class zfit.loss.SimpleLoss(func, deps=<zfit.util.checks.NotSpecified object>, dependents=<zfit.util.checks.NotSpecified object>, errordef=None)[source]

Bases: zfit.core.loss.BaseLoss

Loss from a (function returning a) Tensor.

  • func (Callable) – Callable that constructs the loss and returns a tensor.

  • deps (Iterable[ForwardRef]) – The dependents (independent zfit.Parameter) of the loss. If not given, the dependents are figured out automatically.

  • errordef (Optional[float]) – Definition of which change in the loss corresponds to a change of 1 sigma. For example, 1 for Chi squared, 0.5 for negative log-likelihood.

add_cache_deps(cache_deps, allow_non_cachable=True)

Add dependencies that render the cache invalid if they change.

  • cache_deps (Union[ForwardRef, Iterable[ForwardRef]]) –

  • 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.


TypeError – if one of the cache_dependents is not a ZfitCachable _and_ allow_non_cachable if False.

property dtype

The dtype of the object

Return type



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


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

Return type




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).

Return type


get_params(floating=True, is_yield=None, extract_independent=True, only_floating=<class 'zfit.util.checks.NotSpecified'>)

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.

  • floating (Optional[bool]) – if a parameter is floating, e.g. if floating() returns True

  • is_yield (Optional[bool]) – 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 (Optional[bool]) – If the parameter is an independent parameter, i.e. if it is a ZfitIndependentParameter.

Return type



Register a cacher that caches values produces by this instance; a dependent.


cacher (Union[ForwardRef, Iterable[ForwardRef]]) –


Clear the cache of self and all dependent cachers.