feat(family-11): add DeMark suite (TD Setup, Sequential, DeMarker, REI, Pressure) (#48)

* feat(family-11): add DeMark suite (TD Setup, Sequential, DeMarker, REI, Pressure)

Family 11 (DeMark) was previously empty; this PR adds five
streaming-first DeMark indicators in one batch.

- **TD Setup** (`TdSetup`): parameterised buy/sell setup counter.
  Counts consecutive bars whose close is less-than (buy) or
  greater-than (sell) the close `lookback` bars earlier, saturating
  at `target`. Emits a signed `f64` so callers read direction from
  the sign and run length from the magnitude. Classic config:
  `lookback = 4`, `target = 9`.

- **TD Sequential** (`TdSequential`): the canonical Setup + Countdown
  exhaustion pattern. Output struct `{ setup, countdown, direction }`
  exposes both phase counts as signed numbers plus the active
  countdown direction (+1 buy / -1 sell / 0 none). Countdown
  activates when a setup completes and tracks the close-vs-high/low
  comparison `countdown_lookback` bars back, capped at
  `countdown_target`. Classic: 4/9/2/13.

- **TD DeMarker** (`TdDeMarker`): bounded [0, 1] oscillator from the
  rolling average of upward high expansion (DeMax) and downward low
  expansion (DeMin). Falls back to the neutral 0.5 on a flat market
  (denominator zero).

- **TD REI** (`TdRei`): Range Expansion Index, bounded [-100, 100].
  Per-bar numerator gated on a range-overlap condition vs the bars
  5 and 6 back, normalised by a `period`-bar sum of absolute moves.
  Classic period = 5. Saturates at +100 in a slow steady uptrend
  and at -100 in the mirror downtrend; emits 0 on a flat market.

- **TD Pressure** (`TdPressure`): volume-weighted buying / selling
  pressure normalised to [-100, 100]. Per-bar pressure is the
  intra-bar close-vs-open ratio scaled by volume; the output is the
  rolling mean divided by the rolling mean volume. Zero-range bars
  contribute zero (avoid the undefined ratio) and a flat zero-volume
  window falls back to 0.

Bindings: all five exposed in Python (`ta.TDSetup`, `ta.TDSequential`,
`ta.TDDeMarker`, `ta.TDREI`, `ta.TDPressure`), Node (`wickra.TDSetup`
etc.), and WASM. Multi-output classes (`TDSequential`) return either
a struct `{ setup, countdown, direction }` per bar (streaming) or a
flat interleaved Float64Array of length `3 * n` (batch).

Tests: 47 unit tests across the five new core files (pure-trend
saturation, flat-market neutral fallback, batch-equals-streaming,
zero-parameter rejection, reset semantics, accessors). Python
test_new_indicators.py picks up all five plus a multi-output TD
Sequential block. Node indicators.test.js picks up all five.
Reference values added to test_known_values.py.

Fuzz: candle fuzz target sweeps all five DeMark indicators with the
existing `Vec<f64>` -> `Vec<Candle>` driver.

Benches: BTCUSDT 1-minute dataset benches for each DeMark indicator
in `crates/wickra/benches/indicators.rs`.

Docs: README family table gains a "DeMark" row; indicator counter
bumped 71 -> 76. CHANGELOG entry added under [Unreleased]. Wiki
drafts (deep-dive pages + Sidebar / Overview / Warmup-Periods / Home
deltas) live under `indicator-ideas/families/wiki/family-11-demark/`
for manual merge into the wiki repo.

* feat(family-11): add 7 missing DeMark indicators

Complete the DeMark suite (family 11) with the seven indicators not
covered by the first commit: TD Combo, TD Countdown, TD Lines (TDST),
TD Range Projection, TD Differential, TD Open, and TD Risk Level.

- TdCombo: aggressive countdown variant with three strictness rules
  on top of the classic close-vs-low/high lookback rule (monotone
  low/high, monotone close vs prior bar).
- TdCountdown: standalone 13-bar countdown packaging only the signed
  countdown count (the setup machine runs internally).
- TdLines: TDST horizontal support/resistance levels from the
  highest-high / lowest-low bars of the most-recently-completed
  setup, exposed as a multi-output struct.
- TdRangeProjection: DeMark X-projection of the next bar's high and
  low from the current bar's OHLC via an open-vs-close-weighted
  pivot (three branches: close<open, close>open, close==open).
- TdDifferential: two-bar buying-pressure vs selling-pressure
  reversal pattern emitting +1/-1/0.
- TdOpen: gap-and-fade reversal pattern (open outside prior range
  with subsequent recovery into it) emitting +1/-1/0.
- TdRiskLevel: protective stop levels derived from the setup
  extreme bar +/- its true range.

All seven are wired through Rust core, Python, Node and WASM
bindings, registered in the candle-stream fuzz target, given
benchmark entries on the BTCUSDT 1-minute dataset, and covered by
streaming-vs-batch equivalence, reference-value, lifecycle and
input-validation tests on the Python and Node sides. README counter
moves 76 -> 83 and the CHANGELOG "family 11" entry is extended to
list all twelve indicators.

* fix(td_risk_level tests): check first emission at idx 12, not last bar

TdRiskLevel re-ratchets the sell-risk level on each subsequent setup
completion, so a strictly rising series produces 22.0 at idx 19 (latest
setup) rather than 15.0 (first setup). The test comment already named
idx 12 as the reference; switch the assertion from out[-1] to out[12]
to match the reference computation.

* test(family-11): cover buy-direction branches in TD indicators

Add downtrend tests to TdSequential, TdCombo and TdCountdown so the
buy-side countdown/combo increment branches are exercised; remove an
empty `if buy_countdown == target {}` block in TdSequential whose
behavior is already enforced by the outer strict `<` guard.

Closes codecov/patch gaps reported on PR #48 (10 missed lines across
the three files).

bindings/python/src/lib.rs

@@ -8575,6 +8575,848 @@ impl PyZigZag {
         self.inner.warmup_period()
     }
 }
+// ============================== TD Setup ==============================
+
+#[pyclass(name = "TDSetup", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdSetup {
+    inner: wc::TdSetup,
+}
+
+#[pymethods]
+impl PyTdSetup {
+    #[new]
+    #[pyo3(signature = (lookback=4, target=9))]
+    fn new(lookback: usize, target: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdSetup::new(lookback, target).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: 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))?;
+        if h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "high, low, close must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(h.len());
+        for i in 0..h.len() {
+            let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 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()
+    }
+    #[getter]
+    fn value(&self) -> Option<f64> {
+        self.inner.value()
+    }
+    fn __repr__(&self) -> String {
+        let (lb, tg) = self.inner.params();
+        format!("TDSetup(lookback={lb}, target={tg})")
+    }
+}
+
+// ============================== TD Sequential ==============================
+
+#[pyclass(name = "TDSequential", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdSequential {
+    inner: wc::TdSequential,
+}
+
+#[pymethods]
+impl PyTdSequential {
+    #[new]
+    #[pyo3(signature = (setup_lookback=4, setup_target=9, countdown_lookback=2, countdown_target=13))]
+    fn new(
+        setup_lookback: usize,
+        setup_target: usize,
+        countdown_lookback: usize,
+        countdown_target: usize,
+    ) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdSequential::new(
+                setup_lookback,
+                setup_target,
+                countdown_lookback,
+                countdown_target,
+            )
+            .map_err(map_err)?,
+        })
+    }
+    /// Returns `(setup, countdown, direction)` or `None` during warmup.
+    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.setup, o.countdown, o.direction)))
+    }
+    /// Batch returns shape `(n, 3)`: `[setup, countdown, direction]`.
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: 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 c = close
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        if h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "high, low, close must be equal length",
+            ));
+        }
+        let n = h.len();
+        let mut out = vec![f64::NAN; n * 3];
+        for i in 0..n {
+            let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
+            if let Some(o) = self.inner.update(candle) {
+                out[i * 3] = o.setup;
+                out[i * 3 + 1] = o.countdown;
+                out[i * 3 + 2] = o.direction;
+            }
+        }
+        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()
+    }
+}
+
+// ============================== TD DeMarker ==============================
+
+#[pyclass(name = "TDDeMarker", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdDeMarker {
+    inner: wc::TdDeMarker,
+}
+
+#[pymethods]
+impl PyTdDeMarker {
+    #[new]
+    #[pyo3(signature = (period=14))]
+    fn new(period: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdDeMarker::new(period).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c))
+    }
+    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 candle = wc::Candle::new(l[i], h[i], l[i], l[i], 0.0, 0).map_err(map_err)?;
+            out.push(self.inner.update(candle).unwrap_or(f64::NAN));
+        }
+        Ok(out.into_pyarray(py))
+    }
+    #[getter]
+    fn period(&self) -> usize {
+        self.inner.period()
+    }
+    #[getter]
+    fn value(&self) -> Option<f64> {
+        self.inner.value()
+    }
+    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!("TDDeMarker(period={})", self.inner.period())
+    }
+}
+
+// ============================== TD REI ==============================
+
+#[pyclass(name = "TDREI", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdRei {
+    inner: wc::TdRei,
+}
+
+#[pymethods]
+impl PyTdRei {
+    #[new]
+    #[pyo3(signature = (period=5))]
+    fn new(period: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdRei::new(period).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c))
+    }
+    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 candle = wc::Candle::new(l[i], h[i], l[i], l[i], 0.0, 0).map_err(map_err)?;
+            out.push(self.inner.update(candle).unwrap_or(f64::NAN));
+        }
+        Ok(out.into_pyarray(py))
+    }
+    #[getter]
+    fn period(&self) -> usize {
+        self.inner.period()
+    }
+    #[getter]
+    fn value(&self) -> Option<f64> {
+        self.inner.value()
+    }
+    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!("TDREI(period={})", self.inner.period())
+    }
+}
+
+// ============================== TD Pressure ==============================
+
+#[pyclass(name = "TDPressure", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdPressure {
+    inner: wc::TdPressure,
+}
+
+#[pymethods]
+impl PyTdPressure {
+    #[new]
+    #[pyo3(signature = (period=5))]
+    fn new(period: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdPressure::new(period).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 columns: open, high, low, close, volume.
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        open: PyReadonlyArray1<'py, f64>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: PyReadonlyArray1<'py, f64>,
+        volume: PyReadonlyArray1<'py, f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        let o = open
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        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 o.len() != h.len() || h.len() != l.len() || l.len() != c.len() || c.len() != v.len() {
+            return Err(PyValueError::new_err(
+                "open, high, low, close, volume must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(o.len());
+        for i in 0..o.len() {
+            let candle = wc::Candle::new(o[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))
+    }
+    #[getter]
+    fn period(&self) -> usize {
+        self.inner.period()
+    }
+    #[getter]
+    fn value(&self) -> Option<f64> {
+        self.inner.value()
+    }
+    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!("TDPressure(period={})", self.inner.period())
+    }
+}
+
+// ============================== TD Combo ==============================
+
+#[pyclass(name = "TDCombo", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdCombo {
+    inner: wc::TdCombo,
+}
+
+#[pymethods]
+impl PyTdCombo {
+    #[new]
+    #[pyo3(signature = (setup_lookback=4, setup_target=9, countdown_lookback=2, countdown_target=13))]
+    fn new(
+        setup_lookback: usize,
+        setup_target: usize,
+        countdown_lookback: usize,
+        countdown_target: usize,
+    ) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdCombo::new(
+                setup_lookback,
+                setup_target,
+                countdown_lookback,
+                countdown_target,
+            )
+            .map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: 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))?;
+        if h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "high, low, close must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(h.len());
+        for i in 0..h.len() {
+            let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 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()
+    }
+}
+
+// ============================== TD Countdown ==============================
+
+#[pyclass(name = "TDCountdown", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdCountdown {
+    inner: wc::TdCountdown,
+}
+
+#[pymethods]
+impl PyTdCountdown {
+    #[new]
+    #[pyo3(signature = (setup_lookback=4, setup_target=9, countdown_lookback=2, countdown_target=13))]
+    fn new(
+        setup_lookback: usize,
+        setup_target: usize,
+        countdown_lookback: usize,
+        countdown_target: usize,
+    ) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdCountdown::new(
+                setup_lookback,
+                setup_target,
+                countdown_lookback,
+                countdown_target,
+            )
+            .map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: 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))?;
+        if h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "high, low, close must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(h.len());
+        for i in 0..h.len() {
+            let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 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()
+    }
+}
+
+// ============================== TD Lines ==============================
+
+#[pyclass(name = "TDLines", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdLines {
+    inner: wc::TdLines,
+}
+
+#[pymethods]
+impl PyTdLines {
+    #[new]
+    #[pyo3(signature = (lookback=4, target=9))]
+    fn new(lookback: usize, target: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdLines::new(lookback, target).map_err(map_err)?,
+        })
+    }
+    /// Returns `(resistance, support)` (with `NaN` for unset levels) or
+    /// `None` during warmup.
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<(f64, f64)>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c).map(|o| (o.resistance, o.support)))
+    }
+    /// Batch returns shape `(n, 2)`: `[resistance, support]`.
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: 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 c = close
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        if h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "high, low, close must be equal length",
+            ));
+        }
+        let n = h.len();
+        let mut out = vec![f64::NAN; n * 2];
+        for i in 0..n {
+            let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
+            if let Some(o) = self.inner.update(candle) {
+                out[i * 2] = o.resistance;
+                out[i * 2 + 1] = o.support;
+            }
+        }
+        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()
+    }
+}
+
+// ============================== TD Range Projection ==============================
+
+#[pyclass(
+    name = "TDRangeProjection",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone, Default)]
+struct PyTdRangeProjection {
+    inner: wc::TdRangeProjection,
+}
+
+#[pymethods]
+impl PyTdRangeProjection {
+    #[new]
+    fn new() -> Self {
+        Self {
+            inner: wc::TdRangeProjection::new(),
+        }
+    }
+    /// Returns `(projected_high, projected_low)` for the next bar.
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<(f64, f64)>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c).map(|o| (o.high, o.low)))
+    }
+    /// Batch returns shape `(n, 2)`: `[projected_high, projected_low]`.
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        open: PyReadonlyArray1<'py, f64>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: PyReadonlyArray1<'py, f64>,
+    ) -> PyResult<Bound<'py, PyArray2<f64>>> {
+        let o = open
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        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))?;
+        if o.len() != h.len() || h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "open, high, low, close must be equal length",
+            ));
+        }
+        let n = o.len();
+        let mut out = vec![f64::NAN; n * 2];
+        for i in 0..n {
+            let candle = wc::Candle::new(o[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
+            if let Some(p) = self.inner.update(candle) {
+                out[i * 2] = p.high;
+                out[i * 2 + 1] = p.low;
+            }
+        }
+        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()
+    }
+}
+
+// ============================== TD Differential ==============================
+
+#[pyclass(
+    name = "TDDifferential",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone, Default)]
+struct PyTdDifferential {
+    inner: wc::TdDifferential,
+}
+
+#[pymethods]
+impl PyTdDifferential {
+    #[new]
+    fn new() -> Self {
+        Self {
+            inner: wc::TdDifferential::new(),
+        }
+    }
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: 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))?;
+        if h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "high, low, close must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(h.len());
+        for i in 0..h.len() {
+            let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 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()
+    }
+}
+
+// ============================== TD Open ==============================
+
+#[pyclass(name = "TDOpen", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone, Default)]
+struct PyTdOpen {
+    inner: wc::TdOpen,
+}
+
+#[pymethods]
+impl PyTdOpen {
+    #[new]
+    fn new() -> Self {
+        Self {
+            inner: wc::TdOpen::new(),
+        }
+    }
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<f64>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        open: PyReadonlyArray1<'py, f64>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: PyReadonlyArray1<'py, f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        let o = open
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        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))?;
+        if o.len() != h.len() || h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "open, high, low, close must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(o.len());
+        for i in 0..o.len() {
+            let candle = wc::Candle::new(o[i], h[i], l[i], c[i], 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()
+    }
+}
+
+// ============================== TD Risk Level ==============================
+
+#[pyclass(name = "TDRiskLevel", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyTdRiskLevel {
+    inner: wc::TdRiskLevel,
+}
+
+#[pymethods]
+impl PyTdRiskLevel {
+    #[new]
+    #[pyo3(signature = (lookback=4, target=9))]
+    fn new(lookback: usize, target: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TdRiskLevel::new(lookback, target).map_err(map_err)?,
+        })
+    }
+    /// Returns `(buy_risk, sell_risk)` (with `NaN` for unset levels) or
+    /// `None` during warmup.
+    fn update(&mut self, candle: &Bound<'_, PyAny>) -> PyResult<Option<(f64, f64)>> {
+        let c = extract_candle(candle)?;
+        Ok(self.inner.update(c).map(|o| (o.buy_risk, o.sell_risk)))
+    }
+    /// Batch returns shape `(n, 2)`: `[buy_risk, sell_risk]`.
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        high: PyReadonlyArray1<'py, f64>,
+        low: PyReadonlyArray1<'py, f64>,
+        close: 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 c = close
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        if h.len() != l.len() || l.len() != c.len() {
+            return Err(PyValueError::new_err(
+                "high, low, close must be equal length",
+            ));
+        }
+        let n = h.len();
+        let mut out = vec![f64::NAN; n * 2];
+        for i in 0..n {
+            let candle = wc::Candle::new(c[i], h[i], l[i], c[i], 0.0, 0).map_err(map_err)?;
+            if let Some(o) = self.inner.update(candle) {
+                out[i * 2] = o.buy_risk;
+                out[i * 2 + 1] = o.sell_risk;
+            }
+        }
+        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()
+    }
+}
+
 // ============================== Module ==============================
 
 #[pymodule]
@@ -8718,5 +9560,17 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_class::<PyDemarkPivots>()?;
     m.add_class::<PyWilliamsFractals>()?;
     m.add_class::<PyZigZag>()?;
+    m.add_class::<PyTdSetup>()?;
+    m.add_class::<PyTdSequential>()?;
+    m.add_class::<PyTdDeMarker>()?;
+    m.add_class::<PyTdRei>()?;
+    m.add_class::<PyTdPressure>()?;
+    m.add_class::<PyTdCombo>()?;
+    m.add_class::<PyTdCountdown>()?;
+    m.add_class::<PyTdLines>()?;
+    m.add_class::<PyTdRangeProjection>()?;
+    m.add_class::<PyTdDifferential>()?;
+    m.add_class::<PyTdOpen>()?;
+    m.add_class::<PyTdRiskLevel>()?;
     Ok(())
 }