提取wav文件频谱的java代码

以下是提取WAV文件频谱的Java代码示例：

import javax.sound.sampled.*;
import java.io.*;

public class SpectrumAnalyzer {
    public static void main(String[] args) {
        try {
            File file = new File("audio.wav"); // Replace with your WAV file path
            AudioInputStream audioStream = AudioSystem.getAudioInputStream(file);
            AudioFormat format = audioStream.getFormat();
            byte[] bytes = new byte[(int) (audioStream.getFrameLength() * format.getFrameSize())];
            audioStream.read(bytes);

            int[] audioData = new int[bytes.length / 2];
            for (int i = 0, j = 0; i < bytes.length; i += 2, j++) {
                audioData[j] = ((bytes[i] & 0xff) | (bytes[i + 1] << 8));
            }

            int sampleRate = (int) format.getSampleRate();
            int numChannels = format.getChannels();

            FFT fft = new FFT(audioData.length, sampleRate);

            double[] magnitude = new double[audioData.length];
            double[] phase = new double[audioData.length];

            fft.fft(audioData, magnitude, phase);

            double[] frequencies = fft.getFrequencyArray();
            double[] power = new double[frequencies.length];

            for (int i = 0; i < frequencies.length; i++) {
                power[i] = 20 * Math.log10(magnitude[i]);
            }

            // Do something with the power array, e.g. plot it on a graph
        } catch (UnsupportedAudioFileException | IOException e) {
            e.printStackTrace();
        }
    }
}

class FFT {
    private final int n, m;
    private final double[] cos;
    private final double[] sin;
    private final double[] window;

    public FFT(int n, int sampleRate) {
        this.n = n;
        this.m = (int) (Math.log(n) / Math.log(2));

        cos = new double[n / 2];
        sin = new double[n / 2];
        window = new double[n];

        for (int i = 0; i < n / 2; i++) {
            cos[i] = Math.cos(-2 * Math.PI * i / n);
            sin[i] = Math.sin(-2 * Math.PI * i / n);
        }

        for (int i = 0; i < n; i++) {
            window[i] = 0.5 * (1 - Math.cos(2 * Math.PI * i / (n - 1)));
        }
    }

    public void fft(int[] x, double[] magnitude, double[] phase) {
        for (int i = 0; i < n; i++) {
            x[i] *= window[i];
        }

        for (int i = 0; i < n; i++) {
            int j = Integer.reverse(i) >>> (32 - m);
            if (j > i) {
                int temp = x[i];
                x[i] = x[j];
                x[j] = temp;
            }
        }

        for (int s = 2; s <= n; s *= 2) {
            for (int i = 0; i < n; i += s) {
                for (int j = 0; j < s / 2; j++) {
                    int tIndex = n / s * j;
                    int index1 = i + j;
                    int index2 = i + j + s / 2;

                    double tCos = cos[tIndex];
                    double tSin = sin[tIndex];
                    double tRe = tCos * x[index2] + tSin * x[index2 + 1];
                    double tIm = tCos * x[index2 + 1] - tSin * x[index2];

                    x[index2] = x[index1] - tRe;
                    x[index2 + 1] = x[index1 + 1] - tIm;
                    x[index1] += tRe;
                    x[index1 + 1] += tIm;
                }
            }
        }

        for (int i = 0; i < n / 2; i++) {
            magnitude[i] = Math.sqrt(x[2 * i] * x[2 * i] + x[2 * i + 1] * x[2 * i + 1]);
            phase[i] = Math.atan2(x[2 * i + 1], x[2 * i]);
        }
    }

    public double[] getFrequencyArray() {
        double[] frequency = new double[n / 2];
        for (int i = 0; i < n / 2; i++) {
            frequency[i] = i * 1.0 * sampleRate / n;
        }
        return frequency;
    }
}

该代码使用FFT算法计算了WAV文件的频谱，输出了幅度和相位数组，可以进一步处理这些数组并绘制频谱图。请注意，此代码仅适用于单声道WAV文件。如果要处理立体声文件，请根据需要修改代码。