This file is indexed.

/usr/lib/python3/dist-packages/openturns/experiment.py is in python3-openturns 1.5-7build2.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

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# This file was automatically generated by SWIG (http://www.swig.org).
# Version 2.0.12
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.




"""
Designs of experiments.
"""


from sys import version_info
if version_info >= (2,6,0):
    def swig_import_helper():
        from os.path import dirname
        import imp
        fp = None
        try:
            fp, pathname, description = imp.find_module('_experiment', [dirname(__file__)])
        except ImportError:
            import _experiment
            return _experiment
        if fp is not None:
            try:
                _mod = imp.load_module('_experiment', fp, pathname, description)
            finally:
                fp.close()
            return _mod
    _experiment = swig_import_helper()
    del swig_import_helper
else:
    import _experiment
del version_info
try:
    _swig_property = property
except NameError:
    pass # Python < 2.2 doesn't have 'property'.
def _swig_setattr_nondynamic(self,class_type,name,value,static=1):
    if (name == "thisown"): return self.this.own(value)
    if (name == "this"):
        if type(value).__name__ == 'SwigPyObject':
            self.__dict__[name] = value
            return
    method = class_type.__swig_setmethods__.get(name,None)
    if method: return method(self,value)
    if (not static):
        self.__dict__[name] = value
    else:
        raise AttributeError("You cannot add attributes to %s" % self)

def _swig_setattr(self,class_type,name,value):
    return _swig_setattr_nondynamic(self,class_type,name,value,0)

def _swig_getattr(self,class_type,name):
    if (name == "thisown"): return self.this.own()
    method = class_type.__swig_getmethods__.get(name,None)
    if method: return method(self)
    raise AttributeError(name)

def _swig_repr(self):
    try: strthis = "proxy of " + self.this.__repr__()
    except: strthis = ""
    return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)

try:
    _object = object
    _newclass = 1
except AttributeError:
    class _object : pass
    _newclass = 0


class SwigPyIterator(_object):
    __swig_setmethods__ = {}
    __setattr__ = lambda self, name, value: _swig_setattr(self, SwigPyIterator, name, value)
    __swig_getmethods__ = {}
    __getattr__ = lambda self, name: _swig_getattr(self, SwigPyIterator, name)
    def __init__(self, *args, **kwargs): raise AttributeError("No constructor defined - class is abstract")
    __repr__ = _swig_repr
    __swig_destroy__ = _experiment.delete_SwigPyIterator
    __del__ = lambda self : None;
    def value(self): return _experiment.SwigPyIterator_value(self)
    def incr(self, n=1): return _experiment.SwigPyIterator_incr(self, n)
    def decr(self, n=1): return _experiment.SwigPyIterator_decr(self, n)
    def distance(self, *args): return _experiment.SwigPyIterator_distance(self, *args)
    def equal(self, *args): return _experiment.SwigPyIterator_equal(self, *args)
    def copy(self): return _experiment.SwigPyIterator_copy(self)
    def next(self): return _experiment.SwigPyIterator_next(self)
    def __next__(self): return _experiment.SwigPyIterator___next__(self)
    def previous(self): return _experiment.SwigPyIterator_previous(self)
    def advance(self, *args): return _experiment.SwigPyIterator_advance(self, *args)
    def __eq__(self, *args): return _experiment.SwigPyIterator___eq__(self, *args)
    def __ne__(self, *args): return _experiment.SwigPyIterator___ne__(self, *args)
    def __iadd__(self, *args): return _experiment.SwigPyIterator___iadd__(self, *args)
    def __isub__(self, *args): return _experiment.SwigPyIterator___isub__(self, *args)
    def __add__(self, *args): return _experiment.SwigPyIterator___add__(self, *args)
    def __sub__(self, *args): return _experiment.SwigPyIterator___sub__(self, *args)
    def __iter__(self): return self
SwigPyIterator_swigregister = _experiment.SwigPyIterator_swigregister
SwigPyIterator_swigregister(SwigPyIterator)

GCC_VERSION = _experiment.GCC_VERSION
class TestFailed:
    """TestFailed is used to raise an uniform exception in tests."""

    __type = "TestFailed"

    def __init__(self, reason=""):
        self.reason = reason

    def type(self):
        return TestFailed.__type

    def what(self):
        return self.reason

    def __str__(self):
        return TestFailed.__type + ": " + self.reason

    def __lshift__(self, ch):
        self.reason += ch
        return self

import openturns.common
import openturns.typ
import openturns.wrapper
import openturns.statistics
import openturns.graph
import openturns.func
import openturns.geom
class ExperimentImplementation(openturns.common.PersistentObject):
    """
    Base class for design of experiments.

    Considering :math:`\\vect{x}=x^1,\\dots, x^n` a vector of input parameters, this
    class is used to determine a particular set of values of :math:`\\vect{x}`
    according to a particular design of experiments.

    Different types of design of experiments can be determined:

    - some stratified patterns: axial, composite, factorial or box patterns,

    - some weighted patterns that we can split into different categories:
      the random patterns, the low discrepancy sequences and the deterministic
      patterns.

    See also
    --------
    StratifiedExperiment, WeightedExperiment
    """
    __swig_setmethods__ = {}
    for _s in [openturns.common.PersistentObject]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, ExperimentImplementation, name, value)
    __swig_getmethods__ = {}
    for _s in [openturns.common.PersistentObject]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, ExperimentImplementation, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.ExperimentImplementation_getClassName(self)

    def __repr__(self): return _experiment.ExperimentImplementation___repr__(self)
    def generate(self):
        """
        Generate points according to the type of the experiment.

        Returns
        -------
        sample : 2D float sequence
            The points which constitute the design of experiments. The sampling method
            is defined by the nature of the experiment.

        Examples
        --------
        >>> import openturns as ot
        >>> ot.RandomGenerator.SetSeed(0)
        >>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
        >>> print(myExperiment.generate())
            [ marginal 1 marginal 2 ]
        0 : [  0.608202  -1.26617   ]
        1 : [ -0.438266   1.20548   ]
        2 : [ -2.18139    0.350042  ]
        3 : [ -0.355007   1.43725   ]
        4 : [  0.810668   0.793156  ]
        """
        return _experiment.ExperimentImplementation_generate(self)

    def __init__(self, *args): 
        this = _experiment.new_ExperimentImplementation(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_ExperimentImplementation
    __del__ = lambda self : None;
ExperimentImplementation_swigregister = _experiment.ExperimentImplementation_swigregister
ExperimentImplementation_swigregister(ExperimentImplementation)

class StratifiedExperiment(ExperimentImplementation):
    __swig_setmethods__ = {}
    for _s in [ExperimentImplementation]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, StratifiedExperiment, name, value)
    __swig_getmethods__ = {}
    for _s in [ExperimentImplementation]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, StratifiedExperiment, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.StratifiedExperiment_getClassName(self)

    def __repr__(self): return _experiment.StratifiedExperiment___repr__(self)
    def setCenter(self, *args): return _experiment.StratifiedExperiment_setCenter(self, *args)
    def getCenter(self): return _experiment.StratifiedExperiment_getCenter(self)
    def setLevels(self, *args): return _experiment.StratifiedExperiment_setLevels(self, *args)
    def getLevels(self): return _experiment.StratifiedExperiment_getLevels(self)
    def __init__(self, *args): 
        this = _experiment.new_StratifiedExperiment(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_StratifiedExperiment
    __del__ = lambda self : None;
StratifiedExperiment_swigregister = _experiment.StratifiedExperiment_swigregister
StratifiedExperiment_swigregister(StratifiedExperiment)

class ExperimentImplementationTypedInterfaceObject(openturns.common.InterfaceObject):
    __swig_setmethods__ = {}
    for _s in [openturns.common.InterfaceObject]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, ExperimentImplementationTypedInterfaceObject, name, value)
    __swig_getmethods__ = {}
    for _s in [openturns.common.InterfaceObject]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, ExperimentImplementationTypedInterfaceObject, name)
    __repr__ = _swig_repr
    def __init__(self, *args): 
        this = _experiment.new_ExperimentImplementationTypedInterfaceObject(*args)
        try: self.this.append(this)
        except: self.this = this
    def getImplementation(self, *args):
        """
        Accessor to the underlying implementation.

        Returns
        -------
        impl : Implementation
            The implementation class.
        """
        return _experiment.ExperimentImplementationTypedInterfaceObject_getImplementation(self, *args)

    def setName(self, *args):
        """
        Accessor to the object's name.

        Parameters
        ----------
        name : string
            The name of the object.
        """
        return _experiment.ExperimentImplementationTypedInterfaceObject_setName(self, *args)

    def getName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        name : string
            The name of the object.
        """
        return _experiment.ExperimentImplementationTypedInterfaceObject_getName(self)

    def __eq__(self, *args): return _experiment.ExperimentImplementationTypedInterfaceObject___eq__(self, *args)
    __swig_destroy__ = _experiment.delete_ExperimentImplementationTypedInterfaceObject
    __del__ = lambda self : None;
ExperimentImplementationTypedInterfaceObject_swigregister = _experiment.ExperimentImplementationTypedInterfaceObject_swigregister
ExperimentImplementationTypedInterfaceObject_swigregister(ExperimentImplementationTypedInterfaceObject)

class Experiment(ExperimentImplementationTypedInterfaceObject):
    """
    Base class for design of experiments.

    Considering :math:`\\vect{x}=x^1,\\dots, x^n` a vector of input parameters, this
    class is used to determine a particular set of values of :math:`\\vect{x}`
    according to a particular design of experiments.

    Different types of design of experiments can be determined:

    - some stratified patterns: axial, composite, factorial or box patterns,

    - some weighted patterns that we can split into different categories:
      the random patterns, the low discrepancy sequences and the deterministic
      patterns.

    See also
    --------
    StratifiedExperiment, WeightedExperiment
    """
    __swig_setmethods__ = {}
    for _s in [ExperimentImplementationTypedInterfaceObject]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Experiment, name, value)
    __swig_getmethods__ = {}
    for _s in [ExperimentImplementationTypedInterfaceObject]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Experiment, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.Experiment_getClassName(self)

    def __repr__(self): return _experiment.Experiment___repr__(self)
    def generate(self):
        """
        Generate points according to the type of the experiment.

        Returns
        -------
        sample : 2D float sequence
            The points which constitute the design of experiments. The sampling method
            is defined by the nature of the experiment.

        Examples
        --------
        >>> import openturns as ot
        >>> ot.RandomGenerator.SetSeed(0)
        >>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
        >>> print(myExperiment.generate())
            [ marginal 1 marginal 2 ]
        0 : [  0.608202  -1.26617   ]
        1 : [ -0.438266   1.20548   ]
        2 : [ -2.18139    0.350042  ]
        3 : [ -0.355007   1.43725   ]
        4 : [  0.810668   0.793156  ]
        """
        return _experiment.Experiment_generate(self)

    def setImplementation(self, *args):
        """
        Accessor to the underlying implementation.

        Parameters
        ----------
        implementation : ExperimentImplementation
            An ExperimentImplementation object.

        Examples
        --------
        >>> import openturns as ot
        >>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
        >>> myExperimentImplementation = myExperiment.getImplementation()
        >>> mySecondExperiment = ot.Experiment()
        >>> mySecondExperiment.setImplementation(myExperimentImplementation)
        """
        return _experiment.Experiment_setImplementation(self, *args)

    def __init__(self, *args): 
        this = _experiment.new_Experiment(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_Experiment
    __del__ = lambda self : None;
Experiment_swigregister = _experiment.Experiment_swigregister
Experiment_swigregister(Experiment)

class Axial(StratifiedExperiment):
    __swig_setmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Axial, name, value)
    __swig_getmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Axial, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.Axial_getClassName(self)

    def generate(self):
        """
        Generate points according to the type of the experiment.

        Returns
        -------
        sample : 2D float sequence
            The points which constitute the design of experiments. The sampling method
            is defined by the nature of the experiment.

        Examples
        --------
        >>> import openturns as ot
        >>> ot.RandomGenerator.SetSeed(0)
        >>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
        >>> print(myExperiment.generate())
            [ marginal 1 marginal 2 ]
        0 : [  0.608202  -1.26617   ]
        1 : [ -0.438266   1.20548   ]
        2 : [ -2.18139    0.350042  ]
        3 : [ -0.355007   1.43725   ]
        4 : [  0.810668   0.793156  ]
        """
        return _experiment.Axial_generate(self)

    def __repr__(self): return _experiment.Axial___repr__(self)
    def __init__(self, *args): 
        this = _experiment.new_Axial(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_Axial
    __del__ = lambda self : None;
Axial_swigregister = _experiment.Axial_swigregister
Axial_swigregister(Axial)

class Composite(StratifiedExperiment):
    __swig_setmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Composite, name, value)
    __swig_getmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Composite, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.Composite_getClassName(self)

    def generate(self):
        """
        Generate points according to the type of the experiment.

        Returns
        -------
        sample : 2D float sequence
            The points which constitute the design of experiments. The sampling method
            is defined by the nature of the experiment.

        Examples
        --------
        >>> import openturns as ot
        >>> ot.RandomGenerator.SetSeed(0)
        >>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
        >>> print(myExperiment.generate())
            [ marginal 1 marginal 2 ]
        0 : [  0.608202  -1.26617   ]
        1 : [ -0.438266   1.20548   ]
        2 : [ -2.18139    0.350042  ]
        3 : [ -0.355007   1.43725   ]
        4 : [  0.810668   0.793156  ]
        """
        return _experiment.Composite_generate(self)

    def __repr__(self): return _experiment.Composite___repr__(self)
    def __init__(self, *args): 
        this = _experiment.new_Composite(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_Composite
    __del__ = lambda self : None;
Composite_swigregister = _experiment.Composite_swigregister
Composite_swigregister(Composite)

class Factorial(StratifiedExperiment):
    __swig_setmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Factorial, name, value)
    __swig_getmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Factorial, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.Factorial_getClassName(self)

    def generate(self):
        """
        Generate points according to the type of the experiment.

        Returns
        -------
        sample : 2D float sequence
            The points which constitute the design of experiments. The sampling method
            is defined by the nature of the experiment.

        Examples
        --------
        >>> import openturns as ot
        >>> ot.RandomGenerator.SetSeed(0)
        >>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
        >>> print(myExperiment.generate())
            [ marginal 1 marginal 2 ]
        0 : [  0.608202  -1.26617   ]
        1 : [ -0.438266   1.20548   ]
        2 : [ -2.18139    0.350042  ]
        3 : [ -0.355007   1.43725   ]
        4 : [  0.810668   0.793156  ]
        """
        return _experiment.Factorial_generate(self)

    def __repr__(self): return _experiment.Factorial___repr__(self)
    def __init__(self, *args): 
        this = _experiment.new_Factorial(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_Factorial
    __del__ = lambda self : None;
Factorial_swigregister = _experiment.Factorial_swigregister
Factorial_swigregister(Factorial)

class Box(StratifiedExperiment):
    __swig_setmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Box, name, value)
    __swig_getmethods__ = {}
    for _s in [StratifiedExperiment]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Box, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.Box_getClassName(self)

    def generate(self):
        """
        Generate points according to the type of the experiment.

        Returns
        -------
        sample : 2D float sequence
            The points which constitute the design of experiments. The sampling method
            is defined by the nature of the experiment.

        Examples
        --------
        >>> import openturns as ot
        >>> ot.RandomGenerator.SetSeed(0)
        >>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
        >>> print(myExperiment.generate())
            [ marginal 1 marginal 2 ]
        0 : [  0.608202  -1.26617   ]
        1 : [ -0.438266   1.20548   ]
        2 : [ -2.18139    0.350042  ]
        3 : [ -0.355007   1.43725   ]
        4 : [  0.810668   0.793156  ]
        """
        return _experiment.Box_generate(self)

    def __repr__(self): return _experiment.Box___repr__(self)
    def setLevels(self, *args): return _experiment.Box_setLevels(self, *args)
    def __init__(self, *args): 
        this = _experiment.new_Box(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_Box
    __del__ = lambda self : None;
Box_swigregister = _experiment.Box_swigregister
Box_swigregister(Box)

class CombinatorialGeneratorImplementation(openturns.common.PersistentObject):
    __swig_setmethods__ = {}
    for _s in [openturns.common.PersistentObject]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, CombinatorialGeneratorImplementation, name, value)
    __swig_getmethods__ = {}
    for _s in [openturns.common.PersistentObject]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, CombinatorialGeneratorImplementation, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.CombinatorialGeneratorImplementation_getClassName(self)

    def __repr__(self): return _experiment.CombinatorialGeneratorImplementation___repr__(self)
    def generate(self): return _experiment.CombinatorialGeneratorImplementation_generate(self)
    def __init__(self, *args): 
        this = _experiment.new_CombinatorialGeneratorImplementation(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_CombinatorialGeneratorImplementation
    __del__ = lambda self : None;
CombinatorialGeneratorImplementation_swigregister = _experiment.CombinatorialGeneratorImplementation_swigregister
CombinatorialGeneratorImplementation_swigregister(CombinatorialGeneratorImplementation)

class CombinatorialGeneratorImplementationTypedInterfaceObject(openturns.common.InterfaceObject):
    __swig_setmethods__ = {}
    for _s in [openturns.common.InterfaceObject]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, CombinatorialGeneratorImplementationTypedInterfaceObject, name, value)
    __swig_getmethods__ = {}
    for _s in [openturns.common.InterfaceObject]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, CombinatorialGeneratorImplementationTypedInterfaceObject, name)
    __repr__ = _swig_repr
    def __init__(self, *args): 
        this = _experiment.new_CombinatorialGeneratorImplementationTypedInterfaceObject(*args)
        try: self.this.append(this)
        except: self.this = this
    def getImplementation(self, *args):
        """
        Accessor to the underlying implementation.

        Returns
        -------
        impl : Implementation
            The implementation class.
        """
        return _experiment.CombinatorialGeneratorImplementationTypedInterfaceObject_getImplementation(self, *args)

    def setName(self, *args):
        """
        Accessor to the object's name.

        Parameters
        ----------
        name : string
            The name of the object.
        """
        return _experiment.CombinatorialGeneratorImplementationTypedInterfaceObject_setName(self, *args)

    def getName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        name : string
            The name of the object.
        """
        return _experiment.CombinatorialGeneratorImplementationTypedInterfaceObject_getName(self)

    def __eq__(self, *args): return _experiment.CombinatorialGeneratorImplementationTypedInterfaceObject___eq__(self, *args)
    __swig_destroy__ = _experiment.delete_CombinatorialGeneratorImplementationTypedInterfaceObject
    __del__ = lambda self : None;
CombinatorialGeneratorImplementationTypedInterfaceObject_swigregister = _experiment.CombinatorialGeneratorImplementationTypedInterfaceObject_swigregister
CombinatorialGeneratorImplementationTypedInterfaceObject_swigregister(CombinatorialGeneratorImplementationTypedInterfaceObject)

class CombinatorialGenerator(CombinatorialGeneratorImplementationTypedInterfaceObject):
    __swig_setmethods__ = {}
    for _s in [CombinatorialGeneratorImplementationTypedInterfaceObject]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, CombinatorialGenerator, name, value)
    __swig_getmethods__ = {}
    for _s in [CombinatorialGeneratorImplementationTypedInterfaceObject]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, CombinatorialGenerator, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.CombinatorialGenerator_getClassName(self)

    def __repr__(self): return _experiment.CombinatorialGenerator___repr__(self)
    def generate(self): return _experiment.CombinatorialGenerator_generate(self)
    def setImplementation(self, *args): return _experiment.CombinatorialGenerator_setImplementation(self, *args)
    def __init__(self, *args): 
        this = _experiment.new_CombinatorialGenerator(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_CombinatorialGenerator
    __del__ = lambda self : None;
CombinatorialGenerator_swigregister = _experiment.CombinatorialGenerator_swigregister
CombinatorialGenerator_swigregister(CombinatorialGenerator)

class Combinations(CombinatorialGeneratorImplementation):
    __swig_setmethods__ = {}
    for _s in [CombinatorialGeneratorImplementation]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Combinations, name, value)
    __swig_getmethods__ = {}
    for _s in [CombinatorialGeneratorImplementation]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Combinations, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.Combinations_getClassName(self)

    def generate(self): return _experiment.Combinations_generate(self)
    def __repr__(self): return _experiment.Combinations___repr__(self)
    def setK(self, *args): return _experiment.Combinations_setK(self, *args)
    def getK(self): return _experiment.Combinations_getK(self)
    def setN(self, *args): return _experiment.Combinations_setN(self, *args)
    def getN(self): return _experiment.Combinations_getN(self)
    def __init__(self, *args): 
        this = _experiment.new_Combinations(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_Combinations
    __del__ = lambda self : None;
Combinations_swigregister = _experiment.Combinations_swigregister
Combinations_swigregister(Combinations)

class KPermutations(CombinatorialGeneratorImplementation):
    __swig_setmethods__ = {}
    for _s in [CombinatorialGeneratorImplementation]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, KPermutations, name, value)
    __swig_getmethods__ = {}
    for _s in [CombinatorialGeneratorImplementation]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, KPermutations, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.KPermutations_getClassName(self)

    def generate(self): return _experiment.KPermutations_generate(self)
    def __repr__(self): return _experiment.KPermutations___repr__(self)
    def setK(self, *args): return _experiment.KPermutations_setK(self, *args)
    def getK(self): return _experiment.KPermutations_getK(self)
    def setN(self, *args): return _experiment.KPermutations_setN(self, *args)
    def getN(self): return _experiment.KPermutations_getN(self)
    def __init__(self, *args): 
        this = _experiment.new_KPermutations(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_KPermutations
    __del__ = lambda self : None;
KPermutations_swigregister = _experiment.KPermutations_swigregister
KPermutations_swigregister(KPermutations)

class Tuples(CombinatorialGeneratorImplementation):
    __swig_setmethods__ = {}
    for _s in [CombinatorialGeneratorImplementation]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Tuples, name, value)
    __swig_getmethods__ = {}
    for _s in [CombinatorialGeneratorImplementation]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Tuples, name)
    def getClassName(self):
        """
        Accessor to the object's name.

        Returns
        -------
        class_name : str
            The object class name (`object.__class__.__name__`).
        """
        return _experiment.Tuples_getClassName(self)

    def generate(self): return _experiment.Tuples_generate(self)
    def __repr__(self): return _experiment.Tuples___repr__(self)
    def setBounds(self, *args): return _experiment.Tuples_setBounds(self, *args)
    def getBounds(self): return _experiment.Tuples_getBounds(self)
    def __init__(self, *args): 
        this = _experiment.new_Tuples(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _experiment.delete_Tuples
    __del__ = lambda self : None;
Tuples_swigregister = _experiment.Tuples_swigregister
Tuples_swigregister(Tuples)

# This file is compatible with both classic and new-style classes.