BaseLoss#
- class zfit.loss.BaseLoss(model, data, fit_range=None, constraints=None, options=None)[source]#
Bases:
ZfitLoss
,BaseNumeric
A “simultaneous fit” can be performed by giving one or more
model
,data
,fit_range
to the loss. The length of each has to match the length of the others.- Parameters
model (ztyping.ModelsInputType) – The model or models to evaluate the data on
data (ztyping.DataInputType) – Data to use
fit_range (ztyping.LimitsTypeInput) – The fitting range. It’s the norm_range for the models (if they have a norm_range) and the data_range for the data.
constraints (ztyping.ConstraintsTypeInput) – A Tensor representing a loss constraint. Using
zfit.constraint.*
allows for easy use of predefined constraints.options (Mapping | None) – Different options for the loss calculation.
- __call__(_x=None)[source]#
Calculate the loss value with the given input for the free parameters.
- Parameters
*positional* – Array-like argument to set the parameters. The order of the values correspond to the position of the parameters in
get_params()
(called without any arguments). For more detailed control, it is always possible to wrapvalue()
and set the desired parameters manually.- Return type
Tensor
- Returns
Calculated loss value as a scalar.
- add_cache_deps(cache_deps, allow_non_cachable=True)#
Add dependencies that render the cache invalid if they change.
- Parameters
cache_deps (
Union
[zfit.core.interfaces.ZfitGraphCachable,Iterable
[zfit.core.interfaces.ZfitGraphCachable]]) –allow_non_cachable (
bool
) – IfTrue
, allowcache_dependents
to be non-cachables. IfFalse
, anycache_dependents
that is not aZfitGraphCachable
will raise an error.
- Raises
TypeError – if one of the
cache_dependents
is not aZfitGraphCachable
_and_allow_non_cachable
ifFalse
.
- property dtype: DType#
The dtype of the object.
- Return type
DType
- get_cache_deps(only_floating=True)#
Return a set of all independent
Parameter
that this object depends on.- Parameters
only_floating (
bool
) – IfTrue
, only return floatingParameter
- Return type
OrderedSet
- get_dependencies(only_floating=True)#
DEPRECATED FUNCTION
Deprecated: 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 orget_cache_deps
in case you need the numerical cache dependents (advanced).- Return type
OrderedSet
- 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.
- None: do not filter on this. E.g.
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.
- False: only return parameters that do not fulfil this criterion. E.g.
- Parameters
floating (bool | None) – if a parameter is floating, e.g. if
floating()
returnsTrue
is_yield (bool | None) – 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 (bool | None) – If the parameter is an independent parameter, i.e. if it is a
ZfitIndependentParameter
.
- Return type
set[ZfitParameter]
- register_cacher(cacher)#
Register a
cacher
that caches values produces by this instance; a dependent.- Parameters
cacher (
Union
[zfit.core.interfaces.ZfitGraphCachable,Iterable
[zfit.core.interfaces.ZfitGraphCachable]]) –
- reset_cache_self()#
Clear the cache of self and all dependent cachers.