MaskedArray.__oct__() <==> oct(x)

numpy.polynomial.chebyshev.chebvander2d(x, y, deg) [source] Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y). The pseudo-Vandermonde matrix is defined by where 0 <= i <= deg[0] and 0 <= j <= deg[1]. The leading indices of V index the points (x, y) and the last index encodes the degrees of the Chebyshev polynomials. If V = chebvander2d(x, y, [xdeg, ydeg]), then the columns of V correspond to the elements

MaskedArray.base Base object if memory is from some other object. Examples The base of an array that owns its memory is None: >>> x = np.array([1,2,3,4]) >>> x.base is None True Slicing creates a view, whose memory is shared with x: >>> y = x[2:] >>> y.base is x True

recarray.dumps() Returns the pickle of the array as a string. pickle.loads or numpy.loads will convert the string back to an array. Parameters: None

ndarray.__ior__ x.__ior__(y) <==> x|=y

record.sort() 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

ndarray.var(axis=None, dtype=None, out=None, ddof=0, keepdims=False) Returns the variance of the array elements, along given axis. Refer to numpy.var for full documentation. See also numpy.var equivalent function

chararray.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

numpy.ma.compress_cols(a) [source] Suppress whole columns of a 2-D array that contain masked values. This is equivalent to np.ma.compress_rowcols(a, 1), see extras.compress_rowcols for details. See also extras.compress_rowcols

numpy.ma.all(self, axis=None, out=None) = Check if all of the elements of a are true. Performs a logical_and over the given axis and returns the result. Masked values are considered as True during computation. For convenience, the output array is masked where ALL the values along the current axis are masked: if the output would have been a scalar and that all the values are masked, then the output is masked. Parameters: axis : {None, integer} Axis to perform the operation over. If None,