Source code for bayesflow.adapters.transforms.keep
from collections.abc import Sequence
from keras.saving import (
deserialize_keras_object as deserialize,
register_keras_serializable as serializable,
serialize_keras_object as serialize,
)
from .transform import Transform
[docs]
@serializable(package="bayesflow.adapters")
class Keep(Transform):
"""
Name the data parameters that should be kept for futher calculation.
Parameters
----------
keys : sequence of str
The names of kept data variables as strings.
Examples
--------
Two moons simulator generates data for priors alpha, r and theta as well as observation data x.
We are interested only in theta and x, to keep only theta and x we should use the following;
>>> adapter = (
bf.adapters.Adapter()
# drop data from unneeded priors alpha, and r
# only keep theta and x
.keep(("theta", "x"))
)
The following example shows the usage in a more general case:
>>> a = [1, 2, 3, 4]
>>> b = [[1, 2], [3, 4]]
>>> c = [[5, 6, 7, 8]]
>>> dat = dict(a=a, b=b, c=c)
Here we want to only keep elements b and c
>>> keeper = bf.adapters.transforms.Keep(("b", "c"))
>>> keeper.forward(dat)
{'b': [[1, 2], [3, 4]], 'c': [[5, 6, 7, 8]]}
"""
def __init__(self, keys: Sequence[str]):
self.keys = keys
[docs]
@classmethod
def from_config(cls, config: dict, custom_objects=None) -> "Keep":
return cls(keys=deserialize(config["keys"], custom_objects))
[docs]
def get_config(self) -> dict:
return {"keys": serialize(self.keys)}
[docs]
def forward(self, data: dict[str, any], **kwargs) -> dict[str, any]:
return {key: value for key, value in data.items() if key in self.keys}
[docs]
def inverse(self, data: dict[str, any], **kwargs) -> dict[str, any]:
# non-invertible transform
return data
