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Indicator

indicators::indicator

Trait Indicator 

Source 
pub trait Indicator:
    Send
    + Sync
    + Debug {
    // Required methods
    fn name(&self) -> &'static str;
    fn required_len(&self) -> usize;
    fn required_columns(&self) -> &[&'static str];
    fn calculate(
        &self,
        candles: &[Candle],
    ) -> Result<IndicatorOutput, IndicatorError>;

    // Provided method
    fn check_len(&self, candles: &[Candle]) -> Result<(), IndicatorError> { ... }
}
Expand description

The core trait every indicator must implement.

Analogous to indicators/base.py :: class Indicator(ABC).

§Implementing an indicator

ⓘ
use crate::indicator::{Indicator, IndicatorOutput};
use crate::error::IndicatorError;
use crate::types::Candle;

pub struct Sma {
    pub period: usize,
    pub column: PriceColumn,
}

impl Indicator for Sma {
    fn name(&self) -> &str { "SMA" }

    fn required_len(&self) -> usize { self.period }

    fn required_columns(&self) -> &[&str] { &["close"] }

    fn calculate(&self, candles: &[Candle]) -> Result<IndicatorOutput, IndicatorError> {
    }
}

Required Methods§

Source

fn name(&self) -> &'static str

Short canonical name, e.g. "SMA", "RSI", "MACD".

Source

fn required_len(&self) -> usize

Minimum number of candles required before output is non-NaN. Mirrors Python’s implicit warm-up period used for validation.

Source

fn required_columns(&self) -> &[&'static str]

Which OHLCV fields this indicator reads.

Mirrors @classmethod required_columns() in Python. Valid values: "open", "high", "low", "close", "volume".

Source

fn calculate( &self, candles: &[Candle], ) -> Result<IndicatorOutput, IndicatorError>

Compute the indicator over a full candle slice (batch mode).

Mirrors def calculate(self, data: pd.DataFrame, price_column) -> pd.DataFrame.

  • Returns IndicatorOutput with one or more named columns.
  • Leading warm-up rows should be f64::NAN.
  • Returns Err(IndicatorError::InsufficientData) if candles.len() < required_len().

Provided Methods§

Source

fn check_len(&self, candles: &[Candle]) -> Result<(), IndicatorError>

Validate that enough data was supplied, returning a descriptive error if not.

Call this at the top of every calculate() implementation.

Implementors§