public void compress(List <Spectrum> spectrumGroup, TempScanSZDPD ts)
{
List <int[]> mzListGroup = new List <int[]>();
//Intensity数组会直接合并为一个数组
List <float> intListAllGroup = new List <float>();
for (int i = 0; i < spectrumGroup.Count; i++)
{
BinaryDataDouble mzData = spectrumGroup[i].getMZArray().data;
BinaryDataDouble intData = spectrumGroup[i].getIntensityArray().data;
List <int> mzList = new List <int>();
List <float> intensityList = new List <float>();
var dataCount = mzData.Count;
int[] mzArray = new int[dataCount];
int j = 0;
for (int t = 0; t < mzData.Count; t++)
{
if (jobInfo.jobParams.ignoreZeroIntensity && intData[t] == 0)
{
continue;
}
int mz = Convert.ToInt32(mzData[t] * mzPrecision);
mzArray[j] = mz;
if (jobInfo.jobParams.log2)
{
intensityList.Add(Convert.ToSingle(Math.Round(Math.Log(intData[t]) / log2, 3))); //取log10并且精确到小数点后3位
}
else
{
intensityList.Add(Convert.ToSingle(Math.Round(intData[t], 1))); //精确到小数点后一位
}
j++;
}
//空光谱的情况下会填充一个mz=0,intensity=0的点
if (j == 0)
{
mzListGroup.Add(new int[] { 0 });
intensityList.Add(0);
}
else
{
int[] mzSubArray = new int[j];
Array.Copy(mzArray, mzSubArray, j);
mzListGroup.Add(mzSubArray);
}
//说明是一帧空光谱,那么直接在Aird文件中抹除这一帧的信息
intListAllGroup.AddRange(intensityList);
}
Layers layers = StackCompressUtil.stackEncode(mzListGroup, mzListGroup.Count == Math.Pow(2, jobInfo.jobParams.digit));
// List<int[]> temp = StackCompressUtil.stackDecode(layers);
//使用SZDPD对mz进行压缩
ts.mzArrayBytes = layers.mzArray;
ts.tagArrayBytes = layers.tagArray;
ts.intArrayBytes = CompressUtil.zlibEncoder(intListAllGroup.ToArray());
}
//注意:本函数会操作startPosition这个全局变量
public void addToIndex(BlockIndex index, object tempScan)
{
if (jobInfo.jobParams.useStackZDPD())
{
TempScanSZDPD ts = (TempScanSZDPD)tempScan;
index.nums.AddRange(ts.nums);
index.rts.AddRange(ts.rts);
index.tics.AddRange(ts.tics);
if (jobInfo.jobParams.includeCV)
{
index.cvList.AddRange(ts.cvs);
}
index.mzs.Add(ts.mzArrayBytes.Length);
index.ints.Add(ts.intArrayBytes.Length);
index.tags.Add(ts.tagArrayBytes.Length);
startPosition = startPosition + ts.mzArrayBytes.Length + ts.tagArrayBytes.Length + ts.intArrayBytes.Length;
airdStream.Write(ts.mzArrayBytes, 0, ts.mzArrayBytes.Length);
airdStream.Write(ts.tagArrayBytes, 0, ts.tagArrayBytes.Length);
airdStream.Write(ts.intArrayBytes, 0, ts.intArrayBytes.Length);
}
else
{
TempScan ts = (TempScan)tempScan;
index.nums.Add(ts.num);
index.rts.Add(ts.rt);
index.tics.Add(ts.tic);
if (jobInfo.jobParams.includeCV)
{
index.cvList.Add(ts.cvs);
}
index.mzs.Add(ts.mzArrayBytes.Length);
index.ints.Add(ts.intArrayBytes.Length);
startPosition = startPosition + ts.mzArrayBytes.Length + ts.intArrayBytes.Length;
airdStream.Write(ts.mzArrayBytes, 0, ts.mzArrayBytes.Length);
airdStream.Write(ts.intArrayBytes, 0, ts.intArrayBytes.Length);
}
}
public void compressMS1(BlockIndex index)
{
int layers = (int)Math.Pow(2, converter.jobInfo.jobParams.digit); //计算堆叠层数
int iter = converter.ms1List.Count % layers == 0 ? (converter.ms1List.Count / layers) : (converter.ms1List.Count / layers + 1); //计算循环周期
if (converter.jobInfo.jobParams.threadAccelerate)
{
Hashtable table = Hashtable.Synchronized(new Hashtable());
//使用多线程处理数据提取与压缩
Parallel.For(0, iter, (i, ParallelLoopState) =>
{
converter.jobInfo.log(null, "MS1:" + i + "/" + iter);
List <float> rts = new List <float>();
List <int> nums = new List <int>();
List <long> tics = new List <long>();
List <List <CV> > cvs = new List <List <CV> >();
List <Spectrum> spectrumGroup = new List <Spectrum>();
for (int k = 0; k < layers; k++)
{
int realNum = i * layers + k;
if (realNum >= converter.ms1List.Count)
{
break;
}
TempIndex scanIndex = converter.ms1List[realNum];
rts.Add(scanIndex.rt);
nums.Add(scanIndex.num);
tics.Add(scanIndex.tic);
if (converter.jobInfo.jobParams.includeCV)
{
cvs.Add(scanIndex.cvList);
}
spectrumGroup.Add(converter.spectrumList.spectrum(scanIndex.num, true));
}
TempScanSZDPD ts = new TempScanSZDPD(nums, rts, tics);
if (converter.jobInfo.jobParams.includeCV)
{
ts.cvs = cvs;
}
converter.compress(spectrumGroup, ts);
table.Add(i, ts);
});
converter.outputWithOrder(table, index);
}
else
{
for (int i = 0; i < iter; i++)
{
converter.jobInfo.log(null, "MS1:" + i + "/" + iter);
List <float> rts = new List <float>();
List <int> nums = new List <int>();
List <long> tics = new List <long>();
List <List <CV> > cvs = new List <List <CV> >();
List <Spectrum> spectrumGroup = new List <Spectrum>();
for (int k = 0; k < layers; k++)
{
int realNum = i * layers + k;
if (realNum >= converter.ms1List.Count)
{
break;
}
TempIndex scanIndex = converter.ms1List[realNum];
rts.Add(scanIndex.rt);
nums.Add(scanIndex.num);
tics.Add(scanIndex.tic);
if (converter.jobInfo.jobParams.includeCV)
{
cvs.Add(scanIndex.cvList);
}
spectrumGroup.Add(converter.spectrumList.spectrum(scanIndex.num, true));
}
TempScanSZDPD ts = new TempScanSZDPD(nums, rts, tics);
if (converter.jobInfo.jobParams.includeCV)
{
ts.cvs = cvs;
}
converter.compress(spectrumGroup, ts);
converter.addToIndex(index, ts);
}
}
}