feat(family-16): add ValueArea + InitialBalance + OpeningRange (#52)

* feat(family-16): add ValueArea + InitialBalance + OpeningRange

Opens family #16 (Market Profile) with the three OHLCV-compatible scalar /
multi-output indicators:

- ValueArea(period, bin_count, value_area_pct) -> {poc, vah, val}.
  Rolling bin-approximation volume profile over the last `period`
  candles. Each candle's volume is spread uniformly across [low, high];
  POC is the bin with highest cumulative volume; the value area expands
  symmetrically from POC and always absorbs the higher-volume neighbour
  next, until `value_area_pct` (default 0.70) of total volume is
  enclosed. Defaults (20, 50, 0.70).

- InitialBalance(period) -> {high, low}. Tracks session-opening high
  and low over the first `period` bars, then locks. Default period = 12
  (one-hour IB on 5-minute bars for US equities). Callers MUST invoke
  reset() at every session boundary, otherwise IB stays fixed for the
  lifetime of the instance.

- OpeningRange(period) -> {high, low, breakout_distance}. Same
  lock-after-N-bars semantics as IB with a shorter default period
  (6 = 30 min on 5-minute bars) and a third output that tracks
  close - or_mid (positive above the range mid, negative below).

Histogram-output Market Profile variants (Volume Profile, VPVR,
Composite Profile) are deferred because they need a new histogram
output API layer rather than fixed-arity scalars. Tick-data-only
variants (TPO Profile, Single Print, Order Flow Delta, Cumulative
Delta, Volume-Weighted Open) are out of scope because `wickra-data`
does not currently expose tick / L2 data.

All four bindings (Rust core, Python, Node, WASM) ship the new
indicators with parity tests; benches added; fuzz target extended.
Counter 71 -> 74 across 8 -> 9 families. cargo check --workspace
--all-features green.

* fix(family-16): cover cold paths in InitialBalance + ValueArea

InitialBalance::value() public getter had no test covering the post-update
Some(...) branch — extended accessors_and_metadata to call value() after one
update. ValueArea single-print bar path (c.high == c.low) was unreachable in
existing tests since the only single-print test used a uniform 100-price
window which exits early via the span == 0 guard; added a mixed-window test
that triggers the c.high <= c.low branch directly. The (None, None) arm of
the expansion match was by-construction unreachable (the loop condition
already requires at least one neighbour) and has been folded into an
if/else.

bindings/python/tests/test_new_indicators.py

@@ -581,6 +581,57 @@ def test_multi_scalar_streaming_matches_batch(name, ohlcv):
     assert _eq_nan(batch, np.array(rows, dtype=np.float64)), f"{name} mismatch"
 
 
+# --- Market Profile (multi-output with variable shapes) ------------------
+
+
+def test_value_area_shape_and_streaming(ohlcv):
+    high, low, _close, volume = ohlcv
+    batch = ta.ValueArea(20, 50, 0.70).batch(high, low, volume)
+    assert batch.shape == (high.size, 3)
+    streamer = ta.ValueArea(20, 50, 0.70)
+    rows = []
+    for i in range(high.size):
+        mid = float((high[i] + low[i]) / 2.0)
+        candle = (mid, float(high[i]), float(low[i]), mid, float(volume[i]), i)
+        v = streamer.update(candle)
+        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))
+
+
+def test_initial_balance_shape_and_streaming(ohlcv):
+    high, low, _close, _volume = ohlcv
+    batch = ta.InitialBalance(12).batch(high, low)
+    assert batch.shape == (high.size, 2)
+    streamer = ta.InitialBalance(12)
+    rows = []
+    for i in range(high.size):
+        mid = float((high[i] + low[i]) / 2.0)
+        candle = (mid, float(high[i]), float(low[i]), mid, 0.0, i)
+        v = streamer.update(candle)
+        rows.append([math.nan, math.nan] if v is None else list(v))
+    assert _eq_nan(batch, np.array(rows, dtype=np.float64))
+
+
+def test_opening_range_shape_and_streaming(ohlcv):
+    high, low, close, _volume = ohlcv
+    batch = ta.OpeningRange(6).batch(high, low, close)
+    assert batch.shape == (high.size, 3)
+    streamer = ta.OpeningRange(6)
+    rows = []
+    for i in range(high.size):
+        candle = (
+            float(close[i]),
+            float(high[i]),
+            float(low[i]),
+            float(close[i]),
+            0.0,
+            i,
+        )
+        v = streamer.update(candle)
+        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))
+
+
 # --- TD Pressure (OHLCV-input) -------------------------------------------