Method bar_features

crates/openquant/src/microstructural_features.rs:711–743

(&self, date_time: NaiveDateTime)

        out.push(get_plug_in_entropy(message, 1));
        out.push(get_lempel_ziv_entropy(message));
        out.push(get_konto_entropy(message, 0));
    }

    fn bar_features(&self, date_time: NaiveDateTime) -> Vec<f64> {
        let mut features = vec![
            date_time.and_utc().timestamp_millis() as f64,
            get_avg_tick_size(&self.trade_size),
            self.tick_rule.iter().sum::<f64>(),
            vwap(&self.dollar_size, &self.trade_size),
            get_trades_based_kyle_lambda(&self.price_diff, &self.trade_size, &self.tick_rule),
            get_trades_based_amihud_lambda(&self.log_ret, &self.dollar_size),
            get_trades_based_hasbrouck_lambda(&self.log_ret, &self.dollar_size, &self.tick_rule),
        ];

        let tick_msg =
            encode_tick_rule_array(&self.tick_rule.iter().map(|v| *v as i32).collect::<Vec<_>>())
                .unwrap_or_default();
        self.encode_entropy_features(&tick_msg, &mut features);

        if let Some(enc) = &self.volume_encoding {
            let msg = encode_array(&self.trade_size, enc);
            self.encode_entropy_features(&msg, &mut features);
        }
        if let Some(enc) = &self.pct_encoding {
            let msg = encode_array(&self.log_ret, enc);
            self.encode_entropy_features(&msg, &mut features);
        }
        features
    }

    pub fn get_features_from_csv(&mut self, trades_path: &str) -> Result<Vec<Vec<f64>>, String> {
        let mut rdr = csv::ReaderBuilder::new()
            .has_headers(true)
            .from_path(trades_path)
            .map_err(|e| e.to_string())?;
        let mut bars: Vec<Vec<f64>> = Vec::new();