Matlab basic operation:
>> 5+6
ans =
11
>> 3*4
ans =
12
>> 2^6
ans =
64
>> 1==2
ans =
0
>> 1~=2
ans =
1
>> 1&&0
ans =
0
>> 1||0
ans =
1
>> xor(1,0)
ans =
1
>> xor(1,1)
ans =
0
>> who
您的变量为:
ans
>> whos
Name Size Bytes Class Attributes
ans 1x1 1 logical
>> a=3;
>> b='hi'
b =
hi
>> c=(3>=1)
c =
1
>> a=pi;
>> a
a =
3.1416
>> disp(a);
3.1416
>> disp(sprintf('2 decimals: %0.2f',a))
2 decimals: 3.14
>> disp(sprintf('6 decimals: %0.6f',a))
6 decimals: 3.141593
>> format long
>> a
a =
3.141592653589793
>> format short
>> a
a =
3.1416
>> A=[1 2;3 4;5 6]
A =
1 2
3 4
5 6
>> A=[1 2;
3 4;
5 6]
A =
1 2
3 4
5 6
>> v=[1 2 3]
v =
1 2 3
>> v=[1;2;3]
v =
1
2
3
>> v=1:0.1:2
v =
1.0000 1.1000 1.2000 1.3000 1.4000 1.5000 1.6000 1.7000 1.8000 1.9000 2.0000
>> v=1:0.3:2
v =
1.0000 1.3000 1.6000 1.9000
>> v=1:7
v =
1 2 3 4 5 6 7
>> ones(2,3)
ans =
1 1 1
1 1 1
>> C=2*ones(2,3)
C =
2 2 2
2 2 2
>> w=zeros(3,1)
w =
0
0
0
>> rand(3,3)
ans =
0.8147 0.9134 0.2785
0.9058 0.6324 0.5469
0.1270 0.0975 0.9575
>> rand(3,3)
ans =
0.9649 0.9572 0.1419
0.1576 0.4854 0.4218
0.9706 0.8003 0.9157
>> rand(3,3)
ans =
0.7922 0.0357 0.6787
0.9595 0.8491 0.7577
0.6557 0.9340 0.7431
%rand 平均分布(0~1)
%randn 标准正态分布
>> randn(3,3)
ans =
-0.2256 0.0326 1.5442
1.1174 0.5525 0.0859
-1.0891 1.1006 -1.4916
>> w=-6+sqrt(10)*(randn(1,10000))
>> hist(w)
>> hist(w,50)
>> I=eye(4)
I =
1 0 0 0
0 1 0 0
0 0 1 0
0 0 0 1
>> A
A =
1 2
3 4
5 6
>> size(A)
ans =
3 2
>> sz=size(A)
sz =
3 2
>> size(sz)
ans =
1 2
>> size(A,1)
ans =
3
>> size(A,2)
ans =
2
>> v
v =
1 2 3 4 5 6 7
>> length(v)
ans =
7
>> length(A) %longer dimension
ans =
3
>> v=w(1:10)
v =
-8.3474 -9.3570 1.4328 -7.9467 -3.6344 -6.6085 -3.1900 -8.4187 -10.4344 -10.4979
>> save hello.mat v
>> clear
>> load hello.mat
>> v
v =
-8.3474 -9.3570 1.4328 -7.9467 -3.6344 -6.6085 -3.1900 -8.4187 -10.4344 -10.4979
>> save hello.txt v –ascii
>> A=[1 2;3 4; 5 6]
A =
1 2
3 4
5 6
>> A(3,2)
ans =
6
>> A(2,:)
ans =
3 4
>> A(:,2)
ans =
2
4
6
>> A([1 3],:)
ans =
1 2
5 6
>> A(:,1)
ans =
1
3
5
>> A(:,2)
ans =
2
4
6
>> A(:,2)=[10; 11; 12]
A =
1 10
3 11
5 12
>> A=[A,[100;101;102]] %append another vector to right
A =
1 10 100
3 11 101
5 12 102
>> A(:) % put all the elements into a single vector
ans =
1
3
5
10
11
12
100
101
102
A =
1 2
3 4
5 6
>> B=[7 8;9 10;11 12]
B =
7 8
9 10
11 12
>> C=[A B]
C =
1 2 7 8
3 4 9 10
5 6 11 12
>> A
A =
1 2
3 4
5 6
>> B
B =
7 8
9 10
11 12
>> C=[2 5 ;6 7]
C =
2 5
6 7
>> A*C
ans =
14 19
30 43
46 67
>> A.*B
ans =
7 16
27 40
55 72
>> v=[1;2;3]
v =
1
2
3
>> 1./v
ans =
1.0000
0.5000
0.3333
>> 1./A
ans =
1.0000 0.5000
0.3333 0.2500
0.2000 0.1667
>> log(v)
ans =
0
0.6931
1.0986
>> exp(v)
ans =
2.7183
7.3891
20.0855
>> abs([-1;2;-3])
ans =
1
2
3
>> v+ones(length(v),1)
ans =
2
3
4
>> v+1
ans =
2
3
4
>> a=[1 15 2 0.5]
a =
1.0000 15.0000 2.0000 0.5000
>> max(a)
ans =
15
>> [val,ind]=max(a) %max valus and it’s index
val =
15
ind =
2
>> max(A)
ans =
5 6
>> a<3
ans =
1 0 1 1
>> find(a<3)
ans =
1 3 4
>> [r,c]=find(A>7)
r =
1
3
c =
1
2
>> a
a =
1.0000 15.0000 2.0000 0.5000
>> sum(a)
ans =
18.5000
>> prod(a) %product of a
ans =
15
>> floor(a)
ans =
1 15 2 0
>> ceil(a)
ans =
1 15 2 1
>> rand(3)
ans =
0.8099 0.6218 0.4893
0.6378 0.4146 0.0938
0.8981 0.6476 0.6373
>> rand(3)
ans =
0.9503 0.5915 0.1566
0.4764 0.2253 0.7743
0.6028 0.6684 0.2131
>> max(rand(3),rand(3))
ans =
0.1691 0.8745 0.3584
0.7258 0.6258 0.8875
0.3631 0.2581 0.9005
>> A=magic(3)
A =
8 1 6
3 5 7
4 9 2
>> max(A,[],1)
ans =
8 9 7
>> max(A,[],2)
ans =
8
7
9
>> max(A)
ans =
8 9 7
>> max(max(A))
ans =
9
>> max(A(:))
ans =
9
>> sum(A,1)
ans =
15 15 15
>> sum(A,2)
ans =
15
15
15
>> A.*eye(3)
ans =
8 0 0
0 5 0
0 0 2
>> sum(sum(A.*eye(3)))
ans =
15
>> flipud(eye(3))
ans =
0 0 1
0 1 0
1 0 0
>> A=magic(3)
A =
8 1 6
3 5 7
4 9 2
>> temp=pinv(A)
temp =
0.1472 -0.1444 0.0639
-0.0611 0.0222 0.1056
-0.0194 0.1889 -0.1028
>> temp*A
ans =
1.0000 0.0000 -0.0000
-0.0000 1.0000 0.0000
0.0000 0.0000 1.0000
>>t=[0 :0.1 :0.98] ;
>>y1=sin(2*pi*4*t) ;
>>plot(t,y1)
>> y2=cos(2*pi*4*t);
>> plot(t,y2)
>> plot(t,y1)
>> hold on
>> plot(t,y2)
>> xlabel('time')
>> ylabel('value')
>> legend('sin','cos')
>> title('plot1')
>> print -dpng 'plot1.png' %save the diagram into a png format picture
>> figure(1);plot(t,y1);
>> figure(2);plot(t,y2);
>> subplot(1,2,1);
>> subplot(1,2,1);
>> plot(t,y1)
>> subplot(1,2,2);
>> plot(t,y2)
>> axis([0.5 1 -1 1])
>> clf
>> A=magic(5)
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
>> imagesc(A)
>> imagesc(A),colorbar,colormap gray;
>> imagesc(magic(16)),colorbar,colormap gray;
>> addpath('E:\machine learning\machine-learning-ex1\machine-learning-ex1\ex1')