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.

New in version 1.7.0. Starting in NumPy 1.7, there are core array data types which natively support datetime functionality. The data type is called ?datetime64?, so named because ?datetime? is already taken by the datetime library included in Python. Note The datetime API is experimental in 1.7.0, and may undergo changes in future versions of NumPy. Basic Datetimes The most basic way to create datetimes is from strings in ISO 8601 date or datetime format. The unit for internal storage is

dtype.__reduce__()

generic.clip() 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

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

MaskedArray.__setmask__(mask, copy=False) [source] Set the mask.