Contents
I. 清空环境变量及命令
clear all % 清除Workspace中的所有变量 clc % 清除Command Window中的所有命令
II. 变量命令规则
1. 变量名区分大小写
A = 2 a = 3
A =
2
a =
3
2. 变量名长度不超过63位 ABCDEFGHIJKLMNOPQRSTUVWXYZ123456ABCDEFGHIJKLMNOPQRSTUVWXYZ123456 = 3
3. 变量名以字母开头，可以由字母、数字和下划线组成，但不能使用标点 3A = 4 .a = 5 /b = 5
a_2 = 3
% a.2 = 4
a_2 =
3
4. 变量名应简洁明了，通过变量名可以直观看出变量所表示的物理意义
A = rand(3,5) rows = size(A, 1) cols = size(A, 2)
A =
0.0577 0.5950 0.1930 0.3907 0.3971
0.9798 0.9622 0.3416 0.2732 0.3747
0.2848 0.1858 0.9329 0.1519 0.1311
rows =
3
cols =
5
III. MATLAB数据类型
1. 数字
2 + 4 10 - 7 3 * 5 8 / 2
ans =
6
ans =
3
ans =
15
ans =
4
2. 字符与字符串
s = 'a' abs(s) char(65) num2str(65) str = 'I Love MATLAB & Machine Learning.' length(str) doc num2str
s =
a
ans =
97
ans =
A
ans =
65
str =
I Love MATLAB & Machine Learning.
ans =
33
3. 矩阵
A = [1 2 3; 4 5 2; 3 2 7] B = A' C = A(:) D = inv(A) A * D E = zeros(10,5,3) E(:,:,1) = rand(10,5) E(:,:,2) = randi(5, 10,5) E(:,:,3) = randn(10,5)
A =
1 2 3
4 5 2
3 2 7
B =
1 4 3
2 5 2
3 2 7
C =
1
4
3
2
5
2
3
2
7
D =
-0.9118 0.2353 0.3235
0.6471 0.0588 -0.2941
0.2059 -0.1176 0.0882
ans =
1.0000 0.0000 -0.0000
0.0000 1.0000 -0.0000
0.0000 0.0000 1.0000
E(:,:,1) =
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
E(:,:,2) =
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
E(:,:,3) =
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
E(:,:,1) =
0.4350 0.4963 0.9573 0.2299 0.5566
0.0915 0.6423 0.6203 0.5761 0.5294
0.6146 0.2213 0.6003 0.8106 0.8300
0.0110 0.8371 0.1726 0.4038 0.8588
0.5733 0.9711 0.0903 0.9884 0.7890
0.7897 0.8464 0.2553 0.0900 0.3178
0.2354 0.5060 0.8586 0.3209 0.4522
0.4480 0.2789 0.9111 0.5114 0.7522
0.5694 0.7466 0.6996 0.0606 0.1099
0.0614 0.2369 0.7252 0.7257 0.1097
E(:,:,2) =
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
E(:,:,3) =
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
E(:,:,1) =
0.4350 0.4963 0.9573 0.2299 0.5566
0.0915 0.6423 0.6203 0.5761 0.5294
0.6146 0.2213 0.6003 0.8106 0.8300
0.0110 0.8371 0.1726 0.4038 0.8588
0.5733 0.9711 0.0903 0.9884 0.7890
0.7897 0.8464 0.2553 0.0900 0.3178
0.2354 0.5060 0.8586 0.3209 0.4522
0.4480 0.2789 0.9111 0.5114 0.7522
0.5694 0.7466 0.6996 0.0606 0.1099
0.0614 0.2369 0.7252 0.7257 0.1097
E(:,:,2) =
2 1 2 3 3
3 5 5 5 4
5 3 4 3 5
4 5 2 1 2
2 1 2 1 4
2 3 1 5 5
5 2 4 3 1
5 5 3 2 3
4 1 1 4 3
2 3 1 2 2
E(:,:,3) =
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
E(:,:,1) =
0.4350 0.4963 0.9573 0.2299 0.5566
0.0915 0.6423 0.6203 0.5761 0.5294
0.6146 0.2213 0.6003 0.8106 0.8300
0.0110 0.8371 0.1726 0.4038 0.8588
0.5733 0.9711 0.0903 0.9884 0.7890
0.7897 0.8464 0.2553 0.0900 0.3178
0.2354 0.5060 0.8586 0.3209 0.4522
0.4480 0.2789 0.9111 0.5114 0.7522
0.5694 0.7466 0.6996 0.0606 0.1099
0.0614 0.2369 0.7252 0.7257 0.1097
E(:,:,2) =
2 1 2 3 3
3 5 5 5 4
5 3 4 3 5
4 5 2 1 2
2 1 2 1 4
2 3 1 5 5
5 2 4 3 1
5 5 3 2 3
4 1 1 4 3
2 3 1 2 2
E(:,:,3) =
-0.8320 -0.0056 0.6254 -0.0508 -0.0842
0.4979 1.1072 0.7530 -0.8127 0.0893
2.3156 -0.1856 0.2135 -0.4384 1.4561
-0.7938 -1.1214 -0.7702 0.8586 0.2195
0.5410 0.2464 -0.0071 0.1952 -0.1149
-0.5591 1.5610 0.0932 0.8889 0.0686
1.9766 -1.1966 0.9353 0.0692 0.7515
0.5447 -0.2423 0.6635 2.4868 -0.6894
-0.1379 1.0048 -0.3502 -1.6656 0.4508
0.6199 -1.9201 1.6199 -0.4159 -1.5650
4. 元胞数组
A = cell(1, 6)
A{2} = eye(3)
A{5} = magic(5)
B = A{5}
A =
[] [] [] [] [] []
A =
[] [3x3 double] [] [] [] []
A =
[] [3x3 double] [] [] [5x5 double] []
B =
17 24 1 8 15
23 5 7 14 16
4 6 13 20 22
10 12 19 21 3
11 18 25 2 9
5. 结构体
books = struct('name',{{'Machine Learning','Data Mining'}},'price',[30 40]) books.name books.name(1) books.name{1}
books =
name: {'Machine Learning' 'Data Mining'}
price: [30 40]
ans =
'Machine Learning' 'Data Mining'
ans =
'Machine Learning'
ans =
Machine Learning
IV. MATLAB矩阵操作
1. 矩阵的定义与构造
A = [1 2 3 5 8 5 4 6] B = 1:2:9 C = repmat(B, 3, 1) D = ones(2, 4)
A =
1 2 3 5 8 5 4 6
B =
1 3 5 7 9
C =
1 3 5 7 9
1 3 5 7 9
1 3 5 7 9
D =
1 1 1 1
1 1 1 1
2. 矩阵的四则运算
A = [1 2 3 4; 5 6 7 8]
B = [1 1 2 2; 2 2 1 1]
C = A + B
D = A - B
E = A * B'
F = A .* B
G = A / B % B * G = A
H = A ./ B
A =
1 2 3 4
5 6 7 8
B =
1 1 2 2
2 2 1 1
C =
2 3 5 6
7 8 8 9
D =
0 1 1 2
3 4 6 7
E =
17 13
41 37
F =
1 2 6 8
10 12 7 8
G =
1.8333 -0.1667
3.1667 1.1667
H =
1.0000 2.0000 1.5000 2.0000
2.5000 3.0000 7.0000 8.0000
3. 矩阵的下标
A = magic(5) B = A(2,3) C = A(3,:) D = A(:,4) [m, n] = find(A > 20)
A =
17 24 1 8 15
23 5 7 14 16
4 6 13 20 22
10 12 19 21 3
11 18 25 2 9
B =
7
C =
4 6 13 20 22
D =
8
14
20
21
2
m =
2
1
5
4
3
n =
1
2
3
4
5
V. MATLAB逻辑与流程控制
1. if ... else ... end
A = rand(1,10) limit = 0.75; B = (A > limit); % B is a vector of logical values if any(B) fprintf('Indices of values > %4.2f: \n', limit); disp(find(B)) else disp('All values are below the limit.') end
A =
Columns 1 through 7
0.4785 0.2568 0.3691 0.6618 0.1696 0.2788 0.1982
Columns 8 through 10
0.1951 0.3268 0.8803
Indices of values > 0.75:
10
2. for ... end
k = 10; hilbert = zeros(k,k); % Preallocate matrix for m = 1:k for n = 1:k hilbert(m,n) = 1/(m+n -1); end end hilbert
hilbert =
Columns 1 through 7
1.0000 0.5000 0.3333 0.2500 0.2000 0.1667 0.1429
0.5000 0.3333 0.2500 0.2000 0.1667 0.1429 0.1250
0.3333 0.2500 0.2000 0.1667 0.1429 0.1250 0.1111
0.2500 0.2000 0.1667 0.1429 0.1250 0.1111 0.1000
0.2000 0.1667 0.1429 0.1250 0.1111 0.1000 0.0909
0.1667 0.1429 0.1250 0.1111 0.1000 0.0909 0.0833
0.1429 0.1250 0.1111 0.1000 0.0909 0.0833 0.0769
0.1250 0.1111 0.1000 0.0909 0.0833 0.0769 0.0714
0.1111 0.1000 0.0909 0.0833 0.0769 0.0714 0.0667
0.1000 0.0909 0.0833 0.0769 0.0714 0.0667 0.0625
Columns 8 through 10
0.1250 0.1111 0.1000
0.1111 0.1000 0.0909
0.1000 0.0909 0.0833
0.0909 0.0833 0.0769
0.0833 0.0769 0.0714
0.0769 0.0714 0.0667
0.0714 0.0667 0.0625
0.0667 0.0625 0.0588
0.0625 0.0588 0.0556
0.0588 0.0556 0.0526
3. while ... end
n = 1; nFactorial = 1; while nFactorial < 1e100 n = n + 1; nFactorial = nFactorial * n; end n factorial(69) factorial(70) prod(1:69) prod(1:70)
n =
70
ans =
1.7112e+98
ans =
1.1979e+100
ans =
1.7112e+98
ans =
1.1979e+100
4. switch ... case ... end
mynumber = input('Enter a number:'); switch mynumber case -1 disp('negative one'); case 0 disp('zero'); case 1 disp('positive one'); otherwise disp('other value'); end
Error using input
Cannot call INPUT from EVALC.
Error in Example_1 (line 151)
mynumber = input('Enter a number:');
VI. MATLAB脚本与函数文件
1. 脚本文件
myScript
2. 函数文件
mynumber = input('Enter a number:');
output = myFunction(mynumber)
VII. MATLAB基本绘图操作
1. 二维平面绘图
x = 0:0.01:2*pi; y = sin(x); figure plot(x, y) title('y = sin(x)') xlabel('x') ylabel('sin(x)') xlim([0 2*pi]) x = 0:0.01:20; y1 = 200*exp(-0.05*x).*sin(x); y2 = 0.8*exp(-0.5*x).*sin(10*x); figure [AX,H1,H2] = plotyy(x,y1,x,y2,'plot'); set(get(AX(1),'Ylabel'),'String','Slow Decay') set(get(AX(2),'Ylabel'),'String','Fast Decay') xlabel('Time (\musec)') title('Multiple Decay Rates') set(H1,'LineStyle','--') set(H2,'LineStyle',':')
2. 三维立体绘图
t = 0:pi/50:10*pi; plot3(sin(t),cos(t),t) xlabel('sin(t)') ylabel('cos(t)') zlabel('t') grid on axis square
3. 图形的保存与导出
% (1) Edit → Copy Figure % (2) Toolbar → Save % (3) print('-depsc','-tiff','-r300','picture1') % (4) File → Export Setup
VIII. MATLAB文件导入
1. mat格式
save data.mat x y1 y2 clear all load data.mat
2. txt格式
M = importdata('myfile.txt'); S = M.data; save 'data.txt' S -ascii T = load('data.txt'); isequal(S, T)
3. xls格式
xlswrite('data.xls',S) W = xlsread('data.xls'); isequal(S, W) xlswrite('data.xlsx',S) U = xlsread('data.xlsx'); isequal(S, U)
4. csv格式
csvwrite('data.csv',S) V = csvread('data.csv'); isequal(S, V)