## Define Variable-Size Data for Code Generation

For code generation, before using variables in operations or returning them as outputs, you must assign them a specific class, size, and complexity. Generally, after the initial assignment, you cannot reassign variable properties. Therefore, after assigning a fixed size to a variable or structure field, attempts to grow the variable or structure field might cause a compilation error. In these cases, you must explicitly define the data as variable-size by using one of these methods.

Method | See |
---|---|

Assign the data from a variable-size matrix constructor such as: | Use a Matrix Constructor with Nonconstant Dimensions |

Assign multiple, constant sizes to the same variable before using (reading) the variable. | Assign Multiple Sizes to the Same Variable |

Define all instances of a variable to be variable-size. | Define Variable-Size Data Explicitly by Using coder.varsize |

### Use a Matrix Constructor with Nonconstant Dimensions

You can define a variable-size matrix by using a constructor with nonconstant dimensions. For example:

function s = var_by_assign(u) %#codegen y = ones(3,u); s = numel(y);

If you are not using dynamic memory allocation, you must also add an
`assert`

statement to provide upper bounds for the
dimensions. For
example:

function s = var_by_assign(u) %#codegen assert (u < 20); y = ones(3,u); s = numel(y);

### Assign Multiple Sizes to the Same Variable

Before you use (read) a variable in your code, you can make it variable-size by assigning multiple, constant sizes to it. When the code generator uses static allocation on the stack, it infers the upper bounds from the largest size specified for each dimension. When you assign the same size to a given dimension across all assignments, the code generator assumes that the dimension is fixed at that size. The assignments can specify different shapes and sizes.

When the code generator uses dynamic memory allocation, it does not check for upper bounds. It assumes that the variable-size data is unbounded.

#### Inferring Upper Bounds from Multiple Definitions with Different Shapes

function s = var_by_multiassign(u) %#codegen if (u > 0) y = ones(3,4,5); else y = zeros(3,1); end s = numel(y);

When the code generator uses static allocation, it infers that
`y`

is a matrix with three dimensions:

The first dimension is fixed at size 3

The second dimension is variable-size with an upper bound of 4

The third dimension is variable-size with an upper bound of 5

When the code generator uses dynamic allocation, it analyzes the
dimensions of `y`

differently:

The first dimension is fixed at size 3.

The second and third dimensions are unbounded.

### Define Variable-Size Data Explicitly by Using coder.varsize

To explicitly define variable-size data, use the function `coder.varsize`

. Optionally, you
can also specify which dimensions vary along with their upper bounds. For example:

Define

`B`

as a variable-size 2-dimensional array, where each dimension has an upper bound of 64.coder.varsize('B', [64 64]);

Define

`B`

as a variable-size array:coder.varsize('B');

When you supply only the first argument,

`coder.varsize`

assumes that all dimensions of`B`

can vary and that the upper bound is`size(B)`

.

If a MATLAB Function block input or
output signal is variable-size, in the Property Inspector, you must specify that
the signal is variable-size. You must also provide the upper bounds. You do not
have to use `coder.varsize`

with the corresponding input or
output variable inside the MATLAB Function block. However, if you
specify upper bounds with `coder.varsize`

, they must match
the upper bounds in the Property Inspector.

#### Specify Which Dimensions Vary

You can use the function `coder.varsize`

to specify
which dimensions vary. For example, the following statement defines
`B`

as an array whose first dimension is fixed at 2,
but whose second dimension can grow to a size of
16:

coder.varsize('B',[2, 16],[0 1])

The third argument specifies which dimensions vary. This argument must be
a logical vector or a double vector containing only zeros and ones.
Dimensions that correspond to zeros or `false`

have fixed
size. Dimensions that correspond to ones or `true`

vary in
size. `coder.varsize`

usually treats dimensions of size 1
as fixed. See Define Variable-Size Matrices with Singleton Dimensions.

For an input or output signal, if you specify the
upper bounds with `coder.varsize`

inside the
MATLAB Function block, they must match the upper bounds
in the Property Inspector.

#### Allow a Variable to Grow After Defining Fixed Dimensions

Function `var_by_if`

defines matrix `Y`

with fixed 2-by-2 dimensions before the first use (where the statement
`Y = Y + u`

reads from `Y`

). However,
`coder.varsize`

defines `Y`

as a
variable-size matrix, allowing it to change size based on decision logic in
the `else`

clause:

function Y = var_by_if(u) %#codegen if (u > 0) Y = zeros(2,2); coder.varsize('Y'); if (u < 10) Y = Y + u; end else Y = zeros(5,5); end

Without `coder.varsize`

, the code generator infers
`Y`

to be a fixed-size, 2-by-2 matrix. It generates a
size mismatch error.

#### Define Variable-Size Matrices with Singleton Dimensions

A singleton dimension is a dimension for which
`size(A,dim)`

= 1. Singleton dimensions are fixed in
size when:

You specify a dimension with an upper bound of 1 in

`coder.varsize`

expressions.For example, in this function,

`Y`

behaves like a vector with one variable-size dimension:function Y = dim_singleton(u) %#codegen Y = [1 2]; coder.varsize('Y', [1 10]); if (u > 0) Y = [Y 3]; else Y = [Y u]; end

You initialize variable-size data with singleton dimensions by using matrix constructor expressions or matrix functions.

For example, in this function,

`X`

and`Y`

behave like vectors where only their second dimensions are variable-size.function [X,Y] = dim_singleton_vects(u) %#codegen Y = ones(1,3); X = [1 4]; coder.varsize('Y','X'); if (u > 0) Y = [Y u]; else X = [X u]; end

You can override this behavior by using `coder.varsize`

to specify explicitly that singleton dimensions vary. For
example:

function Y = dim_singleton_vary(u) %#codegen Y = [1 2]; coder.varsize('Y', [1 10], [1 1]); if (u > 0) Y = [Y Y+u]; else Y = [Y Y*u]; end

In this example, the third argument of `coder.varsize`

is a vector of ones, indicating that each dimension of `Y`

varies in size.

#### Define Variable-Size Structure Fields

To define structure fields as variable-size arrays, use a colon
(`:`

) as the index expression. The colon
(`:`

) indicates that
all elements of the array are
variable-size. For example:

function y=struct_example() %#codegen d = struct('values', zeros(1,0), 'color', 0); data = repmat(d, [3 3]); coder.varsize('data(:).values'); for i = 1:numel(data) data(i).color = rand-0.5; data(i).values = 1:i; end y = 0; for i = 1:numel(data) if data(i).color > 0 y = y + sum(data(i).values); end end

The expression `coder.varsize('data(:).values')`

defines
the field `values`

inside each element of matrix
`data`

to be variable-size.

Here are other examples:

`coder.varsize('data.A(:).B')`

In this example,

`data`

is a scalar variable that contains matrix`A`

. Each element of matrix`A`

contains a variable-size field`B`

.`coder.varsize('data(:).A(:).B')`

This expression defines field

`B`

inside each element of matrix`A`

inside each element of matrix`data`

to be variable-size.