record.argsort() 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

record.strides tuple of bytes steps in each dimension

MaskedArray.nonzero() [source] Return the indices of unmasked elements that are not zero. Returns a tuple of arrays, one for each dimension, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values can be obtained with: a[a.nonzero()] To group the indices by element, rather than dimension, use instead: np.transpose(a.nonzero()) The result of this is always a 2d array, with a row for each non-zero element. Parameters: None Returns: tuple_of_ar

recarray.flags Information about the memory layout of the array. Notes The flags object can be accessed dictionary-like (as in a.flags['WRITEABLE']), or by using lowercased attribute names (as in a.flags.writeable). Short flag names are only supported in dictionary access. Only the UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be changed by the user, via direct assignment to the attribute or dictionary entry, or by calling ndarray.setflags. The array flags cannot be set arbitrarily: UPDATE

numpy.random.logseries(p, size=None) Draw samples from a logarithmic series distribution. Samples are drawn from a log series distribution with specified shape parameter, 0 < p < 1. Parameters: loc : float scale : float > 0. 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 a single value is returned. Returns: samples : ndarray or scalar where the values are all integers

numpy.polynomial.chebyshev.chebgrid3d(x, y, z, c) [source] Evaluate a 3-D Chebyshev 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 scala

recarray.conj() Complex-conjugate all elements. Refer to numpy.conjugate for full documentation. See also numpy.conjugate equivalent function

numpy.random.gamma(shape, scale=1.0, size=None) Draw samples from a Gamma distribution. Samples are drawn from a Gamma distribution with specified parameters, shape (sometimes designated ?k?) and scale (sometimes designated ?theta?), where both parameters are > 0. Parameters: shape : scalar > 0 The shape of the gamma distribution. scale : scalar > 0, optional The scale of the gamma distribution. Default is equal to 1. size : int or tuple of ints, optional Output shape. If the

class numpy.polynomial.polynomial.Polynomial(coef, domain=None, window=None) [source] A power series class. The Polynomial class provides the standard Python numerical methods ?+?, ?-?, ?*?, ?//?, ?%?, ?divmod?, ?**?, and ?()? as well as the attributes and methods listed in the ABCPolyBase documentation. Parameters: coef : array_like Polynomial coefficients in order of increasing degree, i.e., (1, 2, 3) give 1 + 2*x + 3*x**2. domain : (2,) array_like, optional Domain to use. The interva

matrix.dump(file) Dump a pickle of the array to the specified file. The array can be read back with pickle.load or numpy.load. Parameters: file : str A string naming the dump file.