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

numpy.core.defchararray.capitalize(a) [source] Return a copy of a with only the first character of each element capitalized. Calls str.capitalize element-wise. For 8-bit strings, this method is locale-dependent. Parameters: a : array_like of str or unicode Input array of strings to capitalize. Returns: out : ndarray Output array of str or unicode, depending on input types See also str.capitalize Examples >>> c = np.array(['a1b2','1b2a','b2a1','2a1b'],'S4'); c array(['a1b2

ndarray.__isub__ x.__isub__(y) <==> x-=y

ndarray.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None) Return the sum along diagonals of the array. Refer to numpy.trace for full documentation. See also numpy.trace equivalent function

numpy.insert(arr, obj, values, axis=None) [source] Insert values along the given axis before the given indices. Parameters: arr : array_like Input array. obj : int, slice or sequence of ints Object that defines the index or indices before which values is inserted. New in version 1.8.0. Support for multiple insertions when obj is a single scalar or a sequence with one element (similar to calling insert multiple times). values : array_like Values to insert into arr. If the type of val

ndarray.real The real part of the array. See also numpy.real equivalent function Examples >>> x = np.sqrt([1+0j, 0+1j]) >>> x.real array([ 1. , 0.70710678]) >>> x.real.dtype dtype('float64')

ndarray.__mod__ x.__mod__(y) <==> x%y

numpy.random.gumbel(loc=0.0, scale=1.0, size=None) Draw samples from a Gumbel distribution. Draw samples from a Gumbel distribution with specified location and scale. For more information on the Gumbel distribution, see Notes and References below. Parameters: loc : float The location of the mode of the distribution. scale : float The scale parameter of the distribution. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples a

numpy.fft.rfftn(a, s=None, axes=None, norm=None) [source] Compute the N-dimensional discrete Fourier Transform for real input. This function computes the N-dimensional discrete Fourier Transform over any number of axes in an M-dimensional real array by means of the Fast Fourier Transform (FFT). By default, all axes are transformed, with the real transform performed over the last axis, while the remaining transforms are complex. Parameters: a : array_like Input array, taken to be real. s

numpy.fft.ifft2(a, s=None, axes=(-2, -1), norm=None) [source] Compute the 2-dimensional inverse discrete Fourier Transform. This function computes the inverse of the 2-dimensional discrete Fourier Transform over any number of axes in an M-dimensional array by means of the Fast Fourier Transform (FFT). In other words, ifft2(fft2(a)) == a to within numerical accuracy. By default, the inverse transform is computed over the last two axes of the input array. The input, analogously to ifft, shoul