public void DataProcess(int time = 100, int samplesize = 128)
{
processbar = 10;
//拆分数据，time即采样间隔时间，单位毫秒，samplesize为fft结果的数据数量=_spec，采样数据数量为sanplesize*2，取每个间隔分段的钱samplesize位
int SamplePerFrame = time; //Mathf.FloorToInt ( time*_audio.clip.frequency / 1000);//每帧间隔的数据数量
//从第一个非0数据开始
int si = 0;
bool offsetfound = false;
while (!offsetfound && si < samples.Length)
{
si++;
if (samples [si] != 0)
{
offsetfound = true;
}
}
if (TxTProcess != null)
{
TxTProcess.text = "processing 10 %";
}
float offset = si * _audio.clip.frequency; /////////////////第一个非0数据所在的时间
int NumOfFrame = Mathf.FloorToInt((samples.Length - si) / SamplePerFrame); //拆分出的数据数量，相当于帧数
freqlength = Mathf.FloorToInt(samplesize * _audio.clip.frequency / AudioSettings.outputSampleRate); //有效频率数量
fft.FFTManagerinit(samplesize * 2, FFT.datafilter.unityspec); //初始化fft
Debug.LogError("offset=" + si + " = " + offset + "SamplePerFrame= " + SamplePerFrame + "--systemtime=" + Time.realtimeSinceStartup);
for (int i = 0; i < NumOfFrame; i++)
{
//帧数
float[] separatedData = new float[samplesize * 2]; //每次采样的数据数量，为了保证fft结果数量为samplesize，数量取两倍
int startindex = si + i * SamplePerFrame; //开始采样的编号
for (int j = 0; j < samplesize * 2; j++)
{
//采样samplesize*2次
if (startindex + j < samples.Length)
{
//编号有效
separatedData [j] = samples [startindex + j];
}
else
{
//超出范围则置0
separatedData [j] = 0;
}
}
float [] result = fft.CalNFFT(fft.windowBlackman(separatedData)); //将采样数据做fft，长度为samplesize
float[] bands = new float[_numBands + 1];
bands = CalcCurrentFrameAvg(result); //按频段拆分，计算当前帧平均值，存入band
bands [_numBands] = (float)startindex / _audio.clip.frequency; //startindex所在时间，单位为秒
BeatAnalysisManager.MAL.Add(bands); //存入MAL
if (TxTProcess != null)
{
processbar = Mathf.Min(Mathf.RoundToInt(90f * i / NumOfFrame) + 10, 100);
TxTProcess.text = "processing " + processbar + " %";
}
} //end 采样samplesize*2次
Debug.LogError("end process--systemtime=" + Time.realtimeSinceStartup);
} //end dataprocess ，band存入MAL
