Because C and C++ are statically typed languages, MATLAB® Coder™ must determine the properties of all variables in the MATLAB files at compile time. To infer variable properties in MATLAB files, MATLAB Coder must be able to identify the properties of the inputs to the primary function, also known as the top-level or entry-point function. Therefore, if your primary function has inputs, you must specify the properties of these inputs, to MATLAB Coder. If your primary function has no input parameters, MATLAB Coder can compile your MATLAB file without modification. You do not need to specify properties of inputs to local functions or external functions called by the primary function.
If you use the tilde (~) character to specify unused function inputs:
In MATLAB Coder projects, if you want a different type to appear in the generated code, specify the type. Otherwise, the inputs default to real, scalar doubles.
When generating code with codegen
,
you must specify the type of these inputs using the -args
option.
If your primary function has inputs, you must specify the following properties for each input.
For | Specify properties | ||||
---|---|---|---|---|---|
Class | Size | Complexity | numerictype | fimath | |
Fixed-point inputs |
|
|
|
|
|
Each field in a structure input | |||||
Other inputs |
|
|
|
MATLAB Coder assigns the following default values for properties of primary function inputs.
Property | Default |
---|---|
class | double |
size | scalar |
complexity | real |
numerictype | No default |
fimath | MATLAB default fimath object |
Specifying Default Values for Structure Fields. In most cases, when you do not explicitly specify values for properties, MATLAB Coder uses defaults except for structure fields. The only way to name a field in a structure is to set at least one of its properties. Therefore, you might need to specify default values for properties of structure fields. For examples, see Specifying Class and Size of Scalar Structure and Specifying Class and Size of Structure Array.
Specifying Default fimath Values for MEX Functions. MEX functions generated with MATLAB
Coder use the
default fimath
value in effect
at compile time. If you do not specify a default fimath
value, MATLAB
Coder uses the MATLAB default fimath
.
The MATLAB factory default has the following properties:
RoundingMethod: Nearest OverflowAction: Saturate ProductMode: FullPrecision SumMode: FullPrecision CastBeforeSum: true
When running MEX functions that depend on the default fimath
value,
do not change this value during your MATLAB session. Otherwise,
you receive a run-time warning, alerting you to a mismatch between
the compile-time and run-time fimath
values.
For example, suppose that you define the following MATLAB function test
:
function y = test %#codegen y = fi(0);
The function test
constructs a fi
object
without explicitly specifying a fimath
object.
Therefore, test
relies on the default fimath
object
in effect at compile time. At the MATLAB prompt,
generate the MEX function text_mex
to use the factory
setting of the MATLAB default fimath
:
codegen test % codegen generates a MEX function, test_mex, % in the current folder
Next, run test_mex
to display the MATLAB default fimath
value:
test_mex ans = 0 DataTypeMode: Fixed-point: binary point scaling Signedness: Signed WordLength: 16 FractionLength: 15
Now create a local MATLAB fimath
value.
so you no longer use the default
setting:
F = fimath('RoundingMethod','Floor');
Finally, clear the MEX function from memory and rerun it:
clear test_mex test_mex
The mismatch is detected and causes an error:
??? This function was generated with a different default fimath than the current default. Error in ==> test_mex
Specifying Multiple Signatures for MEX Function. To generate a multisignature MEX function from an entry-point function,
provide multiple -args
specifications for the same
entry-point function. The generated MEX function works with the multiple
signatures that you provide during code generation. For more information on
multisignature MEX, see Generate One MEX Function That Supports Multiple Signatures.
The following table presents the class names supported by MATLAB Coder.
Class Name | Description |
---|---|
logical | Logical array of true and false values |
char | Character array |
int8 | 8-bit signed integer array |
uint8 | 8-bit unsigned integer array |
int16 | 16-bit signed integer array |
uint16 | 16-bit unsigned integer array |
int32 | 32-bit signed integer array |
uint32 | 32-bit unsigned integer array |
int64 | 64-bit signed integer array |
uint64 | 64–bit unsigned integer array |
single | Single-precision floating-point or fixed-point number array |
double | Double-precision floating-point or fixed-point number array |
struct | Structure array |
embedded.fi | Fixed-point number array |
When specifying the properties of primary inputs, follow these rules:
The order of elements in the cell array must correspond to the order in which inputs appear in the primary function signature. For example, the first element in the cell array defines the properties of the first primary function input.
To generate fewer arguments than those arguments that occur in the MATLAB function, specify properties for only the number of arguments that you want in the generated function.
If the MATLAB function has input arguments, to
generate a function that has no input
arguments, pass an empty cell array to -args
.
For each primary function input whose class is fixed
point (fi
), specify the input numerictype
and fimath
properties.
For each primary function input whose class is struct
,
specify the properties of each of its fields in the order that they
appear in the structure definition.
Method | Advantages | Disadvantages |
---|---|---|
Specify Properties of Entry-Point Function Inputs Using the App |
|
|
Define Input Properties by Example at the Command Line Note If you define input properties programmatically in the MATLAB file, you cannot use this method |
|
|
|
|
Specifying Properties of Primary Inputs by Example at the Command Line
Specifying Properties of Primary Fixed-Point Inputs by Example at the Command Line
The codegen
function provides a
command-line option -args
for specifying the properties of
primary (entry-point) function inputs as a cell array of example values or types.
The cell array can be a variable or literal array of constant values. Using this
option, you specify the properties of inputs at the same time as you generate code
for the MATLAB function with codegen
.
You can pass the output type from one entry-point function as the input to another. See Pass an Entry-Point Function Output as an Input. For information about specifying cell array inputs, see Specify Cell Array Inputs at the Command Line.
If you have a test function or script
that calls the entry-point MATLAB function with the required
types, you can use coder.getArgTypes
to
determine the types of the function inputs. coder.getArgTypes
returns
a cell array of coder.Type
objects
that you can pass to codegen
using the -args
option.
See Specifying General Properties of Primary Inputs for codegen
.
You can also create coder.Type
objects interactively by using the
Coder Type Editor. See Create and Edit Input Types by Using the Coder Type Editor.
When using the -args
command-line option
to define properties by example, follow these rules:
The order of elements in the cell array must correspond to the order in which inputs appear in the primary function signature. For example, the first element in the cell array defines the properties of the first primary function input.
To generate fewer arguments than those arguments that occur in the MATLAB function, specify properties for only the number of arguments that you want in the generated function.
If the MATLAB function has input arguments, to
generate a function that has no input arguments, pass an empty cell array to -args
.
For each primary function input whose class is fixed
point (fi
), specify the input numerictype
and fimath
properties.
For each primary function input whose class is struct
,
specify the properties of each of its fields in the order that they
appear in the structure definition.
Consider a MATLAB function that adds its two inputs:
function y = mcf(u,v) %#codegen y = u + v;
The following examples show how to specify different properties
of the primary inputs u
and v
by
example at the command line:
Use a literal cell array of constants to specify that both inputs are real scalar doubles:
codegen mcf -args {0,0}
Use a literal cell array of constants to specify that
input u
is an unsigned 16-bit, 1-by-4 vector and
input v
is a scalar double:
codegen mcf -args {zeros(1,4,'uint16'),0}
Assign sample values to a cell array variable to specify that both inputs are real, unsigned 8-bit integer vectors:
a = uint8([1;2;3;4]) b = uint8([5;6;7;8]) ex = {a,b} codegen mcf -args ex
To generate a MEX function or C/C++ code for fixed-point MATLAB code, you must install Fixed-Point Designer™ software.
Consider a MATLAB function that calculates the square root of a fixed-point number:
%#codegen function y = sqrtfi(x) y = sqrt(x);
To specify the properties of the primary fixed-point input x
by
example, follow these steps:
Define the numerictype
properties
for x
, for example:
T = numerictype('WordLength',32,... 'FractionLength',23,... 'Signed',true);
Define the fimath
properties for x
,
for example:
F = fimath('SumMode','SpecifyPrecision',... 'SumWordLength',32,... 'SumFractionLength',23,... 'ProductMode','SpecifyPrecision',... 'ProductWordLength',32,... 'ProductFractionLength',23);
Create a fixed-point variable with the numerictype
and fimath
properties
that you defined, for example:
myeg = { fi(4.0,T,F) };
Compile the function sqrtfi
using
the codegen
command, passing the variable myeg
as
the argument to the -args
option, for example:
codegen sqrtfi -args myeg;
If you know that your primary inputs do not change at run time, you can reduce overhead in the generated code by specifying that the primary inputs are constant values. Constant inputs are commonly used for flags that control how an algorithm executes and values that specify the sizes or types of data.
To specify that inputs are constants, use the -args
command-line
option with a coder.Constant
object.
To specify that an input is a constant with the size, class, complexity,
and value of constant_input
, use the following
syntax:
-args {coder.Constant(constant_input
)}
The code generator compiles constant function inputs into the generated code. In the generated C or C++ code, function signatures do not contain the constant inputs. By default, MEX function signatures contain the constant inputs. When you call a MEX function, you must provide values that match the compile-time values. You can control whether a MEX function signature includes constant inputs and whether the MEX function checks the values that you provide for constant inputs. See Constant Input Checking in MEX Functions.
Suppose that you define a structure tmp
in
the MATLAB workspace to specify the dimensions of a matrix:
tmp = struct('rows', 2, 'cols', 3);
The following MATLAB function rowcol
accepts
a structure input p
to define matrix y
:
function y = rowcol(u,p) %#codegen y = zeros(p.rows,p.cols) + u;
The following example shows how to specify that primary input u
is
a double scalar variable and primary input p
is
a constant structure:
codegen rowcol -args {0,coder.Constant(tmp)}
Variable-size data is data whose size might change at run time. MATLAB supports bounded and unbounded variable-size data for code generation.
Bounded variable-size data has fixed upper bounds. This data
can be allocated statically on the stack or dynamically on the heap.
Unbounded variable-size data does not have fixed upper
bounds. This data must be allocated on the heap. You can define inputs to have one or
more variable-size dimensions — and specify their upper bounds — using the
-args
option and coder.typeof
function:
-args {coder.typeof(example_value, size_vector, variable_dims)}
Same class and complexity as
example_value
Same size and upper bounds as
size_vector
Variable dimensions specified by
variable_dims
When you enable dynamic memory allocation, you can specify Inf
in
the size vector for dimensions with unknown upper bounds at compile
time.
When variable_dims
is a scalar, it
is applied to all the dimensions,
with the following exceptions:
If the dimension is 1 or 0, which are fixed.
If the dimension is unbounded, which is always variable size.
For more information,
see coder.typeof
and Generate Code for Variable-Size Data.
Write a function that computes the average of every n
elements
of a vector A
and stores them in a vector B
:
function B = nway(A,n) %#codegen % Compute average of every N elements of A and put them in B. coder.extrinsic('error'); if ((mod(numel(A),n) == 0) && (n>=1 && n<=numel(A))) B = ones(1,numel(A)/n); k = 1; for i = 1 : numel(A)/n B(i) = mean(A(k + (0:n-1))); k = k + n; end else B = zeros(1,0); error('n <= 0 or does not divide number of elements evenly'); end
Specify the first input A
as a
vector of double values. Its first dimension stays fixed in size and
its second dimension can grow to an upper bound of 100. Specify the
second input n
as a double scalar.
codegen -report nway -args {coder.typeof(0,[1 100],1),1}
As an alternative, assign the coder.typeof
expression
to a MATLAB variable, then pass the variable as an argument to -args
:
vareg = coder.typeof(0,[1 100],1) codegen -report nway -args {vareg, 0}