吉他调音器

复制import numpy as np
import pyaudio
import struct

# 实时音高检测（自相关法）
CHUNK = 1024
RATE = 44100

def autocorrelation(signal):
    """自相关函数，检测基频"""
    n = len(signal)
    result = np.correlate(signal, signal, mode='full')
    result = result[n-1:]  # 取后半段
    # 忽略第一个峰值（自身相关），找第二个峰值
    diffs = np.diff(result)
    peaks = np.where((diffs[:-1] > 0) & (diffs[1:] < 0))[0] + 1
    if len(peaks) < 2:
        return 0
    # 第二个峰值的索引对应周期
    period = peaks[1] - peaks[0]
    return RATE / period if period > 0 else 0

p = pyaudio.PyAudio()
stream = p.open(format=pyaudio.paInt16, channels=1, rate=RATE,
                input=True, frames_per_buffer=CHUNK)

print("检测中... 弹奏吉他弦")
try:
    for _ in range(10):  # 采样10次
        data = stream.read(CHUNK)
        signal = np.frombuffer(data, dtype=np.int16).astype(np.float32)
        freq = autocorrelation(signal)
        if freq > 80:  # 吉他最低音约82Hz
            print(f"检测频率: {freq:.1f} Hz")
finally:
    stream.stop_stream()
    stream.close()
    p.terminate()

复制package main

import (
	"fmt"
	"math"
	"github.com/gordonklaus/portaudio"
)

func autocorrelation(signal []float64) float64 {
	n := len(signal)
	var maxCorr, secondMaxIdx float64
	// 简化自相关：找第二个峰值
	for lag := 1; lag < n/2; lag++ {
		var sum float64
		for i := 0; i < n-lag; i++ {
			sum += signal[i] * signal[i+lag]
		}
		if sum > maxCorr {
			secondMaxIdx = float64(lag)
			maxCorr = sum
		}
	}
	if secondMaxIdx == 0 {
		return 0
	}
	return 44100.0 / secondMaxIdx
}

func main() {
	portaudio.Initialize()
	defer portaudio.Terminate()

	stream, _ := portaudio.OpenDefaultStream(1, 0, 44100, 1024)
	defer stream.Close()
	stream.Start()
	defer stream.Stop()

	buffer := make([]float64, 1024)
	fmt.Println("检测中...")
	for i := 0; i < 5; i++ {
		stream.Read()
		// 假设 buffer 已填充音频数据
		freq := autocorrelation(buffer)
		if freq > 80 {
			fmt.Printf("频率: %.1f Hz\n", freq)
		}
	}
}

复制// 浏览器中实时音高检测（Web Audio API）
async function startPitchDetection() {
    const stream = await navigator.mediaDevices.getUserMedia({ audio: true });
    const audioCtx = new AudioContext();
    const source = audioCtx.createMediaStreamSource(stream);
    const analyser = audioCtx.createAnalyser();
    analyser.fftSize = 2048;
    source.connect(analyser);

    const bufferLength = analyser.frequencyBinCount;
    const dataArray = new Float32Array(bufferLength);

    function detectPitch() {
        analyser.getFloatTimeDomainData(dataArray);
        // 自相关法找基频
        let maxCorr = 0;
        let period = 0;
        for (let lag = 1; lag < dataArray.length / 2; lag++) {
            let sum = 0;
            for (let i = 0; i < dataArray.length - lag; i++) {
                sum += dataArray[i] * dataArray[i + lag];
            }
            if (sum > maxCorr) {
                maxCorr = sum;
                period = lag;
            }
        }
        if (period > 0) {
            const freq = audioCtx.sampleRate / period;
            if (freq > 80) {
                console.log(`检测频率: ${freq.toFixed(1)} Hz`);
            }
        }
        requestAnimationFrame(detectPitch);
    }
    detectPitch();
}

startPitchDetection();