/usr/lib/python2.7/dist-packages/openturns/diff.py is in python-openturns 1.7-3.
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This file was automatically generated by SWIG (http://www.swig.org).
# Version 3.0.7
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
"""
Differential algorithms.
"""
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('_diff', [dirname(__file__)])
except ImportError:
import _diff
return _diff
if fp is not None:
try:
_mod = imp.load_module('_diff', fp, pathname, description)
finally:
fp.close()
return _mod
_diff = swig_import_helper()
del swig_import_helper
else:
import _diff
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):
if _newclass:
object.__setattr__(self, name, value)
else:
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_nondynamic(self, class_type, name, static=1):
if (name == "thisown"):
return self.this.own()
method = class_type.__swig_getmethods__.get(name, None)
if method:
return method(self)
if (not static):
return object.__getattr__(self, name)
else:
raise AttributeError(name)
def _swig_getattr(self, class_type, name):
return _swig_getattr_nondynamic(self, class_type, name, 0)
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__ = _diff.delete_SwigPyIterator
__del__ = lambda self: None
def value(self):
return _diff.SwigPyIterator_value(self)
def incr(self, n=1):
return _diff.SwigPyIterator_incr(self, n)
def decr(self, n=1):
return _diff.SwigPyIterator_decr(self, n)
def distance(self, x):
return _diff.SwigPyIterator_distance(self, x)
def equal(self, x):
return _diff.SwigPyIterator_equal(self, x)
def copy(self):
return _diff.SwigPyIterator_copy(self)
def next(self):
return _diff.SwigPyIterator_next(self)
def __next__(self):
return _diff.SwigPyIterator___next__(self)
def previous(self):
return _diff.SwigPyIterator_previous(self)
def advance(self, n):
return _diff.SwigPyIterator_advance(self, n)
def __eq__(self, x):
return _diff.SwigPyIterator___eq__(self, x)
def __ne__(self, x):
return _diff.SwigPyIterator___ne__(self, x)
def __iadd__(self, n):
return _diff.SwigPyIterator___iadd__(self, n)
def __isub__(self, n):
return _diff.SwigPyIterator___isub__(self, n)
def __add__(self, n):
return _diff.SwigPyIterator___add__(self, n)
def __sub__(self, *args):
return _diff.SwigPyIterator___sub__(self, *args)
def __iter__(self):
return self
SwigPyIterator_swigregister = _diff.SwigPyIterator_swigregister
SwigPyIterator_swigregister(SwigPyIterator)
_diff.GCC_VERSION_swigconstant(_diff)
GCC_VERSION = _diff.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.statistics
import openturns.graph
import openturns.func
import openturns.geom
class FiniteDifferenceStepImplementation(openturns.common.PersistentObject):
"""
Base class to define finite difference steps.
Available constructors:
FiniteDifferenceStep(*epsilon=[1.0]*)
Parameters
----------
epsilon : sequence of float
Finite difference steps for each dimension.
Notes
-----
Base class to define how finite difference steps are computed.
Using *FiniteDifferenceStep* is equivalent to use its derived class
:class:`~openturns.ConstantStep`. Another way to compute steps
is through its second derived class :class:`~openturns.BlendedStep`.
"""
__swig_setmethods__ = {}
for _s in [openturns.common.PersistentObject]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, FiniteDifferenceStepImplementation, name, value)
__swig_getmethods__ = {}
for _s in [openturns.common.PersistentObject]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, FiniteDifferenceStepImplementation, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.FiniteDifferenceStepImplementation_getClassName(self)
def __repr__(self):
return _diff.FiniteDifferenceStepImplementation___repr__(self)
def setEpsilon(self, epsilon):
"""
Set the finite difference steps.
Parameters
----------
epsilon : sequence of float
If :class:`~openturns.ConstantStep` : Finite difference steps for each
dimension.
If :class:`~openturns.BlendedStep` : Finite difference step factors for
each dimension.
"""
return _diff.FiniteDifferenceStepImplementation_setEpsilon(self, epsilon)
def getEpsilon(self):
"""
Get the finite difference steps.
Returns
-------
epsilon : :class:`~openturns.NumericalPoint`
If :class:`~openturns.ConstantStep` : Finite difference steps for each
dimension.
If :class:`~openturns.BlendedStep` : Finite difference step factors for
each dimension.
"""
return _diff.FiniteDifferenceStepImplementation_getEpsilon(self)
def __call__(self, inP):
return _diff.FiniteDifferenceStepImplementation___call__(self, inP)
def __init__(self, *args):
this = _diff.new_FiniteDifferenceStepImplementation(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_FiniteDifferenceStepImplementation
__del__ = lambda self: None
FiniteDifferenceStepImplementation_swigregister = _diff.FiniteDifferenceStepImplementation_swigregister
FiniteDifferenceStepImplementation_swigregister(FiniteDifferenceStepImplementation)
class FiniteDifferenceStepImplementationTypedInterfaceObject(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, FiniteDifferenceStepImplementationTypedInterfaceObject, name, value)
__swig_getmethods__ = {}
for _s in [openturns.common.InterfaceObject]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, FiniteDifferenceStepImplementationTypedInterfaceObject, name)
__repr__ = _swig_repr
def __init__(self, *args):
this = _diff.new_FiniteDifferenceStepImplementationTypedInterfaceObject(*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 _diff.FiniteDifferenceStepImplementationTypedInterfaceObject_getImplementation(self, *args)
def setName(self, name):
"""
Accessor to the object's name.
Parameters
----------
name : str
The name of the object.
"""
return _diff.FiniteDifferenceStepImplementationTypedInterfaceObject_setName(self, name)
def getName(self):
"""
Accessor to the object's name.
Returns
-------
name : str
The name of the object.
"""
return _diff.FiniteDifferenceStepImplementationTypedInterfaceObject_getName(self)
def __eq__(self, other):
return _diff.FiniteDifferenceStepImplementationTypedInterfaceObject___eq__(self, other)
__swig_destroy__ = _diff.delete_FiniteDifferenceStepImplementationTypedInterfaceObject
__del__ = lambda self: None
FiniteDifferenceStepImplementationTypedInterfaceObject_swigregister = _diff.FiniteDifferenceStepImplementationTypedInterfaceObject_swigregister
FiniteDifferenceStepImplementationTypedInterfaceObject_swigregister(FiniteDifferenceStepImplementationTypedInterfaceObject)
class FiniteDifferenceStep(FiniteDifferenceStepImplementationTypedInterfaceObject):
"""
Base class to define finite difference steps.
Available constructors:
FiniteDifferenceStep(*epsilon=[1.0]*)
Parameters
----------
epsilon : sequence of float
Finite difference steps for each dimension.
Notes
-----
Base class to define how finite difference steps are computed.
Using *FiniteDifferenceStep* is equivalent to use its derived class
:class:`~openturns.ConstantStep`. Another way to compute steps
is through its second derived class :class:`~openturns.BlendedStep`.
"""
__swig_setmethods__ = {}
for _s in [FiniteDifferenceStepImplementationTypedInterfaceObject]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, FiniteDifferenceStep, name, value)
__swig_getmethods__ = {}
for _s in [FiniteDifferenceStepImplementationTypedInterfaceObject]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, FiniteDifferenceStep, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.FiniteDifferenceStep_getClassName(self)
def __repr__(self):
return _diff.FiniteDifferenceStep___repr__(self)
def setEpsilon(self, epsilon):
"""
Set the finite difference steps.
Parameters
----------
epsilon : sequence of float
If :class:`~openturns.ConstantStep` : Finite difference steps for each
dimension.
If :class:`~openturns.BlendedStep` : Finite difference step factors for
each dimension.
"""
return _diff.FiniteDifferenceStep_setEpsilon(self, epsilon)
def getEpsilon(self):
"""
Get the finite difference steps.
Returns
-------
epsilon : :class:`~openturns.NumericalPoint`
If :class:`~openturns.ConstantStep` : Finite difference steps for each
dimension.
If :class:`~openturns.BlendedStep` : Finite difference step factors for
each dimension.
"""
return _diff.FiniteDifferenceStep_getEpsilon(self)
def __call__(self, inP):
return _diff.FiniteDifferenceStep___call__(self, inP)
def __init__(self, *args):
this = _diff.new_FiniteDifferenceStep(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_FiniteDifferenceStep
__del__ = lambda self: None
FiniteDifferenceStep_swigregister = _diff.FiniteDifferenceStep_swigregister
FiniteDifferenceStep_swigregister(FiniteDifferenceStep)
class ConstantStep(FiniteDifferenceStepImplementation):
"""
Constant step.
Available constructors:
ConstantStep(*epsilon=[1.0]*)
Parameters
----------
epsilon : sequence of float
Finite difference steps for each dimension.
Notes
-----
*ConstantStep* defines a list of constant finite difference steps equal to
*epsilon*.
See also
--------
BlendedStep
Examples
--------
>>> import openturns as ot
>>> epsilon = [1e-4, 2e-4]
>>> steps = ot.ConstantStep(epsilon)
>>> print(steps([2.]*2))
[0.0001,0.0002]
>>> print(steps([0., 3.]))
[0.0001,0.0002]
"""
__swig_setmethods__ = {}
for _s in [FiniteDifferenceStepImplementation]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, ConstantStep, name, value)
__swig_getmethods__ = {}
for _s in [FiniteDifferenceStepImplementation]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, ConstantStep, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.ConstantStep_getClassName(self)
def __repr__(self):
return _diff.ConstantStep___repr__(self)
def __call__(self, inP):
return _diff.ConstantStep___call__(self, inP)
def __init__(self, *args):
this = _diff.new_ConstantStep(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_ConstantStep
__del__ = lambda self: None
ConstantStep_swigregister = _diff.ConstantStep_swigregister
ConstantStep_swigregister(ConstantStep)
class BlendedStep(FiniteDifferenceStepImplementation):
"""
Blended step.
Available constructors:
BlendedStep(*epsilon, eta=1.*)
Parameters
----------
epsilon : sequence of float
Finite difference step factors for each dimension.
eta : positive float, sequence of positive float with the same dimension as *epsilon*
Finite difference step offsets for each dimension.
Notes
-----
*BlendedStep* defines a list of finite difference steps equal to:
*epsilon (|x| + eta)*.
See also
--------
ConstantStep
Examples
--------
>>> import openturns as ot
>>> epsilon = [1e-4, 2e-4]
>>> x = [2.]*2
>>> steps = ot.BlendedStep(epsilon)
>>> print(steps(x))
[0.0003,0.0006]
>>> steps = ot.BlendedStep(epsilon, 0.)
>>> print(steps(x))
[0.0002,0.0004]
>>> steps = ot.BlendedStep(epsilon, [1., 2.])
>>> print(steps(x))
[0.0003,0.0008]
>>> steps = ot.BlendedStep(epsilon, 2.)
>>> print(steps(x))
[0.0004,0.0008]
"""
__swig_setmethods__ = {}
for _s in [FiniteDifferenceStepImplementation]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, BlendedStep, name, value)
__swig_getmethods__ = {}
for _s in [FiniteDifferenceStepImplementation]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, BlendedStep, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.BlendedStep_getClassName(self)
def __repr__(self):
return _diff.BlendedStep___repr__(self)
def __call__(self, inP):
return _diff.BlendedStep___call__(self, inP)
def setEta(self, eta):
"""
Set the finite difference step offsets.
Parameters
----------
eta : sequence of positive float
Finite difference step offsets for each dimension.
"""
return _diff.BlendedStep_setEta(self, eta)
def getEta(self):
"""
Get the finite difference step offsets.
Returns
-------
eta : :class:`~openturns.NumericalPoint`
Finite difference step offsets for each dimension.
"""
return _diff.BlendedStep_getEta(self)
def __init__(self, *args):
this = _diff.new_BlendedStep(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_BlendedStep
__del__ = lambda self: None
BlendedStep_swigregister = _diff.BlendedStep_swigregister
BlendedStep_swigregister(BlendedStep)
class FiniteDifferenceGradient(openturns.func.NumericalMathGradientImplementation):
"""
Base class for first order finite-difference schemes.
Available constructors:
FiniteDifferenceGradient(*epsilon, evalImpl*)
FiniteDifferenceGradient(*step, evalImpl*)
Parameters
----------
evalImpl : :class:`~openturns.NumericalMathEvaluationImplementation`
Implementation of the evaluation of a function.
epsilon : float, sequence of float
Finite difference steps for each dimension.
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
Notes
-----
Base class to define first order finite-difference schemes. The gradient
can be computed only through its derived classes:
- :class:`~openturns.CenteredFiniteDifferenceGradient`,
- :class:`~openturns.NonCenteredFiniteDifferenceGradient`.
"""
__swig_setmethods__ = {}
for _s in [openturns.func.NumericalMathGradientImplementation]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, FiniteDifferenceGradient, name, value)
__swig_getmethods__ = {}
for _s in [openturns.func.NumericalMathGradientImplementation]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, FiniteDifferenceGradient, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.FiniteDifferenceGradient_getClassName(self)
def __eq__(self, other):
return _diff.FiniteDifferenceGradient___eq__(self, other)
def __repr__(self):
return _diff.FiniteDifferenceGradient___repr__(self)
def getInputDimension(self):
"""
Get the input dimension.
Returns
-------
dimension : int
Input dimension.
"""
return _diff.FiniteDifferenceGradient_getInputDimension(self)
def getOutputDimension(self):
"""
Get the output dimension.
Returns
-------
dimension : int
Output dimension.
"""
return _diff.FiniteDifferenceGradient_getOutputDimension(self)
def getEpsilon(self):
"""
Get the finite difference steps.
Returns
-------
epsilon : :class:`~openturns.NumericalPoint`
Finite difference steps for each dimension.
"""
return _diff.FiniteDifferenceGradient_getEpsilon(self)
def getEvaluation(self):
"""
Get the implementation of the evaluation of the function.
Returns
-------
evalImpl : :class:`~openturns.NumericalMathFunctionEvaluationImplementation`
Implementation of the evaluation of a function.
"""
return _diff.FiniteDifferenceGradient_getEvaluation(self)
def setFiniteDifferenceStep(self, finiteDifferenceStep):
"""
Set the finite difference step.
Parameters
----------
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
"""
return _diff.FiniteDifferenceGradient_setFiniteDifferenceStep(self, finiteDifferenceStep)
def getFiniteDifferenceStep(self):
"""
Get the finite difference step.
Returns
-------
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
"""
return _diff.FiniteDifferenceGradient_getFiniteDifferenceStep(self)
def gradient(self, inP):
"""
Get the gradient at some point.
Parameters
----------
point : sequence of float
Point where the gradient is computed.
Returns
-------
gradient : :class:`~openturns.Matrix`
Transposed Jacobian matrix evaluated at *point*.
"""
return _diff.FiniteDifferenceGradient_gradient(self, inP)
def __init__(self, *args):
this = _diff.new_FiniteDifferenceGradient(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_FiniteDifferenceGradient
__del__ = lambda self: None
FiniteDifferenceGradient_swigregister = _diff.FiniteDifferenceGradient_swigregister
FiniteDifferenceGradient_swigregister(FiniteDifferenceGradient)
class FiniteDifferenceHessian(openturns.func.NumericalMathHessianImplementation):
"""
Base class for second order centered finite-difference scheme.
Available constructors:
FiniteDifferenceHessian(*epsilon, evalImpl*)
FiniteDifferenceHessian(*step, evalImpl*)
Parameters
----------
evalImpl : :class:`~openturns.NumericalMathEvaluationImplementation`
Implementation of the evaluation of a function.
epsilon : float, sequence of float
Finite difference steps for each dimension.
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
Notes
-----
Base class to define second order finite-difference scheme. The hessian
can be computed only through its derived class:
- :class:`~openturns.CenteredFiniteDifferenceHessian`.
"""
__swig_setmethods__ = {}
for _s in [openturns.func.NumericalMathHessianImplementation]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, FiniteDifferenceHessian, name, value)
__swig_getmethods__ = {}
for _s in [openturns.func.NumericalMathHessianImplementation]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, FiniteDifferenceHessian, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.FiniteDifferenceHessian_getClassName(self)
def __eq__(self, other):
return _diff.FiniteDifferenceHessian___eq__(self, other)
def __repr__(self):
return _diff.FiniteDifferenceHessian___repr__(self)
def getInputDimension(self):
"""
Get the input dimension.
Returns
-------
dimension : int
Input dimension.
"""
return _diff.FiniteDifferenceHessian_getInputDimension(self)
def getOutputDimension(self):
"""
Get the output dimension.
Returns
-------
dimension : int
Output dimension.
"""
return _diff.FiniteDifferenceHessian_getOutputDimension(self)
def getEpsilon(self):
"""
Get the finite difference steps.
Returns
-------
epsilon : :class:`~openturns.NumericalPoint`
Finite difference steps for each dimension.
"""
return _diff.FiniteDifferenceHessian_getEpsilon(self)
def getEvaluation(self):
"""
Get the implementation of the evaluation of the function.
Returns
-------
evalImpl : :class:`~openturns.NumericalMathFunctionEvaluationImplementation`
Implementation of the evaluation of a function.
"""
return _diff.FiniteDifferenceHessian_getEvaluation(self)
def setFiniteDifferenceStep(self, finiteDifferenceStep):
"""
Set the finite difference step.
Parameters
----------
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
"""
return _diff.FiniteDifferenceHessian_setFiniteDifferenceStep(self, finiteDifferenceStep)
def getFiniteDifferenceStep(self):
"""
Get the finite difference step.
Returns
-------
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
"""
return _diff.FiniteDifferenceHessian_getFiniteDifferenceStep(self)
def hessian(self, inP):
"""
Get the hessian at some point.
Parameters
----------
point : sequence of float
Point where the hessian is computed.
Returns
-------
hessian : :class:`~openturns.SymmetricTensor`
Hessian evaluated at *point*.
"""
return _diff.FiniteDifferenceHessian_hessian(self, inP)
def __init__(self, *args):
this = _diff.new_FiniteDifferenceHessian(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_FiniteDifferenceHessian
__del__ = lambda self: None
FiniteDifferenceHessian_swigregister = _diff.FiniteDifferenceHessian_swigregister
FiniteDifferenceHessian_swigregister(FiniteDifferenceHessian)
class CenteredFiniteDifferenceGradient(FiniteDifferenceGradient):
"""
First order centered finite-difference scheme.
Available constructors:
CenteredFiniteDifferenceGradient(*epsilon, evalImpl*)
CenteredFiniteDifferenceGradient(*step, evalImpl*)
Parameters
----------
evalImpl : :class:`~openturns.NumericalMathEvaluationImplementation`
Implementation of the evaluation of a function.
epsilon : float, sequence of float
Finite difference steps for each dimension.
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
Notes
-----
*CenteredFiniteDifferenceGradient* provides a first order centered finite-
difference scheme:
.. math::
\\frac{\\partial f_j}{\\partial x_i} \\approx \\frac{f_j(x + \\epsilon_i) - f_j(x - \\epsilon_i)}
{2 \\epsilon_i}
Examples
--------
>>> import openturns as ot
>>> formulas = ['x1 * sin(x2)', 'cos(x1 + x2)', '(x2 + 1) * exp(x1 - 2 * x2)']
>>> myFunc = ot.NumericalMathFunction(['x1', 'x2'], ['y1', 'y2', 'y3'], formulas)
>>> epsilon = [0.01]*2
>>> myGradient = ot.CenteredFiniteDifferenceGradient(epsilon, myFunc.getEvaluation())
>>> inPoint = [1.]*2
>>> print(myGradient.gradient(inPoint))
[[ 0.841471 -0.909282 0.735771 ]
[ 0.540293 -0.909282 -1.10366 ]]
"""
__swig_setmethods__ = {}
for _s in [FiniteDifferenceGradient]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, CenteredFiniteDifferenceGradient, name, value)
__swig_getmethods__ = {}
for _s in [FiniteDifferenceGradient]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, CenteredFiniteDifferenceGradient, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.CenteredFiniteDifferenceGradient_getClassName(self)
def __repr__(self):
return _diff.CenteredFiniteDifferenceGradient___repr__(self)
def __str__(self, *args):
return _diff.CenteredFiniteDifferenceGradient___str__(self, *args)
def gradient(self, inP):
"""
Get the gradient at some point.
Parameters
----------
point : sequence of float
Point where the gradient is computed.
Returns
-------
gradient : :class:`~openturns.Matrix`
Transposed Jacobian matrix evaluated at *point*.
"""
return _diff.CenteredFiniteDifferenceGradient_gradient(self, inP)
def __init__(self, *args):
this = _diff.new_CenteredFiniteDifferenceGradient(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_CenteredFiniteDifferenceGradient
__del__ = lambda self: None
CenteredFiniteDifferenceGradient_swigregister = _diff.CenteredFiniteDifferenceGradient_swigregister
CenteredFiniteDifferenceGradient_swigregister(CenteredFiniteDifferenceGradient)
class CenteredFiniteDifferenceHessian(FiniteDifferenceHessian):
"""
Second order centered finite-difference scheme.
Available constructors:
CenteredFiniteDifferenceHessian(*epsilon, evalImpl*)
CenteredFiniteDifferenceHessian(*step, evalImpl*)
Parameters
----------
evalImpl : :class:`~openturns.NumericalMathEvaluationImplementation`
Implementation of the evaluation of a function.
epsilon : float, sequence of float
Finite difference steps for each dimension.
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
Notes
-----
*CenteredFiniteDifferenceHessian* provides a second order centered finite-
difference scheme:
.. math::
\\frac{\\partial^2 f_k}{\\partial x_i \\partial x_j} \\approx
\\frac{
f_k(x + \\epsilon_i + \\epsilon_j) -
f_k(x + \\epsilon_i - \\epsilon_j) +
f_k(x - \\epsilon_i - \\epsilon_j) -
f_k(x - \\epsilon_i + \\epsilon_j)}
{4 \\epsilon_i \\epsilon_j}
Examples
--------
>>> import openturns as ot
>>> formulas = ['x1 * sin(x2)', 'cos(x1 + x2)', '(x2 + 1) * exp(x1 - 2 * x2)']
>>> myFunc = ot.NumericalMathFunction(['x1', 'x2'], ['y1', 'y2', 'y3'], formulas)
>>> epsilon = [0.01]*2
>>> myHessian = ot.CenteredFiniteDifferenceHessian(epsilon, myFunc.getEvaluation())
>>> inPoint = [1.]*2
>>> print(myHessian.hessian(inPoint))
sheet #0
[[ 0 0.540293 ]
[ 0.540293 -0.841443 ]]
sheet #1
[[ 0.416133 0.416133 ]
[ 0.416133 0.416133 ]]
sheet #2
[[ 0.735783 -1.10368 ]
[ -1.10368 1.47152 ]]
"""
__swig_setmethods__ = {}
for _s in [FiniteDifferenceHessian]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, CenteredFiniteDifferenceHessian, name, value)
__swig_getmethods__ = {}
for _s in [FiniteDifferenceHessian]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, CenteredFiniteDifferenceHessian, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.CenteredFiniteDifferenceHessian_getClassName(self)
def __eq__(self, other):
return _diff.CenteredFiniteDifferenceHessian___eq__(self, other)
def __repr__(self):
return _diff.CenteredFiniteDifferenceHessian___repr__(self)
def __str__(self, *args):
return _diff.CenteredFiniteDifferenceHessian___str__(self, *args)
def hessian(self, inP):
"""
Get the hessian at some point.
Parameters
----------
point : sequence of float
Point where the hessian is computed.
Returns
-------
hessian : :class:`~openturns.SymmetricTensor`
Hessian evaluated at *point*.
"""
return _diff.CenteredFiniteDifferenceHessian_hessian(self, inP)
def __init__(self, *args):
this = _diff.new_CenteredFiniteDifferenceHessian(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_CenteredFiniteDifferenceHessian
__del__ = lambda self: None
CenteredFiniteDifferenceHessian_swigregister = _diff.CenteredFiniteDifferenceHessian_swigregister
CenteredFiniteDifferenceHessian_swigregister(CenteredFiniteDifferenceHessian)
class NonCenteredFiniteDifferenceGradient(FiniteDifferenceGradient):
"""
First order non-centered finite-difference scheme.
Available constructors:
NonCenteredFiniteDifferenceGradient(*epsilon, evalImpl*)
NonCenteredFiniteDifferenceGradient(*step, evalImpl*)
Parameters
----------
evalImpl : :class:`~openturns.NumericalMathEvaluationImplementation`
Implementation of the evaluation of a function.
epsilon : float, sequence of float
Finite difference steps for each dimension.
step : :class:`~openturns.FiniteDifferenceStep`
Defines how finite difference steps values are computed.
Notes
-----
*NonCenteredFiniteDifferenceGradient* provides a first order non-centered
finite-difference scheme:
.. math::
\\frac{\\partial f_j}{\\partial x_i} \\approx \\frac{f_j(x + \\epsilon_i) - f_j(x)}
{\\epsilon_i}
Examples
--------
>>> import openturns as ot
>>> formulas = ['x1 * sin(x2)', 'cos(x1 + x2)', '(x2 + 1) * exp(x1 - 2 * x2)']
>>> myFunc = ot.NumericalMathFunction(['x1', 'x2'], ['y1', 'y2', 'y3'], formulas)
>>> epsilon = [0.01]*2
>>> myGradient = ot.NonCenteredFiniteDifferenceGradient(epsilon, myFunc.getEvaluation())
>>> inPoint = [1.]*2
>>> print(myGradient.gradient(inPoint))
[[ 0.841471 -0.907202 0.73945 ]
[ 0.536086 -0.907202 -1.09631 ]]
"""
__swig_setmethods__ = {}
for _s in [FiniteDifferenceGradient]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, NonCenteredFiniteDifferenceGradient, name, value)
__swig_getmethods__ = {}
for _s in [FiniteDifferenceGradient]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, NonCenteredFiniteDifferenceGradient, name)
def getClassName(self):
"""
Accessor to the object's name.
Returns
-------
class_name : str
The object class name (`object.__class__.__name__`).
"""
return _diff.NonCenteredFiniteDifferenceGradient_getClassName(self)
def __repr__(self):
return _diff.NonCenteredFiniteDifferenceGradient___repr__(self)
def __str__(self, *args):
return _diff.NonCenteredFiniteDifferenceGradient___str__(self, *args)
def gradient(self, inP):
"""
Get the gradient at some point.
Parameters
----------
point : sequence of float
Point where the gradient is computed.
Returns
-------
gradient : :class:`~openturns.Matrix`
Transposed Jacobian matrix evaluated at *point*.
"""
return _diff.NonCenteredFiniteDifferenceGradient_gradient(self, inP)
def __init__(self, *args):
this = _diff.new_NonCenteredFiniteDifferenceGradient(*args)
try:
self.this.append(this)
except:
self.this = this
__swig_destroy__ = _diff.delete_NonCenteredFiniteDifferenceGradient
__del__ = lambda self: None
NonCenteredFiniteDifferenceGradient_swigregister = _diff.NonCenteredFiniteDifferenceGradient_swigregister
NonCenteredFiniteDifferenceGradient_swigregister(NonCenteredFiniteDifferenceGradient)
# This file is compatible with both classic and new-style classes.
|