Basic Operations in Octave
GNU Octave is a high-level programming language, primarily intended for numerical computations. It can also be used to implement various machine learning algorithms with ease. Octave is open-source i.e. it is free to use, whereas MATLAB is not thus MATLAB requires a license to operate.
Below are the various basic functionalities of Octave :
1. Arithmetic Operations : Octave can be used to perform basic mathematical operations like addition, subtraction, multiplication, power operation etc.
MATLAB
% addition operation 23 + 65 + 8 % subtraction operation 32 - 74 % power operation 6 ^ 2 % multiplication operation 45 * 7 % division operation 5 / 6 |
Output :
ans = 96 ans = -42 ans = 36 ans = 315 ans = 0.83333
2. Logical Operations : Octave can be used to perform logical operations like AND, OR, NOT etc.
MATLAB
% logical AND 1 && 0 % logical OR 1 || 0 % logical NOT ~1 |
Output :
ans = 0 ans = 1 ans = 0
3. Relational Operations : Octave can be used to perform relational operations like greater than, less than etc.
MATLAB
% equal to 1 == 1 % not equal to 0 ~= 0 % greater than 1 > 0 % less than 1 < 0 % greater than equal to 1 >= 2 % less than equal to 0 <= 0 |
Output :
ans = 1 ans = 0 ans = 1 ans = 0 ans = 0 ans = 1
4. Changing the default Octave prompt symbol : The default Octave prompt symbol is “>>”. We can change the default Octave prompt symbol using the below commands :
MATLAB
PS1( '<< ' ); PS1( '@ ' ); PS1( '# ' ); |
Output :
5. Variables: Like other programming languages, Octave also has variables to temporarily store data.
MATLAB
% variable declaration and initialization var = 2 % if we want to create the variable and don't want to print it % then put a semicolon at the end of that command var = 3; % this time the variable will not be printed % variable of datatype char ch = 'c' % storing the result of an operation in a variable res = (1 != 1) % storing the value of pi in a variable var = pi % printing a variable with disp() function disp(var); % using sprintf() function to print a string disp(sprintf( '3 decimal values : %0.3f' , var)) % using format long to resize format long var % using format short to resize format short var |
Output :
var = 2 ch = c res = 0 var = 3.1416 3.1416 3 decimal values : 3.142 var = 3.141592653589793 var = 3.1416
6. Matrices and Vectors: Now let’s learn how to deal with matrices and vectors in Octave. We can create matrix as shown below.
MATLAB
% creating matrix in row major matrix = [1 2 3; 4 5 6; 7 8 9] |
Output :
matrix = 1 2 3 4 5 6 7 8 9
We can also make a vector, a vector is a matrix with n rows and 1 column(column vector) or 1 rows with n columns(row vector). here in example 2 and 3 the middle value 5 and 0.5 shows that we want to make a vector matrix from range 1 to 20 with the jump of 5 and from range 0 to 5 with a jump of 0.5 respectively.
MATLAB
% creating row vector r_v = [1, 2, 3] % creating column vector c_v = [1; 2; 3] |
Output :
r_v = 1 2 3 c_v = 1 2 3
Here are some utility shortcuts to create matrices and vectors :
MATLAB
% creating vector using ":" % the extreme end values denote the range % and the middle value denotes the step v1 = 1 : 5 : 20 v2 = 1 : 0.5 : 5 % without the step parameter v3 = 1 : 10 % generate matrix of size 4x4 with all element as 1 ones_matrix = ones(4, 4) % generate matrix of size 4x4 with all element as 10 M = 10 * ones(4, 4) % generate row vector of size 5 with all elements 0 zeroes_vector = zeros(1, 5) % generate row vector of some random numbers between 0 and 1 random_vector = rand(1, 5) % generate matrix of some random numbers between 0 and 1 random_matrix = rand(3, 4) % generate matrix with Gaussian distribution % where mean = 0 and variance and standard deviation = 1 gauss_matrix = randn(5, 5) % generate identity matrix with size 5x5 identity_matrix = eye(5) |
Output :
v1 = 1 6 11 16 v2 = 1.0000 1.5000 2.0000 2.5000 3.0000 3.5000 4.0000 4.5000 5.0000 v3 = 1 2 3 4 5 6 7 8 9 10 ones_matrix = 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 M = 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 zeroes_vector = 0 0 0 0 0 random_vector = 0.79085 0.35395 0.92267 0.60234 0.75549 random_matrix = 0.64434 0.67677 0.54105 0.83149 0.70150 0.16149 0.38742 0.90442 0.60075 0.82273 0.37113 0.91496 gauss_matrix = 0.705921 1.336101 -0.097530 0.498245 1.125928 -0.550047 -1.868716 -0.977788 0.319715 -0.603599 -0.018352 -2.133200 0.462272 0.169707 1.733255 0.623343 0.338734 0.618943 1.110172 1.731495 -1.741052 -0.463446 0.556348 1.633956 -1.424136 identity_matrix = Diagonal Matrix 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1
7. Histograms : We can draw the histograms hist() function. We can also change the bucket size or bins of the histogram.
MATLAB
% generate a vector with 1000 elements elements_1000 = 1 + sqrt(25)*(randn(1, 1000)); hist(elements_1000 ) |
Output :
MATLAB
% generate a vector with 1000 elements elements_1000 = 1 + sqrt(25)*(randn(1, 1000)); % histogram with 30 bins hist(elements_1000, 30) |
Output :
8. Help : We can use the help command to see the documentation for any function.
MATLAB
help eye help sqrt help hist |
Output :