ndarray.__array_wrap__()

ndarray.__array_wrap__(obj) ? Object of same type as ndarray object a.

ndarray.__and__

ndarray.__and__ x.__and__(y) <==> x&y

ndarray.__array__()

ndarray.__array__(|dtype) ? reference if type unchanged, copy otherwise. Returns either a new reference to self if dtype is not given or a new array of provided data type if dtype is different from the current dtype of the array.

ndarray.__add__

ndarray.__add__ x.__add__(y) <==> x+y

ndarray.__abs__()

ndarray.__abs__() <==> abs(x)

ndarray.var()

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

ndarray.transpose()

ndarray.transpose(*axes) Returns a view of the array with axes transposed. For a 1-D array, this has no effect. (To change between column and row vectors, first cast the 1-D array into a matrix object.) For a 2-D array, this is the usual matrix transpose. For an n-D array, if axes are given, their order indicates how the axes are permuted (see Examples). If axes are not provided and a.shape = (i[0], i[1], ... i[n-2], i[n-1]), then a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0]). Para

ndarray.view()

ndarray.view(dtype=None, type=None) New view of array with the same data. Parameters: dtype : data-type or ndarray sub-class, optional Data-type descriptor of the returned view, e.g., float32 or int16. The default, None, results in the view having the same data-type as a. This argument can also be specified as an ndarray sub-class, which then specifies the type of the returned object (this is equivalent to setting the type parameter). type : Python type, optional Type of the returned vi

ndarray.tostring()

ndarray.tostring(order='C') Construct Python bytes containing the raw data bytes in the array. Constructs Python bytes showing a copy of the raw contents of data memory. The bytes object can be produced in either ?C? or ?Fortran?, or ?Any? order (the default is ?C?-order). ?Any? order means C-order unless the F_CONTIGUOUS flag in the array is set, in which case it means ?Fortran? order. This function is a compatibility alias for tobytes. Despite its name it returns bytes not strings. Parame

ndarray.trace()

ndarray.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