Re: [Numpy-discussion] size of arrays

[klark--kent]

So is it right that 100 arrays of one element is smaller than one array with size of 100 elements?

14.03.2021, 00:06, "Todd" <toddr...@gmail.com>:

Ideally float64 uses 64 bits for each number while float16 uses 16 bits.  64/16=4.  However, there is some additional overhead.  This overhead makes up a large portion of small arrays, but becomes negligible as the array gets bigger.

On Sat, Mar 13, 2021, 16:01 <klark--k...@yandex.ru> wrote:

Dear colleagues!

 

Size of np.float16(1) is 26

Size of np.float64(1) is 32

32 / 26 = 1.23

 

Since memory is limited I have a question after this code:

 

   import numpy as np

   import sys

 

   a1 = np.ones(1, dtype='float16')

   b1 = np.ones(1, dtype='float64')

   div_1 = sys.getsizeof(b1) / sys.getsizeof(a1)

   # div_1 = 1.06

 

   a2 = np.ones(10, dtype='float16')

   b2 = np.ones(10, dtype='float64')

   div_2 = sys.getsizeof(b2) / sys.getsizeof(a2)    

   # div_2 = 1.51

 

   a3 = np.ones(100, dtype='float16')

   b3 = np.ones(100, dtype='float64')

   div_3 = sys.getsizeof(b3) / sys.getsizeof(a3)

   # div_3 = 3.0

Size of np.float64 numpy arrays is four times more than for np.float16.

Is it possible to minimize the difference close to 1.23?

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