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use ndarray::{Array1, ArrayView1};
#[derive(Debug, Clone)]
pub struct LogProbVector {
log_probabilities: Array1<f32>,
}
impl LogProbVector {
pub fn uniform(n: usize) -> LogProbVector {
LogProbVector {
log_probabilities: vec![0.0; n].into(),
}
}
pub fn deterministic(n: usize, i: usize) -> LogProbVector {
let mut data = vec![std::f32::NEG_INFINITY; n];
if i < n {
data[i] = 0.0;
}
LogProbVector {
log_probabilities: data.into(),
}
}
pub fn from_log_probabilities(log_probabilities: Array1<f32>) -> LogProbVector {
LogProbVector { log_probabilities }
}
pub fn log_probabilities(&self) -> ArrayView1<f32> {
self.log_probabilities.view()
}
pub fn as_probabilities(&self) -> Array1<f32> {
let probabilities = self.log_probabilities.mapv(f32::exp);
let norm_cst = probabilities.sum();
if norm_cst > 0.0 {
probabilities / norm_cst
} else {
probabilities
}
}
pub fn renormalize(&mut self) {
let sum = crate::math::log_sum_exp_vec(self.log_probabilities.view());
self.log_probabilities.map_inplace(|v| *v -= sum);
}
pub fn prod(&mut self, other: &LogProbVector) {
self.log_probabilities += &other.log_probabilities;
}
pub fn reset(&mut self) {
for v in self.log_probabilities.iter_mut() {
*v = 0.0;
}
}
}