写一个可以直接运行的java代码获取wav文件的频谱

以下是一个可以获取wav文件频谱的Java代码示例：

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

public class WavSpectrumAnalyzer {

    public static void main(String[] args) {
        String wavFileName = "test.wav"; // 替换为你的wav文件名
        try {
            AudioInputStream audioInputStream = AudioSystem.getAudioInputStream(new File(wavFileName));
            byte[] audioBytes = new byte[(int) (audioInputStream.getFrameLength() * audioInputStream.getFormat().getFrameSize())];
            audioInputStream.read(audioBytes);

            int numChannels = audioInputStream.getFormat().getChannels();
            int sampleSize = audioInputStream.getFormat().getSampleSizeInBits();
            double sampleRate = audioInputStream.getFormat().getSampleRate();

            // 将字节数组转换为double数组
            double[] audioData = new double[audioBytes.length / (sampleSize / 8)];
            int index = 0;
            for (int i = 0; i < audioBytes.length; i += (sampleSize / 8)) {
                double sample = 0.0;
                if (sampleSize == 8) {
                    sample = audioBytes[i];
                } else {
                    sample = ((audioBytes[i + 1] & 0xff) << 8) | (audioBytes[i] & 0xff);
                }
                if (numChannels == 2) {
                    i++;
                }
                audioData[index++] = sample / 32768.0;
            }

            // 计算FFT
            int fftSize = 1024;
            double[] fftData = new double[fftSize];
            Complex[] fftComplex = new Complex[fftSize];
            for (int i = 0; i < fftSize; i++) {
                fftData[i] = audioData[i];
                fftComplex[i] = new Complex(fftData[i], 0.0);
            }
            fftComplex = FFT.fft(fftComplex);

            // 绘制频谱
            int width = 800;
            int height = 600;
            StdDraw.setCanvasSize(width, height);
            StdDraw.setXscale(0, sampleRate / 2);
            StdDraw.setYscale(-100, 100);
            StdDraw.setPenRadius(0.005);
            for (int i = 0; i <= fftSize / 2; i++) {
                double freq = i * sampleRate / fftSize;
                double magnitude = 10 * Math.log10(fftComplex[i].abs() * fftComplex[i].abs() / (fftSize * fftSize));
                StdDraw.point(freq, magnitude);
            }
        } catch (Exception ex) {
            ex.printStackTrace();
        }
    }
}

class Complex {
    public double re, im;

    public Complex(double real, double imag) {
        re = real;
        im = imag;
    }

    public Complex plus(Complex b) {
        double real = re + b.re;
        double imag = im + b.im;
        return new Complex(real, imag);
    }

    public Complex minus(Complex b) {
        double real = re - b.re;
        double imag = im - b.im;
        return new Complex(real, imag);
    }

    public Complex times(Complex b) {
        double real = re * b.re - im * b.im;
        double imag = re * b.im + im * b.re;
        return new Complex(real, imag);
    }

    public double abs() {
        return Math.sqrt(re * re + im * im);
    }
}

class FFT {
    public static Complex[] fft(Complex[] x) {
        int N = x.length;

        // 偶数项和奇数项分别进行FFT
        Complex[] even = new Complex[N / 2];
        Complex[] odd = new Complex[N / 2];
        for (int k = 0; k < N / 2; k++) {
            even[k] = x[2 * k];
            odd[k] = x[2 * k + 1];
        }
        Complex[] q = fft(even);
        Complex[] r = fft(odd);

        // 合并两个FFT结果
        Complex[] y = new Complex[N];
        for (int k = 0; k < N / 2; k++) {
            double kth = -2 * k * Math.PI / N;
            Complex wk = new Complex(Math.cos(kth), Math.sin(kth));
            y[k] = q[k].plus(wk.times(r[k]));
            y[k + N / 2] = q[k].minus(wk.times(r[k]));
        }
        return y;
    }
}

注意，这个代码使用了一个名为StdDraw的类，用于绘制频谱图。如果你没有这个类，可以到官网下载：https://introcs.cs.princeton.edu/java/stdlib/StdDraw.java.html

此外，代码中还使用了一个名为FFT的类，用于实现快速傅里叶变换。如果你对FFT算法不熟悉，可以参考这篇文章：https://www.jianshu.com/p/5a5e5a8c5e5b

最后，如果你想要更好的频谱分析效果，可以尝试使用更大的FFT窗口大小，更高的采样率，以及其他的信号处理技术。