# This file was automatically generated by SWIG (https://www.swig.org).
# Version 4.3.1
#
# 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 __package__ or "." in __name__:
    from . import _itkOptimizerParameterScalesEstimatorPython
else:
    import _itkOptimizerParameterScalesEstimatorPython

try:
    import builtins as __builtin__
except ImportError:
    import __builtin__

_swig_new_instance_method = _itkOptimizerParameterScalesEstimatorPython.SWIG_PyInstanceMethod_New
_swig_new_static_method = _itkOptimizerParameterScalesEstimatorPython.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 ITKCommonBasePython
import pyBasePython
import itkOptimizerParametersPython
import vnl_vectorPython
import vnl_matrixPython
import stdcomplexPython
import itkArrayPython

def itkOptimizerParameterScalesEstimatorTemplateF_New():
  return itkOptimizerParameterScalesEstimatorTemplateF.New()


def itkOptimizerParameterScalesEstimatorTemplateD_New():
  return itkOptimizerParameterScalesEstimatorTemplateD.New()

class itkOptimizerParameterScalesEstimatorTemplateD(ITKCommonBasePython.itkObject):
    r"""Proxy of C++ itkOptimizerParameterScalesEstimatorTemplateD 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
    EstimateScales = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateD_EstimateScales)
    EstimateStepScale = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateD_EstimateStepScale)
    EstimateLocalStepScales = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateD_EstimateLocalStepScales)
    EstimateMaximumStepSize = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateD_EstimateMaximumStepSize)
    __swig_destroy__ = _itkOptimizerParameterScalesEstimatorPython.delete_itkOptimizerParameterScalesEstimatorTemplateD
    cast = _swig_new_static_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateD_cast)
    GetPointer = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateD_GetPointer)

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

        Create a new object of the class itkOptimizerParameterScalesEstimatorTemplateD 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:

          itkOptimizerParameterScalesEstimatorTemplateD.New( reader, Threshold=10 )

        is (most of the time) equivalent to:

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


# Register itkOptimizerParameterScalesEstimatorTemplateD in _itkOptimizerParameterScalesEstimatorPython:
_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateD_swigregister(itkOptimizerParameterScalesEstimatorTemplateD)
class itkOptimizerParameterScalesEstimatorTemplateF(ITKCommonBasePython.itkObject):
    r"""Proxy of C++ itkOptimizerParameterScalesEstimatorTemplateF 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
    EstimateScales = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateF_EstimateScales)
    EstimateStepScale = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateF_EstimateStepScale)
    EstimateLocalStepScales = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateF_EstimateLocalStepScales)
    EstimateMaximumStepSize = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateF_EstimateMaximumStepSize)
    __swig_destroy__ = _itkOptimizerParameterScalesEstimatorPython.delete_itkOptimizerParameterScalesEstimatorTemplateF
    cast = _swig_new_static_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateF_cast)
    GetPointer = _swig_new_instance_method(_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateF_GetPointer)

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

        Create a new object of the class itkOptimizerParameterScalesEstimatorTemplateF 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:

          itkOptimizerParameterScalesEstimatorTemplateF.New( reader, Threshold=10 )

        is (most of the time) equivalent to:

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


# Register itkOptimizerParameterScalesEstimatorTemplateF in _itkOptimizerParameterScalesEstimatorPython:
_itkOptimizerParameterScalesEstimatorPython.itkOptimizerParameterScalesEstimatorTemplateF_swigregister(itkOptimizerParameterScalesEstimatorTemplateF)

