I don't think NumPy has a function like this (at least, not exposed to Python), but I wrote one for xray, "expanded_indexer", that you are welcome to borrow: https://github.com/xray/xray/blob/v0.6.0/xray/core/indexing.py#L10 Stephan On Sunday, Aug 23, 2015 at 7:54 PM, Fabien <fabien.maussion@gmail.com>, wrote: Folks, My search engine was not able to help me on this one, possibly because I don't know exactly *what* I am looking for. I need to override __getitem__ for a class that wrapps a numpy array. I know the dimensions of my array (which can be variable from instance to instance), and I know what I want to do: for one preselected dimension, I need to select another slice than requested by the user, do something with the data, and return the variable. I am looking for a function that helps me to "clean" the input of __getitem__. There are so many possible cases, when the user uses [:] or [..., 1:2] or [0, ..., :] and so forth. But all these cases have an equivalent index array of len(ndimensions) with only valid slice() objects in it. This array would be much easier for me to work with. in pseudo code: def __getitem__(self, item): # clean input item = np.clean_item(item, ndimensions=4) # Ok now item is guaranteed to be of len 4 item[2] = slice() # Continue etc. Is there such a function in numpy? I hope I have been clear enough... Thanks a lot! Fabien _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion