iphone - 如何在iphone中查看FFT结果？

Question

我已经使用 OouraFFTl 对音频文件进行了 FFT。如何检查采样输出是否正确或错误。有什么更好、更简单的方法来检查它。这是我的代码。

MyAudioFile  *audioFile = [[MyAudioFile alloc]init];
OSStatus result = [audioFile open:var ofType:@"wav"];
int numFrequencies=16384;
int kNumFFTWindows=10;

OouraFFT *myFFT = [[OouraFFT alloc] initForSignalsOfLength:numFrequencies*2    andNumWindows:kNumFFTWindows];
for(long i=0; i<myFFT.dataLength; i++)
 {
myFFT.inputData[i] = (double)audioFile.audioData[i];
} 
 [myFFT calculateWelchPeriodogramWithNewSignalSegment];
NSLog(@"the spectrum data 1 is  %f ",myFFT.spectrumData[1]);
NSLog(@"the spectrum data 2 is  %f",myFFT.spectrumData[2]);
NSLog(@"the spectrum data 8192 is  %f ",myFFT.spectrumData[8192]);

我创建了 MyAudioFile 类，其中包含

    -(OSStatus)open:(NSString *)fileName ofType:(NSString *)fileType{
OSStatus result = -1;

 CFStringRef filePath=fileName;

  CFURLRef audioFileURL = CFURLCreateWithFileSystemPath(kCFAllocatorDefault,      (CFStringRef)filePath, kCFURLPOSIXPathStyle, false);
 //open audio file
 result = AudioFileOpenURL (audioFileURL, kAudioFileReadPermission, 0, &mAudioFile);
 if (result == noErr) {
 //get  format info
 UInt32 size = sizeof(mASBD);

result = AudioFileGetProperty(mAudioFile, kAudioFilePropertyDataFormat, &size, &mASBD);

UInt32 dataSize = sizeof packetCount;
result = AudioFileGetProperty(mAudioFile, kAudioFilePropertyAudioDataPacketCount, &dataSize, &packetCount);
NSLog([NSString stringWithFormat:@"File Opened, packet Count: %d", packetCount]);

UInt32 packetsRead = packetCount;
UInt32 numBytesRead = -1;
if (packetCount > 0) { 
    //allocate  buffer
    audioData = (SInt16*)malloc( 2 *packetCount);
    //read the packets
    result = AudioFileReadPackets (mAudioFile, false, &numBytesRead, NULL, 0, &packetsRead,  audioData); 
    NSLog([NSString stringWithFormat:@"Read %d  bytes,  %d packets", numBytesRead, packetsRead]);
}
}
  else
  NSLog([NSString stringWithFormat:@"Could not open file: %@", filePath]);


CFRelease (audioFileURL);     
return result;
 }

Answer 1

您需要绘制 FFT 输出的幅度。我不熟悉您的编程语言，但在 Python 中您会使用诸如 plot(abs(fft(a))) 之类的东西。对于静默输入，输出应全为零。对于正弦波输入，您应该看到两个尖峰:

对于真实信号，尖峰从左到右对称。如果您正在执行 real FFT ，但是(计算效率更高)您只会得到图的左半部分作为输出，因为它忽略了冗余镜像。

如果频率较高，尖峰将更靠近中心。如果the frequency is perfectly in sync with the chunk size ，尖峰将只有一个点宽，其他一切都将非常接近 0。否则它将有一个像上面一样逐渐变细的“裙子”。