions. * A degree method has been added to the Chebyshev class. * A trimdeg method has been added to the Chebyshev class. It operates like truncate except that the argument is the desired degree of the result, not the number of coefficients. * Chebyshev.fit now uses None as the default domain for the fit. The default Chebyshev domain can be specified by using [] as the domain value. * Weights can be used in both chebfit and Chebyshev.fit * A linspace method has been added to the Chebyshev class to ease plotting. * The chebmulx function was added. * Added functions for the Chebyshev points of the first and second kind. histogram --------- After a two years transition period, the old behavior of the histogram function has been phased out, and the "new" keyword has been removed. correlate --------- The old behavior of correlate was deprecated in 1.4.0, the new behavior (the usual definition for cross-correlation) is now the default. 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