5.5 控制语句: for, while, if 语句
参考视频: 5 - 5 - Control Statements_ for, while, if statements (13 min).mkv
1、for 循环 通过 index 访问列向量
1 >> v = zeros(10,1) 2 v = 3 0 4 0 5 0 6 0 7 0 8 0 9 0 10 0 11 0 12 0 13 >> for i = 1 : 10, 14 v(i) = 2 ^ i; 15 end; 16 >> v 17 v = 18 2 19 4 20 8 21 16 22 32 23 64 24 128 25 256 26 512 27 1024
2、for 循环 直接访问列向量元素
1 >> indices = 1 : 10; 2 >> indices 3 indices = 4 1 2 3 4 5 6 7 8 9 10 5 >> for i = indices, 6 disp(i); 7 end; 8 1 9 2 10 3 11 4 12 5 13 6 14 7 15 8 16 9 17 10
3、while 循环访问列向量
1 >> i = 1; 2 >> while i <= 5, 3 v(i) = 100; 4 i = i + 1; 5 end; 6 >> v 7 v = 8 100 9 100 10 100 11 100 12 100 13 64 14 128 15 256 16 512 17 1024
4、while(true) 和 break
1 >> i = 1 ; 2 >> while(true), 3 v(i) = 999; 4 i = i + 1; 5 if i == 6, 6 break; 7 end; 8 end; 9 >> 10 >> v 11 v = 12 999 13 999 14 999 15 999 16 999 17 64 18 128 19 256 20 512 21 1024
5、if else 语句
1 >> v(1) = 2; 2 >> if v(1) == 1, 3 disp(‘The value is one‘); 4 elseif v(1) == 2, 5 disp(‘The value is two‘); 6 else, 7 disp(‘The value is not one or two‘); 8 end; 9 The value is two
6、自定义函数 function
定义函数 squareThisNumber(x),内容如下:
1 function y = squareThisNumber(x) 2 y = x^2; 3 endfunction
将函数保存为squarethisnumber.m,注意此时是小写。
这时候调用函数 squareThisNumber(2) 提示找不到函数
1 >> squareThisNumber(2); 2 error: ‘squareThisNumber‘ undefined near line 1 column 1 3 >> 4 >> ls 5 [.] featuresX.dat priceY.dat 6 [..] hello.dat squarethisnumber.m
将文件命名为函数一致squareThisNumber.m(大小写也一致),这时候调用函数成功
1 >> ls 2 [.] featuresX.dat priceY.dat 3 [..] hello.dat squareThisNumber.m 4 >> squareThisNumber(2); 5 >> a = squareThisNumber(2); 6 >> a 7 a = 4
这说明:Octave 是大小写敏感的,文件名必须和函数名大小写一致。
7、多个返回值的函数
Octave 函数有和其他语言不一样的地方是可以返回多个值。定义方法squareAndCubeThisNumber(x)如下:
1 function [y1, y2] = squareAndCubeThisNumber(x), 2 y1 = x ^ 2; 3 y2 = x ^ 3; 4 endfunction
调用:
1 >> a = squareAndCubeThisNumber(2) % 接受了第一个返回值 2 a = 4 3 >> [a, b] = squareAndCubeThisNumber(2) % 接受两个返回值 4 a = 4 5 b = 8
8、更复杂的函数
保存下面的函数到costFunctionJ.m中
1 function J = costFunctionJ(X, y, theta), 2 % X is the "design matrix" containing our training examples 3 % y is the class labels 4 5 m = size(X, 1); % number of training examples, size of rows 6 predictions = X * theta; % predictions of hapothesis on all m examples 7 sqrErrors = (predictions - y) .^ 2; % squared errors .^ 指的是对数据中每个元素平方 8 9 J = 1 / (2 * m) * sum(sqrErrors); 10 11 endfunction
针对上边的数据集初始化矩阵。调用函数,计算代价函数的值。
1 >> X = [1 1; 1 2 ; 1 3]; 2 >> y = [1;2;3]; 3 >> theta = [0;1]; % Θ为0,1 h(x)=x 此时完全拟合数据,代价函数的值为0 4 >> j = costFunctionJ(X,y,theta) 5 j = 0
1 >> theta = [0;0]; % Θ 为0,0 h(x)=0 此时不能拟合数据 2 >> j = costFunctionJ(X,y,theta) 3 j = 2.3333 4 5 >> (1^2 + 2^2 + 3^2) / (2*3) % 代价函数的值 6 ans = 2.3333
原文地址:https://www.cnblogs.com/maxiaodoubao/p/9873191.html
时间: 2024-10-10 03:19:26