On Tue, Sep 29, 2009 at 15:52, Neal Becker <ndbecker2@gmail.com> wrote:

I need the max value of an np scalar type.  I had used this code:

def get_max(is_signed, base_type, total_bits):    print 'get_max:', is_signed, base_type, total_bits    if is_signed:        return (~(base_type(-1) << (total_bits-1)))    else:        print type(base_type (-1) << total_bits)        return (~(base_type (-1) << total_bits))

This doesn't work for e.g., np.uint64.  As the 'print' shows,  get_max: False <type 'numpy.uint64'> 10 <type 'long'>

The type of np.uint64 (-1) << 10 is not np.uint64, but long.  This seems very strange to me.

So, 2 questions.

1) Is this expected behavior?

Could be. I'm not entirely sure why it would be doing this, but the code does fall back to generic object implementations under certain conditions. Of course, np.uint64(-1) is the correct answer for unsigned integer types since we implement wraparound.

2) How can I correctly implement get_max?

np.iinfo() for integer types and np.finfo() for floating point types. In [1]: np.iinfo(np.uint64).max Out[1]: 18446744073709551615L In [2]: np.finfo(np.float32).max Out[2]: 3.4028235e+38 -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco