There is a general need for looping over not only functions on scalars but also over functions on vectors (or arrays). This concept is realized in Numpy by generalizing the universal functions (ufuncs)

Background The API exposed by NumPy for third-party extensions has grown over years of releases, and has allowed programmers to directly access NumPy functionality from

New in version 1.6. Array Iterator The array iterator encapsulates many

Several new types are defined in the C-code. Most of these are accessible from Python, but a few are not exposed due to their limited use. Every new Python type has an associated PyObject *

When NumPy is built, information about system configuration is recorded, and is made available for extension modules using Numpy?s C API. These are mostly defined in numpyconfig.h (included

Array structure and data access These macros all access the

Constants UFUNC_ERR_{HANDLER} {HANDLER} can be IGNORE, WARN,

The standard array can have 24 different data types (and has some support for adding your own types). These data types all have an enumerated type, an enumerated type-character, and a corresponding

New in version 1.3.0. Starting from numpy 1.3.0, we are working on separating the pure C, ?computational? code from the