chore(probe): theo doi clipping output (FXRT_PROBE_AMP + flat-top stats)

fxrt_ws_probe.py

@@ -151,7 +151,8 @@ class WorkletSim:
 
 def make_block():
     t = np.arange(BLOCK) / SR
-    sig = 0.2 * np.sin(2 * np.pi * 220 * t) + 0.1 * np.sin(2 * np.pi * 331 * t)
+    amp = float(os.environ.get("FXRT_PROBE_AMP", "1.0"))
+    sig = amp * (0.2 * np.sin(2 * np.pi * 220 * t) + 0.1 * np.sin(2 * np.pi * 331 * t))
     inter = np.empty(BLOCK * 2, dtype=np.float32)
     inter[0::2] = sig
     inter[1::2] = 0.85 * sig
@@ -179,6 +180,8 @@ async def run_ws_probe(port, chain, secs, stall):
     s_prob, s_min, s_max = stall_model(stall)
     sent_bursts = 0
     recv_times = []     # (block_seq, time, peak)
+    out_peaks = []      # output peak per block (cause-5 clipping track)
+    out_flat = []       # flat-top samples per block (|x|>0.9999)
     recv_lock = asyncio.Lock()
     stop = asyncio.Event()
     produced = asyncio.Queue()   # burst buffers
@@ -265,9 +268,13 @@ async def run_ws_probe(port, chain, secs, stall):
                 break
             if isinstance(msg, bytes) and len(msg) == BLOCK * 2 * 4:
                 now = time.perf_counter()
-                pk = float(np.frombuffer(msg, dtype=np.float32)[::2].max())
+                f = np.frombuffer(msg, dtype=np.float32)
+                pk = float(f[::2].max())
+                flat = int(np.count_nonzero(np.abs(f) > 0.9999))
                 async with recv_lock:
                     recv_times.append((len(recv_times), now, pk))
+                    out_peaks.append(pk)
+                    out_flat.append(flat)
             # text frame (latency) bỏ qua
 
     async with websockets.connect(ws_url) as ws:
@@ -319,6 +326,14 @@ async def run_ws_probe(port, chain, secs, stall):
     rate = n_recv / dur
     print("  sent=%d bursts (%d blocks) recv=%d blocks over %.1fs = %.1f blk/s (expect 187.5)"
           % (len(sent_times), n_sent, n_recv, dur, rate))
+    if out_peaks:
+        op = np.array(out_peaks)
+        of = np.array(out_flat)
+        print("  OUT peak: min=%.4f p50=%.4f p95=%.4f max=%.4f" %
+              (op.min(), np.percentile(op, 50), np.percentile(op, 95), op.max()))
+        print("  OUT flat-top(|x|>0.9999): blocks=%d samples=%d (%.4f%%)" %
+              (int(np.count_nonzero(of > 0)), int(of.sum()),
+               100.0 * of.sum() / max(1, len(of) * BLOCK * 2)))
     print("  lost blocks (sent-recv): %d" % max(0, n_sent - n_recv))
     if len(times) > 1:
         gaps = [b - a for (i, a, _), (j, b, _) in zip(times[:-1], times[1:])]