#Matlab vectorize code#

#Matlab vectorize code#

In fact, it’s typically best to make it a habit of terminating every line of code with a semicolon and using the ‘disp’ command to write formatted output.Īside from displaying text in the command window, drawing figures is also very time-consuming. Means that MATLAB will print the entire million element array for EACH of the million iterations! This takes a small eternity – hit CTRL-C to kill it and put that semicolon in. In the previous FOR loop example, leaving off the semicolon on the line: out(i,j) = sqrt(matrix(i,j)) * 2 Just as if you’d thrown a cout/printf after that line of code. In MATLAB, if you don’t terminate a line with a semicolon, that’s OK! Your code will still run, but without the semicolon, MATLAB will print the output to the Command Window. In the above FOR loop example, adding one line cuts the execution time in half: out = zeros(size(matrix)) % Preallocate output matrixĮnd Suppress Output (aka Semicolons are your friend) If MATLAB has to keep reallocating memory for the array as it grows, it slows down a lot. This is important in most languages, but especially so in MATLAB. The MathWorks guide to vectorization is here. Basically, whenever you want to write a FOR loop do to something on an array, you should instead be vectorizing it. Not only is the vectorized version much faster (0.022 vs 1.1882 seconds – 125X – on a 1M element array in MATLAB 2009b on an Intel Core i5), it’s much shorter to type. The proper, vectorized way is simply: out = sqrt(matrix) * 2 % Vectorized! For instance, in C, to take the square root of every element of a 2-D array and multiply them by 2, you’d need to have a nested set of FOR loops to iterate over every element – this would look something like: (using MATLAB syntax) for i = 1:size(matrix, 1) % Loops BAD!

Fortunately, because MATLAB was designed to work with matrices, most of the built-in functions can process entire matrices at a time, rather than having to process them one element at a time as you would in most languages. Basically, in MATLAB, the fewer lines of code you can do something in, the better. So in particular, loops are pretty bad because MATLAB has to interpret every line of code individually and loops just mean lots of time spent interpreting. This can cause MATLAB code to execute up to hundreds of times slower! Vectorize This is largely because MATLAB is an interpreted language – that handy ability to set a breakpoint and then run code and plot data comes at the cost of not being able to compile or optimize the code in advance and having to do everything on-the-fly. However, it’s definitely pretty slow when it comes to code-execution performance compared to, well, almost every other language out there. Here we discuss the types of vector operation which include arithmetic and relational Operation along with some Examples.MATLAB is a great environment to quickly prototype scientific algorithms, especially with interactive debugging, decent data plotting facilities, dynamic typing, and all the built-in toolboxes. In Matlab, we can create different types of vectors where we can perform various operations like addition, subtraction, multiplication, square, square root, power, scaling, vector multiplication, dot product, etc. Output will be 1 1 1 ,that means all values are greater than values of vector n. We can compare a given matrix with any arithmetic constant or with any other vector. M ): Greater than the operator represents by the symbol ( ‘ > ’). we can compare a given matrix with any arithmetic constant or with any other vector. Less than operator (<): Less than the operator represents by symbol ‘ <’. O represents false and 1 represents true.ī. The above statement will give output as 0 1 0, which means first no is not equal, the second number is equal and the third no is not equal. Equal to the operator: this operator compares each n every element from two vectors and gives output is zero and one form.Īs we know there are three elements in vector m and vector n, Suppose I want to find out the square of one particular vector or I want to multiply the vector by that vector only. Syntax: variable name = vector name dot operator multiplication operator vector name Therefore we need to add a dot operator ( ‘.

Multiplication of Vectors: If we want to do multiplication of two vectors then a simple multiplication operator ( * ) will not work. Similarly, we can do subtraction operation like sub = p – qĮ. Syntax: vector name operator ( + ) vector name