## Write Fully Inlined S-Functions with mdlRTW Routine

You can inline more complex S-functions by using the S-function `mdlRTW`

routine. The `mdlRTW`

routine
provides the code generation process with more information about how the S-function is
to be inlined by creating a parameter record of a non-tunable parameter for use with a
TLC file. The `mdlRTW`

routine places information in the

file. The
* model*.rtw

`mdlRTW`

function is described in the text file
`matlabroot`

/simulink/src/sfuntmpl_doc.c

.To use the `mdlRTW`

function, take steps to create a direct-index
lookup S-function. Lookup tables are collections of ordered data points of a function.
Typically, these tables use some interpolation scheme to approximate values of the
associated function between known data points. To incorporate the example lookup table
algorithm into a Simulink^{®} model, the first step is to write an S-function that executes the
algorithm in `mdlOutputs`

. To produce the most efficient code, the
next step is to create a corresponding TLC file to eliminate computational overhead and
improve the speed of the lookup computations.

The Simulink product provides support for general-purpose lookup 1-D, 2-D, and n-D
algorithms. You can use these algorithms as they are or create a custom lookup table
S-function to fit your requirements. You can create a 1-D lookup S-function,
`sfun_directlook.c`

, and its corresponding inlined
`sfun_directlook.tlc`

file (see Target Language Compiler for more details). You can:

Error check of S-function parameters.

Cache information for the S-function that does not change during model execution.

Use the

`mdlRTW`

function to customize the code generator to produce the optimal code for a given set of block parameters.Create a

`TLC`

file for an S-function that either fully inlines the lookup table code or calls a wrapper function for the lookup table algorithm.

### S-Function RTWdata

`RTWdata`

is a property of blocks, which can be used by the
Target Language Compiler when inlining an S-function. `RTWdata`

is
a structure of character vectors that you can attach to a block.
`RTWdata`

is saved with the model and placed in the

file when you
generate code. For example, this set of MATLAB* model*.rtw

^{®}commands:

mydata.field1 = 'information for field1'; mydata.field2 = 'information for field2'; set_param(gcb,'RTWdata',mydata) get_param(gcb,'RTWdata')

produces this result:

ans = field1: 'information for field1' field2: 'information for field2'

The information for the associated S-Function block inside the

file is:* model*.rtw

Block { Type "S-Function" RTWdata { field1 "information for field1" field2 "information for field2" }

**Note**

`RTWdata`

is saved in the model file for S-functions that are
not linked to a library. However, `RTWdata`

is **not persistent** for S-Function blocks that are linked
to a library.

### Direct-Index Lookup Table Algorithm

The 1-D lookup table block provided in the Simulink library uses interpolation or extrapolation when computing outputs. In
this example, you create a lookup table that directly indexes the output vector
(*y*-data vector) based on the current input
(*x*-data) point.

This direct 1-D lookup example computes an approximate solution
*p(x)*to a partially known function *f(x)*
at *x=x0*, given data point pairs *(x,y)* in
the form of an *x*-data vector and a *y*-data
vector. For a given data pair (for example, the *i'th* pair),
*y_i = f(x_i)*. It is assumed that the
*x*-data values are monotonically increasing. If
*x0* is outside the range of the *x*-data
vector, the first or last point is returned.

The parameters to the S-function are:

XData, YData, XEvenlySpaced

`XData`

and `YData`

are double vectors of equal
length representing the values of the unknown function.
`XDataEvenlySpaced`

is a scalar, `0.0`

for
false and `1.0`

for true. If the `XData`

vector is
evenly spaced, `XDataEvenlySpaced`

is `1.0`

and
more efficient code is generated.

The graph shows how the parameters `XData=[1:6]`

and
`YData=[1,2,7,4,5,9]`

are handled. For example, if the input
(*x*-value) to the S-Function block is 3, the output
(*y*-value) is 7.

### Direct-Index Lookup Table Example

Improve the lookup table by inlining a direct-index S-function with a TLC file. This direct-index lookup table S-function does not require a TLC file. The example uses a TLC file for the direct-index lookup table S-function to reduce the code size and increase efficiency of the generated code.

Implementation of the direct-index algorithm with an inlined TLC file requires the
S-function main module, `sfun_directlook.c`

and a corresponding `lookup_index.c`

module. The `lookup_index.c`

module contains the `GetDirectLookupIndex`

function that is used
to locate the index in the `XData`

for the current
`x`

input value when the `XData`

is unevenly
spaced. The `GetDirectLookupIndex`

routine is called from the
S-function and the generated code. The example uses the wrapper concept for sharing
C/C++ code between Simulink MEX-files and the generated code.

If the `XData`

is evenly spaced, then both the S-function main
module and the generated code contain the lookup algorithm to compute the
*y*-value of a given *x*-value because the
algorithm is short.

The inlined TLC file is `sfun_directlook.tlc`

, which is used to either perform a
wrapper call or embed the optimal C/C++ code for the S-function. (See the example in
mdlRTW Usage).

### Error Handling

In `sfun_directlook.tlc`

, the
`mdlCheckParameters`

routine verifies that:

The new parameter settings are valid.

`XData`

and`YData`

are vectors of the same length containing real, finite numbers.`XDataEvenlySpaced`

is a scalar.The

`XData`

vector is a monotonically increasing vector and evenly spaced.

The `mdlInitializeSizes`

function explicitly calls
`mdlCheckParameters`

after it verifies the number of
parameters passed to the S-function. After the Simulink engine calls `mdlInitializeSizes`

, it then calls
`mdlCheckParameters`

whenever you change the parameters or
reevaluate them.

### User Data Caching

In `sfun_directlook.tlc`

, the `mdlStart`

routine shows how to cache information that does not change during the simulation or
while the generated code is executing. The example caches the value of the
`XDataEvenlySpaced`

parameter in `UserData`

, a
field of the `SimStruct`

. The following line in
`mdlInitializeSizes`

instructs the Simulink engine to disallow changes to
`XDataEvenlySpaced`

.

ssSetSFcnParamTunable(S, iParam, SS_PRM_NOT_TUNABLE);

During execution, `mdlOutputs`

accesses the value of
`XDataEvenlySpaced`

from `UserData`

rather
than calling the `mxGetPr`

MATLAB API function.

### mdlRTW Usage

The code generator calls the `mdlRTW`

routine while generating
the

file. To produce optimal
code for your Simulink model, you can add information to the
* model*.rtw

`model`

.rtw

file about the mode
in which your S-Function block is operating.The example adds parameter settings to the

file. The parameter
settings do not change during execution. In this case, the
* model*.rtw

`XDataEvenlySpaced`

S-function parameter cannot change during
execution (`ssSetSFcnParamTunable`

was specified as false
(`0`

) for it in `mdlInitializeSizes`

). The
parameter setting (`XSpacing`

) uses the function
`ssWriteRTWParamSettings`

.Because `xData`

and `yData`

are registered as
run-time parameters in `mdlSetWorkWidths`

, the code generator
writes to the

file
automatically.* model*.rtw

Before examining the S-function and the inlined TLC file, consider the generated code for this model.

The model uses evenly spaced `XData`

in the top S-Function block
and unevenly spaced `XData`

in the bottom S-Function block. When
creating this model, specify the following commands for each S-Function
block.

set_param('sfun_directlook_ex/S-Function','SFunctionModules','lookup_index') set_param('sfun_directlook_ex/S-Function1','SFunctionModules','lookup_index')

The build process uses the module `lookup_index.c`

when creating
the executable.

When generating code for this model, the code generator uses the S-function
`mdlRTW`

method to generate a

file with the value
* model*.rtw

`EvenlySpaced`

for the `XSpacing`

parameter
for the top S-Function block and the value `UnEvenlySpaced`

for the
`XSpacing`

parameter for the bottom S-Function block. The
TLC-file uses the value of `XSpacing`

to determine what algorithm
to include in the generated code. The generated code contains the lookup algorithm
when the `XData`

is evenly spaced, but calls the
`GetDirectLookupIndex`

routine when the
`XData`

is unevenly spaced. The generated
`model`

.c

or
`model`

.cpp

code for the lookup
table example model is similar to this code:/* * sfun_directlook_ex.c * * Code generation for Simulink model * "sfun_directlook_ex.slx". * ... */ #include "sfun_directlook_ex.h" #include "sfun_directlook_ex_private.h" /* External outputs (root outports fed by signals with auto storage) */ ExtY_sfun_directlook_ex_T sfun_directlook_ex_Y; /* Real-time model */ RT_MODEL_sfun_directlook_ex_T sfun_directlook_ex_M_; RT_MODEL_sfun_directlook_ex_T *const sfun_directlook_ex_M = &sfun_directlook_ex_M_; /* Model output function */ void sfun_directlook_ex_output(void) { /* local block i/o variables */ real_T rtb_SFunction; real_T rtb_SFunction1; /* Sin: '<Root>/Sine Wave' */ rtb_SFunction1 = sin(sfun_directlook_ex_M->Timing.t[0]);/* Code that is inlined for the top S-function block in the * sfun_directlook_ex model *//* S-Function (sfun_directlook): '<Root>/S-Function' */ { const real_T *xData = sfun_directlook_ex_ConstP.SFunction_XData; const real_T *yData = sfun_directlook_ex_ConstP.SFunction_YData; real_T spacing = xData[1] - xData[0]; if (rtb_SFunction1 <= xData[0] ) { rtb_SFunction = yData[0]; } else if (rtb_SFunction1 >= yData[20] ) { rtb_SFunction = yData[20]; } else { int_T idx = (int_T)( ( rtb_SFunction1 - xData[0] ) / spacing ); rtb_SFunction = yData[idx]; } } /* Outport: '<Root>/Out1' */ sfun_directlook_ex_Y.Out1 = rtb_SFunction;/* Code that is inlined for the bottom S-function block in the * sfun_directlook_ex model *//* S-Function (sfun_directlook): '<Root>/S-Function1' */ { const real_T *xData = sfun_directlook_ex_ConstP.SFunction1_XData; const real_T *yData = sfun_directlook_ex_ConstP.SFunction1_YData; int_T idx; idx = GetDirectLookupIndex(xData, 5, rtb_SFunction1); rtb_SFunction1 = yData[idx]; } /* Outport: '<Root>/Out2' */ sfun_directlook_ex_Y.Out2 = rtb_SFunction1; } /* Model update function */ void sfun_directlook_ex_update(void) { /* signal main to stop simulation */ { /* Sample time: [0.0s, 0.0s] */ if ((rtmGetTFinal(sfun_directlook_ex_M)!=-1) && !((rtmGetTFinal(sfun_directlook_ex_M)-sfun_directlook_ex_M->Timing.t[0]) > sfun_directlook_ex_M->Timing.t[0] * (DBL_EPSILON))) { rtmSetErrorStatus(sfun_directlook_ex_M, "Simulation finished"); } } /* Update absolute time for base rate */ /* The "clockTick0" counts the number of times the code of this task has * been executed. The absolute time is the multiplication of "clockTick0" * and "Timing.stepSize0". Size of "clockTick0" ensures timer will not * overflow during the application lifespan selected. * Timer of this task consists of two 32 bit unsigned integers. * The two integers represent the low bits Timing.clockTick0 and the high bits * Timing.clockTickH0. When the low bit overflows to 0, the high bits increment. */ if (!(++sfun_directlook_ex_M->Timing.clockTick0)) { ++sfun_directlook_ex_M->Timing.clockTickH0; } sfun_directlook_ex_M->Timing.t[0] = sfun_directlook_ex_M->Timing.clockTick0 * sfun_directlook_ex_M->Timing.stepSize0 + sfun_directlook_ex_M->Timing.clockTickH0 * sfun_directlook_ex_M->Timing.stepSize0 * 4294967296.0; } ...