Numpy creating an array of powers of 2

Question

I tried :

>>>a = np.array(2**np.arange(42)[::-1],dtype = np.uint64)

and got

>>> a
array([                   0,                    0,                    0,
                          0,                    0,                    0,
                          0,                    0,                    0,
                          0, 18446744071562067968,           1073741824,
                  536870912,            268435456,            134217728,
                   67108864,             33554432,             16777216,
                    8388608,              4194304,              2097152,
                    1048576,               524288,               262144,
                     131072,                65536,                32768,
                      16384,                 8192,                 4096,
                       2048,                 1024,                  512,
                        256,                  128,                   64,
                         32,                   16,                    8,
                          4,                    2,                    1], dtype=uint64)

18446744071562067968 is certainly not 2 to the power 31 and after that the answers are certainly not zero!
to check for some kind of overflow error I tried :

>>> a[0] = 2**42

and got:

>>> a
array([       4398046511104, ..... 

  the rest the same

Can anybody tell me what has gone wrong?

You're doing the computations in the wrong dtype and casting too late. Same reason float(1/2) is 0.0 in Python 2 and decimal.Decimal(1.0/10.0) isn't decimal.Decimal('0.1'). — user2357112
– user2357112, Commented Oct 9, 2017 at 19:35

juanpa.arrivillaga · Accepted Answer · 2017-10-09 19:31:52Z

3

Yes, np.arange(42) is defaulting to a signed integer, likely np.int32, probably because you are on a 32-bit architecture or you are on Windows. Ditch the np.array wrapper, which is totally useless, and pass the dtype to np.arange:

2**np.arange(42, dtype = np.uint64)[::-1]

answered Oct 9, 2017 at 19:31

juanpa.arrivillaga

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