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Preallocation

`for` and `while` loops that incrementally increase the size of a data structure each time through the loop can adversely affect performance and memory use. Repeatedly resizing arrays often requires MATLAB® to spend extra time looking for larger contiguous blocks of memory, and then moving the array into those blocks. Often, you can improve code execution time by preallocating the maximum amount of space required for the array.

The following code displays the amount of time needed to create a scalar variable, `x`, and then to gradually increase the size of `x` in a `for` loop.

```tic x = 0; for k = 2:1000000 x(k) = x(k-1) + 5; end toc```
`Elapsed time is 0.301528 seconds.`

If you preallocate a 1-by-1,000,000 block of memory for `x` and initialize it to zero, then the code runs much faster because there is no need to repeatedly reallocate memory for the growing data structure.

```tic x = zeros(1, 1000000); for k = 2:1000000 x(k) = x(k-1) + 5; end toc```
`Elapsed time is 0.011938 seconds.`

Use the appropriate preallocation function for the kind of array you want to initialize:

• `zeros` for numeric arrays

• `cell` for character arrays

Preallocating a Nondouble Matrix

When you preallocate a block of memory to hold a matrix of some type other than `double`, avoid using the method

`A = int8(zeros(100));`

This statement preallocates a 100-by-100 matrix of `int8`, first by creating a full matrix of `double` values, and then by converts each element to `int8`. Creating the array as `int8` values saves time and memory. For example:

`A = zeros(100, 'int8');`