classmethod Laguerre.cast(series, domain=None, window=None) [source] Convert series to series of this class. The series is expected to be an instance of some polynomial series of one of the types supported by by the numpy.polynomial module, but could be some other class that supports the convert method. New in version 1.7.0. Parameters: series : series The series instance to be converted. domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where b

classmethod Laguerre.basis(deg, domain=None, window=None) [source] Series basis polynomial of degree deg. Returns the series representing the basis polynomial of degree deg. New in version 1.7.0. Parameters: deg : int Degree of the basis polynomial for the series. Must be >= 0. domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where beg and end are the endpoints of the domain. If None is given then the class domain is used. The default is Non

New in version 1.6.0. This module provides a number of objects (mostly functions) useful for dealing with Laguerre series, including a Laguerre class that encapsulates the usual arithmetic operations. (General information on how this module represents and works with such polynomials is in the docstring for its ?parent? sub-package, numpy.polynomial). Laguerre Class Laguerre(coef[, domain, window]) A Laguerre series class. Basics lagval(x, c[, tensor]) Evaluate a Laguerre series at point

The iterator object nditer, introduced in NumPy 1.6, provides many flexible ways to visit all the elements of one or more arrays in a systematic fashion. This page introduces some basic ways to use the object for computations on arrays in Python, then concludes with how one can accelerate the inner loop in Cython. Since the Python exposure of nditer is a relatively straightforward mapping of the C array iterator API, these ideas will also provide help working with array iteration from C or C++

Introduction The Simple Wrapper and Interface Generator (or SWIG) is a powerful tool for generating wrapper code for interfacing to a wide variety of scripting languages. SWIG can parse header files, and using only the code prototypes, create an interface to the target language. But SWIG is not omnipotent. For example, it cannot know from the prototype: double rms(double* seq, int n); what exactly seq is. Is it a single value to be altered in-place? Is it an array, and if so what is its leng

Array structure and data access These macros all access the PyArrayObject structure members. The input argument, arr, can be any PyObject * that is directly interpretable as a PyArrayObject * (any instance of the PyArray_Type and its sub-types). int PyArray_NDIM(PyArrayObject *arr) The number of dimensions in the array. npy_intp *PyArray_DIMS(PyArrayObject *arr) Returns a pointer to the dimensions/shape of the array. The number of elements matches the number of dimensions of the ar

Numpy binary files (NPY, NPZ) load(file[, mmap_mode, allow_pickle, ...]) Load arrays or pickled objects from .npy, .npz or pickled files. save(file, arr[, allow_pickle, fix_imports]) Save an array to a binary file in NumPy .npy format. savez(file, *args, **kwds) Save several arrays into a single file in uncompressed .npz format. savez_compressed(file, *args, **kwds) Save several arrays into a single file in compressed .npz format. The format of these binary file types is documented in h

See also Indexing Generating index arrays c_ Translates slice objects to concatenation along the second axis. r_ Translates slice objects to concatenation along the first axis. s_ A nicer way to build up index tuples for arrays. nonzero(a) Return the indices of the elements that are non-zero. where(condition, [x, y]) Return elements, either from x or y, depending on condition. indices(dimensions[, dtype]) Return an array representing the indices of a grid. ix_(*args) Construct an open m

iinfo.min Minimum value of given dtype.

iinfo.max Maximum value of given dtype.