Struct FallingThreeMethods 

pub struct FallingThreeMethods { /* private fields */ }

Falling Three Methods — a 5-bar bearish continuation. A long black candle is followed by three small white bars that drift up but stay inside its range (a brief rest), then a second long black candle opens below the last rest bar’s close and closes below the first, resuming the decline (Nison; TA-Lib CDLRISEFALL3METHODS).

long body = |close − open| >= 0.5 * (high − low)
small body = |close − open| <= 0.5 * body1
bar1 black & long
bar2, bar3, bar4 small white bodies, each overlapping bar1's high/low range
                 (min(open, close) < high1 and max(open, close) > low1),
                 with rising closes (close3 > close2, close4 > close3)
bar5 black & long, opening below bar4's close (open5 < close4)
                 and closing below bar1's close (close5 < close1)

Output is −1.0 when the pattern completes and 0.0 otherwise. Falling Three Methods is a single-direction (bearish-only) continuation, so it never emits +1.0. The first four bars always return 0.0 because the five-bar window is not yet filled. Body thresholds follow the geometric house style rather than TA-Lib’s rolling averages. Pattern-shape check only — no trend filter is applied; combine with a trend indicator for actionable signals.

Signed ±1 encoding

This detector emits the uniform candlestick sign convention shared across the pattern family — −1.0 bearish, 0.0 no pattern — so it drops straight into a machine-learning feature matrix as a single dimension.

Example

use wickra_core::{Candle, FallingThreeMethods, Indicator};

let mut indicator = FallingThreeMethods::new();
indicator.update(Candle::new(15.0, 15.1, 9.9, 10.0, 1.0, 0).unwrap());
indicator.update(Candle::new(11.0, 12.1, 10.9, 12.0, 1.0, 1).unwrap());
indicator.update(Candle::new(11.5, 12.6, 11.4, 12.5, 1.0, 2).unwrap());
indicator.update(Candle::new(12.0, 13.1, 11.9, 13.0, 1.0, 3).unwrap());
let out = indicator
    .update(Candle::new(12.5, 12.6, 8.9, 9.0, 1.0, 4).unwrap());
assert_eq!(out, Some(-1.0));

Implementations

impl FallingThreeMethods

pub const fn new() -> Self

Construct a new Falling Three Methods detector.

Trait Implementations

impl Clone for FallingThreeMethods

fn clone(&self) -> Self

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for FallingThreeMethods

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for FallingThreeMethods

fn default() -> Self

Returns the “default value” for a type.

impl Indicator for FallingThreeMethods

type Input = Candle

Type of one input data point (typically f64 for a price, or Candle / Tick).

type Output = f64

Type of one output value.

fn update(&mut self, candle: Candle) -> Option<f64>

Feed one new data point into the indicator and return the freshly computed output, or None if there is no value for this input.

fn reset(&mut self)

Reset all internal state, leaving the indicator equivalent to a freshly constructed instance with the same parameters.

fn warmup_period(&self) -> usize

Number of inputs required before the first non-None output can be produced.

fn is_ready(&self) -> bool

Whether the indicator has emitted at least one value since the last reset.

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

Stable, human-readable indicator name. Used by chaining and diagnostics.

fn batch_nan_into(&mut self, inputs: &[Self::Input], out: &mut [f64])

where Self::Input: Copy, Self::Output: Into<f64>,

Run the indicator over inputs, writing one output per input into the caller-owned out buffer (NaN where update returns None). It exists for every indicator whose output converts to an f64; the batch pipelines use it for the scalar f64 -> f64 ones.

fn batch_fast_into(&mut self, inputs: &[Self::Input], out: &mut [f64])

where Self::Input: Copy, Self::Output: Into<f64>,

Opt-in fast batch: like batch_nan_into, but an indicator with a vectorised kernel may reassociate its arithmetic to run it in SIMD lanes. Each value then agrees with the exact batch to within the tolerance the indicator documents (a few units in the last place), not bit for bit; warmup positions, NaN placement and the output length are identical. The kernels are deterministic: the same input produces the same bits on every platform, with or without SIMD hardware.