pyhf.experimental.modifiers.add_custom_modifier

pyhf.experimental.modifiers.add_custom_modifier(func_name: str, deps: list[str], new_params: dict[str, dict[str, Sequence[float]]]) → dict[str, tuple[pyhf.experimental.modifiers.BaseBuilder, pyhf.experimental.modifiers.BaseApplier]]

Add a custom modifier type with the modifier data defined through a custom numexpr string expression.

Example

>>> import pyhf
>>> import pyhf.experimental.modifiers
>>> pyhf.set_backend("numpy")
>>> new_params = {
...     "m1": {"inits": (1.0,), "bounds": ((-5.0, 5.0),)},
...     "m2": {"inits": (1.0,), "bounds": ((-5.0, 5.0),)},
... }
>>> expanded_pyhf = pyhf.experimental.modifiers.add_custom_modifier(
...     "custom", ["m1", "m2"], new_params
... )
>>> model = pyhf.Model(
...     {
...         "channels": [
...             {
...                 "name": "singlechannel",
...                 "samples": [
...                     {
...                         "name": "signal",
...                         "data": [10, 20],
...                         "modifiers": [
...                             {
...                                 "name": "f2",
...                                 "type": "custom",
...                                 "data": {"expr": "m1"},
...                             },
...                         ],
...                     },
...                     {
...                         "name": "background",
...                         "data": [100, 150],
...                         "modifiers": [
...                             {
...                                 "name": "f1",
...                                 "type": "custom",
...                                 "data": {"expr": "m1+(m2**2)"},
...                             },
...                         ],
...                     },
...                 ],
...             }
...         ]
...     },
...     modifier_set=expanded_pyhf,
...     poi_name="m1",
...     validate=False,
...     batch_size=1,
... )
>>> model.config.modifiers
[('f1', 'custom'), ('f2', 'custom')]

Parameters:

• func_name (str) – The name of the custom modifier type.

• deps (list) – The names of the new parameters of the modifier function.

• new_params (dict) – The new parameters.

Returns:

The updated pyhf.modifiers.histfactory_set with the added custom modifier type.

Return type:

dict

New in version 0.8.0.