Pierre GM <pgmdevlist <at> gmail.com> writes: > > > On Jul 23, 2009, at 1:13 PM, Jacopo wrote: > > > > In short, I want to create a class Dummy, inherited from np.ndarray, > > which > > returns a plain array whenever an instance is sliced or viewed. I > > cannot figure > > out how. > > Easy enough for slices: > class Dummy(np.ndarray): > def __new__(cls, array): > obj=array.view(cls) > return obj > def __getslice__(self, i, j): > return np.ndarray.__getslice__(self, i, j).view(np.ndarray) > > For views, the problem needs to be better described: why would you > want to get just a basic ndarray ? >
Pierre, Dummy(np.ndarray) is designed to contain a 2d-array and 2 vectors, one for the x-Axis and the other for the y-Axis. I use this coordinates to select and order row and columns of the 2d-array. i.e if I sum two Dummys I may have to reorder the column of one term to be consistent with the other. After the rearrangement I want to perform some liner algebra with the matrices. So let's I want to compute the transpose, I dont want to keep track also of the changes in the x axis and y axis, at this stage I am happy to lose this information and not to have the overhead. (e.g, if i compute the inverse the axis start to have no meaning anymore.) Thanks, Jacopo _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
