record.flat a 1-d view of scalar

RandomState.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

MaskedArray.__nonzero__ x.__nonzero__() <==> x != 0

generic.round() Not implemented (virtual attribute) Class generic exists solely to derive numpy scalars from, and possesses, albeit unimplemented, all the attributes of the ndarray class so as to provide a uniform API. See also The

numpy.blackman(M) [source] Return the Blackman window. The Blackman window is a taper formed by using the first three terms of a summation of cosines. It was designed to have close to the minimal leakage possible. It is close to optimal, only slightly worse than a Kaiser window. 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 i

Aliases for functions which may be accelerated by Scipy. Scipy can be built to use accelerated or otherwise improved libraries for FFTs, linear algebra, and special functions. This module allows developers to transparently support these accelerated functions when scipy is available but still support users who have only installed Numpy. Linear algebra cholesky(a) Cholesky decomposition. det(a) Compute the determinant of an array. eig(a) Compute the eigenvalues and right eigenvectors of a sq

numpy.copyto(dst, src, casting='same_kind', where=None) Copies values from one array to another, broadcasting as necessary. Raises a TypeError if the casting rule is violated, and if where is provided, it selects which elements to copy. New in version 1.7.0. Parameters: dst : ndarray The array into which values are copied. src : array_like The array from which values are copied. casting : {?no?, ?equiv?, ?safe?, ?same_kind?, ?unsafe?}, optional Controls what kind of data casting may

numpy.ma.around = Round an array to the given number of decimals. Refer to around for full documentation. See also around equivalent function

In addition to the MaskedArray class, the numpy.ma module defines several constants. numpy.ma.masked The masked constant is a special case of MaskedArray, with a float datatype and a null shape. It is used to test whether a specific entry of a masked array is masked, or to mask one or several entries of a masked array: >>> x = ma.array([1, 2, 3], mask=[0, 1, 0]) >>> x[1] is ma.masked True >>> x[-1] = ma.masked >>> x masked_array(data = [1 -- --],

numpy.polynomial.legendre.legx = array([0, 1])