nautilus-indicators 0.61.0

// -------------------------------------------------------------------------------------------------
//  Copyright (C) 2015-2026 Nautech Systems Pty Ltd. All rights reserved.
//  https://nautechsystems.io
//
//  Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
//  You may not use this file except in compliance with the License.
//  You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
//
//  Unless required by applicable law or agreed to in writing, software
//  distributed under the License is distributed on an "AS IS" BASIS,
//  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
//  See the License for the specific language governing permissions and
//  limitations under the License.
// -------------------------------------------------------------------------------------------------

use std::fmt::Display;

use nautilus_model::{data::QuoteTick, identifiers::InstrumentId};

use crate::indicator::Indicator;

/// An indicator which calculates the efficiency ratio across a rolling window.
///
/// The Kaufman Efficiency measures the ratio of the relative market speed in
/// relation to the volatility, this could be thought of as a proxy for noise.
#[repr(C)]
#[derive(Debug)]
#[cfg_attr(
    feature = "python",
    pyo3::pyclass(module = "nautilus_trader.core.nautilus_pyo3.indicators")
)]
#[cfg_attr(
    feature = "python",
    pyo3_stub_gen::derive::gen_stub_pyclass(module = "nautilus_trader.indicators")
)]
pub struct SpreadAnalyzer {
    pub capacity: usize,
    pub instrument_id: InstrumentId,
    pub current: f64,
    pub average: f64,
    pub initialized: bool,
    has_inputs: bool,
    spreads: Vec<f64>,
}

impl Display for SpreadAnalyzer {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        write!(
            f,
            "{}({},{})",
            self.name(),
            self.capacity,
            self.instrument_id
        )
    }
}

impl Indicator for SpreadAnalyzer {
    fn name(&self) -> String {
        stringify!(SpreadAnalyzer).to_string()
    }

    fn has_inputs(&self) -> bool {
        self.has_inputs
    }
    fn initialized(&self) -> bool {
        self.initialized
    }

    fn handle_quote(&mut self, quote: &QuoteTick) -> anyhow::Result<()> {
        if quote.instrument_id != self.instrument_id {
            return Ok(());
        }

        // Check initialization
        if !self.initialized {
            self.has_inputs = true;

            if self.spreads.len() == self.capacity {
                self.initialized = true;
            }
        }

        let bid: f64 = quote.bid_price.into();
        let ask: f64 = quote.ask_price.into();
        let spread = ask - bid;

        self.current = spread;
        self.spreads.push(spread);

        // Bound the rolling window to `capacity`, matching the Cython
        // `deque(maxlen=capacity)`. Without this the buffer grows unbounded and
        // `fast_mean_iterated` errors (panicking on `unwrap`) once the length
        // exceeds `capacity`.
        if self.spreads.len() > self.capacity {
            self.spreads.remove(0);
        }

        // Recompute the average over the bounded window. The Cython reference uses an
        // incremental `fast_mean_iterated(..., drop_left=false)` update, but at capacity
        // that subtracts `values[length - 1]` (the spread just pushed) rather than the
        // evicted oldest value, so the average freezes for non-constant spreads.
        // Recomputing from the bounded window is O(capacity) and always correct.
        self.average = fast_mean(&self.spreads);
        Ok(())
    }

    fn reset(&mut self) {
        self.current = 0.0;
        self.average = 0.0;
        self.spreads.clear();
        self.initialized = false;
        self.has_inputs = false;
    }
}

impl SpreadAnalyzer {
    /// Creates a new [`SpreadAnalyzer`] instance.
    #[must_use]
    pub fn new(capacity: usize, instrument_id: InstrumentId) -> Self {
        Self {
            capacity,
            instrument_id,
            current: 0.0,
            average: 0.0,
            initialized: false,
            has_inputs: false,
            spreads: Vec::with_capacity(capacity),
        }
    }
}

fn fast_mean(values: &[f64]) -> f64 {
    if values.is_empty() {
        0.0
    } else {
        values.iter().sum::<f64>() / values.len() as f64
    }
}

#[cfg(test)]
mod tests {

    use rstest::rstest;

    use crate::{
        indicator::Indicator,
        ratio::spread_analyzer::SpreadAnalyzer,
        stubs::{spread_analyzer_10, *},
    };
    #[rstest]
    fn test_efficiency_ratio_initialized(spread_analyzer_10: SpreadAnalyzer) {
        let display_str = format!("{spread_analyzer_10}");
        assert_eq!(display_str, "SpreadAnalyzer(10,ETHUSDT-PERP.BINANCE)");
        assert_eq!(spread_analyzer_10.capacity, 10);
        assert!(!spread_analyzer_10.initialized);
    }

    #[rstest]
    fn test_with_correct_number_of_required_inputs(mut spread_analyzer_10: SpreadAnalyzer) {
        let bid_price: [&str; 10] = [
            "100.50", "100.45", "100.55", "100.60", "100.52", "100.48", "100.53", "100.57",
            "100.49", "100.51",
        ];

        let ask_price: [&str; 10] = [
            "100.55", "100.50", "100.60", "100.65", "100.57", "100.53", "100.58", "100.62",
            "100.54", "100.56",
        ];

        for i in 1..10 {
            spread_analyzer_10
                .handle_quote(&stub_quote(bid_price[i], ask_price[i]))
                .unwrap();
        }
        assert!(!spread_analyzer_10.initialized);
    }

    #[rstest]
    fn test_value_with_one_input(mut spread_analyzer_10: SpreadAnalyzer) {
        spread_analyzer_10
            .handle_quote(&stub_quote("100.50", "100.55"))
            .unwrap();
        assert_eq!(spread_analyzer_10.average, 0.049_999_999_999_997_16);
    }

    #[rstest]
    fn test_value_with_all_higher_inputs_returns_expected_value(
        mut spread_analyzer_10: SpreadAnalyzer,
    ) {
        let bid_price: [&str; 15] = [
            "100.50", "100.45", "100.55", "100.60", "100.52", "100.48", "100.53", "100.57",
            "100.49", "100.51", "100.54", "100.56", "100.58", "100.50", "100.52",
        ];

        let ask_price: [&str; 15] = [
            "100.55", "100.50", "100.60", "100.65", "100.57", "100.53", "100.58", "100.62",
            "100.54", "100.56", "100.59", "100.61", "100.63", "100.55", "100.57",
        ];

        for i in 0..10 {
            spread_analyzer_10
                .handle_quote(&stub_quote(bid_price[i], ask_price[i]))
                .unwrap();
        }

        assert_eq!(spread_analyzer_10.average, 0.050_000_000_000_001_42);
    }

    #[rstest]
    fn test_handles_more_inputs_than_capacity_without_panic(
        mut spread_analyzer_10: SpreadAnalyzer,
    ) {
        // Regression: feeding more than `capacity` quotes must not panic, and the
        // internal window must stay bounded to `capacity` (matching the Cython
        // `deque(maxlen=capacity)`). Previously the unbounded buffer caused
        // `fast_mean_iterated` to error and panic on the (capacity + 1)th quote.
        let bid_price: [&str; 15] = [
            "100.50", "100.45", "100.55", "100.60", "100.52", "100.48", "100.53", "100.57",
            "100.49", "100.51", "100.54", "100.56", "100.58", "100.50", "100.52",
        ];

        let ask_price: [&str; 15] = [
            "100.55", "100.50", "100.60", "100.65", "100.57", "100.53", "100.58", "100.62",
            "100.54", "100.56", "100.59", "100.61", "100.63", "100.55", "100.57",
        ];

        for i in 0..15 {
            spread_analyzer_10
                .handle_quote(&stub_quote(bid_price[i], ask_price[i]))
                .unwrap();
        }

        assert!(spread_analyzer_10.initialized());
        assert_eq!(spread_analyzer_10.spreads.len(), 10);
        assert!((spread_analyzer_10.average - 0.05).abs() < 1e-9);
    }

    #[rstest]
    fn test_average_tracks_varying_spreads_past_capacity(mut spread_analyzer_10: SpreadAnalyzer) {
        // Regression: with non-constant spreads past `capacity`, the average must keep
        // tracking the bounded window rather than freezing. Feeding 15 monotonically
        // increasing spreads (0.01..=0.15) leaves the window holding the last 10
        // (0.06..=0.15), whose mean is 0.105. The earlier incremental update froze the
        // average at 0.055 (the mean of the first full window 0.01..=0.10).
        let bid_price: [&str; 15] = ["100.00"; 15];
        let ask_price: [&str; 15] = [
            "100.01", "100.02", "100.03", "100.04", "100.05", "100.06", "100.07", "100.08",
            "100.09", "100.10", "100.11", "100.12", "100.13", "100.14", "100.15",
        ];

        for i in 0..15 {
            spread_analyzer_10
                .handle_quote(&stub_quote(bid_price[i], ask_price[i]))
                .unwrap();
        }

        assert_eq!(spread_analyzer_10.spreads.len(), 10);
        assert!((spread_analyzer_10.average - 0.105).abs() < 1e-9);
    }

    #[rstest]
    fn test_reset_successfully_returns_indicator_to_fresh_state(
        mut spread_analyzer_10: SpreadAnalyzer,
    ) {
        spread_analyzer_10
            .handle_quote(&stub_quote("100.50", "100.55"))
            .unwrap();
        spread_analyzer_10.reset();
        assert!(!spread_analyzer_10.initialized());
        assert_eq!(spread_analyzer_10.current, 0.0);
        assert_eq!(spread_analyzer_10.average, 0.0);
        assert!(!spread_analyzer_10.has_inputs);
        assert!(!spread_analyzer_10.initialized);
    }
}