On 29/1/19 9:22 am, Yuping Wang wrote:
Dear Nmupy developers and users: I am a new user of Numpy ,I have encountered a question about Numpy recently, which need your help. The question is below:
I don know why there are negative numbers can somebody explain to me why these happens Thanks in advance!
NumPy ndarrays are typed. Since you do not specify a type in arange, numpy assumes you want `a` to be the type of 2000. I assume you are on a system where numpy converts 2000 to an `int32`, so if you ask what is the type of a: (`a.dtype`) it will show `int32`, meaning the values in a are interpreted as if they are 32 bit integers. 2000*2000*2000 overflows a 32 bit signed integer, so it wraps around to a negative value. The way around this is to specify what type you wish to use: `a=np.arange(2000, dtype=float)**3` or `a=np.arange(2000, dtype='int64`)**3 will not overflow. For floats, most CPUs/compilers provide an indication when float values overflow, so we can raise a warning appropriately. Unfortunately, detecting overflows with ints has no hardware support, so adding a warning would mean checking each value before a calculation, causing an unacceptable slow down. Where did you start learning about NumPy? Perhaps you could suggest they add this explanation (or if it is in our documentation point out where you think would be appropriate) since it seems many people have problems with dtypes and overflow. Matti