Source code for bayesflow.adapters.transforms.log

import numpy as np

from bayesflow.utils.serialization import serializable, serialize

from .elementwise_transform import ElementwiseTransform


[docs] @serializable("bayesflow.adapters") class Log(ElementwiseTransform): """Log transforms a variable. Parameters ---------- p1 : boolean Add 1 to the input before taking the logarithm? Examples -------- >>> adapter = bf.Adapter().log(["x"]) """ def __init__(self, *, p1: bool = False): super().__init__() self.p1 = p1
[docs] def forward(self, data: np.ndarray, **kwargs) -> np.ndarray: if self.p1: return np.log1p(data) else: return np.log(data)
[docs] def inverse(self, data: np.ndarray, **kwargs) -> np.ndarray: if self.p1: return np.expm1(data) else: return np.exp(data)
[docs] def get_config(self) -> dict: return serialize({"p1": self.p1})
[docs] def log_det_jac(self, data: np.ndarray, inverse: bool = False, **kwargs) -> np.ndarray: if self.p1: ldj = -np.log1p(data) else: ldj = -np.log(data) if inverse: ldj = -ldj return np.sum(ldj, axis=tuple(range(1, ldj.ndim)))