generic.mean()

generic.mean() 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.ma.make_mask_none()

numpy.ma.make_mask_none(newshape, dtype=None) [source] Return a boolean mask of the given shape, filled with False. This function returns a boolean ndarray with all entries False, that can be used in common mask manipulations. If a complex dtype is specified, the type of each field is converted to a boolean type. Parameters: newshape : tuple A tuple indicating the shape of the mask. dtype : {None, dtype}, optional If None, use a MaskType instance. Otherwise, use a new datatype with the

Polynomial.cast()

classmethod Polynomial.cast(series, domain=None, window=None) [source] Convert series to series of this class. The series is expected to be an instance of some polynomial series of one of the types supported by by the numpy.polynomial module, but could be some other class that supports the convert method. New in version 1.7.0. Parameters: series : series The series instance to be converted. domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where

numpy.polynomial.hermite.hermgrid3d()

numpy.polynomial.hermite.hermgrid3d(x, y, z, c) [source] Evaluate a 3-D Hermite 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.

chararray.lower()

chararray.lower() [source] Return an array with the elements of self converted to lowercase. See also char.lower

numpy.fix()

numpy.fix(x, y=None) [source] Round to nearest integer towards zero. Round an array of floats element-wise to nearest integer towards zero. The rounded values are returned as floats. Parameters: x : array_like An array of floats to be rounded y : ndarray, optional Output array Returns: out : ndarray of floats The array of rounded numbers See also trunc, floor, ceil around Round to given number of decimals Examples >>> np.fix(3.14) 3.0 >>> np.fix(3) 3.0 >&

numpy.polynomial.hermite_e.hermeval2d()

numpy.polynomial.hermite_e.hermeval2d(x, y, c) [source] Evaluate a 2-D HermiteE series at points (x, y). This function returns the values: The parameters x and y are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars and they must have the same shape after conversion. In either case, either x and y or their elements must support multiplication and addition both with themselves and with the elements of c. If c is a 1-D array a one is implicitly

numpy.polynomial.chebyshev.chebval3d()

numpy.polynomial.chebyshev.chebval3d(x, y, z, c) [source] Evaluate a 3-D Chebyshev series at points (x, y, z). This function returns the values: 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 and they must have the same shape after conversion. In either case, either x, y, and z or their elements must support multiplication and addition both with themselves and with the elements of c. If c has fewer than 3 dim

matrix.nonzero()

matrix.nonzero() Return the indices of the elements that are non-zero. Refer to numpy.nonzero for full documentation. See also numpy.nonzero equivalent function

MaskedArray.__deepcopy__()

MaskedArray.__deepcopy__(memo=None) [source]