On Feb 7, 3:07 pm, <mma...@gmx.net> wrote: > On Sat, 7 Feb 2009 12:50:22 -0800 (PST) > Rhamphoryncus <rha...@gmail.com> wrote: > > Can you explain this in a little more detail? > > In the application, there is one main numpy array of type "O". > Each element of the array corresponds to one cell in a grid. The user > may enter a Python expression into the grid cell. The input is > evaled and the result is stored in the numpy array (the actual process > is a bit more complicated). Therefore, the object inside a numpy array > element may be an inconsistent, nested, iterable type. > > The user now may access the result grid via __getitem__. When doing > this, a numpy array that is as flat as possible while comprising the > maximum possible data depth is returned, i.e.: > > 1. Non-string and non-unicode iterables of similar length for each of > the cells form extra dimensions. > > 2. In order to remove different container types, the result is > flattened, cast into a numpy.array and re-shaped. > > 3. Dimensions of length 1 are eliminated. > > Therefore, the user can conveniently use numpy ufuncs on the results. > > I am referring to the flatten operation in step 2
I'm afraid I still don't understand it, but I'm only minimally familiar with numpy, nevermind your spreadsheet app. -- http://mail.python.org/mailman/listinfo/python-list
