lou
93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
"""回声诊断: 播单脉冲, 录数字输出, 看是平滑混响衰减还是离散回声。
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离散回声 = 主峰之后出现孤立的、比周围明显高的峰(延迟 20ms 以上);
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平滑混响 = 包络单调下降。分湿量 0 / 0.3 各测一次, 好判断回声是不是混响造成的。
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"""
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from __future__ import annotations
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import json
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import subprocess
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import time
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import urllib.request
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from pathlib import Path
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import numpy as np
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from scipy.io import wavfile
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RATE = 96000
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MAT = Path("/tmp/echo_mat.wav")
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REC = Path("/tmp/echo_rec.wav")
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API = "http://127.0.0.1:8789"
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def api(path: str, payload: dict[str, object] | None = None) -> dict[str, object]:
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"""调面板 API。"""
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headers = {"Content-Type": "application/json"}
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data = json.dumps(payload).encode() if payload else None
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req = urllib.request.Request(API + path, data=data, headers=headers)
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with urllib.request.urlopen(req, timeout=5) as r:
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return json.loads(r.read())
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def db(x: float) -> float:
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"""线性转 dBFS。"""
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return 20 * np.log10(max(float(x), 1e-7))
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def find_monitor() -> str:
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"""找数字输出的 monitor 名字。"""
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out = subprocess.run(["pw-dump"], capture_output=True, text=True, timeout=20).stdout
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for line in out.splitlines():
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if '"node.name"' in line and "iec958" in line:
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return line.split('"')[3] + ".monitor"
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return ""
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def main() -> None:
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"""跑诊断。"""
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n = int(RATE * 3.5)
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x = np.zeros(n, dtype=np.float32)
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x[int(RATE * 1.0)] = 0.5
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wavfile.write(MAT, RATE, (x * 32767).astype(np.int16))
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mon = find_monitor()
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print("录音设备:", mon or "(没找到, 用默认)")
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args = ["pw-record", "--rate", str(RATE), "--channels", "2", "--format", "s16", str(REC)]
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if mon:
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args[1:1] = ["--target", mon]
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# 静音 Chrome(它会往默认输出送声音, 污染测量), 完事恢复
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subprocess.run(["wpctl", "set-mute", "90", "1"], capture_output=True, timeout=10)
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for wet in (0.0, 0.3):
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api("/api/wet", {"wet": wet})
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time.sleep(0.3)
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REC.unlink(missing_ok=True)
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rec = subprocess.Popen(args)
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time.sleep(0.6)
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subprocess.run(["pw-play", "--target", "collaplex_vsink", str(MAT)], timeout=30)
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time.sleep(0.8)
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rec.terminate()
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rec.wait(timeout=5)
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_r, data = wavfile.read(REC)
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mono = data[:, 0].astype(np.float64) / 32768.0
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pk = int(np.argmax(np.abs(mono)))
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print(f"\n湿量 {wet:.2f}: 主峰 @ {pk / RATE * 1000:.1f} ms, {db(abs(mono[pk])):.1f} dBFS")
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seg: list[float] = []
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for k in range(1, 61):
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a = pk + int(RATE * 0.02 * (k - 1))
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b = pk + int(RATE * 0.02 * k)
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if b > len(mono):
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break
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seg.append(db(np.max(np.abs(mono[a:b]))))
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print(" 主峰后每 20ms 包络(dBFS):")
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print(" ", " ".join(f"{v:.0f}" for v in seg[:40]))
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api("/api/wet", {"wet": 0.3})
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subprocess.run(["wpctl", "set-mute", "90", "0"], capture_output=True, timeout=10)
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print("\n(湿量恢复 0.3, Chrome 已取消静音)")
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main()
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