如何在MATLAB中更改浮点运算的舍入模式?

时间:2019-04-15 02:53:15

标签: matlab floating-point rounding

我想更改MATLAB中浮点运算的舍入模式。根据IEEE 754-2008,有五种舍入策略:

  • 四舍五入至最接近
  • 四舍五入到最接近的地方,领带从零开始
  • 四舍五入
  • 向上舍入(向正无穷大)
  • 向下舍入(向负无穷大)

MATLAB支持这5种策略吗?如何在MATLAB中更改浮点运算的舍入模式?

1 个答案:

答案 0 :(得分:3)

答案

种类。有一个未公开的feature('setround')函数调用,可以用来获取或设置Matlab使用的舍入模式。

因此,可以做到,但您不应该这样做。 :)

  

警告:这是一个未记录的,不受支持的功能!使用后果自负!

feature('setround')支持5种IEEE-754舍入模式中的4种:仅存在一种“最近”模式,并且我不知道它是“平坦的关系”还是“远离零的关系”。 / p>

支持的模式:

  • feature('setround') –获取当前的舍入模式
  • feature('setround', 0.5) –四舍五入到最近的位置(不知道它是零还是零)。
  • feature('setround', Inf) –向上舍入(向+ Inf)
  • feature('setround', 0) –向零舍入
  • feature('setround', -Inf) –下舍入(向-Inf方向移动)

测试注意事项:IEEE-754舍入模式不影响round()及其亲属。而是控制算术运算如何在浮点精度的限制范围内表现。

演示

%ROUNDINGEXAMPLE Demonstrates IEEE-754 Rounding Mode control
%
% This uses a completely undocumented and unsupported feature!
% Not for production use!

%% Setup
clear; clc

n = 2000;
X = ones(n)*1E-30; % matrix with n^2 elements
defaultRoundingMode = feature('setround'); % store default rounding mode

%%
feature('setround',0.5);
r1 = prettyPrint('Nearest', sum(X(:)));
%{
  sign   exponent                       mantissa
     0 01110110001 0011010101111100001010011001101001110101010000011110
     | \_________/ \__________________________________________________/
     |      |             ______________________|___________________________
     |      |            /                                                  \
(-1)^0 2^( 945 - 1023) 1.0011010101111100001010011001101001110101010000011110 = 4e-24
%}

%%
feature('setround',-Inf);
r2 = prettyPrint('To -Infinity', sum(X(:)));
%{
  sign   exponent                       mantissa
     0 01110110001 0011010101111100001010011001101001011100000111000110
     | \_________/ \__________________________________________________/
     |      |             ______________________|___________________________
     |      |            /                                                  \
(-1)^0 2^( 945 - 1023) 1.0011010101111100001010011001101001011100000111000110 = 4e-24
%}

%%
feature('setround',Inf);
r3 = prettyPrint('To Infinity', sum(X(:)));
%{
  sign   exponent                       mantissa
     0 01110110001 0011010101111100001010011001101010100011101100100001
     | \_________/ \__________________________________________________/
     |      |             ______________________|___________________________
     |      |            /                                                  \
(-1)^0 2^( 945 - 1023) 1.0011010101111100001010011001101010100011101100100001 = 4e-24
%}

%%
feature('setround',0);
r4 = prettyPrint('To zero', sum(X(:)));
%{
  sign   exponent                       mantissa
     0 01110110001 0011010101111100001010011001101001011100000111000110
     | \_________/ \__________________________________________________/
     |      |             ______________________|___________________________
     |      |            /                                                  \
(-1)^0 2^( 945 - 1023) 1.0011010101111100001010011001101001011100000111000110 = 4e-24
%}

%%
feature('setround',defaultRoundingMode);
r5 = prettyPrint('No accumulated roundoff error', 4e-24);
%{
  sign   exponent                       mantissa
     0 01110110001 0011010101111100001010011001101010001000111010100111
     | \_________/ \__________________________________________________/
     |      |             ______________________|___________________________
     |      |            /                                                  \
(-1)^0 2^( 945 - 1023) 1.0011010101111100001010011001101010001000111010100111 = 4e-24
%}

%% Helper function
function r = prettyPrint(s, r)
    fprintf('%s:\n%65.60f\n\n', s, r); 
end

我得到:

Nearest:
   0.000000000000000000000003999999999966490758963870373537264729

To -Infinity:
   0.000000000000000000000003999999999789077070014108839608005726

To Infinity:
   0.000000000000000000000004000000000118618095059505975310731249

To zero:
   0.000000000000000000000003999999999789077070014108839608005726

No accumulated roundoff error:
   0.000000000000000000000003999999999999999694801998206811298525

致谢

感谢MathWorks技术支持的Ryan Klots为我提供了直接的帮助,并提供了不错的演示代码!