One thing I'm really missing is something like matlab's fixed-pt toolbox. I'd love to see this added to numpy.
A fixed point integer (fpi) type is based on an integer, but keeps track of where the 'binary point' is. When created, the fpi has a specified number of fractional bits and integer bits. When assigned to, the fpi will check for overflow. On overflow various actions can be taken, including raise exception and ignore (just wraparound). numpy arrays of fpi should support all numeric operations. Also mixed fpi/integer operations. I'm not sure how to go about implementing this. At first, I was thinking to just subclass numpy array. But, I don't think this provides fpi scalars, and their associated operations. I have code in c++ for a scalar fpi data type (not numpy scalar, just a c++ type) that I think has all the required behavior. It depends on boost::python and other boost code (and unreleased boost constrained_value), so probably would not be interesting to a larger numpy audience. I'm thinking this might all be implemented in cython. I haven't used cython yet, so this could be an opportunity. OTOH, I don't know if cython has all the capabilities to implement a new numpy scalar/array type. Thoughts? Interest? _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
