Fix OAMD ramp timing and band-0 DC filter gating

src/binaural_metadata.py

@@ -7,10 +7,9 @@ import numpy as np
 
 from adm_atmos import q_to_adm_xyz
 from oamd_bits import JocFieldState, frame_update
+from oamd_tracks import align_metadata_sample
 from variant_error import UnsupportedVariantError
 
-OAMD_UPDATE_QUANTUM_SAMPLES = 64
-
 
 @dataclass(frozen=True)
 class PositionTransition:
@@ -154,11 +153,8 @@ class OamdPositionTimeline:
             self.payload_count += 1
             return
 
-        ramp_duration = int(update["ramp_duration_samples"])
-        effective_ramp = max(0, ramp_duration - OAMD_UPDATE_QUANTUM_SAMPLES)
-        transition_start = coded_event + object_delay
-        if effective_ramp:
-            transition_start += OAMD_UPDATE_QUANTUM_SAMPLES
+        effective_ramp = max(0, int(update["ramp_duration_samples"]))
+        transition_start = align_metadata_sample(coded_event + object_delay)
         for index, target in enumerate(targets):
             if self.previous_targets[index] == target:
                 continue

src/joc_decode.py

@@ -35,6 +35,8 @@ def _load_huff_tables():
 H = _load_huff_tables()
 
 JOC_NUM_CHANNELS = {0: 5, 1: 7, 2: 7, 3: 5, 4: 7}          # Table 33
+# band-0 的 21-tap DC 补偿只在 downmix 配置 3/4 下启用。
+DC_FILTER_DMX_CONFIGS = (3, 4)
 JOC_NUM_BANDS = {0: 1, 1: 3, 2: 5, 3: 7, 4: 9, 5: 12, 6: 15, 7: 23}  # Table 35
 JOC_NUM_QUANT = {0: 96, 1: 192}                            # Table 51
 # dense 的量化零点就是 nquant/2；sparse 的递推起点比它高 2 个量化步。

src/joc_qmf.py

@@ -130,8 +130,12 @@ _SURROUND_DC_B = np.array([
 _SURROUND_DC_C = _SURROUND_DC_B + 1j * _SURROUND_DC_A
 
 
-def surround_post_frame(x, delay, dc_hist):
-    """处理 Ls/Rs 的 10 槽延迟、-j 旋转和 band-0 FIR。"""
+def surround_post_frame(x, delay, dc_hist, apply_dc_filter=True):
+    """处理 Ls/Rs 的 10 槽延迟、-j 旋转和 band-0 FIR。
+
+    ``apply_dc_filter=False`` 时跳过 band-0 的 21-tap DC 补偿，只做延迟与
+    -j 旋转；延迟线与 DC 历史仍照常推进，便于逐帧切换。
+    """
     src = np.asarray(x, dtype=np.complex128)
     qdelay = np.asarray(delay, dtype=np.complex128).copy()
     hist = np.asarray(dc_hist, dtype=np.complex128).copy()
@@ -144,8 +148,9 @@ def surround_post_frame(x, delay, dc_hist):
         block = -1j * queued[:, :4, :]
         qdelay = queued[:, 4:, :]
         dc_buf = np.concatenate((hist, current[:, :, 0]), axis=1)
-        windows = np.lib.stride_tricks.sliding_window_view(dc_buf, 21, axis=1)
-        block[:, :, 0] = 2.0 * np.sum(windows * _SURROUND_DC_C[None, None, :], axis=2)
+        if apply_dc_filter:
+            windows = np.lib.stride_tricks.sliding_window_view(dc_buf, 21, axis=1)
+            block[:, :, 0] = 2.0 * np.sum(windows * _SURROUND_DC_C[None, None, :], axis=2)
         hist = dc_buf[:, 4:]
         out[:, :, group:group + 4] = block.transpose(0, 2, 1)
     return out, qdelay, hist

src/native_renderer.py

@@ -14,7 +14,7 @@ import sys
 import numpy as np
 
 from evo_unpack import unpack_evolution
-from joc_decode import dequantize, diff_decode, parse_joc
+from joc_decode import DC_FILTER_DMX_CONFIGS, dequantize, diff_decode, parse_joc
 
 FRAME_SAMPLES = 1536
 MAX_OBJECTS = 15
@@ -88,6 +88,9 @@ def _load_library(path):
     lib.ejoc_renderer_reset.restype = ctypes.c_int
     lib.ejoc_renderer_set_threads.argtypes = [ctypes.c_void_p, ctypes.c_uint32]
     lib.ejoc_renderer_set_threads.restype = ctypes.c_int
+    if hasattr(lib, "ejoc_renderer_set_dc_filter"):
+        lib.ejoc_renderer_set_dc_filter.argtypes = [ctypes.c_void_p, ctypes.c_uint32]
+        lib.ejoc_renderer_set_dc_filter.restype = ctypes.c_int
     lib.ejoc_renderer_thread_count.argtypes = [ctypes.c_void_p]
     lib.ejoc_renderer_thread_count.restype = ctypes.c_uint32
     lib.ejoc_renderer_last_error.argtypes = [ctypes.c_void_p]
@@ -225,6 +228,21 @@ class NativeJocRenderer:
             self._dq[object_index, :points, :, :bands] = values
         return mask
 
+    def _set_dc_filter(self, dmx_config_idx):
+        """band-0 的 21-tap DC 补偿只在 downmix 配置 3/4 下启用。"""
+        enabled = dmx_config_idx in DC_FILTER_DMX_CONFIGS
+        setter = getattr(self._lib, "ejoc_renderer_set_dc_filter", None)
+        if setter is None:
+            if not enabled:
+                raise RuntimeError(
+                    "native library has no ejoc_renderer_set_dc_filter; rebuild "
+                    "eac3joc_core to disable the band-0 DC filter for "
+                    f"dmx_config_idx={dmx_config_idx}")
+            return
+        result = setter(self._handle, 1 if enabled else 0)
+        if result != 0:
+            self._raise_native("set_dc_filter", result)
+
     def render_frame(self, payload_bytes, bed5_pcm, lfe_pcm=None):
         subs, _ = unpack_evolution(payload_bytes, loose=True)
         return self.render_subpayloads(subs, bed5_pcm, lfe_pcm)
@@ -233,6 +251,7 @@ class NativeJocRenderer:
         self._require_open()
         out, _, mix_dq = self.decode_subpayloads(subs)
         object_mask = self._pack_frame(out, mix_dq)
+        self._set_dc_filter(out["dmx_config_idx"])
         bed5 = np.ascontiguousarray(bed5_pcm, dtype=np.float32)
         if bed5.shape != (CORE_CHANNELS, FRAME_SAMPLES):
             raise ValueError(f"core PCM shape must be (5,1536), got {bed5.shape}")

src/oamd_tracks.py

@@ -5,6 +5,18 @@ from adm_atmos import q_to_adm_xyz
 from oamd_bits import JocFieldState, frame_update
 from variant_error import UnsupportedVariantError
 
+# 元数据更新时刻按渲染器处理块对齐，与 Dolby 的 processing_block_size 及
+# speaker_renderer 的 block_size 落在同一网格。
+METADATA_BLOCK_SAMPLES = 32
+
+
+def align_metadata_sample(sample, block_samples=METADATA_BLOCK_SAMPLES):
+    """把更新时刻量化到处理块边界。"""
+    block = int(block_samples)
+    if block <= 0:
+        raise ValueError("block_samples must be positive")
+    return block * ((int(sample) + block // 2 - 1) // block)
+
 
 def _lerp_xyz(start, target, amount):
     return tuple(a + (b - a) * amount for a, b in zip(start, target))
@@ -18,18 +30,19 @@ def _append_point(points, sample, xyz, interpolation_samples):
         points.append(item)
 
 
-def _expand_events_dense64(events, total_samples, rate, update_quantum_samples,
+def _expand_events_dense64(events, total_samples, rate, update_block_samples,
                            object_delay_samples, object_index):
     if not events:
         return [(0.0, 0.0, 0.0, 0.0, total_samples / float(rate), 0.0)]
 
+    block = int(update_block_samples)
     # 初始位置从成品 sample 0 起有效；合成延迟只作用于后续位置变化。
     current = events[0][1]
     points = []
     _append_point(points, 0, current, 0)
 
     for event_index, (coded_start, target, ramp_samples) in enumerate(events[1:], 1):
-        start = coded_start + object_delay_samples
+        start = align_metadata_sample(coded_start + object_delay_samples, block)
         if start >= total_samples:
             break
         if start < points[-1][0]:
@@ -43,15 +56,16 @@ def _expand_events_dense64(events, total_samples, rate, update_quantum_samples,
         if start > points[-1][0]:
             _append_point(points, start, current, 0)
 
-        effective_ramp = max(0, int(ramp_samples) - update_quantum_samples)
-        if effective_ramp == 0:
+        ramp = max(0, int(ramp_samples))
+        if ramp == 0:
             _append_point(points, start, target, 0)
             current = target
             continue
 
-        end = start + math.ceil(effective_ramp / update_quantum_samples) * update_quantum_samples
+        end = start + math.ceil(ramp / block) * block
         if event_index + 1 < len(events):
-            next_start = events[event_index + 1][0] + object_delay_samples
+            next_start = align_metadata_sample(
+                events[event_index + 1][0] + object_delay_samples, block)
             if next_start < end:
                 raise UnsupportedVariantError(
                     "oamd", "overlapping_position_ramps",
@@ -61,23 +75,23 @@ def _expand_events_dense64(events, total_samples, rate, update_quantum_samples,
                         "ramp_start_sample": start,
                         "ramp_end_sample": end,
                         "next_update_sample": next_start,
-                        "repair_hint": "按 64-sample 状态机截断旧 ramp，再从当前插值位置启动新 ramp",
+                        "repair_hint": "按 32-sample 状态机截断旧 ramp，再从当前插值位置启动新 ramp",
                     })
 
-        # 逐位置更新节拍复现状态机。1536-sample ramp 在首次 64-sample
-        # 更新后剩余 1472 samples，因此共有 23 个中间/终点坐标。
-        future = effective_ramp
+        # 从对齐后的更新点起按处理块推进，整条 ramp 覆盖 ramp_samples 个样本；
+        # 几何式逼近望远镜化简为精确线性，每个中间点都落在真实 ramp 上。
+        future = ramp
         elapsed = 0
         position = current
         while future > 0:
-            amount = min(update_quantum_samples / float(future), 1.0)
+            amount = min(block / float(future), 1.0)
             position = _lerp_xyz(position, target, amount)
-            elapsed += update_quantum_samples
+            elapsed += block
             sample = start + elapsed
             if sample >= total_samples:
                 break
-            _append_point(points, sample, position, update_quantum_samples)
-            future -= update_quantum_samples
+            _append_point(points, sample, position, block)
+            future -= block
         current = target
 
     blocks = []
@@ -94,16 +108,14 @@ def _expand_events_dense64(events, total_samples, rate, update_quantum_samples,
 
 
 
-def _compact_events(events, total_samples, rate, update_quantum_samples,
+def _compact_events(events, total_samples, rate, update_block_samples,
                     object_delay_samples, object_index):
     """Represent each linear OAMD ramp with one ADM interpolation block.
 
-    The existing dense64 representation keeps the old position at ``start``,
-    writes its first interpolated target at ``start + quantum``, and lets ADM
-    interpolate that block over one quantum. Consequently, the interpreted
-    motion begins at ``start + quantum`` and reaches the final target at
-    ``start + ramp_duration``. This compact form preserves that timing with one
-    target block whose interpolationLength is ``ramp_duration - quantum``.
+    The update instant is quantized to the processing block boundary, the motion
+    starts there immediately, and ``interpolationLength`` spans the full
+    ``ramp_duration``. The interpreted motion therefore covers
+    ``[align(start), align(start) + ramp_duration]``.
     """
     if not events:
         return [(0.0, 0.0, 0.0, 0.0, total_samples / float(rate), 0.0)]
@@ -112,15 +124,16 @@ def _compact_events(events, total_samples, rate, update_quantum_samples,
     current = events[0][1]
     _append_point(points, 0, current, 0)
 
+    block = int(update_block_samples)
     for event_index, (coded_start, target, ramp_samples) in enumerate(events[1:], 1):
-        event_start = coded_start + object_delay_samples
+        event_start = align_metadata_sample(coded_start + object_delay_samples, block)
         if event_start >= total_samples:
             break
-        effective_ramp = max(0, int(ramp_samples) - update_quantum_samples)
-        block_start = event_start + (update_quantum_samples if effective_ramp else 0)
+        ramp = max(0, int(ramp_samples))
+        block_start = event_start
         if block_start >= total_samples:
             break
-        ramp_end = block_start + effective_ramp
+        ramp_end = block_start + ramp
 
         if block_start < points[-1][0]:
             raise UnsupportedVariantError(
@@ -131,9 +144,9 @@ def _compact_events(events, total_samples, rate, update_quantum_samples,
 
         if event_index + 1 < len(events):
             next_coded_start, _, next_ramp_samples = events[event_index + 1]
-            next_event_start = next_coded_start + object_delay_samples
-            next_effective = max(0, int(next_ramp_samples) - update_quantum_samples)
-            next_block_start = next_event_start + (update_quantum_samples if next_effective else 0)
+            next_event_start = align_metadata_sample(
+                next_coded_start + object_delay_samples, block)
+            next_block_start = next_event_start
             if next_block_start < ramp_end:
                 raise UnsupportedVariantError(
                     "oamd", "overlapping_compact_position_ramps",
@@ -147,10 +160,10 @@ def _compact_events(events, total_samples, rate, update_quantum_samples,
                     })
 
         block_target = target
-        block_interpolation = effective_ramp
+        block_interpolation = ramp
         available = total_samples - block_start
-        if effective_ramp > available:
-            block_target = _lerp_xyz(current, target, available / float(effective_ramp))
+        if ramp > available:
+            block_target = _lerp_xyz(current, target, available / float(ramp))
             block_interpolation = available
         _append_point(points, block_start, block_target, block_interpolation)
         current = target
@@ -168,25 +181,26 @@ def _compact_events(events, total_samples, rate, update_quantum_samples,
     return blocks
 
 
-def _expand_events(events, total_samples, rate, update_quantum_samples,
+def _expand_events(events, total_samples, rate, update_block_samples,
                    object_delay_samples, object_index, trajectory_mode):
     if trajectory_mode == "compact":
-        return _compact_events(events, total_samples, rate, update_quantum_samples,
+        return _compact_events(events, total_samples, rate, update_block_samples,
                                object_delay_samples, object_index)
     if trajectory_mode == "dense64":
-        return _expand_events_dense64(events, total_samples, rate, update_quantum_samples,
+        return _expand_events_dense64(events, total_samples, rate, update_block_samples,
                                       object_delay_samples, object_index)
     raise ValueError(f"未知 trajectory_mode: {trajectory_mode}")
 
 def build_adm_tracks(index, frames=None, rate=48000, frame_samples=1536,
-                     update_quantum_samples=64, object_delay_samples=1473,
-                     trajectory_mode="compact"):
+                     update_block_samples=METADATA_BLOCK_SAMPLES,
+                     object_delay_samples=1473, trajectory_mode="compact"):
     """从统一 metadata index 构造 15 条 ADM 轨迹。
 
     返回 ``[(name, [(rtime,x,y,z,duration,interpolation), ...]), ...]``。
-    OAMD 的内外层 sample offset、block offset 和 ramp 均保留。
+    OAMD 的内外层 sample offset、block offset 和 ramp 均保留；更新时刻量化到
+    ``update_block_samples`` 的块边界，ramp 覆盖完整的 ramp_duration。
     ``trajectory_mode="compact"`` 用一个长 ADM interpolation block 表示每条
-    线性 ramp；``dense64`` 保留逐 64-sample 展开作为兼容回退。
+    线性 ramp；``dense64`` 保留逐块展开作为兼容回退。
     ``object_delay_samples`` 将位置更新与对象 PCM 的 decoder 输出时刻对齐。
     slot1..15 与对象 PCM ch1..15 一一对应。
     """
@@ -221,7 +235,7 @@ def build_adm_tracks(index, frames=None, rate=48000, frame_samples=1536,
     return [
         (f"JOC_Object_{obj}",
          _expand_events(events[obj - 1], total_samples, rate,
-                        update_quantum_samples, object_delay_samples, obj,
+                        update_block_samples, object_delay_samples, obj,
                         trajectory_mode))
         for obj in range(1, 16)
     ]

src/renderer.py

@@ -13,7 +13,7 @@ output_scale:
 """
 import numpy as np
 
-from joc_decode import parse_joc, diff_decode, dequantize
+from joc_decode import DC_FILTER_DMX_CONFIGS, parse_joc, diff_decode, dequantize
 from joc_qmf import (N, QMF5_WINDOW, qmf_analysis_frame,
                      surround_post_frame, interp_matrix)
 from evo_unpack import unpack_evolution
@@ -60,11 +60,12 @@ class JocRenderer:
         mix_dq = dequantize(out, mix_q)
         return out, mix_q, mix_dq
 
-    def qmf_x(self, bed5, phase_new=0.0625):
+    def qmf_x(self, bed5, phase_new=0.0625, apply_dc_filter=True):
         """核心 5ch PCM → 对象矩阵使用的复数 QMF ``x``。
 
         先以 float32 对当前帧应用 phase；phase 变化时仅前 256 个样本从旧值
         线性过渡。缩放后的 L/R/C 延迟 10 槽，Ls/Rs 不延迟，再进入分析 QMF。
+        ``apply_dc_filter`` 控制 Ls/Rs band-0 的 21-tap DC 补偿。
         """
         pcm = np.asarray(bed5, dtype=np.float32)
         if pcm.shape != (5, 1536):
@@ -87,7 +88,8 @@ class JocRenderer:
         x, self._analysis_fifo = qmf_analysis_frame(self._analysis_fifo, blocks)
         self._analysis_phase = new_phase
         x[3:], self._surround_qmf_delay, self._surround_dc_hist = surround_post_frame(
-            x[3:], self._surround_qmf_delay, self._surround_dc_hist)
+            x[3:], self._surround_qmf_delay, self._surround_dc_hist,
+            apply_dc_filter=apply_dc_filter)
         return x
 
     def object_z(self, out, mix_dq, x):
@@ -244,7 +246,9 @@ class JocRenderer:
     def render_subpayloads(self, subs, bed5_pcm, lfe_pcm=None):
         """以已拆出的 EMDF payload 字典渲染一帧，避免绑定 transport 容器。"""
         out, mix_q, mix_dq = self.decode_subpayloads(subs)
-        x = self.qmf_x(bed5_pcm)
+        x = self.qmf_x(
+            bed5_pcm,
+            apply_dc_filter=out["dmx_config_idx"] in DC_FILTER_DMX_CONFIGS)
         self._last_x = x.copy()
         z_all = self.object_z(out, mix_dq, x)
         # joc_clipgain 在对象逆 QMF 后应用，并与用户 output_scale 分离。