minimize¶
-
class
zfit.minimize.
Minuit
(strategy: zfit.minimizers.baseminimizer.ZfitStrategy = None, minimize_strategy: int = 1, tolerance: float = None, verbosity: int = 5, name: str = None, ncall: int = 10000, **minimizer_options)[source]¶ Bases:
zfit.minimizers.baseminimizer.BaseMinimizer
,zfit.util.cache.Cachable
Parameters: - () (**minimizer_options) – A
ZfitStrategy
object that defines the behavior of - minimizer in certain situations. (the) –
- () – A number used by minuit to define the strategy
- () – Internal numerical tolerance
- () – Regulates how much will be printed during minimization. Values between 0 and 10 are valid.
- () – Name of the minimizer
- () – Maximum number of minimization steps.
- () – Options for the minimizer internally used.
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add_cache_dependents
(cache_dependents: Union[zfit.core.interfaces.ZfitCachable, Iterable[zfit.core.interfaces.ZfitCachable]], allow_non_cachable: bool = True)¶ Add dependents that render the cache invalid if they change.
Parameters: - cache_dependents (ZfitCachable) –
- allow_non_cachable (bool) – If True, allow cache_dependents to be non-cachables. If False, any cache_dependents that is not a ZfitCachable will raise an error.
Raises: TypeError
– if one of the cache_dependents is not a ZfitCachable _and_ allow_non_cachable if False.
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minimize
(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult¶ Fully minimize the loss with respect to params.
Parameters: - loss (ZfitLoss) – Loss to be minimized.
- params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.
Returns: The fit result.
Return type: FitResult
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register_cacher
(cacher: Union[zfit.core.interfaces.ZfitCachable, Iterable[zfit.core.interfaces.ZfitCachable]])¶ Register a cacher that caches values produces by this instance; a dependent.
Parameters: () (cacher) –
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reset_cache
(reseter: zfit.util.cache.ZfitCachable)¶
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reset_cache_self
()¶ Clear the cache of self and all dependent cachers.
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sess
¶
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set_sess
(sess: tensorflow.python.client.session.Session)¶ Set the session (temporarily) for this instance. If None, the auto-created default is taken.
Parameters: sess (tf.Session) –
-
step
(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None)¶ Perform a single step in the minimization (if implemented).
Parameters: () (params) – Returns:
Raises: NotImplementedError
– if the step method is not implemented in the minimizer.
-
tolerance
¶
- () (**minimizer_options) – A
-
class
zfit.minimize.
Scipy
(minimizer='L-BFGS-B', tolerance=None, verbosity=5, name=None, **minimizer_options)[source]¶ Bases:
zfit.minimizers.baseminimizer.BaseMinimizer
-
copy
()¶
-
minimize
(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult¶ Fully minimize the loss with respect to params.
Parameters: - loss (ZfitLoss) – Loss to be minimized.
- params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.
Returns: The fit result.
Return type: FitResult
-
sess
¶
-
set_sess
(sess: tensorflow.python.client.session.Session)¶ Set the session (temporarily) for this instance. If None, the auto-created default is taken.
Parameters: sess (tf.Session) –
-
step
(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None)¶ Perform a single step in the minimization (if implemented).
Parameters: () (params) – Returns:
Raises: NotImplementedError
– if the step method is not implemented in the minimizer.
-
tolerance
¶
-
-
class
zfit.minimize.
Adam
(tolerance=None, learning_rate=0.2, beta1=0.9, beta2=0.999, epsilon=1e-08, use_locking=False, name='Adam', **kwargs)[source]¶ Bases:
zfit.minimizers.base_tf.WrapOptimizer
-
copy
()¶
-
minimize
(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult¶ Fully minimize the loss with respect to params.
Parameters: - loss (ZfitLoss) – Loss to be minimized.
- params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.
Returns: The fit result.
Return type: FitResult
-
sess
¶
-
set_sess
(sess: tensorflow.python.client.session.Session)¶ Set the session (temporarily) for this instance. If None, the auto-created default is taken.
Parameters: sess (tf.Session) –
-
step
(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None)¶ Perform a single step in the minimization (if implemented).
Parameters: () (params) – Returns:
Raises: NotImplementedError
– if the step method is not implemented in the minimizer.
-
tolerance
¶
-
-
class
zfit.minimize.
WrapOptimizer
(optimizer, tolerance=None, verbosity=None, name=None, **kwargs)[source]¶ Bases:
zfit.minimizers.baseminimizer.BaseMinimizer
-
copy
()¶
-
minimize
(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult¶ Fully minimize the loss with respect to params.
Parameters: - loss (ZfitLoss) – Loss to be minimized.
- params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.
Returns: The fit result.
Return type: FitResult
-
sess
¶
-
set_sess
(sess: tensorflow.python.client.session.Session)¶ Set the session (temporarily) for this instance. If None, the auto-created default is taken.
Parameters: sess (tf.Session) –
-
step
(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None)¶ Perform a single step in the minimization (if implemented).
Parameters: () (params) – Returns:
Raises: NotImplementedError
– if the step method is not implemented in the minimizer.
-
tolerance
¶
-
-
class
zfit.minimize.
Adam
(tolerance=None, learning_rate=0.2, beta1=0.9, beta2=0.999, epsilon=1e-08, use_locking=False, name='Adam', **kwargs)[source] Bases:
zfit.minimizers.base_tf.WrapOptimizer
-
copy
()
-
minimize
(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult Fully minimize the loss with respect to params.
Parameters: - loss (ZfitLoss) – Loss to be minimized.
- params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.
Returns: The fit result.
Return type: FitResult
-
sess
-
set_sess
(sess: tensorflow.python.client.session.Session) Set the session (temporarily) for this instance. If None, the auto-created default is taken.
Parameters: sess (tf.Session) –
-
step
(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None) Perform a single step in the minimization (if implemented).
Parameters: () (params) – Returns:
Raises: NotImplementedError
– if the step method is not implemented in the minimizer.
-
tolerance
-
-
class
zfit.minimize.
Minuit
(strategy: zfit.minimizers.baseminimizer.ZfitStrategy = None, minimize_strategy: int = 1, tolerance: float = None, verbosity: int = 5, name: str = None, ncall: int = 10000, **minimizer_options)[source] Bases:
zfit.minimizers.baseminimizer.BaseMinimizer
,zfit.util.cache.Cachable
Parameters: - () (**minimizer_options) – A
ZfitStrategy
object that defines the behavior of - minimizer in certain situations. (the) –
- () – A number used by minuit to define the strategy
- () – Internal numerical tolerance
- () – Regulates how much will be printed during minimization. Values between 0 and 10 are valid.
- () – Name of the minimizer
- () – Maximum number of minimization steps.
- () – Options for the minimizer internally used.
-
add_cache_dependents
(cache_dependents: Union[zfit.core.interfaces.ZfitCachable, Iterable[zfit.core.interfaces.ZfitCachable]], allow_non_cachable: bool = True) Add dependents that render the cache invalid if they change.
Parameters: - cache_dependents (ZfitCachable) –
- allow_non_cachable (bool) – If True, allow cache_dependents to be non-cachables. If False, any cache_dependents that is not a ZfitCachable will raise an error.
Raises: TypeError
– if one of the cache_dependents is not a ZfitCachable _and_ allow_non_cachable if False.
-
copy
()[source]
-
minimize
(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult Fully minimize the loss with respect to params.
Parameters: - loss (ZfitLoss) – Loss to be minimized.
- params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.
Returns: The fit result.
Return type: FitResult
-
register_cacher
(cacher: Union[zfit.core.interfaces.ZfitCachable, Iterable[zfit.core.interfaces.ZfitCachable]]) Register a cacher that caches values produces by this instance; a dependent.
Parameters: () (cacher) –
-
reset_cache
(reseter: zfit.util.cache.ZfitCachable)
-
reset_cache_self
() Clear the cache of self and all dependent cachers.
-
sess
-
set_sess
(sess: tensorflow.python.client.session.Session) Set the session (temporarily) for this instance. If None, the auto-created default is taken.
Parameters: sess (tf.Session) –
-
step
(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None) Perform a single step in the minimization (if implemented).
Parameters: () (params) – Returns:
Raises: NotImplementedError
– if the step method is not implemented in the minimizer.
-
tolerance
- () (**minimizer_options) – A
-
class
zfit.minimize.
Scipy
(minimizer='L-BFGS-B', tolerance=None, verbosity=5, name=None, **minimizer_options)[source] Bases:
zfit.minimizers.baseminimizer.BaseMinimizer
-
copy
()
-
minimize
(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult Fully minimize the loss with respect to params.
Parameters: - loss (ZfitLoss) – Loss to be minimized.
- params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.
Returns: The fit result.
Return type: FitResult
-
sess
-
set_sess
(sess: tensorflow.python.client.session.Session) Set the session (temporarily) for this instance. If None, the auto-created default is taken.
Parameters: sess (tf.Session) –
-
step
(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None) Perform a single step in the minimization (if implemented).
Parameters: () (params) – Returns:
Raises: NotImplementedError
– if the step method is not implemented in the minimizer.
-
tolerance
-