You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: hyperloglog.rs
    path of file: ./repos/stract/crates/core/src
    
    the code of the file until where you have to start completion: // Stract is an open source web search engine.
// Copyright (C) 2023 Stract ApS
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as
// published by the Free Software Foundation, either version 3 of the
// License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <https://www.gnu.org/licenses/>.

// This file is heavily inspired by the hyperloglog implementation in https://github.com/crepererum/pdatastructs.rs.
// It seemed a bit excessive to add another dependency just for hyperloglog
// but huge credits to the authors of that crate.

use std::{
    collections::hash_map::DefaultHasher,
    hash::{Hash as _, Hasher as _},
    marker::PhantomData,
};

use serde::{Deserialize, Serialize};

pub(crate) const THRESHOLD_DATA_OFFSET: usize = 4;
pub(crate) const THRESHOLD_DATA_VEC: &[usize] 
    
    pub fn estimate_bias(&self, e: f64, b: usize) -> f64 {
        const K: usize = 6;

        // binary search first nearest neighbor
        let lookup_array = RAW_ESTIMATE_DATA_VEC[b - 1 - RAW_ESTIMATE_DATA_OFFSET];

        let mut idx_left = match lookup_array.binary_search_by(|v| v.total_cmp(&e)) {
            Err(i) if i == lookup_array.len() => Some(i - 1), // no match, i points to end of array
            Ok(i) | Err(i) => Some(i),                        // exact match
        };

        let mut idx_right = match idx_left {
            Some(i) => {
                if i < lookup_array.len() - 1 {
                    Some(i + 1)
                } else {
                    None
                }
            }
            _ => None,
        };

        // collect k nearest neighbors
        debug_assert!(lookup_array.len() >= K);
        let mut neighbors = [0; K];
        for neighbor in &mut neighbors {
            let (right_instead_left, idx) = match (idx_left, idx_right) {
                (Some(i_left), Some(i_right)) => {
                    // 2 candidates, find better one
                    let delta_left = (lookup_array[i_left] - e).abs();
                    let delta_right = (lookup_array[i_right] - e).abs();
                    if delta_right < delta_left {
                        (true, i_right)
                    } else {
                        (false, i_left)
                    }
                }
                (Some(i_left), None) => {
                    // just left one is there, use it
                    (false, i_left)
                }
                (None, Some(i_right)) => {
                    // just right one is there, use it
                    (true, i_right)
                }
                _ => unreachable!("neighborhood search failed, this is bug!"),
            };
            *neighbor = idx;
            if right_instead_left {
                idx_right = if idx < lookup_array.len() - 1 {
                    Some(idx + 1)
                } else {
                    None
                };
            } else {
                idx_left = if idx > 0 { Some(idx - 1) } else { None };
            }
        }

        // calculate mean of neighbors
        let bias_data = BIAS_DATA_VEC[b - 1 - BIAS_DATA_OFFSET];

        neighbors.iter().map(|&i| bias_data[i]).sum::<f64>() / (K as f64)
    }