# Octave Programming Tutorial/Vectors and matrices

# Creating vectors and matrices[edit]

Here is how we specify a row vector in Octave:

octave:1> x = [1, 3, 2] x = 1 3 2

Note that

- the vector is enclosed in square brackets;
- each entry is separated by an optional comma.
`x = [1 3 2]`

results in the same row vector.

To specify a column vector, we simply replace the commas with semicolons:

octave:2> x = [1; 3; 2] x = 1 3 2

From this you can see that we use a comma to go to the next column of a vector (or matrix) and a semicolon to go to the next row. So, to specify a matrix, type in the rows (separating each entry with a comma) and use a semicolon to go to the next row.

octave:3> A = [1, 1, 2; 3, 5, 8; 13, 21, 34] A = 1 1 2 3 5 8 13 21 34

# Operators[edit]

You can use the standard operators to

- add (
`+`

), - subtract (
`-`

), and - multiply (
`*`

)

matrices, vectors and scalars with one another. Note that the matrices need to have matching dimensions (inner dimensions in the case of multiplication) for these operators to work.

- The transpose operator is the single quote:
`'`

. To continue from the example in the previous section,

octave:4> A' ans = 1 3 13 1 5 21 2 8 34

(Note: this is actually the complex conjugate transpose operator, but for real matrices this is the same as the transpose. To compute the transpose of a complex matrix, use the dot transpose (`.'`

) operator.)

- The power operator (
`^`

) can also be used to compute real powers of square matrices.

## Element operations[edit]

When you have two matrices of the same size, you can perform element by element operations on them. For example, the following divides each element of *A* by the corresponding element in *B*:

octave:1> A = [1, 6, 3; 2, 7, 4] A = 1 6 3 2 7 4 octave:2> B = [2, 7, 2; 7, 3, 9] B = 2 7 2 7 3 9 octave:3> A ./ B ans = 0.50000 0.85714 1.50000 0.28571 2.33333 0.44444

Note that you use the *dot divide* (`./`

) operator to perform element by element division. There are similar operators for multiplication (`.*`

) and exponentiation (`.^`

).

Let's introduce a scalar for future use.

a = 5;

The dot divide operators can also be used together with scalars in the following manner.

C = a ./ B

returns a matrix, *C* where each entry is defined by

i.e. *a* is divided by each entry in *B*. Similarly

C = a .^ B

return a matrix with

# Indexing[edit]

You can work with parts of matrices and vectors by indexing into them. You use a vector of integers to tell Octave which elements of a vector or matrix to use. For example, we create a vector

octave:1> x = [1.2, 5, 7.6, 3, 8] x = 1.2000 5.0000 7.6000 3.0000 8.0000

Now, to see the second element of *x*, type

octave:2> x(2) ans = 5

You can also view a list of elements as follows.

octave:3> x([1, 3, 4]) ans = 1.2000 7.6000 3.0000

This last command displays the 1st, 3rd and 4th elements of the vector *x*.

To select rows and columns from a matrix, we use the same principle. Let's define a matrix

octave:4> A = [1, 2, 3; 4, 5, 6; 7, 8, 9] A = 1 2 3 4 5 6 7 8 9

and select the 1st and 3rd rows and 2nd and 3rd columns:

octave:5> A([1, 3], [2, 3]) ans = 2 3 8 9

The colon operator (`:`

) can be used to select *all* rows or columns from a matrix. So, to select all the elements from the 2nd row, type

octave:6> A(2, :) ans = 4 5 6

You can also use `:`

like this to select all Matrix elements:

octave:7> A(:,:) ans = 1 2 3 4 5 6 7 8 9

## Ranges[edit]

We can also select a range of rows or columns from a matrix. We specify a range with

start:step:stop

You can actually type ranges at the Octave prompt to see what the results are. For example,

octave:3> 1:3:10 ans = 1 4 7 10

The first number displayed was `start`

, the second was `start + step`

, the third, `start + (2 * step)`

. And the last number was less than or equal to `stop`

.

Often, you simply want the step size to be 1. In this case, you can leave out the step parameter and type

octave:4> 1:10 ans = 1 2 3 4 5 6 7 8 9 10

As you can see, the result of a range command is simply a vector of integers. We can now use this to index into a vector or matrix. To select the submatrix at the top left of *A*, use

octave:4> A(1:2, 1:2) ans = 1 2 4 5

Finally, there is a keyword called `end`

that can be used when indexing into a matrix or vector. It refers to the last element in the row or column. For example, to see the last column in a Matrix, you can use

octave:5> A(:,end) ans = 3 6 9

# Functions[edit]

The following functions can be used to create and manipulate matrices.

## Creating matrices[edit]

`tril(A)`

returns the lower triangular part of*A*.

`triu(A)`

returns the upper triangular part of*A*.

`eye(n)`

returns the identity matrix. You can also use`eye(m, n)`

to return rectangular identity matrices.

`ones(m, n)`

returns an matrix filled with 1s. Similarly,`ones(n)`

returns square matrix.

`zeros(m, n)`

returns an matrix filled with 0s. Similarly,`zeros(n)`

returns square matrix.

`rand(m, n)`

returns an matrix filled with random elements drawn uniformly from . Similarly,`rand(n)`

returns square matrix.

`randn(m, n)`

returns an matrix filled with normally distributed random elements.

`randperm(n)`

returns a row vector containing a random permutation of the numbers .

`diag(x)`

or`diag(A)`

. For a vector,*x*, this returns a square matrix with the elements of*x*on the diagonal and 0s everywhere else. For a matrix,*A*, this returns a vector containing the diagonal elements of*A*. For example,

octave:16> A = [1, 2, 3; 4, 5, 6; 7, 8, 9] A = 1 2 3 4 5 6 7 8 9 octave:17> x = diag(A) ans = 1 5 9 octave:18> diag(x) ans = 1 0 0 0 5 0 0 0 9

`linspace(a, b, n)`

returns a vector with*n*values, such that the first element equals*a*, the last element equals*b*and the difference between consecutive elements is constant. The last argument,*n*, is optional with default value 100.

octave:186> linspace(2, 4, 2) ans = 2 4 octave:187> linspace(2, 4, 4) ans = 2.0000 2.6667 3.3333 4.0000 octave:188> linspace(2, 4, 6) ans = 2.0000 2.4000 2.8000 3.2000 3.6000 4.0000

`logspace(a, b, n)`

returns a vector with*n*values, such that the first element equals , the last element equals and the ratio between consecutive elements is constant. The last argument,*n*is optional with default value 50.

octave:189> logspace(2, 4, 2) ans = 100 10000 octave:190> logspace(2, 4, 4) ans = 1.0000e+02 4.6416e+02 2.1544e+03 1.0000e+04 octave:191> logspace(2, 4, 5) ans = 1.0000e+02 3.1623e+02 1.0000e+03 3.1623e+03 1.0000e+04

### Other matrices[edit]

There are some more functions for creating special matrices. These are

`hankel`

(Hankel matrix),`hilb`

(Hilbert matrix),`invhilb`

(Inverse of a Hilbert matrix),`sylvester_matrix`

(Sylvester matrix) - In v3.8.1 there is a warning: sylvester_matrix is obsolete and will be removed from a future version of Octave; please use hadamard(2^k) instead,`toeplitz`

(Toeplitz matrix),`vander`

(Vandermonde matrix).

Use `help`

to find out more about how to use these functions.

## Changing matrices[edit]

`fliplr(A)`

returns a copy of matrix*A*with the order of the columns reversed, for example,

octave:49> A = [1, 2, 3, 4; 5, 6, 7, 8; 9, 10, 11, 12] A = 1 2 3 4 5 6 7 8 9 10 11 12 octave:50> fliplr(A) ans = 4 3 2 1 8 7 6 5 12 11 10 9

`flipud(A)`

returns a copy of matrix*A*with the order of the rows reversed, for example,

octave:51> flipud(A) ans = 9 10 11 12 5 6 7 8 1 2 3 4

`rot90(A, n)`

returns a copy of matrix*A*that has been rotated by (90n)° counterclockwise. The second argument, , is optional with default value 1, and it may be negative.

octave:52> rot90(A) ans = 4 8 12 3 7 11 2 6 10 1 5 9

`reshape(A, m, n)`

creates an matrix with elements taken from*A*. The number of elements in*A*has to be equal to . The elements are taken from*A*in column major order, meaning that values in the first column () are read first, then the second column (), etc.

octave:53> reshape(A, 2, 6) ans = 1 9 6 3 11 8 5 2 10 7 4 12

`sort(x)`

returns a copy of the vector*x*with the elements sorted in increasing order.

octave:54> x = rand(1, 6) x = 0.25500 0.33525 0.26586 0.92658 0.68799 0.69682 octave:55> sort(x) ans = 0.25500 0.26586 0.33525 0.68799 0.69682 0.92658

# Linear algebra[edit]

For a description of more operators and functions that can be used to manipulate vectors and matrices, find eigenvalues, etc., see the Linear algebra section.

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