如何将浮点数组转换为二进制?

Question

这是我的数组:

array([-0.1142  ,  0.11127 ,  0.0374  ,  0.02007 , -0.05737 , -0.02058 ,
-0.1595  , -0.1288  ,  0.1436  , -0.05212 ,  0.2437  ,  0.0046  ,
-0.1456  , -0.09485 , -0.0788  ,  0.1755  , -0.2429  , -0.1204  ,
-0.01064 ,  0.01154 ,  0.06058 , -0.02666 ,  0.01773 ,  0.03436 ,
-0.1262  , -0.3428  , -0.068   , -0.10645 ,  0.0669  , -0.02094 ,
-0.0751  ,  0.001348, -0.1737  ,  0.01146 ,  0.01648 ,  0.03613 ,
0.03384 , -0.063   ,  0.1617  , -0.03023 , -0.258   ,  0.0385  ,
0.0382  ,  0.1821  ,  0.2104  , -0.01604 ,  0.05945 , -0.1809  ,
0.1847  , -0.1569  ,  0.02007 ,  0.1757  ,  0.08514 ,  0.07886 ,
-0.00872 , -0.1108  , -0.01473 ,  0.1075  , -0.1221  ,  0.0163  ,
0.03275 , -0.01775 ,  0.01232 , -0.0705  ], dtype=float16)

我需要将其转换为二进制，应该识别小数和负号，然后每个元素应该输出16位，但我不知道如何请帮助我。我正在使用Jupyter Notebook来运行我的python程序。

Answer 1

使用struct模块将一半(16位浮点数)解释为整数，然后将该整数转换为16个字符长的二进制字符串。

根据文档，!表示使用计算机系统(大端或小端)对两个字节进行排序，H表示unsigned short(16位无符号整数)，e表示half(16位浮点数)

import numpy as np
import struct

arr = np.array([-0.1142  ,  0.11127 ,  0.0374  ,  0.02007 , -0.05737 , -0.02058 ,
-0.1595  , -0.1288  ,  0.1436  , -0.05212 ,  0.2437  ,  0.0046  ,
-0.1456  , -0.09485 , -0.0788  ,  0.1755  , -0.2429  , -0.1204  ,
-0.01064 ,  0.01154 ,  0.06058 , -0.02666 ,  0.01773 ,  0.03436 ,
-0.1262  , -0.3428  , -0.068   , -0.10645 ,  0.0669  , -0.02094 ,
-0.0751  ,  0.001348, -0.1737  ,  0.01146 ,  0.01648 ,  0.03613 ,
0.03384 , -0.063   ,  0.1617  , -0.03023 , -0.258   ,  0.0385  ,
0.0382  ,  0.1821  ,  0.2104  , -0.01604 ,  0.05945 , -0.1809  ,
0.1847  , -0.1569  ,  0.02007 ,  0.1757  ,  0.08514 ,  0.07886 ,
-0.00872 , -0.1108  , -0.01473 ,  0.1075  , -0.1221  ,  0.0163  ,
0.03275 , -0.01775 ,  0.01232 , -0.0705  ], dtype=np.float16)
def half_to_binstr(half):
bits, = struct.unpack('!H', struct.pack('!e', half))
return "{:016b}".format(bits)
res = np.vectorize(half_to_binstr)(arr)

输出:

array(['1010111101001111', '0010111100011111', '0010100011001010',
'0010010100100011', '1010101101011000', '1010010101000101',
'1011000100011011', '1011000000011111', '0011000010011000',
'1010101010101100', '0011001111001100', '0001110010110110',
'1011000010101001', '1010111000010010', '1010110100001011',
'0011000110011110', '1011001111000110', '1010111110110101',
'1010000101110011', '0010000111101001', '0010101111000001',
'1010011011010011', '0010010010001010', '0010100001100110',
'1011000000001010', '1011010101111100', '1010110001011010',
'1010111011010000', '0010110001001000', '1010010101011100',
'1010110011001110', '0001010110000101', '1011000110001111',
'0010000111011110', '0010010000111000', '0010100010100000',
'0010100001010101', '1010110000001000', '0011000100101101',
'1010011110111101', '1011010000100001', '0010100011101110',
'0010100011100100', '0011000111010100', '0011001010111100',
'1010010000011011', '0010101110011100', '1011000111001010',
'0011000111101001', '1011000100000101', '0010010100100011',
'0011000110011111', '0010110101110011', '0010110100001100',
'1010000001110111', '1010111100010111', '1010001110001011',
'0010111011100001', '1010111111010000', '0010010000101100',
'0010100000110001', '1010010010001011', '0010001001001111',
'1010110010000011'], dtype='<U16')