feat: Family 03 MACD & Price Oscillators — APO / AO-Hist / CFO / Zero-Lag MACD / Elder Impulse / STC (#41)

* feat(apo): add Absolute Price Oscillator

EMA(close, fast) - EMA(close, slow). Like MACD without the signal EMA.
Defaults to (fast = 12, slow = 26); fast must be strictly less than
slow.

Touchpoints: apo.rs + mod.rs + lib.rs re-export, PyApo + __init__.py
+ test_new_indicators SCALAR + test_known_values flat reference,
ApoNode + index.d.ts/index.js + indicators.test.js factory + reference,
WasmApo via scalar macro, scalar-fuzz target, README + CHANGELOG.

* fix(apo): add PyApo + ApoNode + WasmApo bindings missed from ec269d8

The previous APO commit (ec269d8) only registered APO in the Python
__init__.py / Node index.js / Node index.d.ts / fuzz / tests / docs.
The actual PyApo pyclass, ApoNode napi class, and WasmApo wasm class
edits silently no-op'd because the underlying lib.rs files had been
touched by a branch switch between Read and Edit. The bindings were
therefore advertising APO from the Python module / Node package /
WASM module but not actually exposing it.

Fix: insert PyApo block + add_class call in bindings/python/src/lib.rs,
ApoNode block in bindings/node/src/lib.rs, WasmApo macro line in
bindings/wasm/src/lib.rs. cargo test workspace stays at 615 (no new
tests added; the existing test_known_values + indicators.test.js
references would have failed at import once the bindings rebuilt
without these classes).

* feat(ao-histogram): add Awesome Oscillator Histogram

AO - SMA(AO, sma_period). A configurable variant of the existing
AcceleratorOscillator (which fixes fast=5, slow=34, sma=5).
Three parameters; defaults match Bill Williams' Accelerator.

Touchpoints: awesome_oscillator_histogram.rs + mod.rs + lib.rs
re-export, PyAoHist + __init__.py + test_new_indicators CANDLE_SCALAR
+ test_known_values flat reference, AwesomeOscillatorHistogramNode +
index.d.ts/index.js + indicators.test.js factory + reference,
WasmAoHist, candle-fuzz target, README + CHANGELOG.

* feat(cfo): add Chande Forecast Oscillator

100 * (close - LinReg(close, period)) / close. Positive when close
overshoots the linear forecast, negative when it undershoots. Holds
the previous value if the close is zero (percentage form undefined).
Single param period (default 14).

Touchpoints: cfo.rs + mod.rs + lib.rs re-export, PyCfo + __init__.py
+ test_new_indicators SCALAR + test_known_values linear reference,
CfoNode + index.d.ts/index.js + indicators.test.js factory + reference,
WasmCfo via scalar macro, scalar-fuzz target, README + CHANGELOG.

* fix(cfo): add WasmCfo binding missed from 733afd9

* feat(zero-lag-macd): add Zero-Lag MACD

Classic MACD topology with ZLEMA substituted for EMA everywhere:
faster reaction to trend changes at the cost of slightly noisier
readings. Multi-output ZeroLagMacdOutput { macd, signal, histogram }.
Three parameters (fast = 12, slow = 26, signal = 9); fast must be
strictly less than slow.

Touchpoints: zero_lag_macd.rs + mod.rs + lib.rs re-export, PyZeroLagMacd
+ __init__.py + test_new_indicators MULTI + test_known_values flat
reference, ZeroLagMacdNode + ZeroLagMacdValue + index.d.ts/index.js +
indicators.test.js multi factory + reference, WasmZeroLagMacd, scalar
fuzz with hand-rolled drive (multi-output bypasses the f64-only
helper), README + CHANGELOG.

* feat(elder-impulse): add Alexander Elder Impulse System

Tri-state momentum gauge: +1 (green/buy) when EMA trend and MACD
histogram both rise, -1 (red/sell) when both fall, 0 (blue/neutral)
on disagreement. Four parameters (ema_period, macd_fast, macd_slow,
macd_signal); defaults (13, 12, 26, 9) match Elder.

Internally feeds both branches on every input so they warm in parallel;
needs one bar past the slowest branch to seed direction state.

Touchpoints: elder_impulse.rs + mod.rs + lib.rs re-export, PyElderImpulse
+ __init__.py + test_new_indicators SCALAR + test_known_values neutral
reference, ElderImpulseNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmElderImpulse via scalar macro, scalar-fuzz
target, README + CHANGELOG.

* feat(stc): add Schaff Trend Cycle

Doug Schaff's doubly-Stochastic-smoothed MACD. Bounded [0, 100]
reading that reacts faster than MACD by extracting the percentile of
MACD within a recent window, half-EMA-smoothing it, and re-stochasing
the smoothed series. Four parameters (fast = 23, slow = 50,
schaff_period = 10, factor = 0.5); fast must be strictly less than
slow and factor must lie in (0, 1].

Output clamped to [0, 100] to absorb floating-point rounding. The
stochastic stages clamp to 0 when their rolling range collapses (flat
input or perfectly monotone trend), so a flat series settles
deterministically at 0 after warmup.

Touchpoints: stc.rs + mod.rs + lib.rs re-export, PyStc + __init__.py
+ test_new_indicators SCALAR + test_known_values flat reference,
StcNode + index.d.ts/index.js + indicators.test.js factory + reference,
WasmStc via scalar macro, scalar-fuzz target, README + CHANGELOG.

* fix(stc): rename last_stc -> last_value to satisfy clippy

* ci: Retry setup-node and setup-python on CDN flakes

Setup-node on Windows runners and setup-python across all OSes
occasionally fail with a silent hang or 5xx mid-download ("Attempting
to download 18..." → fail in <1s) — pure upstream CDN flake. The fix
ran on this branch's previous merge commit (24e723f) had to be
re-triggered manually via `gh run rerun --failed`.

Wrap both setup actions with continue-on-error and a follow-up retry
step that waits 30s and re-runs the same setup. The retry only fires
when the first attempt failed (steps.<id>.outcome == 'failure'), so a
green setup costs nothing extra. The retry uses the identical pinned
SHA so we still get supply-chain verification on both attempts.

Applied to ci.yml (Python matrix and Node matrix). release.yml has
the same setup-node / setup-python steps but is rarely re-run, so
the existing manual rerun pattern stays sufficient for now.

* test(zero-lag-macd): Fix MULTI dict shape mismatch + cover warmup_period

ZeroLagMACD was registered in the Python MULTI dict (which asserts a
(n, 2) batch shape) but actually emits (n, 3) — macd, signal,
histogram — like MACD. Moved out into its own standalone test
test_zero_lag_macd_streaming_matches_batch (3-tuple shape), and
included in the lifecycle sweep. Mirrors the existing Alligator
pattern for 3-output candle indicators.

Also adds a unit test for ZeroLagMacd::warmup_period that pins both
the (12, 26, 9) classic case and a small-period config — these four
lines were the codecov/patch miss on PR 41.

bindings/python/tests/test_new_indicators.py

@@ -56,6 +56,10 @@ SCALAR = [
     (ta.PMO, (35, 20)),
     (ta.StochRSI, (14, 14)),
     (ta.PPO, (12, 26)),
+    (ta.APO, (12, 26)),
+    (ta.CFO, (14,)),
+    (ta.ElderImpulse, (13, 12, 26, 9)),
+    (ta.STC, (23, 50, 10, 0.5)),
     (ta.DPO, (20,)),
     (ta.Coppock, (14, 11, 10)),
     (ta.StdDev, (20,)),
@@ -159,6 +163,10 @@ CANDLE_SCALAR = {
         lambda: ta.AcceleratorOscillator(5, 34, 5),
         lambda ind, h, l, c, v: ind.batch(h, l),
     ),
+    "AwesomeOscillatorHistogram": (
+        lambda: ta.AwesomeOscillatorHistogram(5, 34, 5),
+        lambda ind, h, l, c, v: ind.batch(h, l),
+    ),
     "BalanceOfPower": (
         # The streaming 6-tuple feeds open == close, so batch matches with
         # the close column standing in for open.
@@ -275,6 +283,22 @@ def test_multi_scalar_streaming_matches_batch(name, ohlcv):
     assert _eq_nan(batch, np.array(rows, dtype=np.float64)), f"{name} mismatch"
 
 
+# --- ZeroLagMACD (scalar input, 3-tuple output: macd / signal / histogram) -
+
+
+def test_zero_lag_macd_streaming_matches_batch(ohlcv):
+    _, _, close, _ = ohlcv
+    batch = ta.ZeroLagMACD(12, 26, 9).batch(close)
+    assert batch.shape == (close.size, 3)
+
+    streamer = ta.ZeroLagMACD(12, 26, 9)
+    rows = []
+    for p in close:
+        v = streamer.update(float(p))
+        rows.append([math.nan, math.nan, math.nan] if v is None else list(v))
+    assert _eq_nan(batch, np.array(rows, dtype=np.float64)), "ZeroLagMACD mismatch"
+
+
 # --- Alligator (3-tuple output) -------------------------------------------
 
 
@@ -362,8 +386,10 @@ def test_z_score_reference():
 def test_new_indicators_expose_lifecycle():
     instances = [make() for make, _ in CANDLE_SCALAR.values()]
     instances += [make() for make, _ in MULTI.values()]
+    instances += [make() for make, _ in MULTI_SCALAR_INPUT.values()]
     instances += [cls(*args) for cls, args in SCALAR]
     instances.append(ta.Alligator(13, 8, 5))
+    instances.append(ta.ZeroLagMACD(12, 26, 9))
     for ind in instances:
         assert ind.is_ready() is False
         assert ind.warmup_period() >= 1