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

MaskedArray.__xor__ x.__xor__(y) <==> x^y

MaskedArray.__array_wrap__(obj, context=None) [source] Special hook for ufuncs. Wraps the numpy array and sets the mask according to context.

recarray.nbytes Total bytes consumed by the elements of the array. Notes Does not include memory consumed by non-element attributes of the array object. Examples >>> x = np.zeros((3,5,2), dtype=np.complex128) >>> x.nbytes 480 >>> np.prod(x.shape) * x.itemsize 480

ndarray.cumsum(axis=None, dtype=None, out=None) Return the cumulative sum of the elements along the given axis. Refer to numpy.cumsum for full documentation. See also numpy.cumsum equivalent function

numpy.obj2sctype(rep, default=None) [source] Return the scalar dtype or NumPy equivalent of Python type of an object. Parameters: rep : any The object of which the type is returned. default : any, optional If given, this is returned for objects whose types can not be determined. If not given, None is returned for those objects. Returns: dtype : dtype or Python type The data type of rep. See also sctype2char, issctype, issubsctype, issubdtype, maximum_sctype Examples >>>

numpy.ma.outer(a, b) [source] Compute the outer product of two vectors. Given two vectors, a = [a0, a1, ..., aM] and b = [b0, b1, ..., bN], the outer product [R50] is: [[a0*b0 a0*b1 ... a0*bN ] [a1*b0 . [ ... . [aM*b0 aM*bN ]] Parameters: a : (M,) array_like First input vector. Input is flattened if not already 1-dimensional. b : (N,) array_like Second input vector. Input is flattened if not already 1-dimensional. out : (M, N) ndarray, optional A location w

ndarray.__long__() <==> long(x)