Stateflow

ml Data Type

Stateflow data of type ml is typed internally with the MATLAB type mxArray. This means that you can assign (store) any type of data available in Stateflow to a data of type ml. This includes any type of data defined in Stateflow or returned from MATLAB with the ml namespace operator or ml function.

The following features and limitations apply to Stateflow data of type ml.

• ml data can be initialized from the MATLAB workspace just like other data in Stateflow (see the Initialize from property in Setting Data Properties).
• Any numerical scalar or array of ml data in Stateflow can participate in any kind of unary operation and any kind of binary operation with any other data in Stateflow.

• If ml data participates in any numerical operation with other data, the size of the ml data must be inferred from the context in which it is used, just as return data from the ml namespace operator and ml function are. See Inferring Return Size for ml Expressions.

Note    The preceding feature does not apply to ml data storing MATLAB 64 bit integers. ml data can store 64 bit MATLAB integers but cannot be used in Stateflow action language.

• ml data cannot be defined with the scope Constant or specified as an array.

• These options are disabled in the data properties dialog and Stateflow Explorer for Stateflow data of type ml.

• ml data can be used in building a simulation target (sfun) but not in building an RTW target (rtw).
• If data of type ml contains an array, the elements of the array can be accessed through indexing with the following rules:
1. Only arrays with numerical elements can be indexed.
2. Numerical arrays can be indexed according to their dimension only.

• This means that only one-dimensional arrays can be accessed by a single index value. You cannot access a multidimensional array with a single index value.

3. The first index value for each dimension of an array is 1, and not 0, as in C-language arrays.

• In the examples that follow, mldata is a Stateflow data of type ml, ws_num_array is a 2-by-2 MATLAB workspace array with numerical values, and ws_str_array is a 2-by-2 MATLAB workspace array with string values.

  • mldata = ml.ws_num_array; /* OK */
    n21 = mldata[2][1]; /* OK for numerical data of type ml */
    n21 = mldata[3]; /* NOT OK for 2-by-2 array data */
    mldata = ml.ws_str_array; /* OK */
    s21 = mldata[2][1]; /* NOT OK for string data of type ml*/
    

• ml data cannot have a scope outside Stateflow; that is, it cannot be scoped as Input to Simulink or Output to Simulink.

Place Holder for Workspace Data

Both the ml namespace operator and the ml function can access data directly in the MATLAB workspace and return it to Stateflow. However, maintaining data in the MATLAB workspace can present Stateflow users with conflicts with other data already resident in the workspace. Consequently, with the ml data type, you can maintain ml data in Stateflow and use it for MATLAB computations in Stateflow action language.

As an example, in the following Stateflow action language statements, mldata1 and mldata2 are Stateflow data of type ml:

• mldata1 = ml.rand(3);
  mldata2 = ml.transpose(mldata1);
  

In the first line of this example, mldata1 receives the return value of the rand function in MATLAB, which, in this case, returns a 3-by-3 array of random numbers. Note that mldata1 is not specified as an array or sized in any way. It can receive any MATLAB workspace data or the return of any MATLAB function because it is defined as a Stateflow data of type ml.

In the second line of the example, mldata2, also of Stateflow data type ml, receives the transpose matrix of the matrix in mldata1. It is assigned the return value of the MATLAB function transpose in which mldata1 is the argument.

Note the differences in notation if the preceding example were to use MATLAB workspace data (wsdata1 and wsdata2) instead of Stateflow ml data to hold the generated matrices:

• ml.wsdata1 = ml.rand(3);
  ml.wsdata2 = ml.transpose(ml.wsdata);
  

In this case, each workspace data must be accessed through the ml namespace operator.

Which ml Should I Use?

Inferring Return Size for ml Expressions