#Matlab 2008 meshgrid code

Variables in MATLAB require a contiguous space in memory for all elements of the array.

#Matlab 2008 meshgrid code

Looping constructs can usually be rewritten using array operations to generate faster, simpler, vectorized code.Д®ven in cases where your code cannot be vectorized, you may be able to use the following tips to improve code speed:Дynamically sizing vectors requires system time to find a new piece of memory to hold the current matrix plus the elements being added. This example clearly demonstrates the benefits of vectorization in MATLAB.

You can try another example with larger vectors, to see the difference:

The first example executes faster than the second, and is the way MATLAB is meant to be used. An equivalent M-code, non-vectorized computation is: In C and FORTRAN, you must write a loop to perform this operation. However for looping constructs (FOR and WHILE loops), the interpretation process consumes valuable time, and can produce a noticeable difference in the speed at which your code runs.Д¬onsider the following two examples of array operations: This process is generally so fast that you don't notice it. This is different from compiled languages, like FORTRAN and C, where your code is first converted into instructions, and then these instructions are run to generate your results.Д®very command in standard M-code requires that the MATLAB interpreter parse the code, checking the syntax and creating the instructions that need to be run.

When you type a command, the interpreter parses the command (checking syntax) and sends instructions to the processor to carry out the operations you have described with your command. Now let's consider why we do math in this manner in MATLAB.