Struct BetterVolume 

pub struct BetterVolume { /* private fields */ }

Better Volume — Barry Taylor’s (emini-watch) classification of each volume bar by its effort (volume) against its result (range) over a period-bar lookback.

range      = high − low
low volume : volume          is a new low  of the lookback   -> 1
climax     : volume · range  is a new high of the lookback   -> +3 up bar, −3 down bar
churn      : volume / range  is a new high of the lookback   -> 2
both       : climax and churn on the same bar                -> 4
otherwise                                                    -> 0

The rules are applied in that order and a later match overrides an earlier one, as in Taylor’s original. “New high / low” means strictly beyond every one of the previous period − 1 bars, so a run of identical bars stays neutral. A zero-range bar has no defined volume per range and never counts as churn.

Reading the codes (Volume Spread Analysis): a climax is the most effort meeting the widest result — often the start or end of a move; churn is heavy volume going nowhere — professional absorption near turning points; and a low-volume bar shows the absence of interest that marks pullbacks and tests.

Input = Candle, Output = f64 (one of 0, 1, 2, ±3, 4), warmup_period == period.

Example

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

let mut bv = BetterVolume::new(3).unwrap();
bv.update(Candle::new(100.0, 101.0, 99.0, 100.5, 1_000.0, 0).unwrap());
bv.update(Candle::new(100.5, 101.5, 99.5, 101.0, 1_000.0, 1).unwrap());
// A wide up bar with the most volume · range, but not the most volume per
// point of range: a climax up bar.
let out = bv.update(Candle::new(101.0, 105.0, 100.5, 104.5, 2_000.0, 2).unwrap());
assert_eq!(out, Some(3.0));

Implementations

impl BetterVolume

pub fn new(period: usize) -> Result<Self>

Construct a new Better Volume classifier with the given lookback period.

Errors

Returns Error::PeriodZero if period == 0.

pub const fn period(&self) -> usize

Configured lookback period.

pub const fn value(&self) -> Option<f64>

Current value if available.

Trait Implementations

impl Clone for BetterVolume

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 BetterVolume

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

Formats the value using the given formatter.

impl Indicator for BetterVolume

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.