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.
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|
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
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);
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.
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
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
The first dimension is fixed at size 3.
The second and third dimensions are unbounded.
To explicitly define variable-size data, use the function
Optionally, you can also specify which dimensions vary along with
their upper bounds. For example:
B as a variable-size 2-dimensional
array, where each dimension has an upper bound of 64.
coder.varsize('B', [64 64]);
B as a variable-size array:
When you supply only the first argument,
that all dimensions of
vary and that the upper bound is
If a MATLAB Function block
input or output signal is variable-size, in the Ports and Data Manager,
you must specify that the signal is variable-size. You must also provide
the upper bounds. You do not have to use
the corresponding input or output variable inside the MATLAB
Function block. However, if you specify upper bounds with
they must match the upper bounds in the Ports and Data Manager.
You can use the function
specify which dimensions vary. For example, the following statement
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
fixed size. Dimensions that correspond to ones or
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
the MATLAB Function block, they must match the upper
bounds in the Ports and Data Manager.
var_by_if defines matrix
fixed 2-by-2 dimensions before the first use (where the statement
= Y + u reads from
a variable-size matrix, allowing it to change size based on decision
logic in the
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
coder.varsize, the code generator
Y to be a fixed-size, 2-by-2 matrix. It
generates a size mismatch error.
A singleton dimension is a dimension for which
1. Singleton dimensions are fixed in size when:
You specify a dimension with an upper bound of 1 in
For example, in this function,
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,
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
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
a vector of ones, indicating that each dimension of
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
values inside each element of matrix
Here are other examples:
In this example,
data is a scalar variable
that contains matrix
A. Each element of matrix
a variable-size field
This expression defines field
B inside each
element of matrix
A inside each element of matrix