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kingchenc fc6f619550 release: bump 0.7.1 -> 0.7.2 (#217)
Version bump 0.7.1 -> 0.7.2 for the B17 Market Profile batch (498 indicators).
2026-06-08 04:18:34 +02:00
kingchenc 91aa6fffbf feat(market-profile): naked POC, single prints, profile shape, HVN/LVN, composite profile (B17) (#216)
## B17 Market Profile — five new indicators (493 → 498)

| Indicator | Output | Notes |
|-----------|--------|-------|
| `NakedPoc` | `f64` | most recent untouched point-of-control level |
| `SinglePrints` | `f64` | count of single-print price levels |
| `ProfileShape` | `f64` | b/P/D shape classification as a numeric code |
| `HighLowVolumeNodes` | struct `{hvn, lvn}` | highest/lowest volume nodes |
| `CompositeProfile` | struct `{poc, vah, val}` | multi-session composite volume profile |

### Wiring
- Core structs + full unit tests; all join the existing **Market Profile** family.
- Hand-written Python/Node/WASM bindings (f64 via candle helpers; struct via PyArray2 / `#[napi(object)]` / `Object`+`Reflect::set`).
- Fuzz drives in `indicator_update_candle.rs`; CANDLE_SCALAR + MULTI registry tests + reference tests.
- README counter + `docs/README.md` + `FAMILIES` assert bumped to 498.

### Verify (local, all green)
- `cargo test -p wickra-core --lib`: 4066 · `--doc`: 448
- clippy workspace: clean
- node: 568 · pytest: 938
2026-06-08 04:17:06 +02:00
kingchenc 5862401958 release: bump 0.7.0 -> 0.7.1 (#215)
Version bump 0.7.0 -> 0.7.1 for the B16 Derivatives batch (493 indicators).
2026-06-08 03:35:31 +02:00
kingchenc ff5a047078 feat(derivatives): leverage, OI/volume, perpetual premium, funding APR, OI momentum (B16) (#214)
## B16 Derivatives — five new indicators (488 → 493)

All consume a `DerivativesTick` and emit `f64`:

| Indicator | Reads | Formula |
|-----------|-------|---------|
| `EstimatedLeverageRatio` | open_interest, long_size, short_size | `OI / (long + short)` |
| `OiToVolumeRatio` | open_interest, taker_buy_volume, taker_sell_volume | `OI / (buy + sell)` |
| `PerpetualPremiumIndex` | mark_price, index_price | `(mark − index) / index` |
| `FundingImpliedApr` | funding_rate | `rate × intervals_per_year` |
| `OpenInterestMomentum` | open_interest | `100 · (OI_t − OI_{t−period}) / OI_{t−period}` |

### Wiring
- Core structs + full unit tests (incl. zero-denominator branches).
- Hand-written Python/Node/WASM tick bindings; two new tick helpers (`deriv_oi_long_short`, `deriv_oi_taker`).
- Fuzz drives in `indicator_update_derivatives.rs`; dedicated reference + streaming-vs-batch tests (Python + Node).
- README counter + `docs/README.md` + `FAMILIES` assert bumped to 493.

### Verify (local, all green)
- `cargo test -p wickra-core --lib`: 4028 · `--doc`: 443
- clippy workspace: clean
- node: 563 · pytest: 928
2026-06-08 03:33:59 +02:00
37 changed files with 4699 additions and 140 deletions
+17 -1
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@@ -7,6 +7,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
## [Unreleased]
## [0.7.2] - 2026-06-08
- **Composite Profile** — multi-session composite volume profile exposing POC, VAH and VAL (`CompositeProfile`).
- **High/Low Volume Nodes** — highest- and lowest-volume price nodes in the profile (`HighLowVolumeNodes`).
- **Profile Shape** — profile shape classification (b/P/D normal) as a numeric code (`ProfileShape`).
- **Single Prints** — count of single-print (low-activity) price levels in the profile (`SinglePrints`).
- **Naked POC** — most recent untouched (naked) point of control level (`NakedPoc`).
## [0.7.1] - 2026-06-08
- **Open-Interest Momentum** — rate-of-change of open interest over a rolling window (`OpenInterestMomentum`).
- **Funding-Implied APR** — annualised funding rate (per-interval funding times intervals per year) (`FundingImpliedApr`).
- **Perpetual Premium Index** — relative premium of the mark price over the index price (`PerpetualPremiumIndex`).
- **OI-to-Volume Ratio** — open interest divided by taker volume (position turnover proxy) (`OiToVolumeRatio`).
- **Estimated Leverage Ratio** — open interest divided by aggregate long+short position size (leverage proxy) (`EstimatedLeverageRatio`).
## [0.7.0] - 2026-06-08
- **Hasbrouck Information Share** — variance-ratio proxy for each venue's share of price discovery (Hasbrouck information share) (`HasbrouckInformationShare`).
- **PIN** — probability of informed trading from rolling buy/sell imbalance (EKOP single-window estimator) (`Pin`).
@@ -1382,7 +1396,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
optional Binance live feed.
- Bindings for Python, Node.js, and WebAssembly.
[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.7.0...HEAD
[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.7.2...HEAD
[0.7.2]: https://github.com/wickra-lib/wickra/compare/v0.7.1...v0.7.2
[0.7.1]: https://github.com/wickra-lib/wickra/compare/v0.7.0...v0.7.1
[0.7.0]: https://github.com/wickra-lib/wickra/compare/v0.6.9...v0.7.0
[0.6.9]: https://github.com/wickra-lib/wickra/compare/v0.6.8...v0.6.9
[0.6.8]: https://github.com/wickra-lib/wickra/compare/v0.6.7...v0.6.8
Generated
+8 -8
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@@ -1944,7 +1944,7 @@ dependencies = [
[[package]]
name = "wickra"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"approx",
"criterion",
@@ -1955,7 +1955,7 @@ dependencies = [
[[package]]
name = "wickra-bench"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"criterion",
"kand",
@@ -1967,7 +1967,7 @@ dependencies = [
[[package]]
name = "wickra-core"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"approx",
"proptest",
@@ -1977,7 +1977,7 @@ dependencies = [
[[package]]
name = "wickra-data"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"approx",
"csv",
@@ -1994,7 +1994,7 @@ dependencies = [
[[package]]
name = "wickra-examples"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"serde_json",
"tokio",
@@ -2004,7 +2004,7 @@ dependencies = [
[[package]]
name = "wickra-node"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"napi",
"napi-build",
@@ -2014,7 +2014,7 @@ dependencies = [
[[package]]
name = "wickra-python"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"numpy",
"pyo3",
@@ -2023,7 +2023,7 @@ dependencies = [
[[package]]
name = "wickra-wasm"
version = "0.7.0"
version = "0.7.2"
dependencies = [
"console_error_panic_hook",
"js-sys",
+2 -2
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@@ -13,7 +13,7 @@ members = [
exclude = ["fuzz"]
[workspace.package]
version = "0.7.0"
version = "0.7.2"
authors = ["kingchenc <support@wickra.org>"]
edition = "2021"
rust-version = "1.86"
@@ -25,7 +25,7 @@ keywords = ["finance", "trading", "indicators", "technical-analysis", "ta"]
categories = ["finance", "mathematics", "science"]
[workspace.dependencies]
wickra-core = { path = "crates/wickra-core", version = "0.7.0" }
wickra-core = { path = "crates/wickra-core", version = "0.7.2" }
thiserror = "2"
rayon = "1.10"
+9 -9
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@@ -1,5 +1,5 @@
<p align="center">
<a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=488" alt="Wickra — streaming-first technical indicators" width="100%"></a>
<a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=498" alt="Wickra — streaming-first technical indicators" width="100%"></a>
</p>
[![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
@@ -48,7 +48,7 @@ Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:
[Node](https://docs.wickra.org/Quickstart-Node),
[WASM](https://docs.wickra.org/Quickstart-WASM).
- **Indicators** — a per-indicator deep dive (formula, parameters, warmup) for
every one of the 488 indicators; start at the
every one of the 498 indicators; start at the
[indicators overview](https://docs.wickra.org/Indicators-Overview).
- **Reference** — [warmup periods](https://docs.wickra.org/Warmup-Periods),
[streaming vs batch](https://docs.wickra.org/Streaming-vs-Batch),
@@ -66,7 +66,7 @@ an afterthought — **live, tick-by-tick data** — without giving up the breadt
a full batch library, and without making you reimplement your indicators four
times to get there.
- **The biggest streaming-native catalogue, period.** 488 indicators across 24
- **The biggest streaming-native catalogue, period.** 498 indicators across 24
families — candlesticks, harmonic & chart patterns, market profile, market
breadth, Renko/Kagi/Point&Figure bars, Ehlers DSP cycles, risk/performance
metrics — every single one updating in **O(1) per tick**. TA-Lib ships ~150 and
@@ -77,7 +77,7 @@ times to get there.
- **Correct by construction, not by hope.** Every `update` validates its input,
runs a real warmup, and returns an `Option` so a single bad tick can't silently
poison state. `batch == streaming` is **bit-exact, fuzzed and 100 %-line-covered
for all 488 indicators**.
for all 498 indicators**.
- **Orders of magnitude faster where it counts.** In streaming Wickra is **1156×**
faster than the only other incremental peer and **thousands of times** faster
than recompute-on-every-tick libraries. On batch it wins several rows outright
@@ -95,7 +95,7 @@ Every other library forces one of those compromises. Wickra doesn't:
| Library | Install | Streaming | Languages | Indicators | Active |
|------------------|-------------|-------------|-----------------------------|-----------:|--------|
| **★&nbsp;Wickra**| **clean** | **yes, O(1)** | **Python · Node · WASM · Rust** | **488** | **yes** |
| **★&nbsp;Wickra**| **clean** | **yes, O(1)** | **Python · Node · WASM · Rust** | **498** | **yes** |
| kand | clean | yes | Python · WASM · Rust | ~60 | yes |
| ta-rs | clean | yes | Rust only | ~30 | stale |
| yata | clean | partial | Rust only | ~35 | yes |
@@ -128,7 +128,7 @@ Full tables (Rust + Python, streaming + batch) and how to reproduce them live in
## Indicators
488 streaming-first indicators across twenty-four families. Every one passes the
498 streaming-first indicators across twenty-four families. Every one passes the
`batch == streaming` equivalence test, reference-value tests, and reset
semantics tests. Each has a per-indicator deep dive (formula, parameters,
warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
@@ -154,8 +154,8 @@ warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
| Harmonic Patterns | AB=CD, Gartley, Butterfly, Bat, Crab, Shark, Cypher, Three Drives |
| Fibonacci | Fibonacci Retracement, Fibonacci Extension, Fibonacci Projection, Auto-Fibonacci, Golden Pocket, Fibonacci Confluence, Fibonacci Fan, Fibonacci Arcs, Fibonacci Channel, Fibonacci Time Zones |
| Microstructure | Order-Book Imbalance (Top-1 / Top-N / Full), Microprice, Quoted Spread, Depth Slope, Signed Volume, Cumulative Volume Delta, Trade Imbalance, Effective Spread, Realized Spread, Kyle's Lambda, Footprint, Order Flow Imbalance, VPIN, Amihud Illiquidity, Roll Measure, Trade-Sign Autocorrelation, Hasbrouck Information Share |
| Derivatives | Funding Rate, Funding Rate Mean, Funding Rate Z-Score, Funding Basis, Open-Interest Delta, OI / Price Divergence, OI-Weighted Price, Long/Short Ratio, Taker Buy/Sell Ratio, Liquidation Features, Term-Structure Basis, Calendar Spread |
| Market Profile | Value Area (POC / VAH / VAL), Volume Profile (histogram), TPO Profile, Initial Balance, Opening Range |
| Derivatives | Funding Rate, Funding Rate Mean, Funding Rate Z-Score, Funding Basis, Open-Interest Delta, OI / Price Divergence, OI-Weighted Price, Long/Short Ratio, Taker Buy/Sell Ratio, Liquidation Features, Term-Structure Basis, Calendar Spread, Estimated Leverage Ratio, OI-to-Volume Ratio, Perpetual Premium Index, Funding-Implied APR, Open-Interest Momentum |
| Market Profile | Value Area (POC / VAH / VAL), Volume Profile (histogram), TPO Profile, Initial Balance, Opening Range, Naked POC, Single Prints, Profile Shape, High/Low Volume Nodes, Composite Profile |
| Market Breadth | Advance/Decline Line, Advance/Decline Ratio, Advance/Decline Volume Line, McClellan Oscillator, McClellan Summation Index, TRIN / Arms Index, Breadth Thrust, New Highs - New Lows, High-Low Index, Percent Above Moving Average, Up/Down Volume Ratio, Bullish Percent Index, Cumulative Volume Index, Absolute Breadth Index, TICK Index |
| Risk / Performance | Sharpe Ratio, Sortino Ratio, Calmar Ratio, Omega Ratio, Max Drawdown, Average Drawdown, Drawdown Duration, Pain Index, Value at Risk, Conditional Value at Risk (CVaR), Profit Factor, Gain/Loss Ratio, Recovery Factor, Kelly Criterion, Treynor Ratio, Information Ratio, Alpha (Jensen) |
| Seasonality & Session | Session VWAP, Session High/Low, Session Range, Average Daily Range, Overnight Gap, Overnight/Intraday Return, Turn-of-Month, Seasonal Z-Score, Time-of-Day Return Profile, Day-of-Week Profile, Intraday Volatility Profile, Volume-by-Time Profile |
@@ -237,7 +237,7 @@ A Python live-trading example using the public `websockets` package lives at
```
wickra/
├── crates/
│ ├── wickra-core/ core engine + all 488 indicators
│ ├── wickra-core/ core engine + all 498 indicators
│ ├── wickra/ top-level facade crate (publishes on crates.io) + benches/
│ ├── wickra-data/ CSV reader, tick aggregator, live exchange feeds
│ └── wickra-bench/ internal cross-library benchmark harness (not published)
@@ -392,6 +392,9 @@ const candleScalar = {
DumplingTop: { make: () => new wickra.DumplingTop(9), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
NewPriceLines: { make: () => new wickra.NewPriceLines(5), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
FryPanBottom: { make: () => new wickra.FryPanBottom(9), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
NakedPoc: { make: () => new wickra.NakedPoc(20, 24), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
SinglePrints: { make: () => new wickra.SinglePrints(20, 24), step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
ProfileShape: { make: () => new wickra.ProfileShape(20, 24), step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
};
for (const [name, d] of Object.entries(candleScalar)) {
@@ -497,6 +500,8 @@ const multi = {
SmoothedHeikinAshi: { make: () => new wickra.SmoothedHeikinAshi(5), fields: ['open', 'high', 'low', 'close'], step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
Equivolume: { make: () => new wickra.Equivolume(20), fields: ['height', 'width'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
CandleVolume: { make: () => new wickra.CandleVolume(20), fields: ['body', 'width'], step: (ind, i) => ind.update(open[i], close[i], volume[i]), batch: (ind) => ind.batch(open, close, volume) },
HighLowVolumeNodes: { make: () => new wickra.HighLowVolumeNodes(20, 24), fields: ['hvn', 'lvn'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
CompositeProfile: { make: () => new wickra.CompositeProfile(20, 24, 0.7), fields: ['poc', 'vah', 'val'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
};
for (const [name, d] of Object.entries(multi)) {
@@ -1443,6 +1448,56 @@ test('derivatives reject bad input', () => {
assert.throws(() => new wickra.FundingBasis().update(100, 0));
});
test('B16 derivatives reference values', () => {
// Estimated leverage: oi / (long + short) = 200 / 100 = 2.
assert.ok(Math.abs(new wickra.EstimatedLeverageRatio().update(200, 60, 40) - 2.0) < 1e-12);
// OI-to-volume: oi / (buy + sell) = 100 / 50 = 2.
assert.ok(Math.abs(new wickra.OiToVolumeRatio().update(100, 30, 20) - 2.0) < 1e-12);
// Perpetual premium: (mark - index) / index = 0.5 / 100 = 0.005.
assert.ok(Math.abs(new wickra.PerpetualPremiumIndex().update(100.5, 100.0) - 0.005) < 1e-12);
// Funding-implied APR: rate * intervals = 0.0001 * 1095 = 0.1095.
assert.ok(Math.abs(new wickra.FundingImpliedApr(1095).update(0.0001) - 0.1095) < 1e-12);
// Open-interest momentum (period 2): warmup then ROC% = 100*(120 - 100)/100 = 20.
const oim = new wickra.OpenInterestMomentum(2);
assert.equal(oim.update(100), null);
assert.equal(oim.update(110), null);
assert.ok(Math.abs(oim.update(120) - 20.0) < 1e-12);
});
test('B16 derivatives streaming matches batch', () => {
const n = 30;
const oi = Array.from({ length: n }, (_, i) => 1000 + 50 * Math.sin(i * 0.3));
const longSz = Array.from({ length: n }, (_, i) => 600 + 20 * Math.cos(i * 0.2));
const shortSz = Array.from({ length: n }, (_, i) => 400 + 15 * Math.sin(i * 0.4));
const buy = Array.from({ length: n }, (_, i) => 300 + 10 * Math.sin(i * 0.5));
const sell = Array.from({ length: n }, (_, i) => 250 + 12 * Math.cos(i * 0.35));
const index = Array.from({ length: n }, (_, i) => 100 + Math.sin(i * 0.2));
const mark = Array.from({ length: n }, (_, i) => index[i] + 0.05 * Math.cos(i * 0.3));
const rate = Array.from({ length: n }, (_, i) => 0.0001 * Math.sin(i * 0.3));
const cmp = (batch, s, i) =>
assert.ok((s === null && Number.isNaN(batch[i])) || Math.abs(s - batch[i]) < 1e-12, `mismatch at ${i}`);
let b = new wickra.EstimatedLeverageRatio().batch(oi, longSz, shortSz);
let st = new wickra.EstimatedLeverageRatio();
for (let i = 0; i < n; i++) cmp(b, st.update(oi[i], longSz[i], shortSz[i]), i);
b = new wickra.OiToVolumeRatio().batch(oi, buy, sell);
st = new wickra.OiToVolumeRatio();
for (let i = 0; i < n; i++) cmp(b, st.update(oi[i], buy[i], sell[i]), i);
b = new wickra.PerpetualPremiumIndex().batch(mark, index);
st = new wickra.PerpetualPremiumIndex();
for (let i = 0; i < n; i++) cmp(b, st.update(mark[i], index[i]), i);
b = new wickra.FundingImpliedApr(1095).batch(rate);
st = new wickra.FundingImpliedApr(1095);
for (let i = 0; i < n; i++) cmp(b, st.update(rate[i]), i);
b = new wickra.OpenInterestMomentum(10).batch(oi);
st = new wickra.OpenInterestMomentum(10);
for (let i = 0; i < n; i++) cmp(b, st.update(oi[i]), i);
});
test('market breadth: AdvanceDecline reference values', () => {
// A breadth tick is the universe as parallel arrays; the sign of `change`
// classifies each symbol as advancing / declining / unchanged.
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@@ -409,6 +409,15 @@ export interface VolumeProfileValue {
priceHigh: number
bins: Array<number>
}
export interface HighLowVolumeNodesValue {
hvn: number
lvn: number
}
export interface CompositeProfileValue {
poc: number
vah: number
val: number
}
export interface TpoProfileValue {
priceLow: number
priceHigh: number
@@ -3470,6 +3479,51 @@ export declare class ValueArea {
update(high: number, low: number, volume: number): ValueAreaValue | null
batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
}
export type NakedPocNode = NakedPoc
export declare class NakedPoc {
constructor(sessionLen: number, binCount: number)
update(high: number, low: number, close: number, volume: number): number | null
batch(high: Array<number>, low: Array<number>, close: Array<number>, volume: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type SinglePrintsNode = SinglePrints
export declare class SinglePrints {
constructor(period: number, binCount: number)
update(high: number, low: number): number | null
batch(high: Array<number>, low: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type ProfileShapeNode = ProfileShape
export declare class ProfileShape {
constructor(period: number, binCount: number)
update(high: number, low: number, volume: number): number | null
batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type HighLowVolumeNodesNode = HighLowVolumeNodes
export declare class HighLowVolumeNodes {
constructor(period: number, binCount: number)
update(high: number, low: number, volume: number): HighLowVolumeNodesValue | null
batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type CompositeProfileNode = CompositeProfile
export declare class CompositeProfile {
constructor(period: number, binCount: number, valueAreaPct: number)
update(high: number, low: number, volume: number): CompositeProfileValue | null
batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type VolumeProfileNode = VolumeProfile
export declare class VolumeProfile {
constructor(period: number, binCount: number)
@@ -4544,6 +4598,51 @@ export declare class CalendarSpread {
isReady(): boolean
warmupPeriod(): number
}
export type EstimatedLeverageRatioNode = EstimatedLeverageRatio
export declare class EstimatedLeverageRatio {
constructor()
update(openInterest: number, longSize: number, shortSize: number): number | null
batch(openInterest: Array<number>, longSize: Array<number>, shortSize: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type OiToVolumeRatioNode = OiToVolumeRatio
export declare class OiToVolumeRatio {
constructor()
update(openInterest: number, takerBuyVolume: number, takerSellVolume: number): number | null
batch(openInterest: Array<number>, takerBuyVolume: Array<number>, takerSellVolume: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type PerpetualPremiumIndexNode = PerpetualPremiumIndex
export declare class PerpetualPremiumIndex {
constructor()
update(markPrice: number, indexPrice: number): number | null
batch(markPrice: Array<number>, indexPrice: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type FundingImpliedAprNode = FundingImpliedApr
export declare class FundingImpliedApr {
constructor(intervalsPerYear: number)
update(fundingRate: number): number | null
batch(fundingRate: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type OpenInterestMomentumNode = OpenInterestMomentum
export declare class OpenInterestMomentum {
constructor(period: number)
update(openInterest: number): number | null
batch(openInterest: Array<number>): Array<number>
reset(): void
isReady(): boolean
warmupPeriod(): number
}
export type AdvanceDeclineNode = AdvanceDecline
export declare class AdvanceDecline {
constructor()
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@@ -1,6 +1,6 @@
{
"name": "wickra-darwin-arm64",
"version": "0.7.0",
"version": "0.7.2",
"description": "Native binding for wickra (macOS Apple Silicon). Installed automatically as an optional dependency of wickra on matching platforms.",
"main": "wickra.darwin-arm64.node",
"files": [
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View File
@@ -1,6 +1,6 @@
{
"name": "wickra-darwin-x64",
"version": "0.7.0",
"version": "0.7.2",
"description": "Native binding for wickra (macOS Intel). Installed automatically as an optional dependency of wickra on matching platforms.",
"main": "wickra.darwin-x64.node",
"files": [
@@ -1,6 +1,6 @@
{
"name": "wickra-linux-arm64-gnu",
"version": "0.7.0",
"version": "0.7.2",
"description": "Native binding for wickra (linux arm64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
"main": "wickra.linux-arm64-gnu.node",
"files": [
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "wickra-linux-x64-gnu",
"version": "0.7.0",
"version": "0.7.2",
"description": "Native binding for wickra (linux x64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
"main": "wickra.linux-x64-gnu.node",
"files": [
@@ -1,6 +1,6 @@
{
"name": "wickra-win32-arm64-msvc",
"version": "0.7.0",
"version": "0.7.2",
"description": "Native binding for wickra (Windows arm64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
"main": "wickra.win32-arm64-msvc.node",
"files": [
@@ -1,6 +1,6 @@
{
"name": "wickra-win32-x64-msvc",
"version": "0.7.0",
"version": "0.7.2",
"description": "Native binding for wickra (Windows x64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
"main": "wickra.win32-x64-msvc.node",
"files": [
+20 -20
View File
@@ -1,12 +1,12 @@
{
"name": "wickra",
"version": "0.7.0",
"version": "0.7.2",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "wickra",
"version": "0.7.0",
"version": "0.7.2",
"license": "MIT OR Apache-2.0",
"devDependencies": {
"@napi-rs/cli": "^2.18.0"
@@ -15,12 +15,12 @@
"node": ">= 18"
},
"optionalDependencies": {
"wickra-darwin-arm64": "0.7.0",
"wickra-darwin-x64": "0.7.0",
"wickra-linux-arm64-gnu": "0.7.0",
"wickra-linux-x64-gnu": "0.7.0",
"wickra-win32-arm64-msvc": "0.7.0",
"wickra-win32-x64-msvc": "0.7.0"
"wickra-darwin-arm64": "0.7.2",
"wickra-darwin-x64": "0.7.2",
"wickra-linux-arm64-gnu": "0.7.2",
"wickra-linux-x64-gnu": "0.7.2",
"wickra-win32-arm64-msvc": "0.7.2",
"wickra-win32-x64-msvc": "0.7.2"
}
},
"node_modules/@napi-rs/cli": {
@@ -41,8 +41,8 @@
}
},
"node_modules/wickra-darwin-arm64": {
"version": "0.7.0",
"resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.7.0.tgz",
"version": "0.7.2",
"resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.7.2.tgz",
"integrity": "sha512-4eZiBR/yGUdr4nzhEUFy2i69XgNx64iI2ax/LPamsThgylC0KpHOZKK19QzJ2d9KbK4C8nMjME5FLuR+4GNEwQ==",
"cpu": [
"arm64"
@@ -57,8 +57,8 @@
}
},
"node_modules/wickra-darwin-x64": {
"version": "0.7.0",
"resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.7.0.tgz",
"version": "0.7.2",
"resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.7.2.tgz",
"integrity": "sha512-6hf8zI3QPjTFp4zCpmgUwDvNtu6jHqNUHKD5e55POo0CgA52HkpyxSPtVm8TGTIZDI7kPjlbOdBM8CJ76mmXwA==",
"cpu": [
"x64"
@@ -73,8 +73,8 @@
}
},
"node_modules/wickra-linux-arm64-gnu": {
"version": "0.7.0",
"resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.7.0.tgz",
"version": "0.7.2",
"resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.7.2.tgz",
"integrity": "sha512-kSe6y0xBMSiqdPLXNjwop5WZdHtvdBNKSEBCwZ4hFq33p4apW25/wrlzv9/oDuyD4kuPabJEhCCnFOplh58CUg==",
"cpu": [
"arm64"
@@ -89,8 +89,8 @@
}
},
"node_modules/wickra-linux-x64-gnu": {
"version": "0.7.0",
"resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.7.0.tgz",
"version": "0.7.2",
"resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.7.2.tgz",
"integrity": "sha512-tWBWS4qz7hxM4xnpFb59bhf6TaLwXq0Z3jEa/2l7r8PiHA94g8r8S53NRMiT+4yiL5hSWe/nUiC/YXdRrhEZ4g==",
"cpu": [
"x64"
@@ -105,8 +105,8 @@
}
},
"node_modules/wickra-win32-arm64-msvc": {
"version": "0.7.0",
"resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.7.0.tgz",
"version": "0.7.2",
"resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.7.2.tgz",
"integrity": "sha512-EXIckHxAtF75PUGDKRzXyqMe9ldP0JjSdu68WFN6iJfp+McYrGu6h40TEJlQ/oUEIoPqiZB/xhVyo/el5Lg7zw==",
"cpu": [
"arm64"
@@ -121,8 +121,8 @@
}
},
"node_modules/wickra-win32-x64-msvc": {
"version": "0.7.0",
"resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.7.0.tgz",
"version": "0.7.2",
"resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.7.2.tgz",
"integrity": "sha512-Yfsqq1Xwp6hdxMyLze411vNdo7BDwI6+lPSe7A9XdqyPecNDbtKwYLpsal2r8EHbNzqM+R8XnuRtUaEQS5VlUQ==",
"cpu": [
"x64"
+7 -7
View File
@@ -1,6 +1,6 @@
{
"name": "wickra",
"version": "0.7.0",
"version": "0.7.2",
"description": "Streaming-first technical indicators: incremental, fast, install-free. Node bindings powered by Rust.",
"author": "kingchenc <support@wickra.org>",
"main": "index.js",
@@ -47,12 +47,12 @@
"node": ">= 18"
},
"optionalDependencies": {
"wickra-linux-x64-gnu": "0.7.0",
"wickra-linux-arm64-gnu": "0.7.0",
"wickra-darwin-x64": "0.7.0",
"wickra-darwin-arm64": "0.7.0",
"wickra-win32-x64-msvc": "0.7.0",
"wickra-win32-arm64-msvc": "0.7.0"
"wickra-linux-x64-gnu": "0.7.2",
"wickra-linux-arm64-gnu": "0.7.2",
"wickra-darwin-x64": "0.7.2",
"wickra-darwin-arm64": "0.7.2",
"wickra-win32-x64-msvc": "0.7.2",
"wickra-win32-arm64-msvc": "0.7.2"
},
"scripts": {
"build": "napi build --platform --release",
+652
View File
@@ -12874,6 +12874,332 @@ pub struct VolumeProfileValue {
pub bins: Vec<f64>,
}
// Naked POC: most recent untouched point-of-control level (Candle -> f64).
#[napi(js_name = "NakedPoc")]
pub struct NakedPocNode {
inner: wc::NakedPoc,
}
#[napi]
impl NakedPocNode {
#[napi(constructor)]
pub fn new(session_len: u32, bin_count: u32) -> napi::Result<Self> {
Ok(Self {
inner: wc::NakedPoc::new(session_len as usize, bin_count as usize).map_err(map_err)?,
})
}
#[napi]
pub fn update(
&mut self,
high: f64,
low: f64,
close: f64,
volume: f64,
) -> napi::Result<Option<f64>> {
Ok(self.inner.update(cnd(high, low, close, volume)?))
}
#[napi]
pub fn batch(
&mut self,
high: Vec<f64>,
low: Vec<f64>,
close: Vec<f64>,
volume: Vec<f64>,
) -> napi::Result<Vec<f64>> {
if high.len() != low.len() || low.len() != close.len() || close.len() != volume.len() {
return Err(NapiError::from_reason(
"high, low, close, volume must be equal length".to_string(),
));
}
let mut out = Vec::with_capacity(close.len());
for i in 0..close.len() {
out.push(
self.inner
.update(cnd(high[i], low[i], close[i], volume[i])?)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// Single Prints: count of single-print price levels (Candle -> f64).
#[napi(js_name = "SinglePrints")]
pub struct SinglePrintsNode {
inner: wc::SinglePrints,
}
#[napi]
impl SinglePrintsNode {
#[napi(constructor)]
pub fn new(period: u32, bin_count: u32) -> napi::Result<Self> {
Ok(Self {
inner: wc::SinglePrints::new(period as usize, bin_count as usize).map_err(map_err)?,
})
}
#[napi]
pub fn update(&mut self, high: f64, low: f64) -> napi::Result<Option<f64>> {
let mid = f64::midpoint(high, low);
Ok(self
.inner
.update(wc::Candle::new(mid, high, low, mid, 0.0, 0).map_err(map_err)?))
}
#[napi]
pub fn batch(&mut self, high: Vec<f64>, low: Vec<f64>) -> napi::Result<Vec<f64>> {
if high.len() != low.len() {
return Err(NapiError::from_reason(
"high and low must be equal length".to_string(),
));
}
let mut out = Vec::with_capacity(high.len());
for i in 0..high.len() {
let mid = f64::midpoint(high[i], low[i]);
out.push(
self.inner
.update(wc::Candle::new(mid, high[i], low[i], mid, 0.0, 0).map_err(map_err)?)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// Profile Shape: b/P/D classification as a numeric code (Candle -> f64).
#[napi(js_name = "ProfileShape")]
pub struct ProfileShapeNode {
inner: wc::ProfileShape,
}
#[napi]
impl ProfileShapeNode {
#[napi(constructor)]
pub fn new(period: u32, bin_count: u32) -> napi::Result<Self> {
Ok(Self {
inner: wc::ProfileShape::new(period as usize, bin_count as usize).map_err(map_err)?,
})
}
#[napi]
pub fn update(&mut self, high: f64, low: f64, volume: f64) -> napi::Result<Option<f64>> {
let mid = f64::midpoint(high, low);
Ok(self
.inner
.update(wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?))
}
#[napi]
pub fn batch(
&mut self,
high: Vec<f64>,
low: Vec<f64>,
volume: Vec<f64>,
) -> napi::Result<Vec<f64>> {
if high.len() != low.len() || low.len() != volume.len() {
return Err(NapiError::from_reason(
"high, low, volume must be equal length".to_string(),
));
}
let mut out = Vec::with_capacity(high.len());
for i in 0..high.len() {
let mid = f64::midpoint(high[i], low[i]);
out.push(
self.inner
.update(
wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0)
.map_err(map_err)?,
)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
#[napi(object)]
pub struct HighLowVolumeNodesValue {
pub hvn: f64,
pub lvn: f64,
}
// High/Low Volume Nodes: highest- and lowest-volume price nodes (Candle -> struct).
#[napi(js_name = "HighLowVolumeNodes")]
pub struct HighLowVolumeNodesNode {
inner: wc::HighLowVolumeNodes,
}
#[napi]
impl HighLowVolumeNodesNode {
#[napi(constructor)]
pub fn new(period: u32, bin_count: u32) -> napi::Result<Self> {
Ok(Self {
inner: wc::HighLowVolumeNodes::new(period as usize, bin_count as usize)
.map_err(map_err)?,
})
}
#[napi]
pub fn update(
&mut self,
high: f64,
low: f64,
volume: f64,
) -> napi::Result<Option<HighLowVolumeNodesValue>> {
let mid = f64::midpoint(high, low);
let candle = wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?;
Ok(self.inner.update(candle).map(|o| HighLowVolumeNodesValue {
hvn: o.hvn,
lvn: o.lvn,
}))
}
#[napi]
pub fn batch(
&mut self,
high: Vec<f64>,
low: Vec<f64>,
volume: Vec<f64>,
) -> napi::Result<Vec<f64>> {
if high.len() != low.len() || low.len() != volume.len() {
return Err(NapiError::from_reason(
"high, low, volume must be equal length".to_string(),
));
}
let n = high.len();
let mut out = vec![f64::NAN; n * 2];
for i in 0..n {
let mid = f64::midpoint(high[i], low[i]);
let candle =
wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0).map_err(map_err)?;
if let Some(o) = self.inner.update(candle) {
out[i * 2] = o.hvn;
out[i * 2 + 1] = o.lvn;
}
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
#[napi(object)]
pub struct CompositeProfileValue {
pub poc: f64,
pub vah: f64,
pub val: f64,
}
// Composite Profile: multi-session composite volume profile (Candle -> struct).
#[napi(js_name = "CompositeProfile")]
pub struct CompositeProfileNode {
inner: wc::CompositeProfile,
}
#[napi]
impl CompositeProfileNode {
#[napi(constructor)]
pub fn new(period: u32, bin_count: u32, value_area_pct: f64) -> napi::Result<Self> {
Ok(Self {
inner: wc::CompositeProfile::new(period as usize, bin_count as usize, value_area_pct)
.map_err(map_err)?,
})
}
#[napi]
pub fn update(
&mut self,
high: f64,
low: f64,
volume: f64,
) -> napi::Result<Option<CompositeProfileValue>> {
let mid = f64::midpoint(high, low);
let candle = wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?;
Ok(self.inner.update(candle).map(|o| CompositeProfileValue {
poc: o.poc,
vah: o.vah,
val: o.val,
}))
}
#[napi]
pub fn batch(
&mut self,
high: Vec<f64>,
low: Vec<f64>,
volume: Vec<f64>,
) -> napi::Result<Vec<f64>> {
if high.len() != low.len() || low.len() != volume.len() {
return Err(NapiError::from_reason(
"high, low, volume must be equal length".to_string(),
));
}
let n = high.len();
let mut out = vec![f64::NAN; n * 3];
for i in 0..n {
let mid = f64::midpoint(high[i], low[i]);
let candle =
wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0).map_err(map_err)?;
if let Some(o) = self.inner.update(candle) {
out[i * 3] = o.poc;
out[i * 3 + 1] = o.vah;
out[i * 3 + 2] = o.val;
}
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
#[napi(js_name = "VolumeProfile")]
pub struct VolumeProfileNode {
inner: wc::VolumeProfile,
@@ -14450,6 +14776,50 @@ fn deriv_taker(taker_buy_volume: f64, taker_sell_volume: f64) -> napi::Result<wc
.map_err(map_err)
}
fn deriv_oi_long_short(
open_interest: f64,
long_size: f64,
short_size: f64,
) -> napi::Result<wc::DerivativesTick> {
wc::DerivativesTick::new(
0.0,
1.0,
1.0,
1.0,
open_interest,
long_size,
short_size,
0.0,
0.0,
0.0,
0.0,
0,
)
.map_err(map_err)
}
fn deriv_oi_taker(
open_interest: f64,
taker_buy_volume: f64,
taker_sell_volume: f64,
) -> napi::Result<wc::DerivativesTick> {
wc::DerivativesTick::new(
0.0,
1.0,
1.0,
1.0,
open_interest,
0.0,
0.0,
taker_buy_volume,
taker_sell_volume,
0.0,
0.0,
0,
)
.map_err(map_err)
}
fn deriv_liquidation(
long_liquidation: f64,
short_liquidation: f64,
@@ -15165,6 +15535,288 @@ impl CalendarSpreadNode {
}
}
// Estimated leverage ratio: open interest over aggregate long+short size.
#[napi(js_name = "EstimatedLeverageRatio")]
pub struct EstimatedLeverageRatioNode {
inner: wc::EstimatedLeverageRatio,
}
impl Default for EstimatedLeverageRatioNode {
fn default() -> Self {
Self::new()
}
}
#[napi]
impl EstimatedLeverageRatioNode {
#[napi(constructor)]
pub fn new() -> Self {
Self {
inner: wc::EstimatedLeverageRatio::new(),
}
}
#[napi]
pub fn update(
&mut self,
open_interest: f64,
long_size: f64,
short_size: f64,
) -> napi::Result<Option<f64>> {
Ok(self
.inner
.update(deriv_oi_long_short(open_interest, long_size, short_size)?))
}
#[napi]
pub fn batch(
&mut self,
open_interest: Vec<f64>,
long_size: Vec<f64>,
short_size: Vec<f64>,
) -> napi::Result<Vec<f64>> {
if open_interest.len() != long_size.len() || long_size.len() != short_size.len() {
return Err(NapiError::from_reason(
"open_interest, long_size, short_size must be equal length".to_string(),
));
}
let mut out = Vec::with_capacity(open_interest.len());
for i in 0..open_interest.len() {
out.push(
self.inner
.update(deriv_oi_long_short(
open_interest[i],
long_size[i],
short_size[i],
)?)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// OI-to-volume ratio: open interest over taker buy+sell volume.
#[napi(js_name = "OiToVolumeRatio")]
pub struct OiToVolumeRatioNode {
inner: wc::OiToVolumeRatio,
}
impl Default for OiToVolumeRatioNode {
fn default() -> Self {
Self::new()
}
}
#[napi]
impl OiToVolumeRatioNode {
#[napi(constructor)]
pub fn new() -> Self {
Self {
inner: wc::OiToVolumeRatio::new(),
}
}
#[napi]
pub fn update(
&mut self,
open_interest: f64,
taker_buy_volume: f64,
taker_sell_volume: f64,
) -> napi::Result<Option<f64>> {
Ok(self.inner.update(deriv_oi_taker(
open_interest,
taker_buy_volume,
taker_sell_volume,
)?))
}
#[napi]
pub fn batch(
&mut self,
open_interest: Vec<f64>,
taker_buy_volume: Vec<f64>,
taker_sell_volume: Vec<f64>,
) -> napi::Result<Vec<f64>> {
if open_interest.len() != taker_buy_volume.len()
|| taker_buy_volume.len() != taker_sell_volume.len()
{
return Err(NapiError::from_reason(
"open_interest, taker_buy_volume, taker_sell_volume must be equal length"
.to_string(),
));
}
let mut out = Vec::with_capacity(open_interest.len());
for i in 0..open_interest.len() {
out.push(
self.inner
.update(deriv_oi_taker(
open_interest[i],
taker_buy_volume[i],
taker_sell_volume[i],
)?)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// Perpetual premium index: relative premium of mark over index price.
#[napi(js_name = "PerpetualPremiumIndex")]
pub struct PerpetualPremiumIndexNode {
inner: wc::PerpetualPremiumIndex,
}
impl Default for PerpetualPremiumIndexNode {
fn default() -> Self {
Self::new()
}
}
#[napi]
impl PerpetualPremiumIndexNode {
#[napi(constructor)]
pub fn new() -> Self {
Self {
inner: wc::PerpetualPremiumIndex::new(),
}
}
#[napi]
pub fn update(&mut self, mark_price: f64, index_price: f64) -> napi::Result<Option<f64>> {
Ok(self.inner.update(deriv_basis(mark_price, index_price)?))
}
#[napi]
pub fn batch(&mut self, mark_price: Vec<f64>, index_price: Vec<f64>) -> napi::Result<Vec<f64>> {
if mark_price.len() != index_price.len() {
return Err(NapiError::from_reason(
"mark_price and index_price must be equal length".to_string(),
));
}
let mut out = Vec::with_capacity(mark_price.len());
for i in 0..mark_price.len() {
out.push(
self.inner
.update(deriv_basis(mark_price[i], index_price[i])?)
.unwrap_or(f64::NAN),
);
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// Funding-implied APR: per-interval funding annualised.
#[napi(js_name = "FundingImpliedApr")]
pub struct FundingImpliedAprNode {
inner: wc::FundingImpliedApr,
}
#[napi]
impl FundingImpliedAprNode {
#[napi(constructor)]
pub fn new(intervals_per_year: f64) -> napi::Result<Self> {
Ok(Self {
inner: wc::FundingImpliedApr::new(intervals_per_year).map_err(map_err)?,
})
}
#[napi]
pub fn update(&mut self, funding_rate: f64) -> napi::Result<Option<f64>> {
Ok(self.inner.update(deriv_funding(funding_rate)?))
}
#[napi]
pub fn batch(&mut self, funding_rate: Vec<f64>) -> napi::Result<Vec<f64>> {
let mut out = Vec::with_capacity(funding_rate.len());
for r in funding_rate {
out.push(self.inner.update(deriv_funding(r)?).unwrap_or(f64::NAN));
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// Open-interest momentum: rate-of-change of open interest over a window.
#[napi(js_name = "OpenInterestMomentum")]
pub struct OpenInterestMomentumNode {
inner: wc::OpenInterestMomentum,
}
#[napi]
impl OpenInterestMomentumNode {
#[napi(constructor)]
pub fn new(period: u32) -> napi::Result<Self> {
Ok(Self {
inner: wc::OpenInterestMomentum::new(period as usize).map_err(map_err)?,
})
}
#[napi]
pub fn update(&mut self, open_interest: f64) -> napi::Result<Option<f64>> {
Ok(self.inner.update(deriv_oi(open_interest)?))
}
#[napi]
pub fn batch(&mut self, open_interest: Vec<f64>) -> napi::Result<Vec<f64>> {
let mut out = Vec::with_capacity(open_interest.len());
for oi in open_interest {
out.push(self.inner.update(deriv_oi(oi)?).unwrap_or(f64::NAN));
}
Ok(out)
}
#[napi]
pub fn reset(&mut self) {
self.inner.reset();
}
#[napi(js_name = "isReady")]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[napi(js_name = "warmupPeriod")]
pub fn warmup_period(&self) -> u32 {
self.inner.warmup_period() as u32
}
}
// ---------- Market Breadth (CrossSection input) ----------
//
// A breadth tick is the per-symbol state of the whole universe, passed as four
+1 -1
View File
@@ -4,7 +4,7 @@ build-backend = "maturin"
[project]
name = "wickra"
version = "0.7.0"
version = "0.7.2"
description = "Streaming-first technical indicators: incremental, fast, install-free."
readme = "README.md"
license = "MIT OR Apache-2.0"
+20
View File
@@ -350,6 +350,11 @@ from ._wickra import (
Equivolume,
CandleVolume,
# Market Profile
CompositeProfile,
HighLowVolumeNodes,
ProfileShape,
SinglePrints,
NakedPoc,
ValueArea,
VolumeProfile,
TpoProfile,
@@ -480,6 +485,11 @@ from ._wickra import (
# Microstructure: footprint
Footprint,
# Derivatives
OpenInterestMomentum,
FundingImpliedApr,
PerpetualPremiumIndex,
OiToVolumeRatio,
EstimatedLeverageRatio,
FundingRate,
FundingRateMean,
FundingRateZScore,
@@ -868,6 +878,11 @@ __all__ = [
"Equivolume",
"CandleVolume",
# Market Profile
"CompositeProfile",
"HighLowVolumeNodes",
"ProfileShape",
"SinglePrints",
"NakedPoc",
"ValueArea",
"VolumeProfile",
"TpoProfile",
@@ -998,6 +1013,11 @@ __all__ = [
# Microstructure: footprint
"Footprint",
# Derivatives
"OpenInterestMomentum",
"FundingImpliedApr",
"PerpetualPremiumIndex",
"OiToVolumeRatio",
"EstimatedLeverageRatio",
"FundingRate",
"FundingRateMean",
"FundingRateZScore",
+693
View File
@@ -18140,6 +18140,349 @@ impl PyOpeningRange {
}
}
// Naked POC: most recent untouched point-of-control level (Candle -> f64).
#[pyclass(name = "NakedPoc", module = "wickra._wickra", skip_from_py_object)]
#[derive(Clone)]
struct PyNakedPoc {
inner: wc::NakedPoc,
}
#[pymethods]
impl PyNakedPoc {
#[new]
#[pyo3(signature = (session_len=20, bin_count=24))]
fn new(session_len: usize, bin_count: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::NakedPoc::new(session_len, bin_count).map_err(map_err)?,
})
}
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
let c = extract_candle(candle)?;
Ok(self.inner.update(c))
}
/// Batch over numpy high, low, close, volume arrays (all 1-D, equal length).
fn batch<'py>(
&mut self,
py: Python<'py>,
high: PyReadonlyArray1<'py, f64>,
low: PyReadonlyArray1<'py, f64>,
close: PyReadonlyArray1<'py, f64>,
volume: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let h = high
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let l = low
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let c = close
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let v = volume
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
if h.len() != l.len() || l.len() != c.len() || c.len() != v.len() {
return Err(PyValueError::new_err(
"high, low, close, volume must be equal length",
));
}
let mut out = Vec::with_capacity(c.len());
for i in 0..c.len() {
let candle = wc::Candle::new(c[i], h[i], l[i], c[i], v[i], 0).map_err(map_err)?;
out.push(self.inner.update(candle).unwrap_or(f64::NAN));
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
let (s, b) = self.inner.params();
format!("NakedPoc(session_len={s}, bin_count={b})")
}
}
// Single Prints: count of single-print price levels in the profile (Candle -> f64).
#[pyclass(name = "SinglePrints", module = "wickra._wickra", skip_from_py_object)]
#[derive(Clone)]
struct PySinglePrints {
inner: wc::SinglePrints,
}
#[pymethods]
impl PySinglePrints {
#[new]
#[pyo3(signature = (period=20, bin_count=24))]
fn new(period: usize, bin_count: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::SinglePrints::new(period, bin_count).map_err(map_err)?,
})
}
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
let c = extract_candle(candle)?;
Ok(self.inner.update(c))
}
/// Batch over numpy high, low arrays (1-D, equal length).
fn batch<'py>(
&mut self,
py: Python<'py>,
high: PyReadonlyArray1<'py, f64>,
low: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let h = high
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let l = low
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
if h.len() != l.len() {
return Err(PyValueError::new_err("high and low must be equal length"));
}
let mut out = Vec::with_capacity(h.len());
for i in 0..h.len() {
let mid = f64::midpoint(h[i], l[i]);
let candle = wc::Candle::new(mid, h[i], l[i], mid, 0.0, 0).map_err(map_err)?;
out.push(self.inner.update(candle).unwrap_or(f64::NAN));
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
let (p, b) = self.inner.params();
format!("SinglePrints(period={p}, bin_count={b})")
}
}
// Profile Shape: b/P/D shape classification as a numeric code (Candle -> f64).
#[pyclass(name = "ProfileShape", module = "wickra._wickra", skip_from_py_object)]
#[derive(Clone)]
struct PyProfileShape {
inner: wc::ProfileShape,
}
#[pymethods]
impl PyProfileShape {
#[new]
#[pyo3(signature = (period=20, bin_count=24))]
fn new(period: usize, bin_count: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::ProfileShape::new(period, bin_count).map_err(map_err)?,
})
}
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
let c = extract_candle(candle)?;
Ok(self.inner.update(c))
}
/// Batch over numpy high, low, volume arrays (1-D, equal length).
fn batch<'py>(
&mut self,
py: Python<'py>,
high: PyReadonlyArray1<'py, f64>,
low: PyReadonlyArray1<'py, f64>,
volume: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let h = high
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let l = low
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let v = volume
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
if h.len() != l.len() || l.len() != v.len() {
return Err(PyValueError::new_err(
"high, low, volume must be equal length",
));
}
let mut out = Vec::with_capacity(h.len());
for i in 0..h.len() {
let mid = f64::midpoint(h[i], l[i]);
let candle = wc::Candle::new(mid, h[i], l[i], mid, v[i], 0).map_err(map_err)?;
out.push(self.inner.update(candle).unwrap_or(f64::NAN));
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
let (p, b) = self.inner.params();
format!("ProfileShape(period={p}, bin_count={b})")
}
}
// High/Low Volume Nodes: highest- and lowest-volume price nodes (Candle -> struct).
#[pyclass(
name = "HighLowVolumeNodes",
module = "wickra._wickra",
skip_from_py_object
)]
#[derive(Clone)]
struct PyHighLowVolumeNodes {
inner: wc::HighLowVolumeNodes,
}
#[pymethods]
impl PyHighLowVolumeNodes {
#[new]
#[pyo3(signature = (period=20, bin_count=24))]
fn new(period: usize, bin_count: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::HighLowVolumeNodes::new(period, bin_count).map_err(map_err)?,
})
}
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<(f64, f64)>> {
let c = extract_candle(candle)?;
Ok(self.inner.update(c).map(|o| (o.hvn, o.lvn)))
}
/// Batch over numpy high, low, volume. Returns shape `(n, 2)` `[hvn, lvn]`.
fn batch<'py>(
&mut self,
py: Python<'py>,
high: PyReadonlyArray1<'py, f64>,
low: PyReadonlyArray1<'py, f64>,
volume: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray2<f64>>> {
let h = high
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let l = low
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let v = volume
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
if h.len() != l.len() || l.len() != v.len() {
return Err(PyValueError::new_err(
"high, low, volume must be equal length",
));
}
let n = h.len();
let mut out = vec![f64::NAN; n * 2];
for i in 0..n {
let mid = f64::midpoint(h[i], l[i]);
let candle = wc::Candle::new(mid, h[i], l[i], mid, v[i], 0).map_err(map_err)?;
if let Some(o) = self.inner.update(candle) {
out[i * 2] = o.hvn;
out[i * 2 + 1] = o.lvn;
}
}
Ok(numpy::ndarray::Array2::from_shape_vec((n, 2), out)
.expect("shape consistent")
.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
let (p, b) = self.inner.params();
format!("HighLowVolumeNodes(period={p}, bin_count={b})")
}
}
// Composite Profile: multi-session composite volume profile (Candle -> struct).
#[pyclass(
name = "CompositeProfile",
module = "wickra._wickra",
skip_from_py_object
)]
#[derive(Clone)]
struct PyCompositeProfile {
inner: wc::CompositeProfile,
}
#[pymethods]
impl PyCompositeProfile {
#[new]
#[pyo3(signature = (period=20, bin_count=24, value_area_pct=0.70))]
fn new(period: usize, bin_count: usize, value_area_pct: f64) -> PyResult<Self> {
Ok(Self {
inner: wc::CompositeProfile::new(period, bin_count, value_area_pct).map_err(map_err)?,
})
}
fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<(f64, f64, f64)>> {
let c = extract_candle(candle)?;
Ok(self.inner.update(c).map(|o| (o.poc, o.vah, o.val)))
}
/// Batch over numpy high, low, volume. Returns shape `(n, 3)` `[poc, vah, val]`.
fn batch<'py>(
&mut self,
py: Python<'py>,
high: PyReadonlyArray1<'py, f64>,
low: PyReadonlyArray1<'py, f64>,
volume: PyReadonlyArray1<'py, f64>,
) -> PyResult<Bound<'py, PyArray2<f64>>> {
let h = high
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let l = low
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
let v = volume
.as_slice()
.map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
if h.len() != l.len() || l.len() != v.len() {
return Err(PyValueError::new_err(
"high, low, volume must be equal length",
));
}
let n = h.len();
let mut out = vec![f64::NAN; n * 3];
for i in 0..n {
let mid = f64::midpoint(h[i], l[i]);
let candle = wc::Candle::new(mid, h[i], l[i], mid, v[i], 0).map_err(map_err)?;
if let Some(o) = self.inner.update(candle) {
out[i * 3] = o.poc;
out[i * 3 + 1] = o.vah;
out[i * 3 + 2] = o.val;
}
}
Ok(numpy::ndarray::Array2::from_shape_vec((n, 3), out)
.expect("shape consistent")
.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
let (p, b, pct) = self.inner.params();
format!("CompositeProfile(period={p}, bin_count={b}, value_area_pct={pct})")
}
}
// ============================== Candlestick Patterns ==============================
//
// All 15 patterns take Candles and emit a signed f64 signal per bar:
@@ -19420,6 +19763,50 @@ fn deriv_taker(taker_buy_volume: f64, taker_sell_volume: f64) -> PyResult<wc::De
.map_err(map_err)
}
fn deriv_oi_long_short(
open_interest: f64,
long_size: f64,
short_size: f64,
) -> PyResult<wc::DerivativesTick> {
wc::DerivativesTick::new(
0.0,
1.0,
1.0,
1.0,
open_interest,
long_size,
short_size,
0.0,
0.0,
0.0,
0.0,
0,
)
.map_err(map_err)
}
fn deriv_oi_taker(
open_interest: f64,
taker_buy_volume: f64,
taker_sell_volume: f64,
) -> PyResult<wc::DerivativesTick> {
wc::DerivativesTick::new(
0.0,
1.0,
1.0,
1.0,
open_interest,
0.0,
0.0,
taker_buy_volume,
taker_sell_volume,
0.0,
0.0,
0,
)
.map_err(map_err)
}
fn deriv_liquidation(
long_liquidation: f64,
short_liquidation: f64,
@@ -20140,6 +20527,302 @@ impl PyCalendarSpread {
}
}
// Estimated leverage ratio: open interest over aggregate long+short size.
#[pyclass(
name = "EstimatedLeverageRatio",
module = "wickra._wickra",
skip_from_py_object
)]
#[derive(Clone)]
struct PyEstimatedLeverageRatio {
inner: wc::EstimatedLeverageRatio,
}
#[pymethods]
impl PyEstimatedLeverageRatio {
#[new]
fn new() -> Self {
Self {
inner: wc::EstimatedLeverageRatio::new(),
}
}
fn update(
&mut self,
open_interest: f64,
long_size: f64,
short_size: f64,
) -> PyResult<Option<f64>> {
Ok(self
.inner
.update(deriv_oi_long_short(open_interest, long_size, short_size)?))
}
fn batch<'py>(
&mut self,
py: Python<'py>,
open_interest: Vec<f64>,
long_size: Vec<f64>,
short_size: Vec<f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
if open_interest.len() != long_size.len() || long_size.len() != short_size.len() {
return Err(PyValueError::new_err(
"open_interest, long_size, short_size must be equal length",
));
}
let mut out = Vec::with_capacity(open_interest.len());
for i in 0..open_interest.len() {
out.push(
self.inner
.update(deriv_oi_long_short(
open_interest[i],
long_size[i],
short_size[i],
)?)
.unwrap_or(f64::NAN),
);
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
"EstimatedLeverageRatio()".to_string()
}
}
// OI-to-volume ratio: open interest over taker buy+sell volume.
#[pyclass(
name = "OiToVolumeRatio",
module = "wickra._wickra",
skip_from_py_object
)]
#[derive(Clone)]
struct PyOiToVolumeRatio {
inner: wc::OiToVolumeRatio,
}
#[pymethods]
impl PyOiToVolumeRatio {
#[new]
fn new() -> Self {
Self {
inner: wc::OiToVolumeRatio::new(),
}
}
fn update(
&mut self,
open_interest: f64,
taker_buy_volume: f64,
taker_sell_volume: f64,
) -> PyResult<Option<f64>> {
Ok(self.inner.update(deriv_oi_taker(
open_interest,
taker_buy_volume,
taker_sell_volume,
)?))
}
fn batch<'py>(
&mut self,
py: Python<'py>,
open_interest: Vec<f64>,
taker_buy_volume: Vec<f64>,
taker_sell_volume: Vec<f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
if open_interest.len() != taker_buy_volume.len()
|| taker_buy_volume.len() != taker_sell_volume.len()
{
return Err(PyValueError::new_err(
"open_interest, taker_buy_volume, taker_sell_volume must be equal length",
));
}
let mut out = Vec::with_capacity(open_interest.len());
for i in 0..open_interest.len() {
out.push(
self.inner
.update(deriv_oi_taker(
open_interest[i],
taker_buy_volume[i],
taker_sell_volume[i],
)?)
.unwrap_or(f64::NAN),
);
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
"OiToVolumeRatio()".to_string()
}
}
// Perpetual premium index: relative premium of mark over index price.
#[pyclass(
name = "PerpetualPremiumIndex",
module = "wickra._wickra",
skip_from_py_object
)]
#[derive(Clone)]
struct PyPerpetualPremiumIndex {
inner: wc::PerpetualPremiumIndex,
}
#[pymethods]
impl PyPerpetualPremiumIndex {
#[new]
fn new() -> Self {
Self {
inner: wc::PerpetualPremiumIndex::new(),
}
}
fn update(&mut self, mark_price: f64, index_price: f64) -> PyResult<Option<f64>> {
Ok(self.inner.update(deriv_basis(mark_price, index_price)?))
}
fn batch<'py>(
&mut self,
py: Python<'py>,
mark_price: Vec<f64>,
index_price: Vec<f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
if mark_price.len() != index_price.len() {
return Err(PyValueError::new_err(
"mark_price and index_price must be equal length",
));
}
let mut out = Vec::with_capacity(mark_price.len());
for i in 0..mark_price.len() {
out.push(
self.inner
.update(deriv_basis(mark_price[i], index_price[i])?)
.unwrap_or(f64::NAN),
);
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
"PerpetualPremiumIndex()".to_string()
}
}
// Funding-implied APR: per-interval funding annualised.
#[pyclass(
name = "FundingImpliedApr",
module = "wickra._wickra",
skip_from_py_object
)]
#[derive(Clone)]
struct PyFundingImpliedApr {
inner: wc::FundingImpliedApr,
}
#[pymethods]
impl PyFundingImpliedApr {
#[new]
fn new(intervals_per_year: f64) -> PyResult<Self> {
Ok(Self {
inner: wc::FundingImpliedApr::new(intervals_per_year).map_err(map_err)?,
})
}
fn update(&mut self, funding_rate: f64) -> PyResult<Option<f64>> {
Ok(self.inner.update(deriv_funding(funding_rate)?))
}
fn batch<'py>(
&mut self,
py: Python<'py>,
funding_rate: Vec<f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let mut out = Vec::with_capacity(funding_rate.len());
for r in funding_rate {
out.push(self.inner.update(deriv_funding(r)?).unwrap_or(f64::NAN));
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
format!(
"FundingImpliedApr(intervals_per_year={})",
self.inner.intervals_per_year()
)
}
}
// Open-interest momentum: rate-of-change of open interest over a window.
#[pyclass(
name = "OpenInterestMomentum",
module = "wickra._wickra",
skip_from_py_object
)]
#[derive(Clone)]
struct PyOpenInterestMomentum {
inner: wc::OpenInterestMomentum,
}
#[pymethods]
impl PyOpenInterestMomentum {
#[new]
fn new(period: usize) -> PyResult<Self> {
Ok(Self {
inner: wc::OpenInterestMomentum::new(period).map_err(map_err)?,
})
}
fn update(&mut self, open_interest: f64) -> PyResult<Option<f64>> {
Ok(self.inner.update(deriv_oi(open_interest)?))
}
fn batch<'py>(
&mut self,
py: Python<'py>,
open_interest: Vec<f64>,
) -> PyResult<Bound<'py, PyArray1<f64>>> {
let mut out = Vec::with_capacity(open_interest.len());
for oi in open_interest {
out.push(self.inner.update(deriv_oi(oi)?).unwrap_or(f64::NAN));
}
Ok(out.into_pyarray(py))
}
fn reset(&mut self) {
self.inner.reset();
}
fn is_ready(&self) -> bool {
self.inner.is_ready()
}
fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
fn __repr__(&self) -> String {
format!("OpenInterestMomentum(period={})", self.inner.period())
}
}
// ============================== Market Breadth ==============================
//
// Market-breadth indicators consume a `CrossSection`: one tick carrying the
@@ -24932,6 +25615,11 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
m.add_class::<PyPointAndFigureBars>()?;
m.add_class::<PyInitialBalance>()?;
m.add_class::<PyOpeningRange>()?;
m.add_class::<PyNakedPoc>()?;
m.add_class::<PySinglePrints>()?;
m.add_class::<PyProfileShape>()?;
m.add_class::<PyHighLowVolumeNodes>()?;
m.add_class::<PyCompositeProfile>()?;
// Candlestick patterns.
m.add_class::<PyDoji>()?;
m.add_class::<PyHammer>()?;
@@ -25029,6 +25717,11 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
m.add_class::<PyLiquidationFeatures>()?;
m.add_class::<PyTermStructureBasis>()?;
m.add_class::<PyCalendarSpread>()?;
m.add_class::<PyEstimatedLeverageRatio>()?;
m.add_class::<PyOiToVolumeRatio>()?;
m.add_class::<PyPerpetualPremiumIndex>()?;
m.add_class::<PyFundingImpliedApr>()?;
m.add_class::<PyOpenInterestMomentum>()?;
m.add_class::<PyAdvanceDecline>()?;
m.add_class::<PyAdvanceDeclineRatio>()?;
m.add_class::<PyAdVolumeLine>()?;
@@ -383,6 +383,18 @@ def test_relative_strength_streaming_matches_batch():
# 6-tuple candle; the batch helper takes only the columns it needs.
CANDLE_SCALAR = {
"ProfileShape": (
lambda: ta.ProfileShape(20, 24),
lambda ind, h, l, c, v: ind.batch(h, l, v),
),
"SinglePrints": (
lambda: ta.SinglePrints(20, 24),
lambda ind, h, l, c, v: ind.batch(h, l),
),
"NakedPoc": (
lambda: ta.NakedPoc(20, 24),
lambda ind, h, l, c, v: ind.batch(h, l, c, v),
),
"FryPanBottom": (
lambda: ta.FryPanBottom(9),
lambda ind, h, l, c, v: ind.batch(h, l, c),
@@ -1009,6 +1021,16 @@ def test_candle_scalar_streaming_matches_batch(name, ohlcv):
# --- Candle-input, multi-output indicators --------------------------------
MULTI = {
"CompositeProfile": (
lambda: ta.CompositeProfile(20, 24, 0.7),
lambda ind, h, l, c, v: ind.batch(h, l, v),
3,
),
"HighLowVolumeNodes": (
lambda: ta.HighLowVolumeNodes(20, 24),
lambda ind, h, l, c, v: ind.batch(h, l, v),
2,
),
"CandleVolume": (
lambda: ta.CandleVolume(20),
lambda ind, h, l, c, v: ind.batch(c, c, v),
@@ -3331,6 +3353,26 @@ def test_hasbrouck_information_share_reference():
assert t.update(7.0, 9.0) is None
assert t.update(7.0, 9.0) == pytest.approx(0.5)
def test_naked_poc_reference():
t = ta.NakedPoc(20, 24)
def test_single_prints_reference():
t = ta.SinglePrints(20, 24)
def test_profile_shape_reference():
t = ta.ProfileShape(20, 24)
def test_high_low_volume_nodes_reference():
t = ta.HighLowVolumeNodes(20, 24)
def test_composite_profile_reference():
t = ta.CompositeProfile(20, 24, 0.7)
# --- Lifecycle ------------------------------------------------------------
@@ -4082,6 +4124,71 @@ def test_basis_indicators_streaming_equals_batch():
assert _eq_nan(batch, streamed)
def test_b16_derivatives_reference():
# Estimated leverage: oi / (long + short) = 200 / 100 = 2.
assert ta.EstimatedLeverageRatio().update(200.0, 60.0, 40.0) == pytest.approx(2.0)
# OI-to-volume: oi / (buy + sell) = 100 / 50 = 2.
assert ta.OiToVolumeRatio().update(100.0, 30.0, 20.0) == pytest.approx(2.0)
# Perpetual premium: (mark - index) / index = 0.5 / 100 = 0.005.
assert ta.PerpetualPremiumIndex().update(100.5, 100.0) == pytest.approx(0.005)
# Funding-implied APR: rate * intervals = 0.0001 * 1095 = 0.1095.
assert ta.FundingImpliedApr(1095.0).update(0.0001) == pytest.approx(0.1095)
# Open-interest momentum (period 2): warmup then ROC% = 100*(120-100)/100 = 20.
oim = ta.OpenInterestMomentum(2)
assert oim.update(100.0) is None
assert oim.update(110.0) is None
assert oim.update(120.0) == pytest.approx(20.0)
def test_b16_derivatives_streaming_equals_batch():
n = 40
oi = np.array([1000.0 + 50.0 * math.sin(i * 0.3) for i in range(n)], dtype=np.float64)
long_sz = np.array([600.0 + 20.0 * math.cos(i * 0.2) for i in range(n)], dtype=np.float64)
short_sz = np.array([400.0 + 15.0 * math.sin(i * 0.4) for i in range(n)], dtype=np.float64)
buy = np.array([300.0 + 10.0 * math.sin(i * 0.5) for i in range(n)], dtype=np.float64)
sell = np.array([250.0 + 12.0 * math.cos(i * 0.35) for i in range(n)], dtype=np.float64)
index = np.array([100.0 + math.sin(i * 0.2) for i in range(n)], dtype=np.float64)
mark = np.array([index[i] + 0.05 * math.cos(i * 0.3) for i in range(n)], dtype=np.float64)
rate = np.array([0.0001 * math.sin(i * 0.3) for i in range(n)], dtype=np.float64)
# EstimatedLeverageRatio; update(open_interest, long_size, short_size).
batch = ta.EstimatedLeverageRatio().batch(oi, long_sz, short_sz)
streamer = ta.EstimatedLeverageRatio()
streamed = np.array(
[streamer.update(oi[i], long_sz[i], short_sz[i]) for i in range(n)], dtype=np.float64
)
assert batch.shape == (n,)
assert _eq_nan(batch, streamed)
# OiToVolumeRatio; update(open_interest, taker_buy_volume, taker_sell_volume).
batch = ta.OiToVolumeRatio().batch(oi, buy, sell)
streamer = ta.OiToVolumeRatio()
streamed = np.array(
[streamer.update(oi[i], buy[i], sell[i]) for i in range(n)], dtype=np.float64
)
assert _eq_nan(batch, streamed)
# PerpetualPremiumIndex; update(mark_price, index_price).
batch = ta.PerpetualPremiumIndex().batch(mark, index)
streamer = ta.PerpetualPremiumIndex()
streamed = np.array(
[streamer.update(mark[i], index[i]) for i in range(n)], dtype=np.float64
)
assert _eq_nan(batch, streamed)
# FundingImpliedApr; update(funding_rate).
batch = ta.FundingImpliedApr(1095.0).batch(rate)
streamer = ta.FundingImpliedApr(1095.0)
streamed = np.array([streamer.update(rate[i]) for i in range(n)], dtype=np.float64)
assert _eq_nan(batch, streamed)
# OpenInterestMomentum; update(open_interest).
batch = ta.OpenInterestMomentum(10).batch(oi)
streamer = ta.OpenInterestMomentum(10)
streamed = np.array([streamer.update(oi[i]) for i in range(n)], dtype=np.float64)
assert _eq_nan(batch, streamed)
# --- Alt-Chart Bars ------------------------------------------------------
+525
View File
@@ -8526,6 +8526,298 @@ impl WasmValueArea {
}
}
// Naked POC: most recent untouched point-of-control level (Candle -> f64).
#[wasm_bindgen(js_name = NakedPoc)]
pub struct WasmNakedPoc {
inner: wc::NakedPoc,
}
#[wasm_bindgen(js_class = NakedPoc)]
impl WasmNakedPoc {
#[wasm_bindgen(constructor)]
pub fn new(session_len: usize, bin_count: usize) -> Result<WasmNakedPoc, JsError> {
Ok(Self {
inner: wc::NakedPoc::new(session_len, bin_count).map_err(map_err)?,
})
}
pub fn update(
&mut self,
high: f64,
low: f64,
close: f64,
volume: f64,
) -> Result<Option<f64>, JsError> {
Ok(self.inner.update(make_candle(high, low, close, volume)?))
}
pub fn batch(
&mut self,
high: &[f64],
low: &[f64],
close: &[f64],
volume: &[f64],
) -> Result<Float64Array, JsError> {
if high.len() != low.len() || low.len() != close.len() || close.len() != volume.len() {
return Err(JsError::new(
"high, low, close, volume must be equal length",
));
}
let mut out = Vec::with_capacity(close.len());
for i in 0..close.len() {
out.push(
self.inner
.update(make_candle(high[i], low[i], close[i], volume[i])?)
.unwrap_or(f64::NAN),
);
}
Ok(Float64Array::from(out.as_slice()))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// Single Prints: count of single-print price levels (Candle -> f64).
#[wasm_bindgen(js_name = SinglePrints)]
pub struct WasmSinglePrints {
inner: wc::SinglePrints,
}
#[wasm_bindgen(js_class = SinglePrints)]
impl WasmSinglePrints {
#[wasm_bindgen(constructor)]
pub fn new(period: usize, bin_count: usize) -> Result<WasmSinglePrints, JsError> {
Ok(Self {
inner: wc::SinglePrints::new(period, bin_count).map_err(map_err)?,
})
}
pub fn update(&mut self, high: f64, low: f64) -> Result<Option<f64>, JsError> {
let mid = f64::midpoint(high, low);
Ok(self
.inner
.update(wc::Candle::new(mid, high, low, mid, 0.0, 0).map_err(map_err)?))
}
pub fn batch(&mut self, high: &[f64], low: &[f64]) -> Result<Float64Array, JsError> {
if high.len() != low.len() {
return Err(JsError::new("high and low must be equal length"));
}
let mut out = Vec::with_capacity(high.len());
for i in 0..high.len() {
let mid = f64::midpoint(high[i], low[i]);
out.push(
self.inner
.update(wc::Candle::new(mid, high[i], low[i], mid, 0.0, 0).map_err(map_err)?)
.unwrap_or(f64::NAN),
);
}
Ok(Float64Array::from(out.as_slice()))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// Profile Shape: b/P/D classification as a numeric code (Candle -> f64).
#[wasm_bindgen(js_name = ProfileShape)]
pub struct WasmProfileShape {
inner: wc::ProfileShape,
}
#[wasm_bindgen(js_class = ProfileShape)]
impl WasmProfileShape {
#[wasm_bindgen(constructor)]
pub fn new(period: usize, bin_count: usize) -> Result<WasmProfileShape, JsError> {
Ok(Self {
inner: wc::ProfileShape::new(period, bin_count).map_err(map_err)?,
})
}
pub fn update(&mut self, high: f64, low: f64, volume: f64) -> Result<Option<f64>, JsError> {
let mid = f64::midpoint(high, low);
Ok(self
.inner
.update(wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?))
}
pub fn batch(
&mut self,
high: &[f64],
low: &[f64],
volume: &[f64],
) -> Result<Float64Array, JsError> {
if high.len() != low.len() || low.len() != volume.len() {
return Err(JsError::new("high, low, volume must be equal length"));
}
let mut out = Vec::with_capacity(high.len());
for i in 0..high.len() {
let mid = f64::midpoint(high[i], low[i]);
out.push(
self.inner
.update(
wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0)
.map_err(map_err)?,
)
.unwrap_or(f64::NAN),
);
}
Ok(Float64Array::from(out.as_slice()))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// High/Low Volume Nodes: highest- and lowest-volume price nodes (Candle -> struct).
#[wasm_bindgen(js_name = HighLowVolumeNodes)]
pub struct WasmHighLowVolumeNodes {
inner: wc::HighLowVolumeNodes,
}
#[wasm_bindgen(js_class = HighLowVolumeNodes)]
impl WasmHighLowVolumeNodes {
#[wasm_bindgen(constructor)]
pub fn new(period: usize, bin_count: usize) -> Result<WasmHighLowVolumeNodes, JsError> {
Ok(Self {
inner: wc::HighLowVolumeNodes::new(period, bin_count).map_err(map_err)?,
})
}
pub fn batch(
&mut self,
high: &[f64],
low: &[f64],
volume: &[f64],
) -> Result<Float64Array, JsError> {
if high.len() != low.len() || low.len() != volume.len() {
return Err(JsError::new("high, low, volume must be equal length"));
}
let n = high.len();
let mut out = vec![f64::NAN; n * 2];
for i in 0..n {
let mid = f64::midpoint(high[i], low[i]);
let c = wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0).map_err(map_err)?;
if let Some(o) = self.inner.update(c) {
out[i * 2] = o.hvn;
out[i * 2 + 1] = o.lvn;
}
}
Ok(Float64Array::from(out.as_slice()))
}
/// Streaming update. Returns `{ hvn, lvn }` once warm, else `null`.
pub fn update(&mut self, high: f64, low: f64, volume: f64) -> Result<JsValue, JsError> {
let mid = f64::midpoint(high, low);
let c = wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?;
Ok(match self.inner.update(c) {
Some(o) => {
let obj = Object::new();
Reflect::set(&obj, &"hvn".into(), &o.hvn.into()).ok();
Reflect::set(&obj, &"lvn".into(), &o.lvn.into()).ok();
obj.into()
}
None => JsValue::NULL,
})
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// Composite Profile: multi-session composite volume profile (Candle -> struct).
#[wasm_bindgen(js_name = CompositeProfile)]
pub struct WasmCompositeProfile {
inner: wc::CompositeProfile,
}
#[wasm_bindgen(js_class = CompositeProfile)]
impl WasmCompositeProfile {
#[wasm_bindgen(constructor)]
pub fn new(
period: usize,
bin_count: usize,
value_area_pct: f64,
) -> Result<WasmCompositeProfile, JsError> {
Ok(Self {
inner: wc::CompositeProfile::new(period, bin_count, value_area_pct).map_err(map_err)?,
})
}
pub fn batch(
&mut self,
high: &[f64],
low: &[f64],
volume: &[f64],
) -> Result<Float64Array, JsError> {
if high.len() != low.len() || low.len() != volume.len() {
return Err(JsError::new("high, low, volume must be equal length"));
}
let n = high.len();
let mut out = vec![f64::NAN; n * 3];
for i in 0..n {
let mid = f64::midpoint(high[i], low[i]);
let c = wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0).map_err(map_err)?;
if let Some(o) = self.inner.update(c) {
out[i * 3] = o.poc;
out[i * 3 + 1] = o.vah;
out[i * 3 + 2] = o.val;
}
}
Ok(Float64Array::from(out.as_slice()))
}
/// Streaming update. Returns `{ poc, vah, val }` once warm, else `null`.
pub fn update(&mut self, high: f64, low: f64, volume: f64) -> Result<JsValue, JsError> {
let mid = f64::midpoint(high, low);
let c = wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?;
Ok(match self.inner.update(c) {
Some(o) => {
let obj = Object::new();
Reflect::set(&obj, &"poc".into(), &o.poc.into()).ok();
Reflect::set(&obj, &"vah".into(), &o.vah.into()).ok();
Reflect::set(&obj, &"val".into(), &o.val.into()).ok();
obj.into()
}
None => JsValue::NULL,
})
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
#[wasm_bindgen(js_name = VolumeProfile)]
pub struct WasmVolumeProfile {
inner: wc::VolumeProfile,
@@ -9933,6 +10225,50 @@ fn deriv_taker(
.map_err(map_err)
}
fn deriv_oi_long_short(
open_interest: f64,
long_size: f64,
short_size: f64,
) -> Result<wc::DerivativesTick, JsError> {
wc::DerivativesTick::new(
0.0,
1.0,
1.0,
1.0,
open_interest,
long_size,
short_size,
0.0,
0.0,
0.0,
0.0,
0,
)
.map_err(map_err)
}
fn deriv_oi_taker(
open_interest: f64,
taker_buy_volume: f64,
taker_sell_volume: f64,
) -> Result<wc::DerivativesTick, JsError> {
wc::DerivativesTick::new(
0.0,
1.0,
1.0,
1.0,
open_interest,
0.0,
0.0,
taker_buy_volume,
taker_sell_volume,
0.0,
0.0,
0,
)
.map_err(map_err)
}
fn deriv_liquidation(
long_liquidation: f64,
short_liquidation: f64,
@@ -10256,6 +10592,195 @@ impl WasmCalendarSpread {
}
}
// ---------- Estimated Leverage Ratio ----------
#[wasm_bindgen(js_name = EstimatedLeverageRatio)]
pub struct WasmEstimatedLeverageRatio {
inner: wc::EstimatedLeverageRatio,
}
impl Default for WasmEstimatedLeverageRatio {
fn default() -> Self {
Self::new()
}
}
#[wasm_bindgen(js_class = EstimatedLeverageRatio)]
impl WasmEstimatedLeverageRatio {
#[wasm_bindgen(constructor)]
pub fn new() -> WasmEstimatedLeverageRatio {
Self {
inner: wc::EstimatedLeverageRatio::new(),
}
}
pub fn update(
&mut self,
open_interest: f64,
long_size: f64,
short_size: f64,
) -> Result<Option<f64>, JsError> {
Ok(self
.inner
.update(deriv_oi_long_short(open_interest, long_size, short_size)?))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// ---------- OI-to-Volume Ratio ----------
#[wasm_bindgen(js_name = OiToVolumeRatio)]
pub struct WasmOiToVolumeRatio {
inner: wc::OiToVolumeRatio,
}
impl Default for WasmOiToVolumeRatio {
fn default() -> Self {
Self::new()
}
}
#[wasm_bindgen(js_class = OiToVolumeRatio)]
impl WasmOiToVolumeRatio {
#[wasm_bindgen(constructor)]
pub fn new() -> WasmOiToVolumeRatio {
Self {
inner: wc::OiToVolumeRatio::new(),
}
}
pub fn update(
&mut self,
open_interest: f64,
taker_buy_volume: f64,
taker_sell_volume: f64,
) -> Result<Option<f64>, JsError> {
Ok(self.inner.update(deriv_oi_taker(
open_interest,
taker_buy_volume,
taker_sell_volume,
)?))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// ---------- Perpetual Premium Index ----------
#[wasm_bindgen(js_name = PerpetualPremiumIndex)]
pub struct WasmPerpetualPremiumIndex {
inner: wc::PerpetualPremiumIndex,
}
impl Default for WasmPerpetualPremiumIndex {
fn default() -> Self {
Self::new()
}
}
#[wasm_bindgen(js_class = PerpetualPremiumIndex)]
impl WasmPerpetualPremiumIndex {
#[wasm_bindgen(constructor)]
pub fn new() -> WasmPerpetualPremiumIndex {
Self {
inner: wc::PerpetualPremiumIndex::new(),
}
}
pub fn update(&mut self, mark_price: f64, index_price: f64) -> Result<Option<f64>, JsError> {
Ok(self.inner.update(deriv_basis(mark_price, index_price)?))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// ---------- Funding-Implied APR ----------
#[wasm_bindgen(js_name = FundingImpliedApr)]
pub struct WasmFundingImpliedApr {
inner: wc::FundingImpliedApr,
}
#[wasm_bindgen(js_class = FundingImpliedApr)]
impl WasmFundingImpliedApr {
#[wasm_bindgen(constructor)]
pub fn new(intervals_per_year: f64) -> Result<WasmFundingImpliedApr, JsError> {
Ok(Self {
inner: wc::FundingImpliedApr::new(intervals_per_year).map_err(map_err)?,
})
}
pub fn update(&mut self, funding_rate: f64) -> Result<Option<f64>, JsError> {
Ok(self.inner.update(deriv_funding(funding_rate)?))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// ---------- Open-Interest Momentum ----------
#[wasm_bindgen(js_name = OpenInterestMomentum)]
pub struct WasmOpenInterestMomentum {
inner: wc::OpenInterestMomentum,
}
#[wasm_bindgen(js_class = OpenInterestMomentum)]
impl WasmOpenInterestMomentum {
#[wasm_bindgen(constructor)]
pub fn new(period: usize) -> Result<WasmOpenInterestMomentum, JsError> {
Ok(Self {
inner: wc::OpenInterestMomentum::new(period).map_err(map_err)?,
})
}
pub fn update(&mut self, open_interest: f64) -> Result<Option<f64>, JsError> {
Ok(self.inner.update(deriv_oi(open_interest)?))
}
pub fn reset(&mut self) {
self.inner.reset();
}
#[wasm_bindgen(js_name = isReady)]
pub fn is_ready(&self) -> bool {
self.inner.is_ready()
}
#[wasm_bindgen(js_name = warmupPeriod)]
pub fn warmup_period(&self) -> usize {
self.inner.warmup_period()
}
}
// ---------- Heikin-Ashi Oscillator ----------
#[wasm_bindgen(js_name = HeikinAshiOscillator)]
@@ -0,0 +1,347 @@
//! Composite Profile — POC and value area over a long composite window.
use std::collections::VecDeque;
use crate::error::{Error, Result};
use crate::ohlcv::Candle;
use crate::traits::Indicator;
/// Output of [`CompositeProfile`]: the point of control and the value-area bounds.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct CompositeProfileOutput {
/// Point of Control — the price (bin centre) with the most volume.
pub poc: f64,
/// Value-Area High — top of the band holding `value_area_pct` of volume.
pub vah: f64,
/// Value-Area Low — bottom of that band.
pub val: f64,
}
/// Composite Profile — a multi-session volume profile reduced to its **point of
/// control** and **value area**, built over a long composite window.
///
/// ```text
/// build a `bins`-bucket volume profile over the last `period` candles
/// POC = bin with the most volume
/// expand from the POC, always adding the heavier adjacent bin, until the
/// accumulated volume reaches `value_area_pct` of the total
/// VAH / VAL = the highest / lowest price included
/// ```
///
/// A composite profile merges many sessions into one structure to reveal the
/// dominant value area and control price across a longer horizon — the levels that
/// matter for swing positioning rather than a single day. The point of control is
/// the fairest price (heaviest trade); the value area (classically 70% of volume)
/// brackets where the market spent most of its time. Price inside the value area is
/// "in balance"; acceptance outside it signals a value migration.
///
/// The first value lands after `period` candles; each `update` rebuilds the
/// profile in O(`period · bins`).
///
/// # Example
///
/// ```
/// use wickra_core::{Candle, Indicator, CompositeProfile};
///
/// let mut indicator = CompositeProfile::new(100, 50, 0.70).unwrap();
/// let mut last = None;
/// for i in 0..150 {
/// let base = 100.0 + (f64::from(i) * 0.1).sin() * 8.0;
/// let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
/// last = indicator.update(c);
/// }
/// assert!(last.is_some());
/// ```
#[derive(Debug, Clone)]
pub struct CompositeProfile {
period: usize,
bins: usize,
value_area_pct: f64,
window: VecDeque<Candle>,
last: Option<CompositeProfileOutput>,
}
impl CompositeProfile {
/// Construct a Composite Profile.
///
/// # Errors
///
/// Returns [`Error::PeriodZero`] if `period` or `bins` is zero, or
/// [`Error::InvalidParameter`] if `value_area_pct` is not in `(0, 1]`.
pub fn new(period: usize, bins: usize, value_area_pct: f64) -> Result<Self> {
if period == 0 || bins == 0 {
return Err(Error::PeriodZero);
}
if !value_area_pct.is_finite() || value_area_pct <= 0.0 || value_area_pct > 1.0 {
return Err(Error::InvalidParameter {
message: "value_area_pct must be in (0, 1]",
});
}
Ok(Self {
period,
bins,
value_area_pct,
window: VecDeque::with_capacity(period),
last: None,
})
}
/// Configured `(period, bins, value_area_pct)`.
pub const fn params(&self) -> (usize, usize, f64) {
(self.period, self.bins, self.value_area_pct)
}
/// Current value if available.
pub const fn value(&self) -> Option<CompositeProfileOutput> {
self.last
}
#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
fn compute(&self) -> CompositeProfileOutput {
let mut low = f64::INFINITY;
let mut high = f64::NEG_INFINITY;
for c in &self.window {
low = low.min(c.low);
high = high.max(c.high);
}
let span = high - low;
if span <= 0.0 {
return CompositeProfileOutput {
poc: low,
vah: low,
val: low,
};
}
let width = span / self.bins as f64;
let centre = |idx: usize| low + (idx as f64 + 0.5) * width;
let mut hist = vec![0.0; self.bins];
for c in &self.window {
if c.volume == 0.0 {
continue;
}
let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
let share = c.volume / (hi_idx - lo_idx + 1) as f64;
for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
*bin += share;
}
}
let total: f64 = hist.iter().sum();
let mut poc = 0;
let mut poc_vol = f64::NEG_INFINITY;
for (idx, &vol) in hist.iter().enumerate() {
if vol > poc_vol {
poc_vol = vol;
poc = idx;
}
}
let target = total * self.value_area_pct;
let mut acc = hist[poc];
let mut top = poc;
let mut bottom = poc;
while acc < target && (top < self.bins - 1 || bottom > 0) {
let above = if top < self.bins - 1 {
hist[top + 1]
} else {
f64::NEG_INFINITY
};
let below = if bottom > 0 {
hist[bottom - 1]
} else {
f64::NEG_INFINITY
};
if above >= below {
top += 1;
acc += hist[top];
} else {
bottom -= 1;
acc += hist[bottom];
}
}
CompositeProfileOutput {
poc: centre(poc),
vah: centre(top),
val: centre(bottom),
}
}
}
impl Indicator for CompositeProfile {
type Input = Candle;
type Output = CompositeProfileOutput;
fn update(&mut self, candle: Candle) -> Option<CompositeProfileOutput> {
if self.window.len() == self.period {
self.window.pop_front();
}
self.window.push_back(candle);
if self.window.len() < self.period {
return None;
}
let out = self.compute();
self.last = Some(out);
Some(out)
}
fn reset(&mut self) {
self.window.clear();
self.last = None;
}
fn warmup_period(&self) -> usize {
self.period
}
fn is_ready(&self) -> bool {
self.last.is_some()
}
fn name(&self) -> &'static str {
"CompositeProfile"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
fn c(high: f64, low: f64, volume: f64) -> Candle {
Candle::new_unchecked(
f64::midpoint(high, low),
high,
low,
f64::midpoint(high, low),
volume,
0,
)
}
#[test]
fn rejects_invalid_params() {
assert!(matches!(
CompositeProfile::new(0, 50, 0.7),
Err(Error::PeriodZero)
));
assert!(matches!(
CompositeProfile::new(100, 0, 0.7),
Err(Error::PeriodZero)
));
assert!(matches!(
CompositeProfile::new(100, 50, 0.0),
Err(Error::InvalidParameter { .. })
));
assert!(matches!(
CompositeProfile::new(100, 50, 1.5),
Err(Error::InvalidParameter { .. })
));
}
#[test]
fn accessors_and_metadata() {
let p = CompositeProfile::new(100, 50, 0.7).unwrap();
assert_eq!(p.params(), (100, 50, 0.7));
assert_eq!(p.warmup_period(), 100);
assert_eq!(p.name(), "CompositeProfile");
assert!(!p.is_ready());
assert_eq!(p.value(), None);
}
#[test]
fn first_emission_at_warmup_period() {
let mut p = CompositeProfile::new(4, 8, 0.7).unwrap();
let candles: Vec<Candle> = (0..6).map(|_| c(110.0, 90.0, 1_000.0)).collect();
let out = p.batch(&candles);
for v in out.iter().take(3) {
assert!(v.is_none());
}
assert!(out[3].is_some());
}
#[test]
fn value_area_brackets_poc() {
let mut p = CompositeProfile::new(20, 30, 0.7).unwrap();
let candles: Vec<Candle> = (0..40)
.map(|i| {
c(
110.0 + (f64::from(i) * 0.3).sin() * 8.0,
90.0 + (f64::from(i) * 0.3).cos() * 8.0,
1_000.0,
)
})
.collect();
for o in p.batch(&candles).into_iter().flatten() {
assert!(o.val <= o.poc && o.poc <= o.vah);
}
}
#[test]
fn poc_at_heavy_cluster() {
// Volume clustered at ~100; thin pokes elsewhere -> POC near 100.
let mut p = CompositeProfile::new(6, 30, 0.7).unwrap();
let mut candles: Vec<Candle> = (0..5).map(|_| c(101.0, 99.0, 5_000.0)).collect();
candles.push(c(140.0, 60.0, 50.0));
let out = p.batch(&candles).into_iter().flatten().last().unwrap();
assert!(
(out.poc - 100.0).abs() < 5.0,
"POC should sit at the cluster, got {}",
out.poc
);
}
#[test]
fn reset_clears_state() {
let mut p = CompositeProfile::new(4, 8, 0.7).unwrap();
p.batch(&[c(110.0, 90.0, 1_000.0); 6]);
assert!(p.is_ready());
p.reset();
assert!(!p.is_ready());
assert_eq!(p.value(), None);
assert_eq!(p.update(c(110.0, 90.0, 1_000.0)), None);
}
#[test]
fn batch_equals_streaming() {
let candles: Vec<Candle> = (0..120)
.map(|i| {
c(
110.0 + (f64::from(i) * 0.25).sin() * 9.0,
90.0,
1_000.0 + f64::from(i),
)
})
.collect();
let batch = CompositeProfile::new(50, 50, 0.7).unwrap().batch(&candles);
let mut b = CompositeProfile::new(50, 50, 0.7).unwrap();
let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
#[test]
fn flat_window_collapses_to_price() {
// Zero high-low span returns the price for POC, VAH and VAL.
let mut cp = CompositeProfile::new(2, 4, 0.7).unwrap();
cp.update(c(50.0, 50.0, 10.0));
let out = cp.update(c(50.0, 50.0, 10.0)).unwrap();
assert_eq!(out.poc, out.vah);
assert_eq!(out.poc, out.val);
}
#[test]
fn zero_volume_window_is_handled() {
// Non-flat window of zero-volume candles hits the skip path.
let mut cp = CompositeProfile::new(2, 4, 0.7).unwrap();
cp.update(c(60.0, 40.0, 0.0));
assert!(cp.update(c(60.0, 40.0, 0.0)).is_some());
}
#[test]
fn value_area_expands_down_from_top_poc() {
// POC sits in the top bin; with a wide value-area target the area runs
// out of bins above (the ceiling branch) and keeps expanding downward.
let mut cp = CompositeProfile::new(2, 3, 0.9).unwrap();
cp.update(c(100.0, 0.0, 30.0)); // thin spread across all three bins
let out = cp.update(c(100.0, 67.0, 60.0)).unwrap(); // heavy in the top bin
assert!(out.val <= out.poc && out.poc <= out.vah);
}
}
@@ -0,0 +1,155 @@
//! Estimated Leverage Ratio — open interest per unit of aggregate position size.
use crate::derivatives::DerivativesTick;
use crate::traits::Indicator;
/// Estimated Leverage Ratio (ELR) — open interest relative to the aggregate
/// long+short position size, a proxy for how leveraged outstanding positions are.
///
/// ```text
/// ELR = open_interest / (long_size + short_size)
/// ```
///
/// The classic estimated leverage ratio compares open interest (the notional of
/// outstanding contracts) to the capital backing it. With the size fields of a
/// [`DerivativesTick`] standing in for the position base, the ratio rises when a
/// given pool of positions controls more open interest — i.e. when the market is
/// running hotter leverage. Spikes in ELR mark crowded, fragile conditions where a
/// move can cascade into liquidations; a falling ELR marks deleveraging.
///
/// The ratio is non-negative; a tick with zero aggregate size reports `0` rather
/// than dividing by zero. It is stateless — each tick yields one value (no warmup).
/// Each `update` is O(1).
///
/// # Example
///
/// ```
/// use wickra_core::{DerivativesTick, Indicator, EstimatedLeverageRatio};
///
/// let mut indicator = EstimatedLeverageRatio::new();
/// let tick = DerivativesTick::new(0.0001, 100.0, 100.0, 100.0, 1_000.0, 400.0, 600.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
/// let elr = indicator.update(tick).unwrap();
/// assert!((elr - 1.0).abs() < 1e-12); // 1000 / (400 + 600)
/// ```
#[derive(Debug, Clone, Default)]
pub struct EstimatedLeverageRatio {
ready: bool,
}
impl EstimatedLeverageRatio {
/// Construct a new Estimated Leverage Ratio. The indicator is parameter-free.
#[must_use]
pub const fn new() -> Self {
Self { ready: false }
}
}
impl Indicator for EstimatedLeverageRatio {
type Input = DerivativesTick;
type Output = f64;
fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
let base = tick.long_size + tick.short_size;
let elr = if base > 0.0 {
tick.open_interest / base
} else {
0.0
};
self.ready = true;
Some(elr)
}
fn reset(&mut self) {
self.ready = false;
}
fn warmup_period(&self) -> usize {
1
}
fn is_ready(&self) -> bool {
self.ready
}
fn name(&self) -> &'static str {
"EstimatedLeverageRatio"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
use approx::assert_relative_eq;
fn tick(oi: f64, long: f64, short: f64) -> DerivativesTick {
DerivativesTick::new_unchecked(
0.0, 100.0, 100.0, 100.0, oi, long, short, 0.0, 0.0, 0.0, 0.0, 0,
)
}
#[test]
fn accessors_and_metadata() {
let e = EstimatedLeverageRatio::new();
assert_eq!(e.warmup_period(), 1);
assert_eq!(e.name(), "EstimatedLeverageRatio");
assert!(!e.is_ready());
}
#[test]
fn ratio_reference_value() {
let mut e = EstimatedLeverageRatio::new();
// 1000 / (400 + 600) = 1.0.
assert_relative_eq!(
e.update(tick(1_000.0, 400.0, 600.0)).unwrap(),
1.0,
epsilon = 1e-12
);
}
#[test]
fn higher_oi_raises_ratio() {
let mut e = EstimatedLeverageRatio::new();
let low = e.update(tick(1_000.0, 500.0, 500.0)).unwrap();
let high = e.update(tick(3_000.0, 500.0, 500.0)).unwrap();
assert!(high > low);
}
#[test]
fn zero_base_is_zero() {
let mut e = EstimatedLeverageRatio::new();
assert_relative_eq!(
e.update(tick(1_000.0, 0.0, 0.0)).unwrap(),
0.0,
epsilon = 1e-12
);
}
#[test]
fn ready_after_first_update() {
let mut e = EstimatedLeverageRatio::new();
assert!(!e.is_ready());
e.update(tick(1_000.0, 500.0, 500.0));
assert!(e.is_ready());
}
#[test]
fn reset_clears_state() {
let mut e = EstimatedLeverageRatio::new();
e.update(tick(1_000.0, 500.0, 500.0));
assert!(e.is_ready());
e.reset();
assert!(!e.is_ready());
}
#[test]
fn batch_equals_streaming() {
let ticks: Vec<DerivativesTick> = (0..40)
.map(|i| tick(1_000.0 + f64::from(i) * 10.0, 500.0, 500.0))
.collect();
let batch = EstimatedLeverageRatio::new().batch(&ticks);
let mut b = EstimatedLeverageRatio::new();
let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
}
@@ -0,0 +1,164 @@
//! Funding-Implied APR — the per-interval funding rate annualised.
use crate::derivatives::DerivativesTick;
use crate::error::{Error, Result};
use crate::traits::Indicator;
/// Funding-Implied APR — the perpetual's per-interval funding rate scaled to an
/// annualised rate.
///
/// ```text
/// APR = funding_rate · intervals_per_year
/// ```
///
/// Funding is paid in small per-interval amounts (commonly every 8 hours, i.e.
/// `1095` intervals per year). Annualising it converts the headline funding number
/// into the carry cost (or yield) of holding the position for a year, which is far
/// easier to reason about and to compare against spot lending rates, basis trades,
/// and other yields. A large positive APR means longs pay a steep carry to shorts
/// (and vice versa) — the economic incentive behind cash-and-carry and
/// funding-arbitrage strategies.
///
/// The output is a fraction (multiply by `100` for percent) and may be negative.
/// It is stateless — each tick yields one value (no warmup). Each `update` is O(1).
///
/// # Example
///
/// ```
/// use wickra_core::{DerivativesTick, Indicator, FundingImpliedApr};
///
/// // 0.01% per 8h funding -> 0.0001 * 1095 ≈ 10.95% APR.
/// let mut indicator = FundingImpliedApr::new(1095.0).unwrap();
/// let tick = DerivativesTick::new(0.0001, 100.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
/// let apr = indicator.update(tick).unwrap();
/// assert!((apr - 0.1095).abs() < 1e-9);
/// ```
#[derive(Debug, Clone)]
pub struct FundingImpliedApr {
intervals_per_year: f64,
ready: bool,
}
impl FundingImpliedApr {
/// Construct a Funding-Implied APR with the number of funding intervals per
/// year (e.g. `1095` for 8-hour funding, `365` for daily).
///
/// # Errors
///
/// Returns [`Error::InvalidParameter`] if `intervals_per_year` is not finite
/// and positive.
pub fn new(intervals_per_year: f64) -> Result<Self> {
if !intervals_per_year.is_finite() || intervals_per_year <= 0.0 {
return Err(Error::InvalidParameter {
message: "intervals_per_year must be finite and positive",
});
}
Ok(Self {
intervals_per_year,
ready: false,
})
}
/// Configured intervals per year.
pub const fn intervals_per_year(&self) -> f64 {
self.intervals_per_year
}
}
impl Indicator for FundingImpliedApr {
type Input = DerivativesTick;
type Output = f64;
fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
self.ready = true;
Some(tick.funding_rate * self.intervals_per_year)
}
fn reset(&mut self) {
self.ready = false;
}
fn warmup_period(&self) -> usize {
1
}
fn is_ready(&self) -> bool {
self.ready
}
fn name(&self) -> &'static str {
"FundingImpliedApr"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
use approx::assert_relative_eq;
fn tick(funding: f64) -> DerivativesTick {
DerivativesTick::new_unchecked(
funding, 100.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0,
)
}
#[test]
fn rejects_invalid_intervals() {
assert!(matches!(
FundingImpliedApr::new(0.0),
Err(Error::InvalidParameter { .. })
));
assert!(matches!(
FundingImpliedApr::new(-1.0),
Err(Error::InvalidParameter { .. })
));
}
#[test]
fn accessors_and_metadata() {
let f = FundingImpliedApr::new(1095.0).unwrap();
assert_relative_eq!(f.intervals_per_year(), 1095.0, epsilon = 1e-12);
assert_eq!(f.warmup_period(), 1);
assert_eq!(f.name(), "FundingImpliedApr");
assert!(!f.is_ready());
}
#[test]
fn apr_reference_value() {
let mut f = FundingImpliedApr::new(1095.0).unwrap();
assert_relative_eq!(f.update(tick(0.0001)).unwrap(), 0.1095, epsilon = 1e-9);
}
#[test]
fn negative_funding_is_negative_apr() {
let mut f = FundingImpliedApr::new(1095.0).unwrap();
assert!(f.update(tick(-0.0001)).unwrap() < 0.0);
}
#[test]
fn zero_funding_is_zero() {
let mut f = FundingImpliedApr::new(365.0).unwrap();
assert_relative_eq!(f.update(tick(0.0)).unwrap(), 0.0, epsilon = 1e-12);
}
#[test]
fn reset_clears_state() {
let mut f = FundingImpliedApr::new(1095.0).unwrap();
f.update(tick(0.0001));
assert!(f.is_ready());
f.reset();
assert!(!f.is_ready());
}
#[test]
fn batch_equals_streaming() {
let ticks: Vec<DerivativesTick> = (0..40)
.map(|i| tick(0.0001 * (f64::from(i) * 0.3).sin()))
.collect();
let batch = FundingImpliedApr::new(1095.0).unwrap().batch(&ticks);
let mut b = FundingImpliedApr::new(1095.0).unwrap();
let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
}
@@ -0,0 +1,307 @@
//! High/Low Volume Nodes (HVN / LVN) — the busiest and quietest price levels.
use std::collections::VecDeque;
use crate::error::{Error, Result};
use crate::ohlcv::Candle;
use crate::traits::Indicator;
/// Output of [`HighLowVolumeNodes`]: the price of the highest- and lowest-volume
/// node in the profile.
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct HighLowVolumeNodesOutput {
/// High Volume Node — the price level (bin centre) with the most volume.
pub hvn: f64,
/// Low Volume Node — the traded price level with the least volume.
pub lvn: f64,
}
/// High/Low Volume Nodes — the price levels of greatest and least acceptance in a
/// rolling volume profile.
///
/// ```text
/// build a `bins`-bucket volume profile over the last `period` candles
/// HVN = bin centre of the bucket with the most volume
/// LVN = bin centre of the traded bucket with the least volume
/// ```
///
/// A volume profile reveals where the market spent the most effort. A **High Volume
/// Node** (HVN) is a price the market accepted and traded heavily — it acts as a
/// magnet and as strong support/resistance. A **Low Volume Node** (LVN) is a price
/// the market rejected quickly — moves tend to accelerate through LVNs and they
/// often mark the edges between balance areas. Each candle's volume is spread
/// across the price bins its high-low range spans (as in
/// [`VolumeProfile`](crate::VolumeProfile)).
///
/// The first value lands after `period` candles; each `update` rebuilds the profile
/// in O(`period · bins`). A degenerate flat window puts both nodes at the price.
///
/// # Example
///
/// ```
/// use wickra_core::{Candle, Indicator, HighLowVolumeNodes};
///
/// let mut indicator = HighLowVolumeNodes::new(20, 24).unwrap();
/// let mut last = None;
/// for i in 0..40 {
/// let base = 100.0 + (f64::from(i) * 0.3).sin() * 5.0;
/// let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
/// last = indicator.update(c);
/// }
/// assert!(last.is_some());
/// ```
#[derive(Debug, Clone)]
pub struct HighLowVolumeNodes {
period: usize,
bins: usize,
window: VecDeque<Candle>,
last: Option<HighLowVolumeNodesOutput>,
}
impl HighLowVolumeNodes {
/// Construct a High/Low Volume Nodes indicator.
///
/// # Errors
///
/// Returns [`Error::PeriodZero`] if `period` or `bins` is zero.
pub fn new(period: usize, bins: usize) -> Result<Self> {
if period == 0 || bins == 0 {
return Err(Error::PeriodZero);
}
Ok(Self {
period,
bins,
window: VecDeque::with_capacity(period),
last: None,
})
}
/// Configured `(period, bins)`.
pub const fn params(&self) -> (usize, usize) {
(self.period, self.bins)
}
/// Current value if available.
pub const fn value(&self) -> Option<HighLowVolumeNodesOutput> {
self.last
}
/// Build the volume histogram; returns `(low, bin_width, bins)`.
#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
fn profile(&self) -> (f64, f64, Vec<f64>) {
let mut low = f64::INFINITY;
let mut high = f64::NEG_INFINITY;
for c in &self.window {
low = low.min(c.low);
high = high.max(c.high);
}
let mut hist = vec![0.0; self.bins];
let span = high - low;
if span <= 0.0 {
hist[0] = self.window.iter().map(|c| c.volume).sum();
return (low, 0.0, hist);
}
let width = span / self.bins as f64;
for c in &self.window {
if c.volume == 0.0 {
continue;
}
let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
let touched = hi_idx - lo_idx + 1;
let share = c.volume / touched as f64;
for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
*bin += share;
}
}
(low, width, hist)
}
}
impl Indicator for HighLowVolumeNodes {
type Input = Candle;
type Output = HighLowVolumeNodesOutput;
#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
fn update(&mut self, candle: Candle) -> Option<HighLowVolumeNodesOutput> {
if self.window.len() == self.period {
self.window.pop_front();
}
self.window.push_back(candle);
if self.window.len() < self.period {
return None;
}
let (low, width, hist) = self.profile();
let centre = |idx: usize| low + (idx as f64 + 0.5) * width;
let mut hvn_idx = 0;
let mut hvn_vol = f64::NEG_INFINITY;
let mut lvn_idx = 0;
let mut lvn_vol = f64::INFINITY;
for (idx, &vol) in hist.iter().enumerate() {
if vol > hvn_vol {
hvn_vol = vol;
hvn_idx = idx;
}
if vol > 0.0 && vol < lvn_vol {
lvn_vol = vol;
lvn_idx = idx;
}
}
// If no traded bin was found (all zero volume), both default to bin 0.
if !lvn_vol.is_finite() {
lvn_idx = hvn_idx;
}
let out = HighLowVolumeNodesOutput {
hvn: centre(hvn_idx),
lvn: centre(lvn_idx),
};
self.last = Some(out);
Some(out)
}
fn reset(&mut self) {
self.window.clear();
self.last = None;
}
fn warmup_period(&self) -> usize {
self.period
}
fn is_ready(&self) -> bool {
self.last.is_some()
}
fn name(&self) -> &'static str {
"HighLowVolumeNodes"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
fn c(high: f64, low: f64, volume: f64) -> Candle {
Candle::new_unchecked(
f64::midpoint(high, low),
high,
low,
f64::midpoint(high, low),
volume,
0,
)
}
#[test]
fn rejects_zero_params() {
assert!(matches!(
HighLowVolumeNodes::new(0, 24),
Err(Error::PeriodZero)
));
assert!(matches!(
HighLowVolumeNodes::new(20, 0),
Err(Error::PeriodZero)
));
}
#[test]
fn accessors_and_metadata() {
let h = HighLowVolumeNodes::new(20, 24).unwrap();
assert_eq!(h.params(), (20, 24));
assert_eq!(h.warmup_period(), 20);
assert_eq!(h.name(), "HighLowVolumeNodes");
assert!(!h.is_ready());
assert_eq!(h.value(), None);
}
#[test]
fn first_emission_at_warmup_period() {
let mut h = HighLowVolumeNodes::new(4, 8).unwrap();
let candles: Vec<Candle> = (0..6).map(|_| c(110.0, 90.0, 1_000.0)).collect();
let out = h.batch(&candles);
for v in out.iter().take(3) {
assert!(v.is_none());
}
assert!(out[3].is_some());
}
#[test]
fn hvn_at_heavy_price() {
// Most bars cluster at ~100 (heavy volume); one bar pokes up to 120 lightly.
let mut h = HighLowVolumeNodes::new(6, 24).unwrap();
let mut candles: Vec<Candle> = (0..5).map(|_| c(101.0, 99.0, 5_000.0)).collect();
candles.push(c(121.0, 119.0, 100.0));
let out = h.batch(&candles).into_iter().flatten().last().unwrap();
// HVN should sit near the heavy 100 cluster, well below the light 120 poke.
assert!(
out.hvn < 110.0,
"HVN should be at the heavy cluster, got {}",
out.hvn
);
assert!(out.lvn >= out.hvn - 1e9); // lvn is a valid level
}
#[test]
fn hvn_at_or_above_low() {
let mut h = HighLowVolumeNodes::new(10, 24).unwrap();
let candles: Vec<Candle> = (0..30)
.map(|i| {
c(
110.0 + (f64::from(i) * 0.3).sin() * 5.0,
90.0,
1_000.0 + f64::from(i),
)
})
.collect();
for o in h.batch(&candles).into_iter().flatten() {
assert!(o.hvn.is_finite() && o.lvn.is_finite());
}
}
#[test]
fn reset_clears_state() {
let mut h = HighLowVolumeNodes::new(4, 8).unwrap();
h.batch(&[c(110.0, 90.0, 1_000.0); 6]);
assert!(h.is_ready());
h.reset();
assert!(!h.is_ready());
assert_eq!(h.value(), None);
assert_eq!(h.update(c(110.0, 90.0, 1_000.0)), None);
}
#[test]
fn batch_equals_streaming() {
let candles: Vec<Candle> = (0..80)
.map(|i| {
c(
110.0 + (f64::from(i) * 0.25).sin() * 9.0,
90.0,
1_000.0 + f64::from(i),
)
})
.collect();
let batch = HighLowVolumeNodes::new(20, 24).unwrap().batch(&candles);
let mut b = HighLowVolumeNodes::new(20, 24).unwrap();
let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
#[test]
fn flat_window_is_handled() {
// Zero high-low span dumps all volume into bin 0 and returns early.
let mut h = HighLowVolumeNodes::new(2, 4).unwrap();
h.update(c(50.0, 50.0, 10.0));
assert!(h.update(c(50.0, 50.0, 10.0)).is_some());
}
#[test]
fn zero_volume_window_falls_back() {
// All-zero volume leaves no traded bin; the LVN falls back to the HVN.
let mut h = HighLowVolumeNodes::new(2, 4).unwrap();
h.update(c(60.0, 40.0, 0.0));
let out = h.update(c(60.0, 40.0, 0.0)).unwrap();
assert_eq!(out.hvn, out.lvn);
}
}
+31 -1
View File
@@ -84,6 +84,7 @@ mod cmf;
mod cmo;
mod coefficient_of_variation;
mod cointegration;
mod composite_profile;
mod concealing_baby_swallow;
mod conditional_value_at_risk;
mod connors_rsi;
@@ -131,6 +132,7 @@ mod ema;
mod empirical_mode_decomposition;
mod engulfing;
mod equivolume;
mod estimated_leverage_ratio;
mod even_better_sinewave;
mod evening_doji_star;
mod evwma;
@@ -156,6 +158,7 @@ mod fractal_chaos_bands;
mod frama;
mod fry_pan_bottom;
mod funding_basis;
mod funding_implied_apr;
mod funding_rate;
mod funding_rate_mean;
mod funding_rate_zscore;
@@ -180,6 +183,7 @@ mod heikin_ashi;
mod heikin_ashi_oscillator;
mod high_low_index;
mod high_low_range;
mod high_low_volume_nodes;
mod high_wave;
mod highpass_filter;
mod hikkake;
@@ -267,6 +271,7 @@ mod mom;
mod morning_doji_star;
mod morning_evening_star;
mod murrey_math_lines;
mod naked_poc;
mod natr;
mod new_highs_new_lows;
mod new_price_lines;
@@ -278,9 +283,11 @@ mod ob_imbalance_topn;
mod obv;
mod oi_delta;
mod oi_price_divergence;
mod oi_to_volume_ratio;
mod oi_weighted;
mod omega_ratio;
mod on_neck;
mod open_interest_momentum;
mod opening_marubozu;
mod opening_range;
mod order_flow_imbalance;
@@ -295,6 +302,7 @@ mod pearson_correlation;
mod percent_above_ma;
mod percent_b;
mod percentage_trailing_stop;
mod perpetual_premium_index;
mod pgo;
mod piercing_dark_cloud;
mod pin;
@@ -306,6 +314,7 @@ mod point_and_figure_bars;
mod polarized_fractal_efficiency;
mod ppo;
mod ppo_histogram;
mod profile_shape;
mod profit_factor;
mod projection_bands;
mod projection_oscillator;
@@ -361,6 +370,7 @@ mod short_line;
mod signed_volume;
mod sine_wave;
mod sine_weighted_ma;
mod single_prints;
mod skewness;
mod sma;
mod smi;
@@ -572,6 +582,7 @@ pub use cmf::ChaikinMoneyFlow;
pub use cmo::Cmo;
pub use coefficient_of_variation::CoefficientOfVariation;
pub use cointegration::{Cointegration, CointegrationOutput};
pub use composite_profile::{CompositeProfile, CompositeProfileOutput};
pub use concealing_baby_swallow::ConcealingBabySwallow;
pub use conditional_value_at_risk::ConditionalValueAtRisk;
pub use connors_rsi::ConnorsRsi;
@@ -619,6 +630,7 @@ pub use ema::Ema;
pub use empirical_mode_decomposition::EmpiricalModeDecomposition;
pub use engulfing::Engulfing;
pub use equivolume::{Equivolume, EquivolumeOutput};
pub use estimated_leverage_ratio::EstimatedLeverageRatio;
pub use even_better_sinewave::EvenBetterSinewave;
pub use evening_doji_star::EveningDojiStar;
pub use evwma::Evwma;
@@ -644,6 +656,7 @@ pub use fractal_chaos_bands::{FractalChaosBands, FractalChaosBandsOutput};
pub use frama::Frama;
pub use fry_pan_bottom::FryPanBottom;
pub use funding_basis::FundingBasis;
pub use funding_implied_apr::FundingImpliedApr;
pub use funding_rate::FundingRate;
pub use funding_rate_mean::FundingRateMean;
pub use funding_rate_zscore::FundingRateZScore;
@@ -668,6 +681,7 @@ pub use heikin_ashi::{HeikinAshi, HeikinAshiOutput};
pub use heikin_ashi_oscillator::HeikinAshiOscillator;
pub use high_low_index::HighLowIndex;
pub use high_low_range::HighLowRange;
pub use high_low_volume_nodes::{HighLowVolumeNodes, HighLowVolumeNodesOutput};
pub use high_wave::HighWave;
pub use highpass_filter::HighpassFilter;
pub use hikkake::Hikkake;
@@ -755,6 +769,7 @@ pub use mom::Mom;
pub use morning_doji_star::MorningDojiStar;
pub use morning_evening_star::MorningEveningStar;
pub use murrey_math_lines::{MurreyMathLines, MurreyMathLinesOutput};
pub use naked_poc::NakedPoc;
pub use natr::Natr;
pub use new_highs_new_lows::NewHighsNewLows;
pub use new_price_lines::NewPriceLines;
@@ -766,9 +781,11 @@ pub use ob_imbalance_topn::OrderBookImbalanceTopN;
pub use obv::Obv;
pub use oi_delta::OpenInterestDelta;
pub use oi_price_divergence::OIPriceDivergence;
pub use oi_to_volume_ratio::OiToVolumeRatio;
pub use oi_weighted::OIWeighted;
pub use omega_ratio::OmegaRatio;
pub use on_neck::OnNeck;
pub use open_interest_momentum::OpenInterestMomentum;
pub use opening_marubozu::OpeningMarubozu;
pub use opening_range::{OpeningRange, OpeningRangeOutput};
pub use order_flow_imbalance::OrderFlowImbalance;
@@ -783,6 +800,7 @@ pub use pearson_correlation::PearsonCorrelation;
pub use percent_above_ma::PercentAboveMa;
pub use percent_b::PercentB;
pub use percentage_trailing_stop::PercentageTrailingStop;
pub use perpetual_premium_index::PerpetualPremiumIndex;
pub use pgo::Pgo;
pub use piercing_dark_cloud::PiercingDarkCloud;
pub use pin::Pin;
@@ -794,6 +812,7 @@ pub use point_and_figure_bars::{PnfColumn, PointAndFigureBars};
pub use polarized_fractal_efficiency::PolarizedFractalEfficiency;
pub use ppo::Ppo;
pub use ppo_histogram::PpoHistogram;
pub use profile_shape::ProfileShape;
pub use profit_factor::ProfitFactor;
pub use projection_bands::{ProjectionBands, ProjectionBandsOutput};
pub use projection_oscillator::ProjectionOscillator;
@@ -849,6 +868,7 @@ pub use short_line::ShortLine;
pub use signed_volume::SignedVolume;
pub use sine_wave::SineWave;
pub use sine_weighted_ma::SineWeightedMa;
pub use single_prints::SinglePrints;
pub use skewness::Skewness;
pub use sma::Sma;
pub use smi::Smi;
@@ -1478,6 +1498,11 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
"LiquidationFeatures",
"TermStructureBasis",
"CalendarSpread",
"EstimatedLeverageRatio",
"OiToVolumeRatio",
"PerpetualPremiumIndex",
"FundingImpliedApr",
"OpenInterestMomentum",
],
),
(
@@ -1488,6 +1513,11 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
"OpeningRange",
"VolumeProfile",
"TpoProfile",
"NakedPoc",
"SinglePrints",
"ProfileShape",
"HighLowVolumeNodes",
"CompositeProfile",
],
),
(
@@ -1624,6 +1654,6 @@ mod family_tests {
// the actual indicator count is the early-warning signal that an
// indicator was added without being assigned a family.
let total: usize = FAMILIES.iter().map(|(_, ns)| ns.len()).sum();
assert_eq!(total, 488, "FAMILIES total drifted from indicator count");
assert_eq!(total, 498, "FAMILIES total drifted from indicator count");
}
}
@@ -0,0 +1,318 @@
//! Naked POC — the nearest prior-session point of control price has not yet revisited.
use std::collections::VecDeque;
use crate::error::{Error, Result};
use crate::ohlcv::Candle;
use crate::traits::Indicator;
/// Naked (Virgin) POC — the nearest **untested** point of control from a prior
/// session: a heavily-traded price the market has not traded back through since.
///
/// ```text
/// every `session_len` candles forms a session; its POC (heaviest-volume price) is
/// recorded as "naked"
/// a naked POC becomes "tested" once a later candle's high-low range covers it
/// output = the nearest still-naked POC to the current close (or the close itself
/// if every prior POC has been revisited)
/// ```
///
/// A point of control is a magnet — price tends to return to fair value. A *naked*
/// (or virgin) POC is one that has not yet been revisited, so it carries an
/// outstanding "pull": untested POCs are high-probability targets and
/// support/resistance on the approach. This indicator records each completed
/// session's POC, marks them tested as price trades through them, and reports the
/// closest one still outstanding.
///
/// The first value lands after `session_len` candles (the first session's POC).
/// Each `update` is O(`session_len · bins` + naked-count).
///
/// # Example
///
/// ```
/// use wickra_core::{Candle, Indicator, NakedPoc};
///
/// let mut indicator = NakedPoc::new(20, 24).unwrap();
/// let mut last = None;
/// for i in 0..60 {
/// let base = 100.0 + (f64::from(i) * 0.2).sin() * 5.0;
/// let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
/// last = indicator.update(c);
/// }
/// assert!(last.is_some());
/// ```
#[derive(Debug, Clone)]
pub struct NakedPoc {
session_len: usize,
bins: usize,
session: VecDeque<Candle>,
naked: Vec<f64>,
last_close: f64,
ready: bool,
last: Option<f64>,
}
impl NakedPoc {
/// Construct a Naked POC tracker with the given `session_len` and profile
/// `bins`.
///
/// # Errors
///
/// Returns [`Error::PeriodZero`] if `session_len` or `bins` is zero.
pub fn new(session_len: usize, bins: usize) -> Result<Self> {
if session_len == 0 || bins == 0 {
return Err(Error::PeriodZero);
}
Ok(Self {
session_len,
bins,
session: VecDeque::with_capacity(session_len),
naked: Vec::new(),
last_close: 0.0,
ready: false,
last: None,
})
}
/// Configured `(session_len, bins)`.
pub const fn params(&self) -> (usize, usize) {
(self.session_len, self.bins)
}
/// Number of currently-naked POCs.
pub fn naked_count(&self) -> usize {
self.naked.len()
}
/// Current value if available.
pub const fn value(&self) -> Option<f64> {
self.last
}
#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
fn session_poc(&self) -> f64 {
let mut low = f64::INFINITY;
let mut high = f64::NEG_INFINITY;
for c in &self.session {
low = low.min(c.low);
high = high.max(c.high);
}
let span = high - low;
if span <= 0.0 {
return low;
}
let width = span / self.bins as f64;
let mut hist = vec![0.0; self.bins];
for c in &self.session {
if c.volume == 0.0 {
continue;
}
let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
let share = c.volume / (hi_idx - lo_idx + 1) as f64;
for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
*bin += share;
}
}
let mut poc = 0;
let mut poc_vol = f64::NEG_INFINITY;
for (idx, &vol) in hist.iter().enumerate() {
if vol > poc_vol {
poc_vol = vol;
poc = idx;
}
}
low + (poc as f64 + 0.5) * width
}
}
impl Indicator for NakedPoc {
type Input = Candle;
type Output = f64;
fn update(&mut self, candle: Candle) -> Option<f64> {
// Test outstanding naked POCs against this candle's range.
self.naked
.retain(|&poc| !(candle.low <= poc && poc <= candle.high));
self.last_close = candle.close;
// Accumulate the session; finalize a POC at the boundary.
self.session.push_back(candle);
if self.session.len() == self.session_len {
let poc = self.session_poc();
self.naked.push(poc);
self.session.clear();
self.ready = true;
}
if !self.ready {
return None;
}
let nearest = self
.naked
.iter()
.copied()
.min_by(|a, b| {
(a - self.last_close)
.abs()
.total_cmp(&(b - self.last_close).abs())
})
.unwrap_or(self.last_close);
self.last = Some(nearest);
Some(nearest)
}
fn reset(&mut self) {
self.session.clear();
self.naked.clear();
self.last_close = 0.0;
self.ready = false;
self.last = None;
}
fn warmup_period(&self) -> usize {
self.session_len
}
fn is_ready(&self) -> bool {
self.last.is_some()
}
fn name(&self) -> &'static str {
"NakedPoc"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
fn c(high: f64, low: f64, close: f64, volume: f64) -> Candle {
Candle::new_unchecked(f64::midpoint(high, low), high, low, close, volume, 0)
}
#[test]
fn rejects_zero_params() {
assert!(matches!(NakedPoc::new(0, 24), Err(Error::PeriodZero)));
assert!(matches!(NakedPoc::new(20, 0), Err(Error::PeriodZero)));
}
#[test]
fn accessors_and_metadata() {
let n = NakedPoc::new(20, 24).unwrap();
assert_eq!(n.params(), (20, 24));
assert_eq!(n.naked_count(), 0);
assert_eq!(n.warmup_period(), 20);
assert_eq!(n.name(), "NakedPoc");
assert!(!n.is_ready());
assert_eq!(n.value(), None);
}
#[test]
fn first_emission_at_session_end() {
let mut n = NakedPoc::new(4, 8).unwrap();
let candles: Vec<Candle> = (0..6).map(|_| c(101.0, 99.0, 100.0, 1_000.0)).collect();
let out = n.batch(&candles);
for v in out.iter().take(3) {
assert!(v.is_none());
}
assert!(out[3].is_some());
}
#[test]
fn records_session_poc() {
let mut n = NakedPoc::new(4, 16).unwrap();
// A session clustered around 100 -> POC near 100.
n.batch(&[c(101.0, 99.0, 100.0, 5_000.0); 4]);
assert_eq!(n.naked_count(), 1);
let poc = n.value().unwrap();
assert!(
(poc - 100.0).abs() < 2.0,
"POC should be near 100, got {poc}"
);
}
#[test]
fn revisit_marks_poc_tested() {
let mut n = NakedPoc::new(4, 16).unwrap();
// Session 1 around 100 -> naked POC ~100.
n.batch(&[c(101.0, 99.0, 100.0, 5_000.0); 4]);
assert_eq!(n.naked_count(), 1);
// Trade away at 120 (does not cover 100) -> still naked.
n.update(c(121.0, 119.0, 120.0, 1_000.0));
assert_eq!(n.naked_count(), 1);
// A candle whose range covers 100 -> POC tested -> removed.
n.update(c(121.0, 95.0, 100.0, 1_000.0));
assert_eq!(n.naked_count(), 0);
}
#[test]
fn empty_naked_reports_close() {
let mut n = NakedPoc::new(4, 16).unwrap();
n.batch(&[c(101.0, 99.0, 100.0, 5_000.0); 4]);
// Wipe the naked POC with a covering candle.
let out = n.update(c(121.0, 95.0, 117.0, 1_000.0)).unwrap();
assert_eq!(n.naked_count(), 0);
assert!(
(out - 117.0).abs() < 1e-9,
"with no naked POC, output is the close"
);
}
#[test]
fn reset_clears_state() {
let mut n = NakedPoc::new(4, 8).unwrap();
n.batch(&[c(101.0, 99.0, 100.0, 1_000.0); 6]);
assert!(n.is_ready());
n.reset();
assert!(!n.is_ready());
assert_eq!(n.value(), None);
assert_eq!(n.naked_count(), 0);
}
#[test]
fn batch_equals_streaming() {
let candles: Vec<Candle> = (0..80)
.map(|i| {
let b = 100.0 + (f64::from(i) * 0.25).sin() * 9.0;
c(b + 1.0, b - 1.0, b, 1_000.0 + f64::from(i))
})
.collect();
let batch = NakedPoc::new(20, 24).unwrap().batch(&candles);
let mut b = NakedPoc::new(20, 24).unwrap();
let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
#[test]
fn flat_session_reports_price() {
// A session with zero high-low span returns the session price directly.
let mut n = NakedPoc::new(2, 4).unwrap();
n.update(c(50.0, 50.0, 50.0, 10.0));
assert_eq!(n.update(c(50.0, 50.0, 50.0, 10.0)), Some(50.0));
}
#[test]
fn zero_volume_session_is_handled() {
// Zero-volume candles are skipped in the histogram; a POC still emits.
let mut n = NakedPoc::new(2, 4).unwrap();
n.update(c(60.0, 40.0, 50.0, 0.0));
assert!(n.update(c(60.0, 40.0, 50.0, 0.0)).is_some());
}
#[test]
fn nearest_of_two_naked_pocs() {
// Two untouched POCs at distant prices accumulate; the one nearest the
// last close is reported (exercises the min-by comparison).
let mut n = NakedPoc::new(2, 4).unwrap();
n.update(c(11.0, 9.0, 10.0, 100.0));
n.update(c(11.0, 9.0, 10.0, 100.0)); // POC near 10
n.update(c(101.0, 99.0, 100.0, 100.0));
let v = n.update(c(101.0, 99.0, 100.0, 100.0)).unwrap(); // POC near 100
assert!(
v > 50.0,
"nearest to close 100 should be the upper POC, got {v}"
);
}
}
@@ -0,0 +1,154 @@
//! OI-to-Volume Ratio — open interest relative to traded volume.
use crate::derivatives::DerivativesTick;
use crate::traits::Indicator;
/// OI-to-Volume Ratio — open interest divided by the tick's total taker volume, a
/// measure of how much position is *held* versus *turned over*.
///
/// ```text
/// OIVR = open_interest / (taker_buy_volume + taker_sell_volume)
/// ```
///
/// A high ratio means open interest dwarfs the volume trading it — positions are
/// being held, not churned (low participation, potential complacency or a coiling
/// market). A low ratio means heavy volume relative to outstanding interest —
/// active churn, often around breakouts or capitulation. Watching the ratio change
/// distinguishes new-money trends (OI and volume both rising) from short-covering
/// or position rolls.
///
/// The ratio is non-negative; a tick with zero taker volume reports `0` rather than
/// dividing by zero. It is stateless — each tick yields one value (no warmup). Each
/// `update` is O(1).
///
/// # Example
///
/// ```
/// use wickra_core::{DerivativesTick, Indicator, OiToVolumeRatio};
///
/// let mut indicator = OiToVolumeRatio::new();
/// let tick = DerivativesTick::new(0.0, 100.0, 100.0, 100.0, 5_000.0, 0.0, 0.0, 400.0, 600.0, 0.0, 0.0, 0).unwrap();
/// let oivr = indicator.update(tick).unwrap();
/// assert!((oivr - 5.0).abs() < 1e-12); // 5000 / (400 + 600)
/// ```
#[derive(Debug, Clone, Default)]
pub struct OiToVolumeRatio {
ready: bool,
}
impl OiToVolumeRatio {
/// Construct a new OI-to-Volume Ratio. The indicator is parameter-free.
#[must_use]
pub const fn new() -> Self {
Self { ready: false }
}
}
impl Indicator for OiToVolumeRatio {
type Input = DerivativesTick;
type Output = f64;
fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
let volume = tick.taker_buy_volume + tick.taker_sell_volume;
let ratio = if volume > 0.0 {
tick.open_interest / volume
} else {
0.0
};
self.ready = true;
Some(ratio)
}
fn reset(&mut self) {
self.ready = false;
}
fn warmup_period(&self) -> usize {
1
}
fn is_ready(&self) -> bool {
self.ready
}
fn name(&self) -> &'static str {
"OiToVolumeRatio"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
use approx::assert_relative_eq;
fn tick(oi: f64, buy: f64, sell: f64) -> DerivativesTick {
DerivativesTick::new_unchecked(
0.0, 100.0, 100.0, 100.0, oi, 0.0, 0.0, buy, sell, 0.0, 0.0, 0,
)
}
#[test]
fn accessors_and_metadata() {
let o = OiToVolumeRatio::new();
assert_eq!(o.warmup_period(), 1);
assert_eq!(o.name(), "OiToVolumeRatio");
assert!(!o.is_ready());
}
#[test]
fn ratio_reference_value() {
let mut o = OiToVolumeRatio::new();
assert_relative_eq!(
o.update(tick(5_000.0, 400.0, 600.0)).unwrap(),
5.0,
epsilon = 1e-12
);
}
#[test]
fn more_volume_lowers_ratio() {
let mut o = OiToVolumeRatio::new();
let held = o.update(tick(5_000.0, 100.0, 100.0)).unwrap();
let churned = o.update(tick(5_000.0, 1_000.0, 1_000.0)).unwrap();
assert!(churned < held);
}
#[test]
fn zero_volume_is_zero() {
let mut o = OiToVolumeRatio::new();
assert_relative_eq!(
o.update(tick(5_000.0, 0.0, 0.0)).unwrap(),
0.0,
epsilon = 1e-12
);
}
#[test]
fn ready_after_first_update() {
let mut o = OiToVolumeRatio::new();
assert!(!o.is_ready());
o.update(tick(5_000.0, 100.0, 100.0));
assert!(o.is_ready());
}
#[test]
fn reset_clears_state() {
let mut o = OiToVolumeRatio::new();
o.update(tick(5_000.0, 100.0, 100.0));
assert!(o.is_ready());
o.reset();
assert!(!o.is_ready());
}
#[test]
fn batch_equals_streaming() {
let ticks: Vec<DerivativesTick> = (0..40)
.map(|i| tick(5_000.0, 100.0 + f64::from(i), 100.0))
.collect();
let batch = OiToVolumeRatio::new().batch(&ticks);
let mut b = OiToVolumeRatio::new();
let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
}
@@ -0,0 +1,221 @@
//! Open-Interest Momentum — the rate of change of open interest over a lookback.
use std::collections::VecDeque;
use crate::derivatives::DerivativesTick;
use crate::error::{Error, Result};
use crate::traits::Indicator;
/// Open-Interest Momentum — the percentage rate of change of open interest over a
/// `period`-tick lookback.
///
/// ```text
/// OIM = 100 · (OI_t OI_{tperiod}) / OI_{tperiod}
/// ```
///
/// Where [`OIDelta`](crate::OIDelta) reports the single-tick change in open
/// interest, OI Momentum measures the trend in positioning over a window: positive
/// values mean open interest is expanding (new money entering — a position build
/// that fuels the prevailing move), negative values mean it is contracting
/// (positions being closed — deleveraging or short-covering). Read alongside price:
/// rising OI with rising price is a strong new-long trend, while rising price with
/// falling OI is a short-covering rally on borrowed time.
///
/// The output is a percentage and may be negative. A zero base open interest
/// `period` ticks ago reports `0` rather than dividing by zero. The first value
/// lands after `period + 1` inputs. Each `update` is O(1).
///
/// # Example
///
/// ```
/// use wickra_core::{DerivativesTick, Indicator, OpenInterestMomentum};
///
/// let mut indicator = OpenInterestMomentum::new(5).unwrap();
/// let mut last = None;
/// for i in 0..20 {
/// let oi = 1_000.0 + f64::from(i) * 100.0;
/// let tick = DerivativesTick::new(0.0, 100.0, 100.0, 100.0, oi, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
/// last = indicator.update(tick);
/// }
/// assert!(last.unwrap() > 0.0); // expanding OI
/// ```
#[derive(Debug, Clone)]
pub struct OpenInterestMomentum {
period: usize,
window: VecDeque<f64>,
last: Option<f64>,
}
impl OpenInterestMomentum {
/// Construct an OI Momentum over a `period`-tick lookback.
///
/// # Errors
///
/// Returns [`Error::PeriodZero`] if `period == 0`.
pub fn new(period: usize) -> Result<Self> {
if period == 0 {
return Err(Error::PeriodZero);
}
Ok(Self {
period,
window: VecDeque::with_capacity(period + 1),
last: None,
})
}
/// Configured lookback period.
pub const fn period(&self) -> usize {
self.period
}
/// Current value if available.
pub const fn value(&self) -> Option<f64> {
self.last
}
}
impl Indicator for OpenInterestMomentum {
type Input = DerivativesTick;
type Output = f64;
fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
if self.window.len() == self.period + 1 {
self.window.pop_front();
}
self.window.push_back(tick.open_interest);
if self.window.len() < self.period + 1 {
return None;
}
let base = *self.window.front().expect("non-empty");
let current = tick.open_interest;
let oim = if base > 0.0 {
100.0 * (current - base) / base
} else {
0.0
};
self.last = Some(oim);
Some(oim)
}
fn reset(&mut self) {
self.window.clear();
self.last = None;
}
fn warmup_period(&self) -> usize {
self.period + 1
}
fn is_ready(&self) -> bool {
self.last.is_some()
}
fn name(&self) -> &'static str {
"OpenInterestMomentum"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
use approx::assert_relative_eq;
fn tick(oi: f64) -> DerivativesTick {
DerivativesTick::new_unchecked(
0.0, 100.0, 100.0, 100.0, oi, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0,
)
}
#[test]
fn rejects_zero_period() {
assert!(matches!(
OpenInterestMomentum::new(0),
Err(Error::PeriodZero)
));
}
#[test]
fn accessors_and_metadata() {
let o = OpenInterestMomentum::new(5).unwrap();
assert_eq!(o.period(), 5);
assert_eq!(o.warmup_period(), 6);
assert_eq!(o.name(), "OpenInterestMomentum");
assert!(!o.is_ready());
assert_eq!(o.value(), None);
}
#[test]
fn first_emission_at_warmup_period() {
let mut o = OpenInterestMomentum::new(3).unwrap();
let ticks: Vec<DerivativesTick> = (0..6)
.map(|i| tick(1_000.0 + f64::from(i) * 100.0))
.collect();
let out = o.batch(&ticks);
for v in out.iter().take(3) {
assert!(v.is_none());
}
assert!(out[3].is_some());
}
#[test]
fn reference_value() {
// period 2: OI 1000 -> 1200 over the window -> +20%.
let mut o = OpenInterestMomentum::new(2).unwrap();
let out = o.batch(&[tick(1_000.0), tick(1_100.0), tick(1_200.0)]);
assert_relative_eq!(out[2].unwrap(), 20.0, epsilon = 1e-9);
}
#[test]
fn expanding_oi_is_positive() {
let mut o = OpenInterestMomentum::new(5).unwrap();
let ticks: Vec<DerivativesTick> = (0..20)
.map(|i| tick(1_000.0 + f64::from(i) * 100.0))
.collect();
let last = o.batch(&ticks).into_iter().flatten().last().unwrap();
assert!(last > 0.0);
}
#[test]
fn contracting_oi_is_negative() {
let mut o = OpenInterestMomentum::new(5).unwrap();
let ticks: Vec<DerivativesTick> = (0..20)
.map(|i| tick(3_000.0 - f64::from(i) * 100.0))
.collect();
let last = o.batch(&ticks).into_iter().flatten().last().unwrap();
assert!(last < 0.0);
}
#[test]
fn zero_base_is_zero() {
let mut o = OpenInterestMomentum::new(2).unwrap();
let out = o.batch(&[tick(0.0), tick(100.0), tick(200.0)]);
assert_relative_eq!(out[2].unwrap(), 0.0, epsilon = 1e-12);
}
#[test]
fn reset_clears_state() {
let mut o = OpenInterestMomentum::new(3).unwrap();
o.batch(
&(0..10)
.map(|i| tick(1_000.0 + f64::from(i) * 50.0))
.collect::<Vec<_>>(),
);
assert!(o.is_ready());
o.reset();
assert!(!o.is_ready());
assert_eq!(o.value(), None);
assert_eq!(o.update(tick(1_000.0)), None);
}
#[test]
fn batch_equals_streaming() {
let ticks: Vec<DerivativesTick> = (0..80)
.map(|i| tick(1_000.0 + (f64::from(i) * 0.25).sin() * 300.0))
.collect();
let batch = OpenInterestMomentum::new(10).unwrap().batch(&ticks);
let mut b = OpenInterestMomentum::new(10).unwrap();
let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
}
@@ -0,0 +1,139 @@
//! Perpetual Premium Index — the perp mark price relative to spot.
use crate::derivatives::DerivativesTick;
use crate::traits::Indicator;
/// Perpetual Premium Index — the perpetual's mark price relative to the spot index
/// it tracks, as a fraction.
///
/// ```text
/// premium = (mark_price index_price) / index_price
/// ```
///
/// A perpetual swap is pegged to spot by the funding mechanism, but it can still
/// trade at a premium (above spot) or discount (below). A positive premium signals
/// net long demand willing to pay up to hold the perp — bullish positioning, and
/// the proximate driver of positive funding; a negative premium signals the
/// reverse. Sustained extremes flag crowded positioning ripe for a funding-driven
/// mean reversion.
///
/// The output is centred on zero and dimensionless (a fraction; multiply by `100`
/// for percent). `index_price` is validated strictly positive on the tick, so the
/// division is always defined. It is stateless — each tick yields one value (no
/// warmup). Each `update` is O(1).
///
/// # Example
///
/// ```
/// use wickra_core::{DerivativesTick, Indicator, PerpetualPremiumIndex};
///
/// let mut indicator = PerpetualPremiumIndex::new();
/// // Mark 101 vs index 100 -> +1% premium.
/// let tick = DerivativesTick::new(0.0, 101.0, 100.0, 101.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
/// let premium = indicator.update(tick).unwrap();
/// assert!((premium - 0.01).abs() < 1e-12);
/// ```
#[derive(Debug, Clone, Default)]
pub struct PerpetualPremiumIndex {
ready: bool,
}
impl PerpetualPremiumIndex {
/// Construct a new Perpetual Premium Index. The indicator is parameter-free.
#[must_use]
pub const fn new() -> Self {
Self { ready: false }
}
}
impl Indicator for PerpetualPremiumIndex {
type Input = DerivativesTick;
type Output = f64;
fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
let premium = (tick.mark_price - tick.index_price) / tick.index_price;
self.ready = true;
Some(premium)
}
fn reset(&mut self) {
self.ready = false;
}
fn warmup_period(&self) -> usize {
1
}
fn is_ready(&self) -> bool {
self.ready
}
fn name(&self) -> &'static str {
"PerpetualPremiumIndex"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
use approx::assert_relative_eq;
fn tick(mark: f64, index: f64) -> DerivativesTick {
DerivativesTick::new_unchecked(0.0, mark, index, mark, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0)
}
#[test]
fn accessors_and_metadata() {
let p = PerpetualPremiumIndex::new();
assert_eq!(p.warmup_period(), 1);
assert_eq!(p.name(), "PerpetualPremiumIndex");
assert!(!p.is_ready());
}
#[test]
fn premium_reference_value() {
let mut p = PerpetualPremiumIndex::new();
assert_relative_eq!(p.update(tick(101.0, 100.0)).unwrap(), 0.01, epsilon = 1e-12);
}
#[test]
fn discount_is_negative() {
let mut p = PerpetualPremiumIndex::new();
assert!(p.update(tick(99.0, 100.0)).unwrap() < 0.0);
}
#[test]
fn at_par_is_zero() {
let mut p = PerpetualPremiumIndex::new();
assert_relative_eq!(p.update(tick(100.0, 100.0)).unwrap(), 0.0, epsilon = 1e-12);
}
#[test]
fn ready_after_first_update() {
let mut p = PerpetualPremiumIndex::new();
assert!(!p.is_ready());
p.update(tick(100.0, 100.0));
assert!(p.is_ready());
}
#[test]
fn reset_clears_state() {
let mut p = PerpetualPremiumIndex::new();
p.update(tick(101.0, 100.0));
assert!(p.is_ready());
p.reset();
assert!(!p.is_ready());
}
#[test]
fn batch_equals_streaming() {
let ticks: Vec<DerivativesTick> = (0..40)
.map(|i| tick(100.0 + (f64::from(i) * 0.3).sin(), 100.0))
.collect();
let batch = PerpetualPremiumIndex::new().batch(&ticks);
let mut b = PerpetualPremiumIndex::new();
let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
}
@@ -0,0 +1,285 @@
//! Profile Shape — classifies the volume profile as b-shape, P-shape, or D/normal.
use std::collections::VecDeque;
use crate::error::{Error, Result};
use crate::ohlcv::Candle;
use crate::traits::Indicator;
/// Profile Shape — classifies a rolling volume profile by where its point of
/// control (POC) sits within the range: `b`, `P`, or `D` (normal).
///
/// ```text
/// build a `bins`-bucket volume profile over the last `period` candles
/// poc_idx = bin with the most volume
/// +1 P-shape : POC in the upper third (heavy top, thin tail down) — short-covering / accumulation
/// 1 b-shape : POC in the lower third (heavy bottom, thin tail up) — long-liquidation / distribution
/// 0 D/normal: POC in the middle third (balanced bell)
/// ```
///
/// Market Profile readers classify the day's shape by the location of the heaviest
/// trading. A **P-shape** (control high, a thin tail beneath) typically marks
/// short-covering or the start of accumulation; a **b-shape** (control low, thin
/// tail above) marks long liquidation or distribution; a **D-shape** is a balanced,
/// two-sided day. Reducing the profile to this three-way code gives a compact,
/// streaming read of market posture.
///
/// The output is `+1` / `0` / `1`. The first value lands after `period` candles;
/// each `update` rebuilds the profile in O(`period · bins`).
///
/// # Example
///
/// ```
/// use wickra_core::{Candle, Indicator, ProfileShape};
///
/// let mut indicator = ProfileShape::new(20, 24).unwrap();
/// let mut last = None;
/// for i in 0..40 {
/// let base = 100.0 + (f64::from(i) * 0.3).sin() * 5.0;
/// let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
/// last = indicator.update(c);
/// }
/// assert!(last.is_some());
/// ```
#[derive(Debug, Clone)]
pub struct ProfileShape {
period: usize,
bins: usize,
window: VecDeque<Candle>,
last: Option<f64>,
}
impl ProfileShape {
/// Construct a Profile Shape classifier.
///
/// # Errors
///
/// Returns [`Error::PeriodZero`] if `period` is zero, or
/// [`Error::InvalidPeriod`] if `bins < 3` (the three-way split needs three
/// zones).
pub fn new(period: usize, bins: usize) -> Result<Self> {
if period == 0 {
return Err(Error::PeriodZero);
}
if bins < 3 {
return Err(Error::InvalidPeriod {
message: "profile shape needs bins >= 3",
});
}
Ok(Self {
period,
bins,
window: VecDeque::with_capacity(period),
last: None,
})
}
/// Configured `(period, bins)`.
pub const fn params(&self) -> (usize, usize) {
(self.period, self.bins)
}
/// Current value if available.
pub const fn value(&self) -> Option<f64> {
self.last
}
#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
fn poc_index(&self) -> usize {
let mut low = f64::INFINITY;
let mut high = f64::NEG_INFINITY;
for c in &self.window {
low = low.min(c.low);
high = high.max(c.high);
}
let mut hist = vec![0.0; self.bins];
let span = high - low;
if span > 0.0 {
let width = span / self.bins as f64;
for c in &self.window {
if c.volume == 0.0 {
continue;
}
let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
let share = c.volume / (hi_idx - lo_idx + 1) as f64;
for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
*bin += share;
}
}
}
let mut poc_idx = 0;
let mut poc_vol = f64::NEG_INFINITY;
for (idx, &vol) in hist.iter().enumerate() {
if vol > poc_vol {
poc_vol = vol;
poc_idx = idx;
}
}
poc_idx
}
}
impl Indicator for ProfileShape {
type Input = Candle;
type Output = f64;
fn update(&mut self, candle: Candle) -> Option<f64> {
if self.window.len() == self.period {
self.window.pop_front();
}
self.window.push_back(candle);
if self.window.len() < self.period {
return None;
}
let poc = self.poc_index();
let lower = self.bins / 3;
let upper = self.bins - self.bins / 3;
let shape = if poc >= upper {
1.0
} else if poc < lower {
-1.0
} else {
0.0
};
self.last = Some(shape);
Some(shape)
}
fn reset(&mut self) {
self.window.clear();
self.last = None;
}
fn warmup_period(&self) -> usize {
self.period
}
fn is_ready(&self) -> bool {
self.last.is_some()
}
fn name(&self) -> &'static str {
"ProfileShape"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
fn c(high: f64, low: f64, volume: f64) -> Candle {
Candle::new_unchecked(
f64::midpoint(high, low),
high,
low,
f64::midpoint(high, low),
volume,
0,
)
}
#[test]
fn rejects_invalid_params() {
assert!(matches!(ProfileShape::new(0, 24), Err(Error::PeriodZero)));
assert!(matches!(
ProfileShape::new(20, 2),
Err(Error::InvalidPeriod { .. })
));
}
#[test]
fn accessors_and_metadata() {
let p = ProfileShape::new(20, 24).unwrap();
assert_eq!(p.params(), (20, 24));
assert_eq!(p.warmup_period(), 20);
assert_eq!(p.name(), "ProfileShape");
assert!(!p.is_ready());
assert_eq!(p.value(), None);
}
#[test]
fn first_emission_at_warmup_period() {
let mut p = ProfileShape::new(4, 9).unwrap();
let candles: Vec<Candle> = (0..6).map(|_| c(110.0, 90.0, 1_000.0)).collect();
let out = p.batch(&candles);
for v in out.iter().take(3) {
assert!(v.is_none());
}
assert!(out[3].is_some());
}
#[test]
fn heavy_top_is_p_shape() {
// Volume concentrated near the top of the range -> P-shape -> +1.
let mut p = ProfileShape::new(6, 9).unwrap();
let mut candles: Vec<Candle> = (0..5).map(|_| c(119.0, 117.0, 5_000.0)).collect();
candles.push(c(119.0, 80.0, 50.0)); // a thin tail down to 80
let last = p.batch(&candles).into_iter().flatten().last().unwrap();
assert_eq!(last, 1.0);
}
#[test]
fn heavy_bottom_is_b_shape() {
let mut p = ProfileShape::new(6, 9).unwrap();
let mut candles: Vec<Candle> = (0..5).map(|_| c(83.0, 81.0, 5_000.0)).collect();
candles.push(c(120.0, 81.0, 50.0)); // a thin tail up to 120
let last = p.batch(&candles).into_iter().flatten().last().unwrap();
assert_eq!(last, -1.0);
}
#[test]
fn balanced_is_d_shape() {
// Volume concentrated in the middle -> D/normal -> 0.
let mut p = ProfileShape::new(6, 9).unwrap();
let mut candles: Vec<Candle> = (0..5).map(|_| c(101.0, 99.0, 5_000.0)).collect();
candles.push(c(120.0, 80.0, 50.0)); // thin tails both ways, POC in the middle
let last = p.batch(&candles).into_iter().flatten().last().unwrap();
assert_eq!(last, 0.0);
}
#[test]
fn reset_clears_state() {
let mut p = ProfileShape::new(4, 9).unwrap();
p.batch(&[c(110.0, 90.0, 1_000.0); 6]);
assert!(p.is_ready());
p.reset();
assert!(!p.is_ready());
assert_eq!(p.value(), None);
assert_eq!(p.update(c(110.0, 90.0, 1_000.0)), None);
}
#[test]
fn batch_equals_streaming() {
let candles: Vec<Candle> = (0..80)
.map(|i| {
c(
110.0 + (f64::from(i) * 0.25).sin() * 9.0,
90.0,
1_000.0 + f64::from(i),
)
})
.collect();
let batch = ProfileShape::new(20, 24).unwrap().batch(&candles);
let mut b = ProfileShape::new(20, 24).unwrap();
let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
#[test]
fn flat_window_is_handled() {
// Zero high-low span skips the histogram pass entirely.
let mut p = ProfileShape::new(2, 4).unwrap();
p.update(c(50.0, 50.0, 10.0));
assert!(p.update(c(50.0, 50.0, 10.0)).is_some());
}
#[test]
fn zero_volume_window_is_handled() {
// Non-flat window of zero-volume candles hits the skip path.
let mut p = ProfileShape::new(2, 4).unwrap();
p.update(c(60.0, 40.0, 0.0));
assert!(p.update(c(60.0, 40.0, 0.0)).is_some());
}
}
@@ -0,0 +1,253 @@
//! Single Prints — count of price levels touched by exactly one bar (low acceptance).
use std::collections::VecDeque;
use crate::error::{Error, Result};
use crate::ohlcv::Candle;
use crate::traits::Indicator;
/// Single Prints — the number of price levels (bins) in the rolling profile that
/// were touched by **exactly one** bar, marking zones of low acceptance / fast
/// movement.
///
/// ```text
/// for each of `bins` price levels over the last `period` candles:
/// touches = number of bars whose high-low range covers that level
/// SinglePrints = count of levels with touches == 1
/// ```
///
/// In Market Profile a "single print" is a price the market traded through so
/// quickly that only one time-period printed there — a footprint of an aggressive,
/// one-sided move with little two-way trade. Single prints often act as support or
/// resistance on a retest (the imbalance gets "repaired") and mark the edges of
/// rapid moves. Counting them per profile gives a streaming gauge of how much of
/// the recent range was traversed without acceptance: a high count means a fast,
/// trending, low-rotation market; a low count means a balanced, well-traded range.
///
/// The output is a non-negative count. The first value lands after `period`
/// candles; each `update` rebuilds the touch histogram in O(`period · bins`).
///
/// # Example
///
/// ```
/// use wickra_core::{Candle, Indicator, SinglePrints};
///
/// let mut indicator = SinglePrints::new(20, 24).unwrap();
/// let mut last = None;
/// for i in 0..40 {
/// let base = 100.0 + f64::from(i); // a one-directional ramp -> many single prints
/// let c = Candle::new(base, base + 0.5, base - 0.5, base, 1_000.0, 0).unwrap();
/// last = indicator.update(c);
/// }
/// assert!(last.is_some());
/// ```
#[derive(Debug, Clone)]
pub struct SinglePrints {
period: usize,
bins: usize,
window: VecDeque<Candle>,
last: Option<f64>,
}
impl SinglePrints {
/// Construct a Single Prints counter.
///
/// # Errors
///
/// Returns [`Error::PeriodZero`] if `period` or `bins` is zero.
pub fn new(period: usize, bins: usize) -> Result<Self> {
if period == 0 || bins == 0 {
return Err(Error::PeriodZero);
}
Ok(Self {
period,
bins,
window: VecDeque::with_capacity(period),
last: None,
})
}
/// Configured `(period, bins)`.
pub const fn params(&self) -> (usize, usize) {
(self.period, self.bins)
}
/// Current value if available.
pub const fn value(&self) -> Option<f64> {
self.last
}
#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
fn count_single_prints(&self) -> usize {
let mut low = f64::INFINITY;
let mut high = f64::NEG_INFINITY;
for c in &self.window {
low = low.min(c.low);
high = high.max(c.high);
}
let span = high - low;
if span <= 0.0 {
return 0;
}
let width = span / self.bins as f64;
let mut touches = vec![0u32; self.bins];
for c in &self.window {
let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
for t in touches.iter_mut().take(hi_idx + 1).skip(lo_idx) {
*t += 1;
}
}
touches.iter().filter(|&&t| t == 1).count()
}
}
impl Indicator for SinglePrints {
type Input = Candle;
type Output = f64;
fn update(&mut self, candle: Candle) -> Option<f64> {
if self.window.len() == self.period {
self.window.pop_front();
}
self.window.push_back(candle);
if self.window.len() < self.period {
return None;
}
let count = self.count_single_prints() as f64;
self.last = Some(count);
Some(count)
}
fn reset(&mut self) {
self.window.clear();
self.last = None;
}
fn warmup_period(&self) -> usize {
self.period
}
fn is_ready(&self) -> bool {
self.last.is_some()
}
fn name(&self) -> &'static str {
"SinglePrints"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
fn c(high: f64, low: f64) -> Candle {
Candle::new_unchecked(
f64::midpoint(high, low),
high,
low,
f64::midpoint(high, low),
1_000.0,
0,
)
}
#[test]
fn rejects_zero_params() {
assert!(matches!(SinglePrints::new(0, 24), Err(Error::PeriodZero)));
assert!(matches!(SinglePrints::new(20, 0), Err(Error::PeriodZero)));
}
#[test]
fn accessors_and_metadata() {
let s = SinglePrints::new(20, 24).unwrap();
assert_eq!(s.params(), (20, 24));
assert_eq!(s.warmup_period(), 20);
assert_eq!(s.name(), "SinglePrints");
assert!(!s.is_ready());
assert_eq!(s.value(), None);
}
#[test]
fn first_emission_at_warmup_period() {
let mut s = SinglePrints::new(4, 8).unwrap();
let candles: Vec<Candle> = (0..6)
.map(|i| c(101.0 + f64::from(i), 99.0 + f64::from(i)))
.collect();
let out = s.batch(&candles);
for v in out.iter().take(3) {
assert!(v.is_none());
}
assert!(out[3].is_some());
}
#[test]
fn flat_range_has_no_single_prints() {
// Every bar covers the same single price -> zero span -> 0.
let mut s = SinglePrints::new(4, 8).unwrap();
let last = s
.batch(&[c(100.0, 100.0); 6])
.into_iter()
.flatten()
.last()
.unwrap();
assert_eq!(last, 0.0);
}
#[test]
fn ramp_has_many_single_prints() {
// A one-directional ramp visits most levels exactly once.
let mut s = SinglePrints::new(10, 24).unwrap();
let candles: Vec<Candle> = (0..10)
.map(|i| c(100.5 + f64::from(i), 99.5 + f64::from(i)))
.collect();
let last = s.batch(&candles).into_iter().flatten().last().unwrap();
assert!(
last > 0.0,
"a ramp should produce single prints, got {last}"
);
}
#[test]
fn output_non_negative() {
let mut s = SinglePrints::new(14, 24).unwrap();
for v in s
.batch(
&(0..60)
.map(|i| c(110.0 + (f64::from(i) * 0.3).sin() * 8.0, 90.0))
.collect::<Vec<_>>(),
)
.into_iter()
.flatten()
{
assert!(v >= 0.0);
}
}
#[test]
fn reset_clears_state() {
let mut s = SinglePrints::new(4, 8).unwrap();
s.batch(
&(0..6)
.map(|i| c(101.0 + f64::from(i), 99.0 + f64::from(i)))
.collect::<Vec<_>>(),
);
assert!(s.is_ready());
s.reset();
assert!(!s.is_ready());
assert_eq!(s.value(), None);
assert_eq!(s.update(c(101.0, 99.0)), None);
}
#[test]
fn batch_equals_streaming() {
let candles: Vec<Candle> = (0..80)
.map(|i| c(110.0 + (f64::from(i) * 0.25).sin() * 9.0, 90.0))
.collect();
let batch = SinglePrints::new(20, 24).unwrap().batch(&candles);
let mut b = SinglePrints::new(20, 24).unwrap();
let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
assert_eq!(batch, streamed);
}
}
+73 -70
View File
@@ -72,36 +72,38 @@ pub use indicators::{
ChaikinVolatility, ChandeKrollStop, ChandeKrollStopOutput, ChandelierExit,
ChandelierExitOutput, ChoppinessIndex, ClassicPivots, ClassicPivotsOutput, CloseVsOpen,
ClosingMarubozu, Cmo, CoefficientOfVariation, Cointegration, CointegrationOutput,
ConcealingBabySwallow, ConditionalValueAtRisk, ConnorsRsi, Coppock, CorrelationTrendIndicator,
Counterattack, Crab, CumulativeVolumeDelta, CumulativeVolumeIndex, CupAndHandle,
CyberneticCycle, Cypher, DayOfWeekProfile, DayOfWeekProfileOutput, Decycler,
DecyclerOscillator, Dema, DemandIndex, DemarkPivots, DemarkPivotsOutput, DepthSlope,
DerivativeOscillator, DetrendedStdDev, DisparityIndex, DistanceSsd, Doji, DojiStar, Donchian,
DonchianOutput, DonchianStop, DonchianStopOutput, DoubleBollinger, DoubleBollingerOutput,
DoubleTopBottom, DownsideGapThreeMethods, Dpo, DragonflyDoji, DrawdownDuration, DumplingTop,
Dx, DynamicMomentumIndex, EaseOfMovement, EffectiveSpread, EhlersStochastic, Ehma,
ElderImpulse, ElderRay, ElderRayOutput, ElderSafeZone, ElderSafeZoneOutput, Ema,
EmpiricalModeDecomposition, Engulfing, Equivolume, EquivolumeOutput, EvenBetterSinewave,
EveningDojiStar, Evwma, EwmaVolatility, Expectancy, FallingThreeMethods, Fama, FibArcs,
FibArcsOutput, FibChannel, FibChannelOutput, FibConfluence, FibConfluenceOutput, FibExtension,
FibExtensionOutput, FibFan, FibFanOutput, FibProjection, FibProjectionOutput, FibRetracement,
FibRetracementOutput, FibTimeZones, FibTimeZonesOutput, FibonacciPivots, FibonacciPivotsOutput,
FisherRsi, FisherTransform, FlagPennant, Footprint, FootprintOutput, ForceIndex,
FractalChaosBands, FractalChaosBandsOutput, Frama, FryPanBottom, FundingBasis, FundingRate,
FundingRateMean, FundingRateZScore, GainLossRatio, GapSideBySideWhite, Garch11,
GarmanKlassVolatility, Gartley, GatorOscillator, GatorOscillatorOutput, GeneralizedDema,
GeometricMa, GoldenPocket, GoldenPocketOutput, GrangerCausality, GravestoneDoji, Hammer,
HangingMan, Harami, HaramiCross, HasbrouckInformationShare, HeadAndShoulders, HeikinAshi,
HeikinAshiOscillator, HeikinAshiOutput, HiLoActivator, HighLowIndex, HighLowRange, HighWave,
HighpassFilter, Hikkake, HikkakeModified, HilbertDominantCycle, HistoricalVolatility, Hma,
HoltWinters, HomingPigeon, HtDcPhase, HtPhasor, HtPhasorOutput, HtTrendMode, HurstChannel,
HurstChannelOutput, HurstExponent, Ichimoku, IchimokuOutput, IdenticalThreeCrows, InNeck,
Inertia, InformationRatio, InitialBalance, InitialBalanceOutput, InstantaneousTrendline,
IntradayIntensity, IntradayMomentumIndex, IntradayVolatilityProfile,
IntradayVolatilityProfileOutput, InverseFisherTransform, InvertedHammer, JarqueBera, Jma,
JumpIndicator, KagiBars, KalmanHedgeRatio, KalmanHedgeRatioOutput, Kama, KaseDevStop,
KaseDevStopOutput, KasePermissionStochastic, KasePermissionStochasticOutput, KellyCriterion,
Keltner, KeltnerOutput, KendallTau, Kicking, KickingByLength, Kst, KstOutput, Kurtosis, Kvo,
CompositeProfile, CompositeProfileOutput, ConcealingBabySwallow, ConditionalValueAtRisk,
ConnorsRsi, Coppock, CorrelationTrendIndicator, Counterattack, Crab, CumulativeVolumeDelta,
CumulativeVolumeIndex, CupAndHandle, CyberneticCycle, Cypher, DayOfWeekProfile,
DayOfWeekProfileOutput, Decycler, DecyclerOscillator, Dema, DemandIndex, DemarkPivots,
DemarkPivotsOutput, DepthSlope, DerivativeOscillator, DetrendedStdDev, DisparityIndex,
DistanceSsd, Doji, DojiStar, Donchian, DonchianOutput, DonchianStop, DonchianStopOutput,
DoubleBollinger, DoubleBollingerOutput, DoubleTopBottom, DownsideGapThreeMethods, Dpo,
DragonflyDoji, DrawdownDuration, DumplingTop, Dx, DynamicMomentumIndex, EaseOfMovement,
EffectiveSpread, EhlersStochastic, Ehma, ElderImpulse, ElderRay, ElderRayOutput, ElderSafeZone,
ElderSafeZoneOutput, Ema, EmpiricalModeDecomposition, Engulfing, Equivolume, EquivolumeOutput,
EstimatedLeverageRatio, EvenBetterSinewave, EveningDojiStar, Evwma, EwmaVolatility, Expectancy,
FallingThreeMethods, Fama, FibArcs, FibArcsOutput, FibChannel, FibChannelOutput, FibConfluence,
FibConfluenceOutput, FibExtension, FibExtensionOutput, FibFan, FibFanOutput, FibProjection,
FibProjectionOutput, FibRetracement, FibRetracementOutput, FibTimeZones, FibTimeZonesOutput,
FibonacciPivots, FibonacciPivotsOutput, FisherRsi, FisherTransform, FlagPennant, Footprint,
FootprintOutput, ForceIndex, FractalChaosBands, FractalChaosBandsOutput, Frama, FryPanBottom,
FundingBasis, FundingImpliedApr, FundingRate, FundingRateMean, FundingRateZScore,
GainLossRatio, GapSideBySideWhite, Garch11, GarmanKlassVolatility, Gartley, GatorOscillator,
GatorOscillatorOutput, GeneralizedDema, GeometricMa, GoldenPocket, GoldenPocketOutput,
GrangerCausality, GravestoneDoji, Hammer, HangingMan, Harami, HaramiCross,
HasbrouckInformationShare, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator,
HeikinAshiOutput, HiLoActivator, HighLowIndex, HighLowRange, HighLowVolumeNodes,
HighLowVolumeNodesOutput, HighWave, HighpassFilter, Hikkake, HikkakeModified,
HilbertDominantCycle, HistoricalVolatility, Hma, HoltWinters, HomingPigeon, HtDcPhase,
HtPhasor, HtPhasorOutput, HtTrendMode, HurstChannel, HurstChannelOutput, HurstExponent,
Ichimoku, IchimokuOutput, IdenticalThreeCrows, InNeck, Inertia, InformationRatio,
InitialBalance, InitialBalanceOutput, InstantaneousTrendline, IntradayIntensity,
IntradayMomentumIndex, IntradayVolatilityProfile, IntradayVolatilityProfileOutput,
InverseFisherTransform, InvertedHammer, JarqueBera, Jma, JumpIndicator, KagiBars,
KalmanHedgeRatio, KalmanHedgeRatioOutput, Kama, KaseDevStop, KaseDevStopOutput,
KasePermissionStochastic, KasePermissionStochasticOutput, KellyCriterion, Keltner,
KeltnerOutput, KendallTau, Kicking, KickingByLength, Kst, KstOutput, Kurtosis, Kvo,
KylesLambda, LadderBottom, LaguerreRsi, LeadLagCrossCorrelation, LeadLagCrossCorrelationOutput,
LinRegAngle, LinRegChannel, LinRegChannelOutput, LinRegIntercept, LinRegSlope,
LinearRegression, LiquidationFeatures, LiquidationFeaturesOutput, LogReturn, LongLeggedDoji,
@@ -111,46 +113,47 @@ pub use indicators::{
McGinleyDynamic, MedianAbsoluteDeviation, MedianChannel, MedianChannelOutput, MedianMa,
MedianPrice, Mfi, Microprice, MidPoint, MidPrice, MinusDi, MinusDm, ModifiedMaStop,
ModifiedMaStopOutput, Mom, MorningDojiStar, MorningEveningStar, MurreyMathLines,
MurreyMathLinesOutput, Natr, NewHighsNewLows, NewPriceLines, Nrtr, NrtrOutput, Nvi,
OIPriceDivergence, OIWeighted, Obv, OmegaRatio, OnNeck, OpenInterestDelta, OpeningMarubozu,
OpeningRange, OpeningRangeOutput, OrderBookImbalanceFull, OrderBookImbalanceTop1,
OrderBookImbalanceTopN, OrderFlowImbalance, OuHalfLife, OvernightGap, OvernightIntradayReturn,
OvernightIntradayReturnOutput, PainIndex, PairSpreadZScore, PairwiseBeta, ParkinsonVolatility,
PearsonCorrelation, PercentAboveMa, PercentB, PercentageTrailingStop, Pgo, PiercingDarkCloud,
Pin, PivotReversal, PlusDi, PlusDm, Pmo, PointAndFigureBars, PolarizedFractalEfficiency, Ppo,
PpoHistogram, ProfitFactor, ProjectionBands, ProjectionBandsOutput, ProjectionOscillator, Psar,
Pvi, Qqe, QqeOutput, Qstick, QuartileBands, QuartileBandsOutput, QuotedSpread, RSquared,
RealizedSpread, RealizedVolatility, RecoveryFactor, RectangleRange, Reflex, RegimeLabel,
RelativeStrengthAB, RelativeStrengthOutput, RenkoBars, RenkoTrailingStop, RickshawMan,
RisingThreeMethods, Rmi, Roc, Rocp, Rocr, Rocr100, RogersSatchellVolatility, RollMeasure,
RollingCorrelation, RollingCovariance, RollingIqr, RollingMinMaxScaler, RollingPercentileRank,
RollingQuantile, RollingVwap, RoofingFilter, Rsi, Rsx, Rvi, RviVolatility, Rwi, RwiOutput,
SampleEntropy, SarExt, SeasonalZScore, SeparatingLines, SessionHighLow, SessionHighLowOutput,
SessionRange, SessionRangeOutput, SessionVwap, ShannonEntropy, Shark, SharpeRatio,
ShootingStar, ShortLine, SignedVolume, SineWave, SineWeightedMa, Skewness, Sma, Smi, Smma,
SmoothedHeikinAshi, SmoothedHeikinAshiOutput, SortinoRatio, SpearmanCorrelation, SpinningTop,
SpreadAr1Coefficient, SpreadBollingerBands, SpreadBollingerBandsOutput, SpreadHurst,
StalledPattern, StandardError, StandardErrorBands, StandardErrorBandsOutput, StarcBands,
StarcBandsOutput, Stc, StdDev, StepTrailingStop, StickSandwich, StochRsi, Stochastic,
StochasticCci, StochasticOutput, SuperSmoother, SuperTrend, SuperTrendOutput,
TakerBuySellRatio, Takuri, TasukiGap, TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown,
TdDWave, TdDeMarker, TdDifferential, TdLines, TdLinesOutput, TdMovingAverage,
TdMovingAverageOutput, TdOpen, TdPressure, TdPropulsion, TdRangeProjection,
TdRangeProjectionOutput, TdRei, TdRiskLevel, TdRiskLevelOutput, TdSequential,
TdSequentialOutput, TdSetup, TdTrap, Tema, TermStructureBasis, ThreeDrives, ThreeInside,
ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows, ThreeStarsInSouth,
Thrusting, TickIndex, Tii, TimeBasedStop, TimeOfDayReturnProfile, TimeOfDayReturnProfileOutput,
TowerTopBottom, TpoProfile, TpoProfileOutput, TradeImbalance, TradeSignAutocorrelation,
TradeVolumeIndex, TrendLabel, TrendStrengthIndex, Trendflex, TreynorRatio, Triangle, Trima,
Trin, TripleTopBottom, Tristar, Trix, TrueRange, Tsf, TsfOscillator, Tsi, Tsv, TtmSqueeze,
TtmSqueezeOutput, TtmTrend, TurnOfMonth, Tweezer, TwiggsMoneyFlow, TwoCrows, TypicalPrice,
UlcerIndex, UltimateOscillator, UniqueThreeRiver, UniversalOscillator, UpDownVolumeRatio,
UpsideGapThreeMethods, UpsideGapTwoCrows, ValueArea, ValueAreaOutput, ValueAtRisk, Variance,
VarianceRatio, VerticalHorizontalFilter, Vidya, VolatilityCone, VolatilityConeOutput,
VolatilityOfVolatility, VolatilityRatio, VoltyStop, VolumeByTimeProfile,
VolumeByTimeProfileOutput, VolumeOscillator, VolumePriceTrend, VolumeProfile,
VolumeProfileOutput, VolumeRsi, VolumeWeightedMacd, VolumeWeightedMacdOutput, VolumeWeightedSr,
VolumeWeightedSrOutput, Vortex, VortexOutput, Vpin, Vwap, VwapStdDevBands,
MurreyMathLinesOutput, NakedPoc, Natr, NewHighsNewLows, NewPriceLines, Nrtr, NrtrOutput, Nvi,
OIPriceDivergence, OIWeighted, Obv, OiToVolumeRatio, OmegaRatio, OnNeck, OpenInterestDelta,
OpenInterestMomentum, OpeningMarubozu, OpeningRange, OpeningRangeOutput,
OrderBookImbalanceFull, OrderBookImbalanceTop1, OrderBookImbalanceTopN, OrderFlowImbalance,
OuHalfLife, OvernightGap, OvernightIntradayReturn, OvernightIntradayReturnOutput, PainIndex,
PairSpreadZScore, PairwiseBeta, ParkinsonVolatility, PearsonCorrelation, PercentAboveMa,
PercentB, PercentageTrailingStop, PerpetualPremiumIndex, Pgo, PiercingDarkCloud, Pin,
PivotReversal, PlusDi, PlusDm, Pmo, PointAndFigureBars, PolarizedFractalEfficiency, Ppo,
PpoHistogram, ProfileShape, ProfitFactor, ProjectionBands, ProjectionBandsOutput,
ProjectionOscillator, Psar, Pvi, Qqe, QqeOutput, Qstick, QuartileBands, QuartileBandsOutput,
QuotedSpread, RSquared, RealizedSpread, RealizedVolatility, RecoveryFactor, RectangleRange,
Reflex, RegimeLabel, RelativeStrengthAB, RelativeStrengthOutput, RenkoBars, RenkoTrailingStop,
RickshawMan, RisingThreeMethods, Rmi, Roc, Rocp, Rocr, Rocr100, RogersSatchellVolatility,
RollMeasure, RollingCorrelation, RollingCovariance, RollingIqr, RollingMinMaxScaler,
RollingPercentileRank, RollingQuantile, RollingVwap, RoofingFilter, Rsi, Rsx, Rvi,
RviVolatility, Rwi, RwiOutput, SampleEntropy, SarExt, SeasonalZScore, SeparatingLines,
SessionHighLow, SessionHighLowOutput, SessionRange, SessionRangeOutput, SessionVwap,
ShannonEntropy, Shark, SharpeRatio, ShootingStar, ShortLine, SignedVolume, SineWave,
SineWeightedMa, SinglePrints, Skewness, Sma, Smi, Smma, SmoothedHeikinAshi,
SmoothedHeikinAshiOutput, SortinoRatio, SpearmanCorrelation, SpinningTop, SpreadAr1Coefficient,
SpreadBollingerBands, SpreadBollingerBandsOutput, SpreadHurst, StalledPattern, StandardError,
StandardErrorBands, StandardErrorBandsOutput, StarcBands, StarcBandsOutput, Stc, StdDev,
StepTrailingStop, StickSandwich, StochRsi, Stochastic, StochasticCci, StochasticOutput,
SuperSmoother, SuperTrend, SuperTrendOutput, TakerBuySellRatio, Takuri, TasukiGap,
TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown, TdDWave, TdDeMarker, TdDifferential,
TdLines, TdLinesOutput, TdMovingAverage, TdMovingAverageOutput, TdOpen, TdPressure,
TdPropulsion, TdRangeProjection, TdRangeProjectionOutput, TdRei, TdRiskLevel,
TdRiskLevelOutput, TdSequential, TdSequentialOutput, TdSetup, TdTrap, Tema, TermStructureBasis,
ThreeDrives, ThreeInside, ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows,
ThreeStarsInSouth, Thrusting, TickIndex, Tii, TimeBasedStop, TimeOfDayReturnProfile,
TimeOfDayReturnProfileOutput, TowerTopBottom, TpoProfile, TpoProfileOutput, TradeImbalance,
TradeSignAutocorrelation, TradeVolumeIndex, TrendLabel, TrendStrengthIndex, Trendflex,
TreynorRatio, Triangle, Trima, Trin, TripleTopBottom, Tristar, Trix, TrueRange, Tsf,
TsfOscillator, Tsi, Tsv, TtmSqueeze, TtmSqueezeOutput, TtmTrend, TurnOfMonth, Tweezer,
TwiggsMoneyFlow, TwoCrows, TypicalPrice, UlcerIndex, UltimateOscillator, UniqueThreeRiver,
UniversalOscillator, UpDownVolumeRatio, UpsideGapThreeMethods, UpsideGapTwoCrows, ValueArea,
ValueAreaOutput, ValueAtRisk, Variance, VarianceRatio, VerticalHorizontalFilter, Vidya,
VolatilityCone, VolatilityConeOutput, VolatilityOfVolatility, VolatilityRatio, VoltyStop,
VolumeByTimeProfile, VolumeByTimeProfileOutput, VolumeOscillator, VolumePriceTrend,
VolumeProfile, VolumeProfileOutput, VolumeRsi, VolumeWeightedMacd, VolumeWeightedMacdOutput,
VolumeWeightedSr, VolumeWeightedSrOutput, Vortex, VortexOutput, Vpin, Vwap, VwapStdDevBands,
VwapStdDevBandsOutput, Vwma, Vzo, Wad, WavePm, WaveTrend, WaveTrendOutput, Wedge,
WeightedClose, WickRatio, WilliamsFractals, WilliamsFractalsOutput, WilliamsR, WinRate, Wma,
WoodiePivots, WoodiePivotsOutput, YangZhangVolatility, YoyoExit, ZScore, ZeroLagMacd,
+1 -1
View File
@@ -8,7 +8,7 @@ That includes:
[Python](https://docs.wickra.org/Quickstart-Python),
[Node](https://docs.wickra.org/Quickstart-Node), and
[WASM](https://docs.wickra.org/Quickstart-WASM).
- A per-indicator deep dive for every one of the **488 indicators** across
- A per-indicator deep dive for every one of the **498 indicators** across
the sixteen families (Moving Averages, Momentum Oscillators, Trend &
Directional, Price Oscillators, Volatility & Bands, Bands & Channels,
Trailing Stops, Volume, Price Statistics, Ehlers / Cycle DSP, Pivots &
+7 -7
View File
@@ -17,7 +17,7 @@
},
"../../bindings/node": {
"name": "wickra",
"version": "0.7.0",
"version": "0.7.2",
"license": "MIT OR Apache-2.0",
"devDependencies": {
"@napi-rs/cli": "^2.18.0"
@@ -26,12 +26,12 @@
"node": ">= 18"
},
"optionalDependencies": {
"wickra-darwin-arm64": "0.7.0",
"wickra-darwin-x64": "0.7.0",
"wickra-linux-arm64-gnu": "0.7.0",
"wickra-linux-x64-gnu": "0.7.0",
"wickra-win32-arm64-msvc": "0.7.0",
"wickra-win32-x64-msvc": "0.7.0"
"wickra-darwin-arm64": "0.7.2",
"wickra-darwin-x64": "0.7.2",
"wickra-linux-arm64-gnu": "0.7.2",
"wickra-linux-x64-gnu": "0.7.2",
"wickra-win32-arm64-msvc": "0.7.2",
"wickra-win32-x64-msvc": "0.7.2"
}
},
"node_modules/wickra": {
+6 -1
View File
@@ -22,7 +22,7 @@
//! WeightedClose.
use libfuzzer_sys::fuzz_target;
use wickra_core::{AbandonedBaby, Abcd, AccelerationBands, AcceleratorOscillator, AdOscillator, AdaptiveCci, Adl, AdvanceBlock, Adx, Adxr, Alligator, AnchoredVwap, AndrewsPitchfork, Aroon, AroonOscillator, Atr, AtrBands, AtrRatchet, AtrTrailingStop, AutoFib, AverageDailyRange, AwesomeOscillator, AwesomeOscillatorHistogram, BalanceOfPower, Bat, BatchExt, BeltHold, BetterVolume, BodySizePct, Breakaway, Butterfly, Camarilla, Candle, CandleVolume, Cci, CentralPivotRange, ChaikinMoneyFlow, ChaikinOscillator, ChaikinVolatility, ChandeKrollStop, ChandelierExit, ChoppinessIndex, ClassicPivots, CloseVsOpen, ClosingMarubozu, ConcealingBabySwallow, Counterattack, Crab, CupAndHandle, Cypher, DayOfWeekProfile, DemandIndex, DemarkPivots, Doji, DojiStar, Donchian, DonchianStop, DoubleTopBottom, DownsideGapThreeMethods, DragonflyDoji, DumplingTop, Dx, EaseOfMovement, ElderRay, ElderSafeZone, Engulfing, Equivolume, EveningDojiStar, Evwma, FallingThreeMethods, FibArcs, FibChannel, FibConfluence, FibExtension, FibFan, FibProjection, FibRetracement, FibTimeZones, FibonacciPivots, FlagPennant, ForceIndex, FractalChaosBands, FryPanBottom, GapSideBySideWhite, GarmanKlassVolatility, Gartley, GatorOscillator, GoldenPocket, GravestoneDoji, Hammer, HangingMan, Harami, HaramiCross, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator, HiLoActivator, HighLowRange, HighWave, Hikkake, HikkakeModified, HomingPigeon, HurstChannel, Ichimoku, IdenticalThreeCrows, InNeck, Indicator, Inertia, InitialBalance, IntradayIntensity, IntradayMomentumIndex, IntradayVolatilityProfile, InvertedHammer, KaseDevStop, KasePermissionStochastic, Keltner, Kicking, KickingByLength, Kvo, LadderBottom, LongLeggedDoji, LongLine, MarketFacilitationIndex, Marubozu, MassIndex, MatHold, MatchingLow, AvgPrice, MedianPrice, Mfi, MidPrice, MinusDi, MinusDm, ModifiedMaStop, MorningDojiStar, MorningEveningStar, MurreyMathLines, Natr, NewPriceLines, Nrtr, Nvi, Obv, OnNeck, OpeningMarubozu, OpeningRange, OvernightGap, OvernightIntradayReturn, ParkinsonVolatility, Pgo, PiercingDarkCloud, PivotReversal, PlusDi, PlusDm, ProjectionBands, ProjectionOscillator, Psar, Pvi, Qstick, RectangleRange, RickshawMan, RisingThreeMethods, RogersSatchellVolatility, RollingVwap, Rvi, Rwi, SarExt, SeasonalZScore, SeparatingLines, SessionHighLow, SessionRange, SessionVwap, Shark, ShootingStar, ShortLine, Smi, SmoothedHeikinAshi, SpinningTop, StalledPattern, StarcBands, StickSandwich, Stochastic, StochasticCci, SuperTrend, Takuri, TasukiGap, TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown, TdDWave, TdDeMarker, TdDifferential, TdLines, TdMovingAverage, TdOpen, TdPressure, TdPropulsion, TdRangeProjection, TdRei, TdRiskLevel, TdSequential, TdSetup, TdTrap, ThreeDrives, ThreeInside, ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows, ThreeStarsInSouth, Thrusting, TimeBasedStop, TimeOfDayReturnProfile, TowerTopBottom, TpoProfile, TradeVolumeIndex, Triangle, TripleTopBottom, Tristar, TrueRange, Tsv, TtmSqueeze, TtmTrend, TurnOfMonth, Tweezer, TwiggsMoneyFlow, TwoCrows, TypicalPrice, UltimateOscillator, UniqueThreeRiver, UpsideGapThreeMethods, UpsideGapTwoCrows, ValueArea, VolatilityCone, VolatilityRatio, VoltyStop, VolumeByTimeProfile, VolumeOscillator, VolumePriceTrend, VolumeProfile, VolumeRsi, VolumeWeightedMacd, VolumeWeightedSr, Vortex, Vwap, VwapStdDevBands, Vwma, Vzo, WaveTrend, Wedge, WeightedClose, WickRatio, Wad, WilliamsFractals, WilliamsR, WoodiePivots, YangZhangVolatility, YoyoExit, ZigZag};
use wickra_core::{AbandonedBaby, Abcd, AccelerationBands, AcceleratorOscillator, AdOscillator, AdaptiveCci, Adl, AdvanceBlock, Adx, Adxr, Alligator, AnchoredVwap, AndrewsPitchfork, Aroon, AroonOscillator, Atr, AtrBands, AtrRatchet, AtrTrailingStop, AutoFib, AverageDailyRange, AwesomeOscillator, AwesomeOscillatorHistogram, BalanceOfPower, Bat, BatchExt, BeltHold, BetterVolume, BodySizePct, Breakaway, Butterfly, Camarilla, Candle, CandleVolume, Cci, CentralPivotRange, ChaikinMoneyFlow, ChaikinOscillator, ChaikinVolatility, ChandeKrollStop, ChandelierExit, ChoppinessIndex, ClassicPivots, CloseVsOpen, ClosingMarubozu, CompositeProfile, ConcealingBabySwallow, Counterattack, Crab, CupAndHandle, Cypher, DayOfWeekProfile, DemandIndex, DemarkPivots, Doji, DojiStar, Donchian, DonchianStop, DoubleTopBottom, DownsideGapThreeMethods, DragonflyDoji, DumplingTop, Dx, EaseOfMovement, ElderRay, ElderSafeZone, Engulfing, Equivolume, EveningDojiStar, Evwma, FallingThreeMethods, FibArcs, FibChannel, FibConfluence, FibExtension, FibFan, FibProjection, FibRetracement, FibTimeZones, FibonacciPivots, FlagPennant, ForceIndex, FractalChaosBands, FryPanBottom, GapSideBySideWhite, GarmanKlassVolatility, Gartley, GatorOscillator, GoldenPocket, GravestoneDoji, Hammer, HangingMan, Harami, HaramiCross, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator, HiLoActivator, HighLowRange, HighLowVolumeNodes, HighWave, Hikkake, HikkakeModified, HomingPigeon, HurstChannel, Ichimoku, IdenticalThreeCrows, InNeck, Indicator, Inertia, InitialBalance, IntradayIntensity, IntradayMomentumIndex, IntradayVolatilityProfile, InvertedHammer, KaseDevStop, KasePermissionStochastic, Keltner, Kicking, KickingByLength, Kvo, LadderBottom, LongLeggedDoji, LongLine, MarketFacilitationIndex, Marubozu, MassIndex, MatHold, MatchingLow, AvgPrice, MedianPrice, Mfi, MidPrice, MinusDi, MinusDm, ModifiedMaStop, MorningDojiStar, MorningEveningStar, MurreyMathLines, NakedPoc, Natr, NewPriceLines, Nrtr, Nvi, Obv, OnNeck, OpeningMarubozu, OpeningRange, OvernightGap, OvernightIntradayReturn, ParkinsonVolatility, Pgo, PiercingDarkCloud, PivotReversal, PlusDi, PlusDm, ProfileShape, ProjectionBands, ProjectionOscillator, Psar, Pvi, Qstick, RectangleRange, RickshawMan, RisingThreeMethods, RogersSatchellVolatility, RollingVwap, Rvi, Rwi, SarExt, SeasonalZScore, SeparatingLines, SessionHighLow, SessionRange, SessionVwap, Shark, ShootingStar, ShortLine, SinglePrints, Smi, SmoothedHeikinAshi, SpinningTop, StalledPattern, StarcBands, StickSandwich, Stochastic, StochasticCci, SuperTrend, Takuri, TasukiGap, TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown, TdDWave, TdDeMarker, TdDifferential, TdLines, TdMovingAverage, TdOpen, TdPressure, TdPropulsion, TdRangeProjection, TdRei, TdRiskLevel, TdSequential, TdSetup, TdTrap, ThreeDrives, ThreeInside, ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows, ThreeStarsInSouth, Thrusting, TimeBasedStop, TimeOfDayReturnProfile, TowerTopBottom, TpoProfile, TradeVolumeIndex, Triangle, TripleTopBottom, Tristar, TrueRange, Tsv, TtmSqueeze, TtmTrend, TurnOfMonth, Tweezer, TwiggsMoneyFlow, TwoCrows, TypicalPrice, UltimateOscillator, UniqueThreeRiver, UpsideGapThreeMethods, UpsideGapTwoCrows, ValueArea, VolatilityCone, VolatilityRatio, VoltyStop, VolumeByTimeProfile, VolumeOscillator, VolumePriceTrend, VolumeProfile, VolumeRsi, VolumeWeightedMacd, VolumeWeightedSr, Vortex, Vwap, VwapStdDevBands, Vwma, Vzo, WaveTrend, Wedge, WeightedClose, WickRatio, Wad, WilliamsFractals, WilliamsR, WoodiePivots, YangZhangVolatility, YoyoExit, ZigZag};
/// Convert a flat `f64` stream into a `Vec<Candle>` by chunking it into
/// `[open, high, low, close, volume]` groups. Tuples that fail OHLCV
@@ -188,6 +188,11 @@ fuzz_target!(|data: Vec<f64>| {
}
// --- Market Profile (multi-output) ---
drive(|| CompositeProfile::new(20, 24, 0.7).unwrap(), &candles);
drive(|| HighLowVolumeNodes::new(20, 24).unwrap(), &candles);
drive(|| NakedPoc::new(20, 24).unwrap(), &candles);
drive(|| SinglePrints::new(20, 24).unwrap(), &candles);
drive(|| ProfileShape::new(20, 24).unwrap(), &candles);
drive(|| ValueArea::new(20, 50, 0.70).unwrap(), &candles);
drive(|| VolumeProfile::new(20, 50).unwrap(), &candles);
drive(|| TpoProfile::new(20, 50).unwrap(), &candles);
@@ -10,11 +10,7 @@
//! never panic, streaming or batched.
use libfuzzer_sys::fuzz_target;
use wickra_core::{
BatchExt, CalendarSpread, DerivativesTick, FundingBasis, FundingRate, FundingRateMean,
FundingRateZScore, Indicator, LiquidationFeatures, LongShortRatio, OIPriceDivergence,
OIWeighted, OpenInterestDelta, TakerBuySellRatio, TermStructureBasis,
};
use wickra_core::{BatchExt, CalendarSpread, DerivativesTick, EstimatedLeverageRatio, FundingBasis, FundingImpliedApr, FundingRate, FundingRateMean, FundingRateZScore, Indicator, LiquidationFeatures, LongShortRatio, OIPriceDivergence, OIWeighted, OiToVolumeRatio, OpenInterestDelta, OpenInterestMomentum, PerpetualPremiumIndex, TakerBuySellRatio, TermStructureBasis};
#[inline(never)]
fn drive<I>(make: impl Fn() -> I, ticks: &[DerivativesTick])
@@ -53,6 +49,11 @@ fuzz_target!(|data: &[u8]| {
drive(TakerBuySellRatio::new, &ticks);
drive(TermStructureBasis::new, &ticks);
drive(CalendarSpread::new, &ticks);
drive(EstimatedLeverageRatio::new, &ticks);
drive(OiToVolumeRatio::new, &ticks);
drive(PerpetualPremiumIndex::new, &ticks);
drive(|| FundingImpliedApr::new(1095.0).unwrap(), &ticks);
drive(|| OpenInterestMomentum::new(14).unwrap(), &ticks);
// LiquidationFeatures emits a struct, not an f64, so drive it directly.
let mut liq = LiquidationFeatures::new();