Signals, states, and block parameters that you create in a model appear in the generated code as variables. Control the way that the code declares and defines these variables.
Generate efficient code by reducing memory usage and specifying numeric data types. Control the naming, definition, and usage of data types.
Ease the integration of the generated code with your own code by specifying identifiers and file placement of declarations and definitions.
Manage access to signal data and specify parameter tunability.
Package signal and parameter data into structures.
Improve code readability and traceability.
How Generated Code Stores Internal Signal, State, and Parameter Data
To calculate output data from input data, the generated code must store some internal data in memory, such as block state data and nonscalar parameter data.
Standard Data Structures in the Generated Code
The generated code stores data, such as signals and states, in global structures. Use the structures to access and integrate with the data.
Use the Real-Time Model Data Structure
The real-time model data structure describes the generated model code and enables your code to interact with the generated code.
Use a data store to explicitly model a piece of shared global data in the generated code.
Parameter Data Types in the Generated Code
Optimize the generated code and generate code for specific processors by controlling the data types that store parameter data in computer memory.
Generate Local Variables with Localizable Storage Class
For signals, if possible, generate variables that are local to functions rather than in global storage.
Share Data Between Code Generated from Simulink, Stateflow, and MATLAB
Define data shared between Simulink, Stateflow, and MATLAB.
Air-Fuel Ratio Control System with Fixed-Point Data
This example shows how to generate and optimize the code for a fixed-point air-fuel ratio control system designed with Simulink® and Stateflow®.
Code Generation of Matrices and Arrays
Work with code that the code generator produces for matrices and arrays.
Generate Row-Major Code for S-Functions
Enable existing S-functions for row-major code generation by specifying the array layout.
Generate Row-Major Code for Model That Contains a MATLAB Function Block
Use coder.rowMajor
inside the MATLAB Function block to generate
row-major code.
Column-Major Layout to Row-Major Layout Conversion of Models with Lookup Table Blocks
Convert existing column-major model to row-major for code generation.
Row-Major Algorithms for Row-Major Array Layout
Generate code by using the row-major and column-major algorithms for row-major array layout.
Interpolation Algorithm for Row-Major Array Layout
Simulate and generate code by using the interpolation algorithm for row-major and column-major array layout.
Interpolation with Subtable Selection Algorithm for Row-Major Array Layout
Simulate and generate code by using the interpolation with subtable selection algorithm for row-major and column-major array layout.
Direct Lookup Table Algorithm for Row-Major Array Layout
Simulate and generate code by using the Direct Lookup Table algorithm for row-major and column-major array layout.
Dimension Preservation of Multidimensional Arrays
Preserve dimensions of multidimensional arrays in generated code.
Preserve Dimensions of Multidimensional Arrays in Generated Code
Preserve array dimensions for model data elements.
Create Tunable Calibration Parameter in the Generated Code
In the generated code, create tunable parameter data that you can access during rapid prototyping and calibration.
Reuse Parameter Data in Different Data Type Contexts
Reuse parameter data by creating a Simulink.Parameter
object or
numeric MATLAB® variable that you can use in different data type contexts.
Limitations for Block Parameter Tunability in Generated Code
Limitations can prevent a block parameter from appearing in the generated code as tunable, which means you cannot interact with the parameter value after compiling the code.
Access Signal, State, and Parameter Data During Execution
As you iteratively develop a model, capture output signal and state data that model execution generates. Tune parameter values during execution to observe results on the outputs.
Switch Between Sets of Parameter Values During Simulation and Code Execution
Switch between independent sets of values for the same block parameters by storing the sets in an array of structures.
Preserve Variables in Generated Code
As you iteratively develop a model, you can tune block parameter values during simulation or execution of generated code to observe the results on signal and state values.
Configure Packaging of Parameter Arguments in Generated Code
Customize the implementation of parameter arguments in generated code.
Control Signal and State Initialization in the Generated Code
Generate code that enables you to store tunable initial conditions in memory, for example, for modeling a system that shuts down and restarts.
Initialization of Signal, State, and Parameter Data in the Generated Code
To match the numerics of a simulation in Simulink®, the generated code assigns initial values to global data, especially for block states and parameters.
Control Data Type Names in Generated Code
Control the names of primitive, structure, and enumerated data types in the generated code.
Organize Data into Structures in Generated Code
Create structures of signal, state, and parameter data in the generated code.
Use Enumerated Data in Generated Code
Enumerated data is data that is restricted to a finite set of values. Create enumerations in the generated code.
Control File Placement of Custom Data Types
Integrate the generated code with your own code by placing
typedef
statements in generated and imported
files.
Specify Boolean and Data Type Limit Identifiers
Integrate the generated code with your code by specifying
the identifiers that correspond to Boolean false
and true
.
Also, specify the identifiers that correspond to data type limits,
which the generated code uses to determine overflows.