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

Standard FFTs fft(a[, n, axis, norm]) Compute the one-dimensional discrete Fourier Transform. ifft(a[, n, axis, norm]) Compute the one-dimensional inverse discrete Fourier Transform. fft2(a[, s, axes, norm]) Compute the 2-dimensional discrete Fourier Transform ifft2(a[, s, axes, norm]) Compute the 2-dimensional inverse discrete Fourier Transform. fftn(a[, s, axes, norm]) Compute the N-dimensional discrete Fourier Transform. ifftn(a[, s, axes, norm]) Compute the N-dimensional inverse dis

record.imag imaginary part of scalar

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.

numpy.clip(a, a_min, a_max, out=None) [source] Clip (limit) the values in an array. Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1. Parameters: a : array_like Array containing elements to clip. a_min : scalar or array_like Minimum value. a_max : scalar or array_like Maximum value. If a_min or a_max are array_like, then they will be br

MaskedArray.__truediv__(other) [source] Divide other into self, and return a new masked array.

numpy.fft.ifft(a, n=None, axis=-1, norm=None) [source] Compute the one-dimensional inverse discrete Fourier Transform. This function computes the inverse of the one-dimensional n-point discrete Fourier transform computed by fft. In other words, ifft(fft(a)) == a to within numerical accuracy. For a general description of the algorithm and definitions, see numpy.fft. The input should be ordered in the same way as is returned by fft, i.e., a[0] should contain the zero frequency term, a[1:n//

chararray.find(sub, start=0, end=None) [source] For each element, return the lowest index in the string where substring sub is found. See also char.find

numpy.hamming(M) [source] Return the Hamming window. The Hamming window is a taper formed by using a weighted cosine. Parameters: M : int Number of points in the output window. If zero or less, an empty array is returned. Returns: out : ndarray The window, with the maximum value normalized to one (the value one appears only if the number of samples is odd). See also bartlett, blackman, hanning, kaiser Notes The Hamming window is defined as The Hamming was named for R. W. Hammin

numpy.polynomial.legendre.leggrid3d(x, y, z, c) [source] Evaluate a 3-D Legendre series on the Cartesian product of x, y, and z. This function returns the values: where the points (a, b, c) consist of all triples formed by taking a from x, b from y, and c from z. The resulting points form a grid with x in the first dimension, y in the second, and z in the third. The parameters x, y, and z are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars.