numpy.core.defchararray.add(x1, x2) [source] Return element-wise string concatenation for two arrays of str or unicode. Arrays x1 and x2 must have the same shape. Parameters: x1 : array_like of str or unicode Input array. x2 : array_like of str or unicode Input array. Returns: add : ndarray Output array of string_ or unicode_, depending on input types of the same shape as x1 and x2.

ndarray.__abs__() <==> abs(x)

New in version 1.6.0. This module provides a number of objects (mostly functions) useful for dealing with HermiteE series, including a HermiteE 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). HermiteE Class HermiteE(coef[, domain, window]) An HermiteE series class. Basics hermeval(x, c[, tensor]) Evaluate an HermiteE series at p

numpy.binary_repr(num, width=None) [source] Return the binary representation of the input number as a string. For negative numbers, if width is not given, a minus sign is added to the front. If width is given, the two?s complement of the number is returned, with respect to that width. In a two?s-complement system negative numbers are represented by the two?s complement of the absolute value. This is the most common method of representing signed integers on computers [R16]. A N-bit two?s-com

MaskedArray.ctypes An object to simplify the interaction of the array with the ctypes module. This attribute creates an object that makes it easier to use arrays when calling shared libraries with the ctypes module. The returned object has, among others, data, shape, and strides attributes (see Notes below) which themselves return ctypes objects that can be used as arguments to a shared library. Parameters: None Returns: c : Python object Possessing attributes data, shape, strides, etc.

RandomState.wald(mean, scale, size=None) Draw samples from a Wald, or inverse Gaussian, distribution. As the scale approaches infinity, the distribution becomes more like a Gaussian. Some references claim that the Wald is an inverse Gaussian with mean equal to 1, but this is by no means universal. The inverse Gaussian distribution was first studied in relationship to Brownian motion. In 1956 M.C.K. Tweedie used the name inverse Gaussian because there is an inverse relationship between the t

dtype.name A bit-width name for this data-type. Un-sized flexible data-type objects do not have this attribute.

RandomState.pareto(a, size=None) Draw samples from a Pareto II or Lomax distribution with specified shape. The Lomax or Pareto II distribution is a shifted Pareto distribution. The classical Pareto distribution can be obtained from the Lomax distribution by adding 1 and multiplying by the scale parameter m (see Notes). The smallest value of the Lomax distribution is zero while for the classical Pareto distribution it is mu, where the standard Pareto distribution has location mu = 1. Lomax c

numpy.random.poisson(lam=1.0, size=None) Draw samples from a Poisson distribution. The Poisson distribution is the limit of the binomial distribution for large N. Parameters: lam : float or sequence of float Expectation of interval, should be >= 0. A sequence of expectation intervals must be broadcastable over the requested size. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case

dtype.num A unique number for each of the 21 different built-in types. These are roughly ordered from least-to-most precision.