recarray.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None) Return the sum along diagonals of the array. Refer to numpy.trace for full documentation. See also numpy.trace equivalent function

numpy.asscalar(a) [source] Convert an array of size 1 to its scalar equivalent. Parameters: a : ndarray Input array of size 1. Returns: out : scalar Scalar representation of a. The output data type is the same type returned by the input?s item method. Examples >>> np.asscalar(np.array([24])) 24

pad(array, pad_width, mode, **kwargs) Pads an array.

recarray.repeat(repeats, axis=None) Repeat elements of an array. Refer to numpy.repeat for full documentation. See also numpy.repeat equivalent function

record.take() 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.compress() 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.roll(a, shift, axis=None) [source] Roll array elements along a given axis. Elements that roll beyond the last position are re-introduced at the first. Parameters: a : array_like Input array. shift : int The number of places by which elements are shifted. axis : int, optional The axis along which elements are shifted. By default, the array is flattened before shifting, after which the original shape is restored. Returns: res : ndarray Output array, with the same shape as a.

numpy.asarray_chkfinite(a, dtype=None, order=None) [source] Convert the input to an array, checking for NaNs or Infs. Parameters: a : array_like Input data, in any form that can be converted to an array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Success requires no NaNs or Infs. dtype : data-type, optional By default, the data-type is inferred from the input data. order : {?C?, ?F?}, optional Whether to use row-major (C-style) or col

generic.__reduce__()

numpy.ma.getdata(a, subok=True) [source] Return the data of a masked array as an ndarray. Return the data of a (if any) as an ndarray if a is a MaskedArray, else return a as a ndarray or subclass (depending on subok) if not. Parameters: a : array_like Input MaskedArray, alternatively a ndarray or a subclass thereof. subok : bool Whether to force the output to be a pure ndarray (False) or to return a subclass of ndarray if appropriate (True, default). See also getmask Return the ma