# This file was automatically generated by SWIG (https://www.swig.org).
# Version 4.4.1
#
# Do not make changes to this file unless you know what you are doing - modify
# the SWIG interface file instead.

from sys import version_info as _swig_python_version_info
# Import the low-level C/C++ module
if getattr(globals().get("__spec__"), "parent", None) or __package__ or "." in __name__:
    from . import _itkGradientDescentOptimizerBasev4Python
else:
    import _itkGradientDescentOptimizerBasev4Python

try:
    import builtins as __builtin__
except ImportError:
    import __builtin__

_swig_new_instance_method = _itkGradientDescentOptimizerBasev4Python.SWIG_PyInstanceMethod_New
_swig_new_static_method = _itkGradientDescentOptimizerBasev4Python.SWIG_PyStaticMethod_New

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


def _swig_setattr_nondynamic_instance_variable(set):
    def set_instance_attr(self, name, value):
        if name == "this":
            set(self, name, value)
        elif name == "thisown":
            self.this.own(value)
        elif hasattr(self, name) and isinstance(getattr(type(self), name), property):
            set(self, name, value)
        else:
            raise AttributeError("You cannot add instance attributes to %s" % self)
    return set_instance_attr


def _swig_setattr_nondynamic_class_variable(set):
    def set_class_attr(cls, name, value):
        if hasattr(cls, name) and not isinstance(getattr(cls, name), property):
            set(cls, name, value)
        else:
            raise AttributeError("You cannot add class attributes to %s" % cls)
    return set_class_attr


def _swig_add_metaclass(metaclass):
    """Class decorator for adding a metaclass to a SWIG wrapped class - a slimmed down version of six.add_metaclass"""
    def wrapper(cls):
        return metaclass(cls.__name__, cls.__bases__, cls.__dict__.copy())
    return wrapper


class _SwigNonDynamicMeta(type):
    """Meta class to enforce nondynamic attributes (no new attributes) for a class"""
    __setattr__ = _swig_setattr_nondynamic_class_variable(type.__setattr__)


import itkIndexPython
import itkOffsetPython
import itkSizePython
import pyBasePython
import itkObjectToObjectOptimizerBasePython
import itkObjectToObjectMetricBasePython
import itkOptimizerParametersPython
import itkArrayPython
import vnl_vectorPython
import vnl_matrixPython
import stdcomplexPython
import ITKCommonBasePython
import itkSingleValuedCostFunctionv4Python
import itkCostFunctionPython
import itkOptimizerParameterScalesEstimatorPython

def itkGradientDescentOptimizerBasev4TemplateF_New():
  return itkGradientDescentOptimizerBasev4TemplateF.New()


def itkGradientDescentOptimizerBasev4TemplateD_New():
  return itkGradientDescentOptimizerBasev4TemplateD.New()

class itkGradientDescentOptimizerBasev4TemplateD(itkObjectToObjectOptimizerBasePython.itkObjectToObjectOptimizerBaseTemplateD):
    r"""Proxy of C++ itkGradientDescentOptimizerBasev4TemplateD class."""

    thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")

    def __init__(self, *args, **kwargs):
        raise AttributeError("No constructor defined - class is abstract")
    __repr__ = _swig_repr
    MAXIMUM_NUMBER_OF_ITERATIONS = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_MAXIMUM_NUMBER_OF_ITERATIONS
    
    COSTFUNCTION_ERROR = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_COSTFUNCTION_ERROR
    
    UPDATE_PARAMETERS_ERROR = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_UPDATE_PARAMETERS_ERROR
    
    STEP_TOO_SMALL = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_STEP_TOO_SMALL
    
    CONVERGENCE_CHECKER_PASSED = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_CONVERGENCE_CHECKER_PASSED
    
    GRADIENT_MAGNITUDE_TOLEARANCE = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_GRADIENT_MAGNITUDE_TOLEARANCE
    
    OTHER_ERROR = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_OTHER_ERROR
    
    GetGradient = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_GetGradient)
    GetStopCondition = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_GetStopCondition)
    StartOptimization = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_StartOptimization)
    ResumeOptimization = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_ResumeOptimization)
    StopOptimization = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_StopOptimization)
    ModifyGradientByScales = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_ModifyGradientByScales)
    ModifyGradientByLearningRate = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_ModifyGradientByLearningRate)
    ModifyGradientByScalesOverSubRange = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_ModifyGradientByScalesOverSubRange)
    ModifyGradientByLearningRateOverSubRange = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_ModifyGradientByLearningRateOverSubRange)
    __swig_destroy__ = _itkGradientDescentOptimizerBasev4Python.delete_itkGradientDescentOptimizerBasev4TemplateD
    cast = _swig_new_static_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_cast)
    GetPointer = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_GetPointer)

    def New(*args, **kargs):
        """New() -> itkGradientDescentOptimizerBasev4TemplateD

        Create a new object of the class itkGradientDescentOptimizerBasev4TemplateD and set the input and the parameters if some
        named or non-named arguments are passed to that method.

        New() tries to assign all the non named parameters to the input of the new objects - the
        first non named parameter in the first input, etc.

        The named parameters are used by calling the method with the same name prefixed by 'Set'.

        Ex:

          itkGradientDescentOptimizerBasev4TemplateD.New( reader, Threshold=10 )

        is (most of the time) equivalent to:

          obj = itkGradientDescentOptimizerBasev4TemplateD.New()
          obj.SetInput( 0, reader.GetOutput() )
          obj.SetThreshold( 10 )
        """
        obj = itkGradientDescentOptimizerBasev4TemplateD.__New_orig__()
        import itkTemplate
        itkTemplate.New(obj, *args, **kargs)
        return obj
    New = staticmethod(New)


# Register itkGradientDescentOptimizerBasev4TemplateD in _itkGradientDescentOptimizerBasev4Python:
_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateD_swigregister(itkGradientDescentOptimizerBasev4TemplateD)
class itkGradientDescentOptimizerBasev4TemplateF(itkObjectToObjectOptimizerBasePython.itkObjectToObjectOptimizerBaseTemplateF):
    r"""Proxy of C++ itkGradientDescentOptimizerBasev4TemplateF class."""

    thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")

    def __init__(self, *args, **kwargs):
        raise AttributeError("No constructor defined - class is abstract")
    __repr__ = _swig_repr
    MAXIMUM_NUMBER_OF_ITERATIONS = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_MAXIMUM_NUMBER_OF_ITERATIONS
    
    COSTFUNCTION_ERROR = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_COSTFUNCTION_ERROR
    
    UPDATE_PARAMETERS_ERROR = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_UPDATE_PARAMETERS_ERROR
    
    STEP_TOO_SMALL = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_STEP_TOO_SMALL
    
    CONVERGENCE_CHECKER_PASSED = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_CONVERGENCE_CHECKER_PASSED
    
    GRADIENT_MAGNITUDE_TOLEARANCE = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_GRADIENT_MAGNITUDE_TOLEARANCE
    
    OTHER_ERROR = _itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_OTHER_ERROR
    
    GetGradient = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_GetGradient)
    GetStopCondition = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_GetStopCondition)
    StartOptimization = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_StartOptimization)
    ResumeOptimization = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_ResumeOptimization)
    StopOptimization = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_StopOptimization)
    ModifyGradientByScales = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_ModifyGradientByScales)
    ModifyGradientByLearningRate = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_ModifyGradientByLearningRate)
    ModifyGradientByScalesOverSubRange = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_ModifyGradientByScalesOverSubRange)
    ModifyGradientByLearningRateOverSubRange = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_ModifyGradientByLearningRateOverSubRange)
    __swig_destroy__ = _itkGradientDescentOptimizerBasev4Python.delete_itkGradientDescentOptimizerBasev4TemplateF
    cast = _swig_new_static_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_cast)
    GetPointer = _swig_new_instance_method(_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_GetPointer)

    def New(*args, **kargs):
        """New() -> itkGradientDescentOptimizerBasev4TemplateF

        Create a new object of the class itkGradientDescentOptimizerBasev4TemplateF and set the input and the parameters if some
        named or non-named arguments are passed to that method.

        New() tries to assign all the non named parameters to the input of the new objects - the
        first non named parameter in the first input, etc.

        The named parameters are used by calling the method with the same name prefixed by 'Set'.

        Ex:

          itkGradientDescentOptimizerBasev4TemplateF.New( reader, Threshold=10 )

        is (most of the time) equivalent to:

          obj = itkGradientDescentOptimizerBasev4TemplateF.New()
          obj.SetInput( 0, reader.GetOutput() )
          obj.SetThreshold( 10 )
        """
        obj = itkGradientDescentOptimizerBasev4TemplateF.__New_orig__()
        import itkTemplate
        itkTemplate.New(obj, *args, **kargs)
        return obj
    New = staticmethod(New)


# Register itkGradientDescentOptimizerBasev4TemplateF in _itkGradientDescentOptimizerBasev4Python:
_itkGradientDescentOptimizerBasev4Python.itkGradientDescentOptimizerBasev4TemplateF_swigregister(itkGradientDescentOptimizerBasev4TemplateF)

