Before you use the Fixed-Point Tool to propose data types for your Simulink® model, consider how automatic data typing affects your model:
The Fixed-Point Tool proposes new data types for objects in your model. If you choose to apply the proposed data types, the tool changes the data types in your model. Before using the Fixed-Point Tool, back up your model and workspace variables to ensure that you can recover your original data type settings and capture the fixed-point instrumentation and data type override settings using the Advanced System Settings dialog.
For more information, see Best Practices for Fixed-Point Workflow.
Before proposing data types, verify that you can update diagram successfully . Sometimes, changing the data types in your model results in subsequent update diagram errors. Immediately before and after applying data type proposals, it is good practice to test update diagram again. This practice enables you to fix any errors before making further modifications to your model.
For more information, see Update Diagram and Run Simulation (Simulink).
The Fixed-Point Tool alerts you to potential issues with proposed data types for each object in your model:
If the Fixed-Point Tool detects that the proposed data type introduces data type errors when applied to an object, the tool marks the object with an error, . You must inspect this proposal and fix the problem in the Simulink model. After fixing the problem, rerun the simulation and generate a proposal again to confirm that you have resolved the issue.
For more information, see Examine Results to Resolve Conflicts.
If the Fixed-Point Tool detects that the proposed data type poses potential issues for an object, the tool marks the object with a yellow caution, . Review the proposal before accepting it.
If the Fixed-Point Tool detects that the proposed data type poses no issues for an object, the tool marks the object with a green check, .
Caution: The Fixed-Point Tool does not detect all potential data type issues. If the Fixed-Point Tool does not detect any issues for your model, it is still possible to experience subsequent data type propagation issues. For more information, see Models That Might Cause Data Type Propagation Errors.