baseobject

Baseclass for most objects appearing in zfit.

class zfit.core.baseobject.BaseNumeric(name, **kwargs)

Bases: zfit.util.cache.GraphCachable, zfit.core.dependents.BaseDependentsMixin, zfit.core.baseobject.BaseParametrized, zfit.core.interfaces.ZfitNumericParametrized, zfit.core.baseobject.BaseObject

add_cache_deps(cache_deps: Union[zfit.core.interfaces.ZfitCachable, Iterable[zfit.core.interfaces.ZfitCachable]], allow_non_cachable: bool = True)

Add dependencies that render the cache invalid if they change.

Parameters:

• cache_deps (ZfitGraphCachable) –
• 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(deep: bool = False, name: str = None, **overwrite_params) → zfit.core.interfaces.ZfitObject

dtype

The dtype of the object

get_cache_deps(only_floating: bool = True) -> OrderedSet(['z', 'f', 'i', 't', '.', 'P', 'a', 'r', 'm', 'e'])

Return a set of all independent Parameter that this object depends on.

Parameters:only_floating (bool) – If True, only return floating Parameter

get_dependencies(only_floating: bool = True) -> OrderedSet(['z', 'f', 'i', 't', '.', 'P', 'a', 'r', 'm', 'e'])

DEPRECATED FUNCTION

Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use get_params instead if you want to retrieve the independent parameters or get_cache_deps in case you need the numerical cache dependents (advanced).

get_params(floating: Optional[bool] = True, is_yield: Optional[bool] = None, extract_independent: Optional[bool] = True, only_floating=<class 'zfit.util.checks.NotSpecified'>) → Set[zfit.core.interfaces.ZfitParameter]

Recursively collect parameters that this object depends on according to the filter criteria.

Which parameters should be included can be steered using the arguments as a filter.

• None: do not filter on this. E.g. floating=None will return parameters that are floating as well as

  parameters that are fixed.

• True: only return parameters that fulfil this criterion

• False: only return parameters that do not fulfil this criterion. E.g. floating=False will return

  only parameters that are not floating.

Parameters:

• floating – if a parameter is floating, e.g. if floating() returns True
• is_yield – if a parameter is a yield of the _current_ model. This won’t be applied recursively, but may include yields if they do also represent a parameter parametrizing the shape. So if the yield of the current model depends on other yields (or also non-yields), this will be included. If, however, just submodels depend on a yield (as their yield) and it is not correlated to the output of our model, they won’t be included.
• extract_independent – If the parameter is an independent parameter, i.e. if it is a ZfitIndependentParameter.

graph_caching_methods = []

instances = <_weakrefset.WeakSet object>

name

The name of the object.

params

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.ZfitGraphCachable)

reset_cache_self()

Clear the cache of self and all dependent cachers.

class zfit.core.baseobject.BaseObject(name, **kwargs)

Bases: zfit.core.interfaces.ZfitObject

copy(deep: bool = False, name: str = None, **overwrite_params) → zfit.core.interfaces.ZfitObject

name

The name of the object.

class zfit.core.baseobject.BaseParametrized(params, **kwargs)

Bases: zfit.core.interfaces.ZfitParametrized

get_cache_deps(only_floating: bool = True) -> OrderedSet(['z', 'f', 'i', 't', '.', 'P', 'a', 'r', 'm', 'e'])

get_dependencies(only_floating: bool = True) -> OrderedSet(['z', 'f', 'i', 't', '.', 'P', 'a', 'r', 'm', 'e'])

DEPRECATED FUNCTION

Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use get_params instead if you want to retrieve the independent parameters or get_cache_deps in case you need the numerical cache dependents (advanced).

get_params(floating: Optional[bool] = True, is_yield: Optional[bool] = None, extract_independent: Optional[bool] = True, only_floating=<class 'zfit.util.checks.NotSpecified'>) → Set[zfit.core.interfaces.ZfitParameter]

Recursively collect parameters that this object depends on according to the filter criteria.

Which parameters should be included can be steered using the arguments as a filter.

• None: do not filter on this. E.g. floating=None will return parameters that are floating as well as

  parameters that are fixed.

• True: only return parameters that fulfil this criterion

• False: only return parameters that do not fulfil this criterion. E.g. floating=False will return

  only parameters that are not floating.

Parameters:

• floating – if a parameter is floating, e.g. if floating() returns True
• is_yield – if a parameter is a yield of the _current_ model. This won’t be applied recursively, but may include yields if they do also represent a parameter parametrizing the shape. So if the yield of the current model depends on other yields (or also non-yields), this will be included. If, however, just submodels depend on a yield (as their yield) and it is not correlated to the output of our model, they won’t be included.
• extract_independent – If the parameter is an independent parameter, i.e. if it is a ZfitIndependentParameter.

params

zfit.core.baseobject.extract_filter_params(params: Iterable[zfit.core.interfaces.ZfitParametrized], floating: Optional[bool] = True, extract_independent: Optional[bool] = True) → Set[zfit.core.interfaces.ZfitParameter]