c语言使用fopen_s怎么求wav的时域信号功率谱

你可以使用以下代码来求wav的时域信号功率谱：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define BUFFER_SIZE 4096

int main(int argc, char* argv[])
{
    if(argc < 2)
    {
        printf("Usage: %s <input_wav_file>\n", argv[0]);
        return 1;
    }

    FILE* input_file;
    errno_t err = fopen_s(&input_file, argv[1], "rb");
    if(err != 0)
    {
        printf("Error opening input file: %s\n", argv[1]);
        return 1;
    }

    char buffer[BUFFER_SIZE];
    int bytes_read;
    int num_samples = 0;
    int sample_rate = 0;
    short sample;

    // Read the header of the WAV file
    bytes_read = fread(buffer, sizeof(char), 44, input_file);
    if(bytes_read != 44)
    {
        printf("Error reading WAV header\n");
        fclose(input_file);
        return 1;
    }

    // Parse the header to get the number of samples and the sample rate
    num_samples = *(int*)(buffer + 40);
    sample_rate = *(int*)(buffer + 24);

    // Allocate memory for the audio data
    short* audio_data = (short*)malloc(num_samples * sizeof(short));
    if(audio_data == NULL)
    {
        printf("Error allocating memory for audio data\n");
        fclose(input_file);
        return 1;
    }

    // Read the audio data from the file
    bytes_read = fread(audio_data, sizeof(short), num_samples, input_file);
    if(bytes_read != num_samples)
    {
        printf("Error reading audio data\n");
        free(audio_data);
        fclose(input_file);
        return 1;
    }

    fclose(input_file);

    // Compute the power spectrum of the audio data
    int num_bins = BUFFER_SIZE / 2;
    double* power_spectrum = (double*)malloc(num_bins * sizeof(double));
    if(power_spectrum == NULL)
    {
        printf("Error allocating memory for power spectrum\n");
        free(audio_data);
        return 1;
    }

    int window_size = BUFFER_SIZE;
    int hop_size = BUFFER_SIZE / 2;
    int num_frames = (num_samples - window_size) / hop_size + 1;

    for(int i = 0; i < num_frames; i++)
    {
        int start_index = i * hop_size;
        int end_index = start_index + window_size;

        if(end_index > num_samples)
        {
            end_index = num_samples;
        }

        // Apply a window function to the audio data
        for(int j = start_index; j < end_index; j++)
        {
            audio_data[j] *= 0.5 * (1 - cos(2 * M_PI * (j - start_index) / (window_size - 1)));
        }

        // Compute the FFT of the windowed audio data
        double* real_part = (double*)malloc(window_size * sizeof(double));
        double* imag_part = (double*)malloc(window_size * sizeof(double));
        for(int j = 0; j < window_size; j++)
        {
            real_part[j] = audio_data[start_index + j];
            imag_part[j] = 0;
        }
        fft(real_part, imag_part, window_size);

        // Compute the power spectrum of the FFT
        for(int j = 0; j < num_bins; j++)
        {
            double magnitude = sqrt(real_part[j] * real_part[j] + imag_part[j] * imag_part[j]);
            power_spectrum[j] += magnitude * magnitude / (window_size * hop_size);
        }

        free(real_part);
        free(imag_part);
    }

    // Free memory
    free(audio_data);

    // Print the power spectrum to stdout
    for(int i = 0; i < num_bins; i++)
    {
        double frequency = (double)i * sample_rate / BUFFER_SIZE;
        printf("%f %f\n", frequency, power_spectrum[i]);
    }

    free(power_spectrum);

    return 0;
}

// Computes the FFT of the given real and imaginary arrays of length n
void fft(double* real, double* imag, int n)
{
    if(n == 1)
    {
        return;
    }

    double* even_real = (double*)malloc(n / 2 * sizeof(double));
    double* even_imag = (double*)malloc(n / 2 * sizeof(double));
    double* odd_real = (double*)malloc(n / 2 * sizeof(double));
    double* odd_imag = (double*)malloc(n / 2 * sizeof(double));
    for(int i = 0; i < n / 2; i++)
    {
        even_real[i] = real[2 * i];
        even_imag[i] = imag[2 * i];
        odd_real[i] = real[2 * i + 1];
        odd_imag[i] = imag[2 * i + 1];
    }

    fft(even_real, even_imag, n / 2);
    fft(odd_real, odd_imag, n / 2);

    for(int i = 0; i < n / 2; i++)
    {
        double angle = -2 * M_PI * i / n;
        double cos_angle = cos(angle);
        double sin_angle = sin(angle);
        real[i] = even_real[i] + cos_angle * odd_real[i] - sin_angle * odd_imag[i];
        imag[i] = even_imag[i] + cos_angle * odd_imag[i] + sin_angle * odd_real[i];
        real[i + n / 2] = even_real[i] - cos_angle * odd_real[i] + sin_angle * odd_imag[i];
        imag[i + n / 2] = even_imag[i] - cos_angle * odd_imag[i] - sin_angle * odd_real[i];
    }

    free(even_real);
    free(even_imag);
    free(odd_real);
    free(odd_imag);
}

这个代码使用了一个缓冲区来读取WAV文件的数据，并对缓冲区中的数据进行窗口函数和FFT处理，然后计算功率谱。该代码还使用了一个自定义的FFT函数，用于计算实数和虚数数组的FFT。