CASE1:
a=[1, 2, 33;4 ,5, 6; 7 ,8, 66];
a =
1 2 33
4 5 6
7 8 66
a(3) # result is a scalar
ans = 7
a(1:4) # show range form index 1 to(:) index 4, and result is a row vector
ans =
1 4 7 2
a([1; 9]) # show range form index 1 and index 9 result is a column vector
ans =
1
66
a(1, [1, 3]) # row 1, columns 1 and 3
ans =
1 33
a(3, 1:3) # row 3, columns in range 1-2
ans =
7 8 66
a(1, :) # row 1, all columns , use really often !!!
ans =
1 2 33
Case2:
a = [1, 2, 3, 4]
a =
1 2 3 4
a(1:end/2) # first half of a => [1, 2],end is the last element in the matrix
ans =
1 2
a(end + 1) =5 # append element
a =
1 2 3 4 5
a(end) = [] # delete element
a =
1 2 3 4
a(1:2:end) # odd elements of a => [1, 3]
ans =
1 3
a(2:2:end) # even elements of a => [2, 4]
ans =
2 4
a(end:-1:1) # reversal of a => [4, 3, 2 , 1]
ans =
4 3 2 1
CASE3: often use in machine learning cost function
a=[1, 2, 33;4 ,5, 6; 7 ,8, 66];
a =
1 2 33
4 5 6
7 8 66
[99 ; a(1,:)']
ans =
99
1
2
33
num_labels=4;
zeros(num_labels,1)
ans =
0
0
0
0
a=[1, 2, 33;4 ,5, 6; 7 ,8, 66;55 ,476, 22]
a =
1 2 33
4 5 6
7 8 66
55 476 22
a(:,2:end) #from second column to end
ans =
2 33
5 6
8 66
476 22
a(1,:) #get first row
ans =
1 2 33
a(2:end) # start from element 2 to end
ans =
4 7 55 2 5 8 476 33 6 66 22
a(:) # unroll every element
ans =
1
4
7
55
2
5
8
476
33
6
66
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