SWIG and Scilab

# 39 SWIG and Scilab

- Preliminaries
- Running SWIG
  - Generating the module
  - Building the module
  - Loading the module
  - Using the module
  - Scilab command line options
- A basic tour of C/C++ wrapping
  - Overview
  - Identifiers
  - Functions
    - Argument passing
    - Multiple output arguments
  - Global variables
  - Constants and enumerations
    - Constants
    - Enumerations
  - Pointers
    - Utility functions
    - Null pointers:
  - Structures
  - C++ classes
  - C++ inheritance
  - C++ overloading
  - Pointers, references, values, and arrays
  - C++ templates
  - C++ operators
  - C++ namespaces
  - C++ exceptions
  - C++ STL
- Type mappings and libraries
  - Default primitive type mappings
  - Arrays
  - Pointer-to-pointers
  - Matrices
  - STL
- Module initialization
- Building modes
  - No-builder mode
  - Builder mode
- Generated scripts
  - Builder script
  - Loader script
- Other resources

Scilab is a scientific software package for numerical computations providing a powerful open computing environment for engineering and scientific applications that is mostly compatible with MATLAB. More information can be found at www.scilab.org.

This chapter explains how to use SWIG for Scilab. After this introduction, you should be able to generate with SWIG a Scilab external module from a C/C++ library.

## 39.1 Preliminaries

SWIG for Scilab supports Linux. Other operating sytems haven't been tested.

Scilab is supported from version 5.3.3 onwards. The forthcoming version 6, as of January 2015, is also supported.

SWIG for Scilab supports C language. C++ is partially supported. See A basic tour of C/C++ wrapping for further details.

## 39.2 Running SWIG

Let's see how to use SWIG for Scilab on a small example.
In this example we bind from C a function and a global variable into Scilab. The SWIG interface (stored in a file named `example.i`), is the following:

    %module example

    %inline %{
    double Foo = 3.0;

    int fact(int n) {
        if (n < 0) {
            return 0;
        }
        else if (n == 0) {
            return 1;
        }
        else {
            return n * fact(n-1);
        }
    }
    %}

Note: a code in an `%inline` section is both parsed and wrapped by SWIG, and inserted as is in the wrapper source file.

### 39.2.1 Generating the module

The module is generated using the `swig` executable and its `-scilab` option.

    $ swig -scilab example.i

This command generates two files:

- `example_wrap.c`: a C source file containing the wrapping code and also here the wrapped code (the `fact()` and `Foo` definitions)
- `loader.sce`: a Scilab script used to load the module into Scilab

Note: if the following error is returned:

    :1: Error: Unable to find 'swig.swg'
    :3: Error: Unable to find 'scilab.swg'

it may be because the SWIG library is not found. Check the `SWIG_LIB` environment variable or your SWIG installation.

Note: SWIG for Scilab can work in two modes related to the way the module is built, see the Building modes section for details. This example uses the `builder` mode.

The `swig` executable has several other command line options you can use. See Scilab command line options for further details.

### 39.2.2 Building the module

To be loaded in Scilab, the wrapper has to be built into a dynamic module (or shared library).

The commands to compile and link the wrapper (with `gcc`) into the shared library `libexample.so` are:

    $ gcc -fPIC -c -I/usr/local/include/scilab example_wrap.c
    $ gcc -shared example_wrap.o -o libexample.so

Note: we supposed in this example that the path to the Scilab include directory is `/usr/local/include/scilab` (which is the case in a Debian environment), this should be changed for another environment.

### 39.2.3 Loading the module

Loading a module is done by running the loader script in Scilab:

    --> exec loader.sce

Scilab should output the following messages:

    Shared archive loaded.
    Link done.

which means that Scilab has successfully loaded the shared library. The module functions and other symbols are now available in Scilab.

### 39.2.4 Using the module

In Scilab, the function `fact()` is simply called as following:

    --> fact(5)
    ans  =

        120.

For the `Foo` global variable, the accessors need to be used:

    --> Foo_get
    ans  =

        3.

    --> Foo_set(4);

    --> Foo_get
    ans  =

        4.

Note: for conciseness, we assume in the subsequent Scilab code examples that the modules have been beforehand built and loaded in Scilab.

### 39.2.5 Scilab command line options

The following table lists the Scilab specific command line options in addition to the generic SWIG options:

`-builder` | Generate the Scilab builder script
`-buildercflags <cflags>` | Add <cflags> to the builder compiler flags
`-builderldflags <ldflags>` | Add <ldlags> to the builder linker flags
`-buildersources <files>` | Add the (comma separated) files <files> to the builder sources
`-builderverbositylevel <level>` | Set the build verbosity level to <level> (default 0: off, 2: high)
`-builderflagscript <file>` | Use the Scilab script <file> to configure the compiler and linker flags
`-gatewayxml <gateway_id>` | Generate the gateway XML with the given <gateway_id>

These options can be displayed with:

    $ swig -scilab -help

## 39.3 A basic tour of C/C++ wrapping

### 39.3.1 Overview

SWIG for Scilab provides only a low-level C interface for Scilab (see Scripting Languages for the general approach to wrapping). This means that functions, structs, classes, variables, etc... are interfaced through C functions. These C functions are mapped as Scilab functions. There are a few exceptions, such as constants and enumerations, which can be wrapped directly as Scilab variables.

### 39.3.2 Identifiers

In Scilab 5.x, identifier names are composed of 24 characters maximum (this limitation should disappear from Scilab 6.0 onwards).
Thus long function or variable names may be truncated and this can cause ambiguities.

This happens especially when wrapping structs/classes, for which the wrapped function name is composed of the struct/class name and field names. In these cases, the %rename directive can be used to choose a different Scilab name.

### 39.3.3 Functions

Functions are wrapped as new Scilab built-in functions. For example:

    %module example

    %inline %{
    int fact(int n) {
      if (n > 1)
        return n * fact(n - 1);
      else
        return 1;
    }
    %}

creates a built-in function `fact(n)` in Scilab:

    --> fact(4)
    ans  =

        24.

#### 39.3.3.1 Argument passing

In the above example, the function parameter is a primitive type and is marshalled by value. So this function is wrapped without any additional customization. Argument values are converted between C types and Scilab types through type mappings. There are several default type mappings for primitive and complex types, described later in the Scilab typemaps section.

When a parameter is not passed by value, such as a pointer or reference, SWIG does not know if it is an input, output (or both) parameter. The INPUT, OUTPUT, INOUT typemaps defined in the `typemaps.i` library can be used to specify this.

Let's see this on two simple functions: `sub()` which has an output parameter, and `inc()`, which as input/output parameter:

    %module example

    %include <typemaps.i>

    extern void sub(int *INPUT, int *INPUT, int *OUTPUT);
    extern void inc(int *INOUT, int *INPUT);

    %{
    void sub(int *x, int *y, int *result) {
      *result = *x - *y;
    }
    void inc(int *x, int *delta) {
      *x = *x + *delta;
    }
    %}

In Scilab, parameters are passed by value. The output (and inout) parameters are returned as the result of the functions:

    --> sub(5, 3)
     ans  =

        2.

    --> inc(4, 3)
     ans  =

        7.

#### 39.3.3.2 Multiple output arguments

A C function can have several output parameters. They can all be returned as results of the wrapped function as Scilab supports multiple return values from a function when using the `typemaps.i` library. If the C function itself returns a result, this is returned first before the parameter outputs.

The example below shows this for a C function returning 2 values and a result:

    %module example

    %include <typemaps.i>

    int divide(int n, int d, int *OUTPUT, int *OUTPUT);

    %{
      int divide(int n, int d, int q*, int *r) {
        if (d != 0) {
          *q = n / d;
          *r = n % d;
          return 1;
        } else {
          return 0;
        }
      }
    %}

    --> [ret, q, r] = divide(20, 6)
     r  =

        2.
     q  =

        3.
     ret  =

        1.

### 39.3.4 Global variables

Global variables are manipulated through generated accessor functions. For example, for a given `Foo` global variable, SWIG actually generates two functions: `Foo_get()` to get the value of `Foo`, and `Foo_set()` to set the value. These functions are used as following:

    --> exec loader.sce;
    --> c = Foo_get();

    --> Foo_set(4);

    --> c
    c =

        3.

    --> Foo_get()
    ans  =

        4.

It works for variables of primitive type, but also for non-primitive types: arrays, and structs/classes which are described later. For now, an example with two global primitive arrays x and y is shown:

    %module example

    %inline %{
    int x[10];
    double y[7];

    void initArrays()
    {
      int i;
      for (i = 0; i < 10; i++)
        x[i] = 1;
      for (i = 0; i < 7; i++)
        y[i] = 1.0f;
    }
    %}

It works the same:

    --> exec loader.sce

    --> initArrays();
    --> x_get()
     ans  =

        1.    1.    1.    1.    1.    1.    1.    1.    1.    1.

    --> y_set([0:6] / 10);
    --> y_get()
     ans  =

        0.    0.1    0.2    0.3    0.4    0.5    0.6

### 39.3.5 Constants and enumerations

#### 39.3.5.1 Constants

There is not any constant in Scilab. By default, C/C++ constants are wrapped as getter functions. For example, for the following constants:

    %module example
    #define    ICONST      42
    #define    FCONST      2.1828
    #define    CCONST      'x'
    #define    CCONST2     '\n'
    #define    SCONST      "Hello World"
    #define    SCONST2     "\"Hello World\""

the following getter functions are generated:

    --> exec loader.sce;
    --> ICONST_get();
     ans  =

        42.

    --> FCONST_get();
     ans  =

        2.1828

    --> CCONST_get();
     ans  =

        x

    --> CCONST2_get();
     ans  =

    --> SCONST_get();
     ans  =

        Hello World

    --> SCONST2_get();
     ans  =

        "Hello World"

    --> EXPR_get();
     ans  =

        48.5484

    --> iconst_get();
     ans  =

        37.

    --> fconst_get();
     ans  =

        3.14

There is another mode in which constants are wrapped as Scilab variables. The variables are easier to use than functions, but the drawback is that variables are not constant and so can be modified.

This mode can be enabled/disabled at any time in the interface file with `%scilabconst()`, which works like all the other %feature directives. Use the argument value "1" to enable and "0" to disable this mode. For example in this mode the previous constants:

    %module example

    %scilabconst(1);
    #define    ICONST      42
    #define    FCONST      2.1828
    #define    CCONST      'x'
    #define    CCONST2     '\n'
    #define    SCONST      "Hello World"
    #define    SCONST2     "\"Hello World\""

are mapped to Scilab variables, with the same name:

    --> exec loader.sce;
    --> ICONST
     ans  =

        42

    --> FCONST
     ans  =

        2.1828

    --> CCONST
     ans  =

        x

    --> CCONST2
     ans  =

    --> SCONST
     ans  =

        Hello World

    --> SCONST2
     ans  =

        "Hello World"

    --> EXPR
     ans  =

        48.5484

    --> iconst
     ans  =

        37

    --> fconst
     ans  =

        3.14

#### 39.3.5.2 Enumerations

The wrapping of enums is the same as for constants. By default, enums are wrapped as getter functions. For example, with the following enumeration:

    %module example
    typedef enum { RED, BLUE, GREEN } color;

a getter function will be generated for each value of the enumeration:

    --> exec loader.sce;
    --> RED_get()
     ans  =

        0.

    --> BLUE_get()
     ans  =

        1.

    --> GREEN_get()
     ans  =

        2.

The `%scilabconst()` feature is also available for enumerations:

    %module example
    %scilabconst(1) color;
    typedef enum { RED, BLUE, GREEN } color;

    --> exec loader.sce;
    --> RED
     ans  =

        0.

    --> BLUE
     ans  =

        1.

    --> GREEN
     ans  =

        2.

### 39.3.6 Pointers

Pointers are supported by SWIG. A pointer can be returned from a wrapped C/C++ function, stored in a Scilab variable, and used in input argument of another C/C++ function.

Also, thanks to the SWIG runtime which stores informations about types, pointer types are tracked between exchanges Scilab and the native code. Indeed pointer types are stored alongside the pointer adress. A pointer is mapped to a Scilab structure (tlist), which contains as fields the pointer address and the pointer type (in fact a pointer to the type information structure in the SWIG runtime).
Why a native pointer is not mapped to a Scilab pointer (type name: "pointer", type ID: 128) ? The big advantage of mapping to a `tlist` is that it exposes a new type for the pointer in Scilab, type which can be acessed in Scilab with the typeof function, and manipulated using the overloading mechanism.

Notes:

- type tracking needs the SWIG runtime to be first initialized with the appropriate function (see the Module initialization section).
- for any reason, if a wrapped pointer type is unknown (or if the SWIG runtime is not initialized), SWIG maps it to a Scilab pointer. Also, a Scilab pointer is always accepted as a pointer argument of a wrapped function. The drawaback is that pointer type is lost.

Following is an example of the wrapping of the C `FILE*` pointer:

    %module example

    %{
    #include <stdio.h>
    %}

    FILE *fopen(const char *filename, const char *mode);
    int fputs(const char *, FILE *);
    int fclose(FILE *);

These functions can be used the same way as in C from Scilab:

    --> example_Init();

    --> f = fopen("junk", "w");
    --> typeof(f)
     ans  =

      _p_FILE

    --> fputs("Hello World", f);
    --> fclose(f);

Note: the type name `_p_FILE` which means "pointer to FILE".

The user of a pointer is responsible for freeing it or, like in the example, closing any resources associated with it (just as is required in a C program).

#### 39.3.6.1 Utility functions

As a scripting language, Scilab does not provide functions to manipulate pointers. However, in some cases it can be useful, such as for testing or debugging.

SWIG comes with two pointer utility functions:

- `SWIG_this()`: returns the address value of a pointer
- `SWIG_ptr()`: creates a pointer from an address value

Note: a pointer created by `SWIG_ptr()` does not have any type and is mapped as a Scilab pointer.

Following we use the utility functions on the previous example:

    --> f = fopen("junk", "w");
    --> fputs("Hello", f);
    --> addr = SWIG_this(f)
     ans  =

        8219088.

    --> p = SWIG_ptr(addr);
    --> typeof(p)
    ans  =

      pointer

    --> fputs(" World", p);
    --> fclose(f);

#### 39.3.6.2 Null pointers:

Using the previous `SWIG_this()` and `SWIG_ptr()`, it is possible to create and check null pointers:

    --> p = SWIG_ptr(0);
    --> SWIG_this(p) == 0
     ans  =

        T

### 39.3.7 Structures

Structs exist in Scilab, but C structs are not (at least in this version of SWIG) mapped to Scilab structs. A C structure is wrapped through low-level accessor functions, i.e. functions that give access to the member variables of this structure. In Scilab, a structure is manipulated through a pointer which is passed as an argument to the accessor functions.

Let's see it on an example of a struct with two members:

    %module example

    %inline %{

    typedef struct {
        int x;
        int arr[4];
    } Foo;

    %}

Several functions are generated:

- a constructor function `new_Foo()` which returns a pointer to a newly created struct `Foo`.
- two member getter functions `Foo_x_get()`, `Foo_arr_get()`, to get the values of `x` and `y` for the struct pointer (provided as the first parameter to these functions)
- two member setter functions `Foo_x_set()`, `Foo_arr_set()`, to set the values of `x` and `y` for the struct pointer (provided as the first parameter to these functions).
- a destructor function `delete_Foo()` to release the struct pointer.

Usage example:

    --> f = new_Foo();
    --> Foo_x_set(f, 100);
    --> Foo_x_get(f)
    ans  =

        100.

    --> Foo_arr_set(f, [0:3]);
    --> Foo_arr_get(f)
    ans  =

        0.    1.    2.    3.

    --> delete_Foo(f);

Members of a structure that are also structures are also accepted and wrapped as a pointer:

    %module example

    %inline %{

    typedef struct {
      int x;
    } Bar;

    typedef struct {
      Bar b;
    } Foo;

    %}

    --> b = new_Bar();
    --> Bar_x_set(b, 20.);

    --> f = new_Foo();
    --> Foo_b_set(f, b);

    --> b2 = Foo_b_get(f);
    --> Bar_x_get(b2);
    ans  =

        20.

Note: the pointer to the struct works as described in Pointers. For example, the type of the struct pointer can be get with `typeof`, as following:

    --> example_Init();
    --> b = new_Bar();
    --> typeof(b)
     ans  =

        _p_Bar
    --> delete_Bar(b);

### 39.3.8 C++ classes

Classes do not exist in Scilab. The classes are wrapped the same way as structs. Low-level accessor functions are generated for class members. Also, constructor and destructor functions are generated to create and destroy an instance of the class.

For example, the following class:

    %module example

    %inline %{

    class Point {
    public:
      int x, y;
      Point(int _x, int _y) : x(_x), y(_y) {}
      double distance(const Point& rhs) {
        return sqrt(pow(x-rhs.x, 2) + pow(y-rhs.y, 2));
      }
      void set(int _x, int _y) {
        x=_x;
        y=_y;
      }
    };

    %}

can be used in Scilab like this:

    --> p1 = Point_new(3, 5);
    --> p2 = Point_new(1, 2);
    --> p1.distance(p2)
    ans  =

        3.6056

    --> delete_Point(p1);
    --> delete_Point(p2);

Note: like structs, class pointers are mapped as described in Pointers. Let's give an example which shows that each class pointer type is a new type in Scilab that can be used for example (through overloading) to implement a custom print for the `Point` class:

    --> function %_p_Point_p(p)
    -->     mprintf('[%d, %d]\n', Point_x_get(p), Point_y_get(p));
    --> endfunction

    --> example_Init();
    --> p = new_Point(1, 2)
     p  =

    [1, 2]

    --> delete_Point(p);

### 39.3.9 C++ inheritance

Inheritance is supported. SWIG knows the inheritance relationship between classes.

A function is only generated for the class in which it is actually declared. But if one of its parameters is a class, any instance of a derived class is accepted as the argument.

This mechanism also applies for accessor functions: they are generated only in the class in which they are defined. But any instance of a derived class can be used as the argument to these accessor functions.

For example, let's take a base class `Shape` and two derived classes `Circle` and `Square`:

    %module example

    %inline %{

    class Shape {
    public:
      double x, y;
      void set_location(double _x, double _y) { x = _x; y = _y; }
      virtual double get_perimeter() { return 0; };
    };

    class Circle : public Shape {
    public:
      int radius;
      Circle(int _radius): radius(_radius) {};
      virtual double get_perimeter() { return 6.28 * radius; }
    };

    class Square : public Shape {
    public:
      int size;
      Square(int _size): size(_size) {};
      virtual double get_perimeter() { return 4 * size; }
    };

    %}

To set the location of the `Circle`, we have to use the function `set_location()` of the parent `Shape`. But we can use either use the `get_perimeter()` function of the parent class or the derived class:

    --> c = new_Circle(3);

    --> Shape_set_location(c, 2, 3);
    --> Shape_x_get(c)
     ans  =

        2.

    --> Circle_get_perimeter(c)
     ans  =

        18.84

    --> Shape_get_perimeter(c)
     ans  =

        18.84

### 39.3.10 C++ overloading

As explained in 6.15 SWIG provides support for overloaded functions and constructors.

As SWIG knows pointer types, the overloading works also with pointer types, here is is an example with a function `magnify` overloaded for the previous classes `Shape` and `Circle`:

    %module example

    void magnify(Square *square, double factor) {
        square->size *= factor;
    };

    void magnify(Circle *circle, double factor) {
        square->radius *= factor;
    };

    --> example_Init();
    --> c = new_Circle(3);
    --> s = new_Square(2);

    --> magnify(c, 10);
    --> Circle_get_radius(c)
     ans  =

       30;
    --> magnify(s, 10);
    --> Square_get_size(s)
     ans  =

       20;

### 39.3.11 Pointers, references, values, and arrays

In C++ objects can be passed by value, pointer, reference, or by an array:

    %module example

    %{
    #include <sciprint.h>
    %}

    %inline %{

    class Foo {
    public:
      Foo(int _x) : x(_x) {}
      int x;
    };

    void spam1(Foo *f)  { sciprint("%d\n", f->x); }   // Pass by pointer
    void spam2(Foo &f)  { sciprint("%d\n", f.x); }    // Pass by reference
    void spam3(Foo f)   { sciprint("%d\n", f.x); }    // Pass by value
    void spam4(Foo f[]) { sciprint("%d\n", f[0].x); } // Array of objects

    %}

In SWIG, there is no real distinction between these. So in Scilab, it is perfectly legal to do this:

    --> f = new_Foo()
    --> spam1(f)
    3
    --> spam2(f)
    3
    --> spam3(f)
    3
    --> spam4(f)
    3

Similar behaviour occurs for return values. For example, if you had functions like this:

    Foo *spam5();
    Foo &spam6();
    Foo  spam7();

All these functions will return a pointer to an instance of `Foo`. As the function `spam7` returns a value, new instance of `Foo` has to be allocated, and a pointer on this instance is returned.

### 39.3.12 C++ templates

As in other languages, function and class templates are supported in SWIG Scilab.

You have to tell SWIG to create wrappers for a particular template instantiation. The `%template` directive is used for this purpose. For example:

    %module example

    template<class T1, class T2, class T3>
    struct triplet {
      T1 first;
      T2 second;
      T3 third;
      triplet(const T1& a, const T2& b, const T3& c) {
        third = a; second = b; third = c;
      }
    };

    %template(IntTriplet) triplet<int, int, int>;

Then in Scilab:

    --> t = new_IntTriplet(3, 4, 1);

    --> IntTriplet_first_get(t)
     ans  =

        3.

    --> IntTriplet_second_get(t)
     ans  =

        4.

    --> IntTriplet_third_get(t)
     ans  =

        1.

    --> delete_IntTriplet(t);

More details on template support can be found in the templates documentation.

### 39.3.13 C++ operators

C++ operators are partially supported. Operator overloading exists in Scilab, but a C++ operator is not (in this version) wrapped by SWIG as a Scilab operator, but as a function. It is not automatic, you have to rename each operator (with the instruction `%rename`) with the suitable wrapper name.

Let's see it with an example of class with two operators `+` and `double()`:

    %module example

    %rename(plus) operator +;
    %rename(toDouble) operator double();

    %inline %{

    class Complex {
    public:
      Complex(double re, double im) : real(re), imag(im) {};

      Complex operator+(const Complex& other) {
        double result_real = real + other.real;
        double result_imaginary = imag + other.imag;
        return Complex(result_real, result_imaginary);
      }
      operator double() { return real; }
    private:
      double real;
      double imag;
    };

    %}

    --> c1 = new_Complex(3, 7);

    --> c2 = Complex_plus(c, new_Complex(1, 1));

    --> Complex_toDouble(c2)
     ans  =

        4.

### 39.3.14 C++ namespaces

SWIG is aware of C++ namespaces, but does not use it for wrappers. The module is not broken into submodules, nor do namespace appear in functions names. All the namespaces are all flattened in the module. For example with one namespace `Foo`:

    %module example

    %inline %{

    namespace foo {
      int fact(int n) {
        if (n > 1)
          return n * fact(n-1);
        else
          return 1;
      }

      struct Vector {
        double x, y, z;
      };
    };

    %}

In Scilab, there is no need to the specify the `Foo` namespace:

    --> fact(3)
     ans  =

       6.

    --> v = new_Vector();
    --> Vector_x_set(v, 3.4);
    --> Vector_y_get(v)
     ans  =

       0.

If your program has more than one namespace, name conflicts can be resolved using `%rename`. For example:

    %rename(Bar_spam) Bar::spam;

    namespace Foo {
      int spam();
    }

    namespace Bar {
      int spam();
    }

Note: the nspace feature is not supported.

### 39.3.15 C++ exceptions

Scilab does not natively support exceptions, but has errors. When an exception is thrown, SWIG catches it, and sets a Scilab error. An error message is displayed in Scilab. For example:

    %module example

    %inline %{
    void throw_exception() throw(char const *) {
      throw "Bye world !";
    }
    %}

    -->throw_exception()
      !--error 999
    SWIG/Scilab: Exception (char const *) occured: Bye world !

Scilab has a `try-catch` mechanism (and a similar instruction `execstr()`) to handle exceptions. It can be used with the `lasterror()` function as following:

    --> execstr('throw_exception()', 'errcatch');
     ans  =

        999.

    --> lasterror()
     ans  =

        SWIG/Scilab: Exception (char const *) occured: Bye world !

If the function has a `throw` exception specification, SWIG can automatically map the exception type and set an appropriate Scilab error message. It works for a few primitive types, and also for STL exceptions (the library `std_except.i` has to be included to get the STL exception support):

    %module example

    %include <std_except.i>

    %inline %{
    void throw_int() throw(int) {
      throw 12;
    }

    void throw_stl_invalid_arg(int i) throw(std::invalid_argument) {
      if (i < 0)
        throw std::invalid_argument("argument is negative.");
    }
    %}

    --> throw_int();
                !--error 999
    SWIG/Scilab: Exception (int) occured: 12

    -->throw_stl_invalid_arg(-1);
                              !--error 999
    SWIG/Scilab: ValueError: argument is negative.

More complex or custom exception types require specific exception typemaps to be implemented in order to specifically handle a thrown type. See the SWIG C++ documentation for more details.

### 39.3.16 C++ STL

The Standard Template Library (STL) is partially supported. See STL for more details.

## 39.4 Type mappings and libraries

### 39.4.1 Default primitive type mappings

The following table provides the equivalent Scilab type for C/C++ primitive types.

C/C++ type | Scilab type
bool | boolean
char | string
signed char | double or int8
unsigned char | double or uint8
short | double or int16
unsigned short | double or uint16
int | double or int32
unsigned int | double or uint32
long | double or int32
unsigned long | double or uint32
signed long long | not supported in Scilab 5.x
unsigned long long | not supported in Scilab 5.x
float | double
double | double
char * or char[] | string

Notes:

- In Scilab the `double` type is far more used than any integer type. This is why integer values (`int32`, `uint32`, ...) are automatically converted to Scilab `double` values when marshalled from C into Scilab. Additionally on input to a C function, Scilab `double` values are converted into the related integer type.
- When an integer is expected, if the input is a double, the value must be an integer, i.e. it must not have any decimal part, otherwise a SWIG value error occurs.
- In SWIG for Scilab 5.x, the `long long` type is not supported, since Scilab 5.x does not have a 64-bit integer type. The default behaviour is for SWIG to generate code that will give a runtime error if `long long` type arguments are used from Scilab.

### 39.4.2 Arrays

Typemaps are available by default for arrays. Primitive type arrays are automatically converted to/from Scilab matrices. Typemaps are also provided to handle members of a struct or class that are arrays.

In input, the matrix is usually one-dimensional (it can be either a row or column vector). But it can also be a two-dimensional matrix. Warning: in Scilab, the values are column-major ordered, unlike in C, which is row-major ordered.

The type mappings used for arrays is the same for primitive types, described earlier. This means that, if needed, a Scilab `double` vector is converted in input into the related C integer array and this C integer array is automatically converted on output into a Scilab `double` vector. Note that unlike scalars, no control is done for arrays when a `double` is converted into an integer.

The following example illustrates all this:

    %module example

    %#include <stdio.h>

    %inline %{

    void printArray(int values[], int len) {
      int i = 0;
      for (i = 0; i < len; i++) {
        printf("%s %d %s", i==0?"[":"", values[i], i==len-1?"]\n":"");
      }
    }
    %}

    --> printArray([0 1 2 3], 4)
    [ 0  1  2  3 ]

    --> printArray([0.2; -1.8; 2; 3.7], 4)
    [ 0  -1  2  3 ]

    --> printArray([0 1; 2 3], 4)
    [ 0  2  1  3 ]

    --> printArray([0; 1; 2; 3], 4)
    [ 0  1  2  3 ]

### 39.4.3 Pointer-to-pointers

There are no specific typemaps for pointer-to-pointers, they are are mapped as pointers in Scilab.

Pointer-to-pointers are sometimes used to implement matrices in C. The following is a an example of this:

    %module example
    %inline %{

    // Returns the matrix [1 2; 3 4];
    double **create_matrix() {
      double **M;
      int i;
      M = (double **) malloc(2 * sizeof(double *));
      for (i = 0; i < 2; i++) {
        M[i] = (double *) malloc(2 * sizeof(double));
        M[i][0] = 2 * i + 1;
        M[i][1] = 2 * i + 2;
      }
      return M;
    }

    // Gets the item M(i, j) value
    double get_matrix(double **M, int i, int j) {
      return M[i][j];
    }

    // Sets the item M(i, j) value to be val
    void set_matrix(double **M, int i, int j, double val) {
      M[i][j] = val;
    }

    // Prints a matrix (2, 2) to console
    void print_matrix(double **M, int nbRows, int nbCols) {
      int i, j;
      for (i = 0; i < 2; i++) {
        for (j = 0; j < 2; j++) {
          printf("%3g ", M[i][j]);
        }
        printf("\n");
      }
    }

    %}

These functions are used like this in Scilab:

    --> m = create_matrix();

    --> print_matrix(m);
       1.   2.
       3.   4.

    --> set_matrix(m, 1, 1, 5.);

    --> get_matrix(m, 1, 1)
     ans  =

        5.

### 39.4.4 Matrices

The `matrix.i` library provides a set of typemaps which can be useful when working with one-dimensional and two-dimensional matrices.

In order to use this library, just include it in the interface file:

      %include <matrix.i>

Several typemaps are available for the common Scilab matrix types:

- `double`
- `int`
- `char *`
- `bool`

For example: for a matrix of `int`, we have the typemaps, for input:

- `(int *IN, int IN_ROWCOUNT, int IN_COLCOUNT)`
- `(int IN_ROWCOUNT, int IN_COLCOUNT, int *IN)`
- `(int *IN, int IN_SIZE)`
- `(int IN_SIZE, int *IN)`

and output:

- `(int **OUT, int *OUT_ROWCOUNT, int *OUT_COLCOUNT)`
- `(int *OUT_ROWCOUNT, int *OUT_COLCOUNT, int **OUT)`
- `(int **OUT, int *OUT_SIZE)`
- `(int *OUT_SIZE, int **OUT)`

They marshall a Scilab matrix type into the appropriate 2 or 3 C parameters. The following is an example using the typemaps in this library:

    %module example

    %include <matrix.i>

    %apply (int *IN, int IN_ROWCOUNT, int IN_COLCOUNT) { (int *matrix, int matrixNbRow, int matrixNbCol) };
    %apply (int **OUT, int *OUT_ROWCOUNT, int *OUT_COLCOUNT) { (int **outMatrix, int *outMatrixNbRow, int *outMatrixNbCol) };

    %inline %{

    void absolute(int *matrix, int matrixNbRow, int matrixNbCol,
      int **outMatrix, int *outMatrixNbRow, int *outMatrixNbCol) {
      int i, j;
      *outMatrixNbRow = matrixNbRow;
      *outMatrixNbCol = matrixNbCol;
      *outMatrix = malloc(matrixNbRow * matrixNbCol * sizeof(int));
      for (i=0; i < matrixNbRow * matrixNbCol; i++) {
        (*outMatrix)[i] = matrix[i] > 0 ? matrix[i]:-matrix[i];
      }
    }

    %}

    --> absolute([-0 1 -2; 3 4 -5])
     ans  =

        0.    1.    2.
        3.    4.    5.

The remarks made earlier for arrays also apply here:

- The values of matrices in Scilab are column-major orderered,
- There is no control while converting `double` values to integers, `double` values are truncated without any checking or warning.

### 39.4.5 STL

The STL library wraps some containers defined in the STL (Standard Template Library), so that they can be manipulated in Scilab. This library also provides the appropriate typemaps to use the containers in functions and variables.

The list of wrapped sequence containers are:

- `std::vector`
- `std::list`
- `std::deque`

And associative containers are:

- `std::set`
- `std::multiset`

Typemaps are available for the following container types:

- `double`
- `float`
- `int`
- `string`
- `bool`
- `pointer`

Containers of other item types are not supported. Using them does not break compilation, but provokes a runtime error. Containers of enum are not supported yet.

In order to use the STL, the library must first be included in the SWIG interface file:

    %include <stl.i>

Then for each container used, the appropriate template must be instantiated, in the `std` namespace:

    namespace std {
        %template(IntVector)    vector<int>;
        %template(DoubleVector) vector<double>;
    }

Additionally, the module initialization function has to be executed first in Scilab, so that all the types are known to Scilab. See the Module initialization section for more details.

Because in Scilab matrices exist for basic types only, a sequence container of pointers is mapped to a Scilab list. For other item types (double, int, string...) the sequence container is mapped to a Scilab matrix.

The first example below shows how to create a vector (of `int`) in Scilab, add some values to the vector and pass it as an argument of a function. It also shows, thanks to the typemaps, that we can also pass a Scilab matrix of values directly into the function:

    %module example

    %include <stl.i>

    namespace std {
      %template(IntVector) vector<int>;
    }

    %{
    #include <numeric>
    %}

    %inline %{

    double average(std::vector<int> v) {
      return std::accumulate(v.begin(), v.end(), 0.0) / v.size();
    }

    %}

    --> example_Init();

    --> v = new_IntVector();

    --> for i = 1:4
    -->     IntVector_push_back(v, i);
    --> end;

    --> average(v)
     ans  =

        2.5

    --> average([0 1 2 3])
     ans  =

        2.5

    --> delete_IntVector();

In the second example, a set of struct (`Person`) is wrapped. A function performs a search in this set, and returns a subset. As one can see, the result in Scilab is a list of pointers:

    %module example

    %include <stl.i>

    %{
    #include <string>
    %}

    %inline %{

    struct Person {
      Person(std::string _name, int _age) : name(_name), age(_age) {};
      std::string name;
      int age;
    };
    typedef Person * PersonPtr;

    %}

    namespace std {
      %template(PersonPtrSet) set<PersonPtr>;
    }

    %inline %{

    std::set<PersonPtr> findPersonsByAge(std::set<PersonPtr> persons, int minAge, int maxAge) {
      std::set<PersonPtr> foundPersons;
      for (std::set<PersonPtr>::iterator it = persons.begin(); it != persons.end(); it++) {
        if (((*it)->age >= minAge) && ((*it)->age <= maxAge)) {
          foundPersons.insert(*it);
        }
      }
      return foundPersons;
    }

    %}

    --> example_Init();

    --> joe = new_Person("Joe", 25);
    --> susan = new_Person("Susan", 32);
    --> bill = new_Person("Bill", 50);

    --> p = new_PersonPtrSet();
    --> PersonPtrSet_insert(p, susan);
    --> PersonPtrSet_insert(p, joe);
    --> PersonPtrSet_insert(p, bill);

    --> l = findPersonsByAge(p, 20, 40);

    --> size(l)
     ans  =

        2.

    --> Person_name_get(l(1))
    ans  =

        Susan

    --> Person_name_get(l(2))
     ans  =

        Joe

    --> delete_PersonPtrSet(p);

## 39.5 Module initialization

The wrapped module contains an initialization function to:

- initialize the SWIG runtime, needed for pointer type tracking or when working with the STL
- initialize the module constants and enumerations declared with `%scilabconst()`

This initialization function should be executed at the start of a script, before the wrapped library has to be used.

The function has the name of the module suffixed by `_Init`. For example, to initialize the module `example`:

    --> example_Init();

## 39.6 Building modes

The mechanism to load an external module in Scilab is called Dynamic Link and works with dynamic modules (or shared libraries, `.so` files).

To produce a dynamic module, when generating the wrapper, there are two possibilities, or build modes:

- the `nobuilder` mode, this is the default mode in SWIG. The user is responsible of the build.
- the `builder` mode. In this mode, Scilab is responsible of building.

### 39.6.1 No-builder mode

In this mode, used by default, SWIG generates the wrapper sources, which have to be manually compiled and linked. A loader script `loader.sce` is also produced, this one is executed further in Scilab to load the module.

This mode is the best option to use when you have to integrate the module build into a larger build process.

### 39.6.2 Builder mode

In this mode, in addition to the wrapper sources, SWIG produces a builder Scilab script (`builder.sce`), which is executed in Scilab to build the module. In a few words, the Scilab `ilib_build()` command is used, which produces the shared library file, and the loader script `loader.sce` (and also a cleaner script `cleaner.sce`).

An advantage of this mode is that it hides all the complexity of the build and other platform issues. Also it allows the module to conform to a Scilab external module convention which is that an external module should be simply built by calling a builder script.

The builder mode is activated with the `-builder` SWIG option. In this mode, the following SWIG options may be used to setup the build:

- `-buildersources`: to add sources to the build (several files must be separated by a comma)
- `-buildercflags`: to add flags to the builder compiler flags, for example to set library dependencies include paths
- `-builderldflags`: to add flags to the linker flags, for example to set library dependency names and paths

Let's give an example how to build a module `example`, composed of two sources, and using a library dependency:

- the sources are `baa1.c` and `baa2.c` (and are stored in in the current directory)
- the library is `libfoo` in `/opt/foo` (headers stored in `/opt/foo/include`, and shared library in `/opt/foo/lib`)

The command is:

    $ swig -scilab -builder -buildercflags -I/opt/foo/include -builderldflags "-L/opt/foo/lib -lfoo" -buildersources baa1.cxx, baa2.cxx example.i

## 39.7 Generated scripts

In this part we give some details about the generated Scilab scripts.

### 39.7.1 Builder script

`builder.sce` is the name of the builder script generated by SWIG in `builder` mode. It contains code like this:

    ilib_name = "examplelib";
    files = ["example_wrap.c"];
    libs = [];
    table = ["fact", "_wrap_fact";"Foo_set", "_wrap_Foo_set";"Foo_get", "_wrap_Foo_get";];
    ilib_build(ilib_name, table, files, libs);

`ilib_build(lib_name, table, files, libs)` is used to create shared libraries, and to generate a loader file used to dynamically load the shared library into Scilab.

- `ilib_name`: a character string, the generic name of the library without path and extension.
- `files`: string matrix containing objects files needed for shared library creation.
- `libs`: string matrix containing extra libraries needed for shared library creation.
- `table`: two column string matrix containing a table of pairs of 'scilab function name', 'C function name'.

### 39.7.2 Loader script

The loader script is used to load in Scilab all the module functions. When loaded, these functions can be used as other Scilab functions.

The loader script `loader.sce` contains code similar to:

    // ------------------------------------------------------
    // generated by builder.sce: Please do not edit this file
    // ------------------------------------------------------

    libexamplelib_path = get_file_path('loader.sce');
    list_functions = [             'fact';
                'Foo_set';
                'Foo_get';
    ];
    addinter(libexamplelib_path+'/libexamplelib.so', 'libexamplelib', list_functions);
    // remove temp. variables on stack
    clear libexamplelib_path;
    clear list_functions;
    clear get_file_path;
    // ------------------------------------------------------

`addinter(files, spname, fcts)` performs dynamic linking of a compiled C interface function.

- `files`: a character string or a vector of character strings defining the object files (containing the C interface functions) to link with.
- `spname`: a character string. Name of interface routine entry point.
- `fcts`: vector of character strings. The name of new Scilab function.

## 39.8 Other resources

- Example use cases can be found in the `Examples/scilab` directory.
- The test suite in the `Examples/test-suite/scilab` can be another source of useful use cases.
- The Scilab API is used in the generated code and is a useful reference when examining the output.
- This guide describes the Scilab external modules structure and files, in particular the files that are generated by SWIG for Scilab.