private IExtractResult ComputeByFiles(string[] files)
{
IExtractResultArray result = new ExtractResultArray("DRT");
IRasterDataProvider currPrd = null;
for (int i = 0; i < files.Length; i++)
{
currPrd = GeoDataDriver.Open(files[i], null) as IRasterDataProvider;
if (currPrd != null)
{
try
{
IExtractResult temp = ComputeByCurrentRaster(currPrd, _progressTracker);
if (temp == null || (temp as FileExtractResult) == null)
{
continue;
}
result.Add(temp as FileExtractResult);
}
finally
{
currPrd.Dispose();
}
}
}
return(result);
}
private IExtractResult StatProcentRaster <T>(string fname, string statVector, Dictionary <string, Func <short, bool> > filters, Action <int, string> progressTracker, bool weight, float weightZoom)
{
string title;
string[] colDescs;
IStatResult[] results = StatProcentRasterToStatResult(fname, statVector, filters, progressTracker, out title, out colDescs, false, weight, weightZoom);
string outFileIdentify = GetStringArgument("OutFileIdentify");
string[] outFileIdentifys = new string[] { outFileIdentify, outFileIdentify.Substring(1) + "P" };
string productIdentify = _subProductDef.ProductDef.Identify;
IExtractResultArray array = new ExtractResultArray("FIR");
string filename = null;
for (int i = 0; i < results.Length; i++)
{
if (i >= outFileIdentifys.Length)
{
break;
}
filename = StatResultToFile(new string[] { fname }, results[i], productIdentify, outFileIdentifys[i], title + colDescs[i] + "统计", null, 1, false, 1);
array.Add(new FileExtractResult(outFileIdentify, filename));
}
return(array);
}
public override IExtractResult Make(Action <int, string> progressTracker, IContextMessage contextMessage)
{
if (_argumentProvider.GetArg("SelectedPrimaryFiles") == null)
{
return(null);
}
string[] binWater = _argumentProvider.GetArg("SelectedPrimaryFiles") as string[];
for (int i = 0; i < binWater.Length; i++)
{
if (!File.Exists(binWater[i]))
{
return(null);
}
}
_contextMessage = contextMessage;
if (_argumentProvider == null)
{
return(null);
}
if (_argumentProvider.GetArg("AlgorithmName") == null)
{
return(null);
}
IFileExtractResult[] flodFiles = null;
IExtractResult fldsFile = null;
if (_argumentProvider.GetArg("AlgorithmName").ToString() == "DayFLDSAlgorithm")
{
flodFiles = GreateFLODFile(binWater, progressTracker);
if (flodFiles == null || flodFiles.Length == 0 || string.IsNullOrEmpty(flodFiles[0].FileName))
{
return(null);
}
List <string> toFLDSFiles = new List <string>();
foreach (IFileExtractResult item in flodFiles)
{
toFLDSFiles.Add(item.FileName);
}
fldsFile = FLODLastFiles(toFLDSFiles.ToArray(), progressTracker);
}
else if (_argumentProvider.GetArg("AlgorithmName").ToString() == "FloodFLDSAlgorithm")
{
fldsFile = FLODLastFiles(binWater, progressTracker);
}
if (fldsFile != null)
{
IExtractResultArray array = new ExtractResultArray("洪涝持续天数");
if (flodFiles != null && flodFiles.Length != 0)
{
foreach (IFileExtractResult item in flodFiles)
{
(item as IFileExtractResult).SetDispaly(false);
array.Add(item as IExtractResultBase);
}
}
array.Add(fldsFile as IExtractResultBase);
return(array);
}
return(null);
}
private IExtractResultArray CalcGFRF(string[] files)
{
string datFname = GetDatFilename(files);
string GFInfoList = GenGFILfname(files);
using (StreamWriter sw = new StreamWriter(GFInfoList, false, Encoding.Default))
{
sw.WriteLine("NO.\t" + "Latitude\t" + "Longitude\t" + "Size/ha\t" + "Temperature/K\t" + "Fire_Intensity\t" + "Reliability");
}
int[,] fireCountArray = InitValueArray();
int[] firPositionArray = null;
for (int i = 0; i < files.Length; i++)
{
firPositionArray = ProcessVectorToArray(files[i], GFInfoList);
int col, row;
foreach (int cr in firPositionArray)
{
row = cr / _datwidth;
col = (cr % _datwidth);
fireCountArray[row, col] += 1;
}
}
_firePointsCount = 0;
ProcessArrayToRaster(datFname, fireCountArray);
_argumentProvider.SetArg("SelectedPrimaryFiles", datFname);
IFileExtractResult GFRF = GFRFAlgorithm() as IFileExtractResult;
IExtractResultArray array = new ExtractResultArray("全球火点累计");
IFileExtractResult GFIL = new FileExtractResult("GFIL", GFInfoList, true);
GFIL.SetDispaly(false);
array.Add(GFRF);
array.Add(GFIL);
return(array);
}
public override IExtractResult Make(Action <int, string> progressTracker)
{
if (_argumentProvider == null)
{
return(null);
}
List <string> covertDegreeRegions = _argumentProvider.GetArg("CovertDegreeRegion") as List <string>;
if (_argumentProvider.GetArg("AlgorithmName") == null || covertDegreeRegions == null || covertDegreeRegions.Count == 0)
{
return(null);
}
if (_argumentProvider.GetArg("AlgorithmName").ToString() == "BCDF")
{
int count = covertDegreeRegions.Count;
ExtractResultArray results = new ExtractResultArray("BAG_BCDF");
for (int i = 0; i < count; i++)
{
float[] minmax = BAGStatisticHelper.GetCovertDegreeValue(covertDegreeRegions[i]);
FileExtractResult result = FREQAlgorithm(minmax[0], minmax[1]) as FileExtractResult;
results.Add(result);
}
return(results);
}
return(null);
}
private IExtractResult DVIAlgorithm2(Action <int, string> progressTracker)
{
IBandNameRaster bandNameRaster = _argumentProvider.DataProvider as IBandNameRaster;
int bandV = TryGetBandNo(bandNameRaster, "Visible"); //可见光
int bandNear = TryGetBandNo(bandNameRaster, "NearInfrared"); //近红外
if (bandV == -1 || bandNear == -1)
{
PrintInfo("通道序号设置不正确");
return(null);
}
int[] bandNos = new int[] { bandV, bandNear };
double visibleZoom = (double)_argumentProvider.GetArg("Visible_Zoom");
double nearInfrared = (double)_argumentProvider.GetArg("NearInfrared_Zoom");
double[] bandzoom = new double[] { visibleZoom, nearInfrared };
Dictionary <string, string> dic = Obj2Dic(_argumentProvider.GetArg("ArgumentSetting"));
string nearVisiableMinStr = dic.ContainsKey("NearVisableMin") ? dic["NearVisableMin"] : string.Empty;
string nearVisiableMaxStr = dic.ContainsKey("NearVisableMax") ? dic["NearVisableMax"] : string.Empty;
string visibleMinStr = dic.ContainsKey("VisibleMin") ? dic["VisibleMin"] : string.Empty;
float nearVisiableMin = float.Parse(nearVisiableMinStr);
float nearVisiableMax = float.Parse(nearVisiableMaxStr);
float visibleMin = float.Parse(visibleMinStr);
float[] cloudyArgs = new float[] { visibleMin, nearVisiableMax, nearVisiableMin };
Int16 defCloudy = (Int16)_argumentProvider.GetArg("defCloudy");
float zoom = (ushort)_argumentProvider.GetArg("resultZoom");
zoom = zoom == 0f ? 1000 : zoom;
string[] aois = _argumentProvider.GetArg("AOITemplate") as string[];
string aoiTemplate = (aois == null || aois.Length == 0) ? null : aois[0];
string[] inputFiles = GetStringArray("RasterFile");
if (inputFiles == null || inputFiles.Length == 0)
{
PrintInfo("没有设置输入数据");
return(null);
}
bool isFitterCloud;
if (!bool.TryParse(_argumentProvider.GetArg("isFilterCloudy").ToString(), out isFitterCloud))
{
PrintInfo("是否过滤云参数设置不正确！");
return(null);
}
IExtractResultArray results = new ExtractResultArray("NDVI");
foreach (string inputFile in inputFiles)
{
//计算NDVI
IExtractResult ret = CalcDVIAlgorithm2(inputFile, bandNos, zoom, bandzoom, cloudyArgs, defCloudy, isFitterCloud, aoiTemplate, progressTracker);
if (ret != null)
{
results.Add(ret as IExtractResultBase);
}
}
return(results);
}
private IExtractResult DVIAlgorithm1(Action <int, string> progressTracker)
{
IBandNameRaster bandNameRaster = _argumentProvider.DataProvider as IBandNameRaster;
int bandV = TryGetBandNo(bandNameRaster, "Visible"); //可见光
int bandNear = TryGetBandNo(bandNameRaster, "NearInfrared"); //近红外
int bandMid = TryGetBandNo(bandNameRaster, "MiddInfrared"); //中红外
int bandFar = TryGetBandNo(bandNameRaster, "FarInfrared11"); //远红外
if (bandV == -1 || bandNear == -1 || bandMid < 1 || bandFar < 1)
{
PrintInfo("通道序号设置不正确");
return(null);
}
int[] bandNos = new int[] { bandV, bandNear, bandMid, bandFar };
double visibleZoom = (double)_argumentProvider.GetArg("Visible_Zoom");
double nearInfrared = (double)_argumentProvider.GetArg("NearInfrared_Zoom");
double middZoom = (double)_argumentProvider.GetArg("MiddInfrared_Zoom");
double farZoom = (double)_argumentProvider.GetArg("FarInfrared11_Zoom");
double[] bandzoom = new double[] { visibleZoom, nearInfrared, middZoom, farZoom };
float NearInfraredCLMMin = float.Parse(_argumentProvider.GetArg("NearInfraredCLMMin").ToString());
float FarInfrared11CLMMax = float.Parse(_argumentProvider.GetArg("FarInfrared11CLMMax").ToString());
float FarInfrared1112CLMMin = float.Parse(_argumentProvider.GetArg("FarInfrared1112CLMMin").ToString());
float[] cloudyArgs = new float[] { NearInfraredCLMMin, FarInfrared11CLMMax, FarInfrared1112CLMMin };
Int16 defCloudy = (Int16)_argumentProvider.GetArg("defCloudy");
float zoom = (ushort)_argumentProvider.GetArg("resultZoom");
zoom = zoom == 0f ? 1000 : zoom;
string[] aois = _argumentProvider.GetArg("AOITemplate") as string[];
string aoiTemplate = (aois == null || aois.Length == 0) ? null : aois[0];
string[] inputFiles = GetStringArray("RasterFile");
if (inputFiles == null || inputFiles.Length == 0)
{
PrintInfo("没有设置输入数据");
return(null);
}
bool isFitterCloud;
if (!bool.TryParse(_argumentProvider.GetArg("isFilterCloudy").ToString(), out isFitterCloud))
{
PrintInfo("是否过滤云参数设置不正确！");
return(null);
}
IExtractResultArray results = new ExtractResultArray("NDVI");
foreach (string inputFile in inputFiles)
{
//计算NDVI
IExtractResult ret = CalcDVIAlgorithm1(inputFile, bandNos, zoom, bandzoom, cloudyArgs, defCloudy, isFitterCloud, aoiTemplate, progressTracker);
if (ret != null)
{
results.Add(ret as IExtractResultBase);
}
}
return(results);
}
private IExtractResult EDGEAlgorithm()
{
int band = (int)_argumentProvider.GetArg("band");
int smaping = (int)_argumentProvider.GetArg("Smaping");
float dataValue = (float)_argumentProvider.GetArg("dataValue");
bool isOutputUncompleted = (bool)_argumentProvider.GetArg("IsOutputUncompleted");
string[] files = GetStringArray("SelectedPrimaryFiles");
string extInfos = GetStringArgument("extinfo");
if (files == null || files.Length == 0)
{
return(null);
}
try
{
ExtractResultArray array = new ExtractResultArray("FLD");
IRasterDataProvider rdp = null;
string shpFile = null;
GenerateContourLines gcl = null;
FileExtractResult res = null;
RasterIdentify rid;
foreach (string file in files)
{
try
{
//生成等值线shp文件
shpFile = GenEDGEFiename(file);
gcl = new GenerateContourLines(_progressTracker, _contextMessage);
rdp = GeoDataDriver.Open(file, null) as IRasterDataProvider;
rid = new RasterIdentify(rdp);
if (rid.SubProductIdentify == "DBLV" && dataValue == 1)
{
dataValue = 0;
}
gcl.DoGenerateContourLines(rdp, band, _argumentProvider.AOI, new double[] { dataValue }, smaping, shpFile, isOutputUncompleted);
if (!File.Exists(shpFile))
{
PrintInfo(Path.GetFileName(file) + "：生成等值线数据失败。");
continue;
}
res = new FileExtractResult(_subProductDef.Identify, shpFile, true);
res.SetDispaly(false);
array.Add(res);
}
finally
{
rdp.Dispose();
}
}
return(array.PixelMappers == null || array.PixelMappers.Length == 0 ? null : array);
}
finally
{
}
}
private IExtractResult CalcNDVI(Action <int, string> progressTracker)
{
//参数准备
int bandV = (int)_argumentProvider.GetArg("Visible"); //可见光
int bandNear = (int)_argumentProvider.GetArg("NearInfrared"); //近红外
if (bandV == -1 || bandNear == -1)
{
PrintInfo("通道序号设置不正确");
return(null);
}
int[] bandNos = new int[] { bandV, bandNear };
double visibleZoom = (double)_argumentProvider.GetArg("Visible_Zoom");
double nearInfrared = (double)_argumentProvider.GetArg("NearInfrared_Zoom");
float zoom = (ushort)_argumentProvider.GetArg("resultZoom");
zoom = zoom == 0f ? 1000 : zoom;
string[] aois = _argumentProvider.GetArg("AOITemplate") as string[];
string aoiTemplate = aois == null ? null : aois[0];
string[] inputFiles = _argumentProvider.GetArg("RasterFile") as string[];
if (inputFiles == null || inputFiles.Length == 0)
{
PrintInfo("没有设置输入数据");
return(null);
}
IExtractResultArray results = new ExtractResultArray("NDVI");
foreach (string inputFile in inputFiles)
{
//计算NDVI
IExtractResult ret = CalcNDVI(inputFile, bandNos, zoom, aoiTemplate, progressTracker);
if (ret != null)
{
results.Add(ret as IExtractResultBase);
}
}
return(results);
}
public IExtractResult ComputeByFiles(string[] fnames)
{
if (_arg == null)
{
return(null);
}
IExtractResultArray resultAry = new ExtractResultArray(_identify);
IRasterExtracter <UInt16, Int16> extracter = new SimpleRasterExtracter <UInt16, Int16>();
foreach (string fname in fnames)
{
if (!IsSameTypeFile(fname))
{
continue;
}
IExtractResultBase result = ComputeSingleFile(fname, extracter, _arg.BandNos, _arg.Express);
if (result != null)
{
resultAry.Add(result);
}
}
return(resultAry);
}
private IExtractResult TauL55Algorithm()
{
IFileExtractResult U5TTResult = null;
string instanceIdentify = _argumentProvider.GetArg("OutFileIdentify") as string;
if (string.IsNullOrWhiteSpace(instanceIdentify))
{
return(null);
}
SubProductInstanceDef instance = FindSubProductInstanceDefs(instanceIdentify);
if (instance != null)
{
U5TTResult = ThemeGraphyResult(null) as IFileExtractResult;
IExtractResultArray array = new ExtractResultArray("气溶胶产品");
IFileExtractResult U5TIResult = new FileExtractResult("U5TI", _055TauFname, true);
U5TIResult.SetDispaly(false);
array.Add(U5TTResult);
array.Add(U5TIResult);
return(array);
}
return(null);
}
/// <summary>
/// 融合微波雪深文件 和 可见光雪云辨识文件更新雪深
/// </summary>
/// <param name="sdfilname"></param>
/// <param name="visfilename"></param>
/// <returns></returns>
private IFileExtractResult ComputeSD(string sdfilename, string visfilename)
{
List <RasterMaper> rms = null;
IRasterDataProvider outRaster = null;
IRasterDataProvider outClassRaster = null;//融合分类
rms = new List <RasterMaper>();
IRasterDataProvider inRaster1 = GeoDataDriver.Open(sdfilename) as IRasterDataProvider; //微波雪深数据
RasterMaper fileIn1 = new RasterMaper(inRaster1, new int[] { 1 });
rms.Add(fileIn1);
IRasterDataProvider inRaster2 = GeoDataDriver.Open(visfilename) as IRasterDataProvider;//可见云和雪判识结果
RasterMaper fileIn2 = new RasterMaper(inRaster2, new int[] { 1 });
rms.Add(fileIn2);
//林地覆盖率
string forestFile = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "SystemData\\ProductArgs\\MWS\\SnowArgFile\\china_forest._frac.dat");
IRasterDataProvider inRaster3 = GeoDataDriver.Open(forestFile) as IRasterDataProvider;
RasterMaper fileIn3 = new RasterMaper(inRaster3, new int[] { 1 });
rms.Add(fileIn3);
if (inRaster1.ResolutionX != inRaster3.ResolutionX)
{
PrintInfo("雪深数据分辨率与辅助数据分辨率0.1度不同！");
return(null);
}
string visFileName = GetFileName(new string[] { sdfilename }, _subProductDef.ProductDef.Identify, "MWVI", ".dat", null);
outRaster = CreateOutRaster(visFileName, enumDataType.Float, rms.ToArray(), inRaster2.ResolutionX);
//融合分类数据
string classFileName = GetFileName(new string[] { sdfilename }, _subProductDef.ProductDef.Identify, "MCVI", ".dat", null);
outClassRaster = CreateOutRaster(classFileName, enumDataType.Float, rms.ToArray(), inRaster2.ResolutionX);
double minX = outRaster.CoordEnvelope.MinX;
double minY = outRaster.CoordEnvelope.MinY;
double maxX = outRaster.CoordEnvelope.MaxX;
double maxY = outRaster.CoordEnvelope.MaxY;
int xLeft = (int)((minX - inRaster1.CoordEnvelope.MinX) / inRaster1.ResolutionX);
int yUp = (int)((inRaster1.CoordEnvelope.MaxY - maxY) / inRaster1.ResolutionY);
int xRight = (int)((maxX - inRaster1.CoordEnvelope.MinX) / inRaster1.ResolutionX);
int yDown = (int)((inRaster1.CoordEnvelope.MaxY - minY) / inRaster1.ResolutionX);
int xSize = xRight - xLeft;
int ySize = yDown - yUp;
float[] buffer = new float[xSize * ySize];
IRasterBand bandinRaster1 = inRaster1.GetRasterBand(1);
float[] sd = new float[xSize * ySize];
//float[] snowClass = new float[xSize * ySize];
unsafe
{
fixed(float *pointer = buffer)
{
IntPtr ptr = new IntPtr(pointer);
bandinRaster1.Read(xLeft, yUp, xSize, ySize, ptr, inRaster1.DataType, xSize, ySize);
for (int j = 0; j < xSize * ySize; j++)
{
sd[j] = buffer[j];
}
}
}
int visLeftX = (int)((minX - inRaster2.CoordEnvelope.MinX) / inRaster2.ResolutionX);
int visLeftY = (int)((inRaster2.CoordEnvelope.MaxY - maxY) / inRaster2.ResolutionY);
int visRightX = (int)((maxX - inRaster2.CoordEnvelope.MinX) / inRaster2.ResolutionX);
int visRightY = (int)((inRaster2.CoordEnvelope.MaxY - minY) / inRaster2.ResolutionX);
int visxSize = visRightX - visLeftX;
int visySize = visRightY - visLeftY;
Int16[] visbuffer = new Int16[visxSize * visySize];
IRasterBand bandinRaster2 = inRaster2.GetRasterBand(1);
Int16[] visSNW = new Int16[visxSize * visySize];
// float[] sdSnow = new float[outRaster.Width * outRaster.Height];
float[ ,] sdSnow = new float[2, outRaster.Width *outRaster.Height];//一维放融合雪深，二维放融合分类
unsafe
{
fixed(Int16 *pointer = visbuffer)
{
IntPtr ptr = new IntPtr(pointer);
bandinRaster2.Read(visLeftX, visLeftY, visxSize, visySize, ptr, inRaster2.DataType, visxSize, visySize);
for (int j = 0; j < visxSize * visySize; j++)
{
visSNW[j] = visbuffer[j];
}
}
}
//读取森林覆盖率;
int xforestLeft = (int)((minX - inRaster3.CoordEnvelope.MinX) / inRaster3.ResolutionX);
int yforestUp = (int)((inRaster3.CoordEnvelope.MaxY - maxY) / inRaster3.ResolutionY);
int xforestRight = (int)((maxX - inRaster3.CoordEnvelope.MinX) / inRaster3.ResolutionX);
int yforestDown = (int)((inRaster3.CoordEnvelope.MaxY - minY) / inRaster3.ResolutionX);
int xforestSize = xforestRight - xforestLeft;
int yforestSize = yforestDown - yforestUp;
Int16[] forestbuffer = new Int16[xforestSize * yforestSize];
IRasterBand bandinRaster3 = inRaster3.GetRasterBand(1);
Int16[] forestFrac = new Int16[xforestSize * yforestSize];
unsafe
{
fixed(Int16 *pointer = forestbuffer)
{
IntPtr ptr = new IntPtr(pointer);
bandinRaster3.Read(xforestLeft, yforestUp, xforestSize, yforestSize, ptr, inRaster3.DataType, xforestSize, yforestSize);
for (int j = 0; j < xforestSize * yforestSize; j++)
{
forestFrac[j] = forestbuffer[j];
}
}
}
int zoom = (int)(inRaster1.ResolutionX / inRaster2.ResolutionX);
try
{
for (int j = 0; j < xSize * ySize; j++) //低分的格子
{
if (((j + 1) % xSize == 0) && (j != xSize * ySize - 1)) //最后一列并且不是低分最后一个格子
{
int zoomcha = xSize * zoom - visxSize;
Int32[] index = new Int32[zoom * (zoom - zoomcha)];
for (int row = 0; row < zoom; row++) //行还是原来的zoom行
{
for (int col = 0; col < zoom - zoomcha; col++) //列比原来少 zoomcha 列
{
index[col + row * (zoom - zoomcha)] = (j / xSize * zoom * visxSize + j % xSize * zoom) + (row * visxSize) + col;
}
}
sdSnow = SDsnow(zoom - zoomcha, zoom, index, visSNW, sd[j], sdSnow, forestFrac[j]);
}
else
{
if ((j >= xSize * ySize - xSize) && (j != xSize * ySize - 1)) //最后一行并且不是低分最后一个格子
{
int zoomcha = ySize * zoom - visySize;
Int32[] index = new Int32[(zoom - zoomcha) * zoom];
for (int row = 0; row < zoom - zoomcha; row++) //行比原来少 zoomcha行
{
for (int col = 0; col < zoom; col++) //列还是原来列
{
index[col + row * zoom] = (j / xSize * zoom * visxSize + j % xSize * zoom) + (row * visxSize) + col;
}
}
sdSnow = SDsnow(zoom, zoom - zoomcha, index, visSNW, sd[j], sdSnow, forestFrac[j]);
}
else
{
if (j == xSize * ySize - 1) //低分的最后一个格子
{
int zoomcha = ySize * zoom - visySize;
Int32[] index = new Int32[(zoom - zoomcha) * (zoom - zoomcha)];
for (int row = 0; row < zoom - zoomcha; row++) //行比原来少 zoomcha行
{
for (int col = 0; col < zoom - zoomcha; col++) //列列比原来少 zoomcha 列
{
index[col + row * (zoom - zoomcha)] = (j / xSize * zoom * visxSize + j % xSize * zoom) + (row * visxSize) + col;
}
}
sdSnow = SDsnow(zoom - zoomcha, zoom - zoomcha, index, visSNW, sd[j], sdSnow, forestFrac[j]);
}
else
{
Int32[] index = new Int32[zoom * zoom];
for (int row = 0; row < zoom; row++)
{
for (int col = 0; col < zoom; col++)
{
index[col + row * zoom] = (j / xSize * zoom * visxSize + j % xSize * zoom) + (row * visxSize) + col;
}
}
sdSnow = SDsnow(zoom, zoom, index, visSNW, sd[j], sdSnow, forestFrac[j]);
}
}
}
}
}
catch (Exception ex)
{
PrintInfo(ex.Message);
}
float[] sdSnow1 = new float[outRaster.Width * outRaster.Height];
float[] sdclass = new float[outRaster.Width * outRaster.Height];
IExtractResultArray array = new ExtractResultArray("融合雪深分类");
for (int index = 0; index < outRaster.Width * outRaster.Height; index++)
{
sdSnow1[index] = sdSnow[0, index];
sdclass[index] = sdSnow[1, index];
}
try
{
unsafe
{
fixed(float *ptr = sdSnow1)
{
IntPtr sdSnowPtr = new IntPtr(ptr);
IRasterBand bandoutRaster = outRaster.GetRasterBand(1);
bandoutRaster.Write(0, 0, outRaster.Width, outRaster.Height, sdSnowPtr, outRaster.DataType, outRaster.Width, outRaster.Height);
}
fixed(float *ptr = sdclass)
{
IntPtr sdclassPtr = new IntPtr(ptr);
IRasterBand bandoutRaster = outClassRaster.GetRasterBand(1);
bandoutRaster.Write(0, 0, outClassRaster.Width, outClassRaster.Height, sdclassPtr, outClassRaster.DataType, outClassRaster.Width, outClassRaster.Height);
}
}
IFileExtractResult res = new FileExtractResult(_subProductDef.Identify, visFileName, true);
array.Add(res);
IFileExtractResult res2 = new FileExtractResult(_subProductDef.Identify, classFileName, true);
array.Add(res2);
return(res);
}
finally
{
if (outRaster != null)
{
outRaster.Dispose();
}
if (outClassRaster != null)
{
outClassRaster.Dispose();
}
if (rms != null && rms.Count > 0)
{
foreach (RasterMaper rm in rms)
{
if (rm.Raster != null)
{
rm.Raster.Dispose();
}
}
}
}
}
private IExtractResult FRDSAlgorithm(Action <int, string> progressTracker)
{
string[] fileNames = GetStringArray("SelectedPrimaryFiles");
if (fileNames == null || fileNames.Count() == 0)
{
PrintInfo("请选择参与积雪天数统计的数据！");
return(null);
}
foreach (string f in fileNames)
{
if (!File.Exists(f))
{
PrintInfo("所选择的数据:\"" + f + "\"不存在。");
return(null);
}
}
int bandNo = 1;
ExtractResultArray array = new ExtractResultArray("SNW");
//输出文件准备（作为输入栅格并集处理）
RasterIdentify ri = GetRasterIdentifyID(ref fileNames);
string outFileName = ri.ToWksFullFileName(".dat");
//输入文件准备
List <RasterMaper> rms = new List <RasterMaper>();
string tempFilename;
try
{
for (int i = 0; i < fileNames.Length; i++)
{
tempFilename = ProcessCloud(fileNames[i], bandNo);
IRasterDataProvider inRaster = RasterDataDriver.Open(tempFilename) as IRasterDataProvider;
if (inRaster.BandCount < bandNo)
{
PrintInfo("请选择正确的数据进行积雪天数统计。");
return(null);
}
RasterMaper rm = new RasterMaper(inRaster, new int[] { tempFilename == fileNames[i] ? bandNo : 1 });
rms.Add(rm);
}
using (IRasterDataProvider outRaster = CreateOutRaster(outFileName, rms.ToArray()))
{
//栅格数据映射
RasterMaper[] fileIns = rms.ToArray();
RasterMaper[] fileOuts = new RasterMaper[] { new RasterMaper(outRaster, new int[] { 1 }) };
//创建处理模型
RasterProcessModel <Int16, Int16> rfr = null;
rfr = new RasterProcessModel <Int16, Int16>(progressTracker);
rfr.SetRaster(fileIns, fileOuts);
Int16[] nanValues = GetNanValues("CloudyValue");
Int16[] waterValues = GetNanValues("WaterValue");
Int16[] invailValues = GetNanValues("InvailValue");
Int16 currTimeValue = 0;
rfr.RegisterCalcModel(new RasterCalcHandler <Int16, Int16>((rvInVistor, rvOutVistor, aoi) =>
{
int dataLength = rvOutVistor[0].SizeY * rvOutVistor[0].SizeX;
Int16[] timeValue = new Int16[dataLength];
List <Int16> tempValue = new List <Int16>();
for (int i = 0; i < dataLength; i++)
{
timeValue[i] = 0;
}
for (int index = 0; index < dataLength; index++)
{
foreach (RasterVirtualVistor <Int16> rvs in rvInVistor)
{
Int16[] dt = rvs.RasterBandsData[0];
if (dt == null)
{
continue;
}
tempValue.Add(dt[index]);
}
if (tempValue.Count == 0)
{
continue;
}
if (TimeValue(tempValue.ToArray(), nanValues, invailValues, waterValues, out currTimeValue))
{
timeValue[index] = currTimeValue;
}
tempValue.Clear();
}
for (int index = 0; index < dataLength; index++)
{
rvOutVistor[0].RasterBandsData[0][index] = timeValue[index];
}
}));
//执行
rfr.Excute(0);
FileExtractResult res = new FileExtractResult(_subProductDef.Identify, outFileName, true);
array.Add(res);
res.SetDispaly(false);
}
}
finally
{
foreach (RasterMaper rm in rms)
{
rm.Raster.Dispose();
}
}
_argumentProvider.SetArg("SelectedPrimaryFiles", new string[] { outFileName });
string instanceIdentify = _argumentProvider.GetArg("OutFileIdentify") as string;
if (string.IsNullOrWhiteSpace(instanceIdentify))
{
return(array);
}
SubProductInstanceDef instance = FindSubProductInstanceDefs(instanceIdentify);
IExtractResult ress = ThemeGraphyByInstance(instance);
if (ress != null)
{
array.Add(ress as IFileExtractResult);
}
return(array);
}
private IExtractResult SateValAlgorithm(Action <int, string> progressTracker)
{
ValArguments args = _argumentProvider.GetArg("SateArgs") as ValArguments;
if (args == null)
{
return(null);
}
string toValFile = args.FileNamesToVal[0];
string forValFile = args.FileNamesForVal[0];
string invalid = args.Invalid;
//先判断时间是否一样
string toValDate = "0000";
string forValDate = "0000";
try
{
foreach (Regex dt in DataReg)
{
Match m1 = dt.Match(Path.GetFileName(toValFile));
Match m2 = dt.Match(Path.GetFileName(forValFile));
if (m1.Success)
{
toValDate = m1.Value;
}
if (m2.Success)
{
forValDate = m2.Value;
}
}
if (toValDate == "0000" || forValDate == "0000")
{
MessageBox.Show("数据文件时间为空，默认两文件时间相符");
}
else
{
int year = Convert.ToInt32(toValDate.Substring(0, 4));
int month = Convert.ToInt32(toValDate.Substring(4, 2));
int day = Convert.ToInt32(toValDate.Substring(6, 2));
DateTime datetime = new DateTime(year, month, day);
string days = Convert.ToString(datetime.DayOfYear);
if (days != forValDate.Substring(1))
{
MessageBox.Show("提示：对比数据时间不同");
}
}
}
catch (Exception ex)
{
MessageBox.Show("异常信息：" + ex.Message);
}
//再看两个数据范围是否相同
IRasterDataProvider forValRaster = GeoDataDriver.Open(forValFile) as IRasterDataProvider;
IRasterDataProvider toValRaster = GeoDataDriver.Open(toValFile) as IRasterDataProvider;
if (forValRaster.CoordEnvelope.MaxX != toValRaster.CoordEnvelope.MaxX ||
forValRaster.CoordEnvelope.MinX != toValRaster.CoordEnvelope.MinX ||
forValRaster.CoordEnvelope.MaxY != toValRaster.CoordEnvelope.MaxY ||
forValRaster.CoordEnvelope.MinY != toValRaster.CoordEnvelope.MinY ||
toValRaster.Height != forValRaster.Height || toValRaster.Width != toValRaster.Width)
{
MessageBox.Show("两个数据空间范围不一致");
//这里也可修改为读取两数据的交差范围，做直方图
return(null);
}
#region//读取数据
Int16[] toValbuffer = new Int16[toValRaster.Height * toValRaster.Width];
Int16[] forValbuffer = new Int16[toValRaster.Height * toValRaster.Width];
Int16[] toVal = new Int16[toValRaster.Height * toValRaster.Width];
Int16[] forVal = new Int16[toValRaster.Height * toValRaster.Width];
IRasterBand toValBand = toValRaster.GetRasterBand(1);
IRasterBand forValBand = forValRaster.GetRasterBand(1);
unsafe
{
fixed(Int16 *pointer = toValbuffer)
{
IntPtr ptr = new IntPtr(pointer);
toValBand.Read(0, 0, toValRaster.Width, toValRaster.Height, ptr, toValRaster.DataType,
toValRaster.Width, toValRaster.Height);
for (int i = 0; i < toValRaster.Height * toValRaster.Width; i++)
{
toVal[i] = toValbuffer[i];
}
}
fixed(Int16 *pointer = forValbuffer)
{
IntPtr ptr = new IntPtr(pointer);
forValBand.Read(0, 0, forValRaster.Width, forValRaster.Height, ptr, forValRaster.DataType,
forValRaster.Width, forValRaster.Height);
for (int i = 0; i < forValRaster.Height * forValRaster.Width; i++)
{
forVal[i] = forValbuffer[i];
}
}
}
#endregion
IExtractResultArray array = new ExtractResultArray("统计表格");
if (args.CreatHistogram)
{
List <string[]> listRowHist = new List <string[]>();
string histfilename = "";
IStatResult fresult = null;
int maxcol = 10;
if (!String.IsNullOrEmpty(args.MaxColumns))
{
maxcol = Convert.ToInt32(args.MaxColumns);
}
IStaticComputer <Int16> computer = new StaticComputerInt16();
listRowHist = computer.ComputeDeviation(toVal, forVal, GetInvalidArray(args.Invalid), GetInvalidArray(args.ForInvalid), maxcol);
string sentitle = "统计日期：" + DateTime.Now.ToShortDateString();
string[] columns = new string[] { "偏差值", "累加值" };
fresult = new StatResult(sentitle, columns, listRowHist.ToArray());
string title = "陆表温度产品偏差直方图";
histfilename = StatResultToFile(new string[] { toValFile }, fresult, "VAL", "HIST", title, null, 1, true, 1);
IFileExtractResult res = new FileExtractResult("HIST", histfilename);
array.Add(res);
}
if (args.CreatRMSE)
{
IStaticComputer <Int16> computer = new StaticComputerInt16();
double rmse = computer.ComputeRMSE(toVal, forVal, GetInvalidArray(args.Invalid), GetInvalidArray(args.ForInvalid));
MessageBox.Show("数据均方根误差是：" + Convert.ToString(rmse));
}
#region 用这种方式出栅格数据的散点图
//if (args.CreatScatter)
//{
// List<string[]> listRow = new List<string[]>(); //散点图
// for (int i = 0; i < toValRaster.Height * toValRaster.Width; i++)
// {
// //剔除无效值
// if (!String.IsNullOrEmpty(args.invalid))
// {
// if (args.invalid.Contains(Convert.ToString(toVal[i])) || args.invalid.Contains(Convert.ToString(forVal[i])))
// {
// }
// else
// {
// string[] row = new string[] { Convert.ToString(toVal[i]), Convert.ToString(forVal[i]) };
// listRow.Add(row);
// }
// }
// else
// {
// string[] row = new string[] { Convert.ToString(toVal[i]), Convert.ToString(forVal[i]) };
// listRow.Add(row);
// }
// }
// string[][] rows = listRow.ToArray();
// IStatResult result = new StatResult("统计时间:", new string[] { "待验证云参数", "MOD06云产品" }, rows);
// string title = "陆表温度数据与MODIS LST对比";
// string filename = "";
// try
// {
// using (StatResultToChartInExcelFile excelControl = new StatResultToChartInExcelFile())
// {
// excelControl.Init(masExcelDrawStatType.xlXYScatter);
// excelControl.Add("数据对比", result, true, 0, false, result.Columns[0], result.Columns[1
// ]);
// filename = StatResultToFile(new string[] { toValFile }, result, "VAL", "SCAT", title, null, 1, true, 1);
// if (!filename.ToUpper().EndsWith(".XLSX"))
// filename += ".XLSX";
// excelControl.SaveFile(filename);
// IFileExtractResult res = new FileExtractResult("SCAT", filename);
// array.Add(res);
// }
// }
// catch (Exception ex)
// {
// }
//}
#endregion
return(array);
}
private IExtractResult CompareAlgorithm()
{
string[] files = GetStringArray("SelectedPrimaryFiles");
string file = _argumentProvider.GetArg("SelectedPrimaryFiles").ToString();
if (files == null && string.IsNullOrEmpty(file))
{
return(null);
}
if (files != null && files.Length < 2)
{
return(null);
}
if (files == null && !string.IsNullOrEmpty(file))
{
string[] fnames = file.Split('*');
if (fnames != null && fnames.Length > 1)
{
foreach (string item in fnames)
{
if (!File.Exists(item))
{
return(null);
}
}
files = fnames;
}
else
{
return(null);
}
}
//文件列表排序
string[] dstFiles = SortFileName(files);
string outFileIdentify = GetStringArgument("OutFileIdentify");
string productIdentify = _subProductDef.ProductDef.Identify;
ExtractResultArray results = new ExtractResultArray(productIdentify + _identify);
List <IPixelFeatureMapper <Int16> > rasterList = new List <IPixelFeatureMapper <short> >();
List <RasterIdentify> rstIdentifys = new List <RasterIdentify>();
for (int i = 0; i < dstFiles.Length - 1; i++)
{
IPixelFeatureMapper <Int16> rasterResult = MakeCompareRaster <float, Int16>(productIdentify, dstFiles[i], dstFiles[i + 1], (fstFileValue, sedFileValue) =>
{
if (fstFileValue == 1f && sedFileValue == 1f)
{
return(1);
}
else if (fstFileValue == 0f && sedFileValue == 1f)
{
return(4);
}
else if (fstFileValue == 1f && sedFileValue == 0f)
{
return(5);
}
else
{
return(0);
}
}, true);
if (rasterResult == null)
{
continue;
}
rasterList.Add(rasterResult);
rstIdentifys.Add(new RasterIdentify(new string[] { dstFiles[i], dstFiles[i + 1] }));
}
if (rasterList.Count == 0)
{
return(null);
}
else
{
for (int i = 0; i < rasterList.Count; i++)
{
RasterIdentify rid = GetRasterIdentifyID(rstIdentifys[i]);
IInterestedRaster <Int16> iir = new InterestedRaster <Int16>(rid, rasterList[i].Size, rasterList[i].CoordEnvelope, null);
iir.Put(rasterList[i]);
iir.Dispose();
FileExtractResult res = new FileExtractResult(outFileIdentify, iir.FileName);
res.SetDispaly(false);
results.Add(res);
}
}
return(results);
}
private IExtractResult VirrAlgorithm()
{
int farInfraredNo1, farInfraredNo2;
IBandNameRaster bandNameRaster = _argumentProvider.DataProvider as IBandNameRaster;
farInfraredNo1 = TryGetBandNo(bandNameRaster, "FarInfrared1");
farInfraredNo2 = TryGetBandNo(bandNameRaster, "FarInfrared2");
if (farInfraredNo1 == -1 || farInfraredNo2 == -1)
{
PrintInfo("获取波段序号失败,可能是波段映射表配置错误或判识算法波段参数配置错误。");
return(null);
}
int[] bandNos = new int[] { farInfraredNo1, farInfraredNo2 };
if (_argumentProvider.GetArg("BinaryFile") == null)
{
PrintInfo("获取判识结果文件失败。");
return(null);
}
string dblvFile = _argumentProvider.GetArg("BinaryFile").ToString();
if (string.IsNullOrEmpty(dblvFile) || !File.Exists(dblvFile))
{
PrintInfo("获取判识结果文件失败。");
return(null);
}
string angleFile = _argumentProvider.GetArg("AngleFile").ToString();
if (string.IsNullOrEmpty(angleFile) || !File.Exists(angleFile))
{
PrintInfo("获取太阳天顶角文件失败。");
return(null);
}
//参数检查与获取
string landTypeFile = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "SystemData\\ProductArgs\\DST\\GlobleLandCover.dat");
if (!File.Exists(landTypeFile))
{
PrintInfo("土地类型文件不存在！");
return(null);
}
string tempFile = _argumentProvider.GetArg("TemperatureFile").ToString();
if (string.IsNullOrEmpty(tempFile) || !File.Exists(tempFile))
{
PrintInfo("获取温度场文件失败。");
return(null);
}
string pressureFile = _argumentProvider.GetArg("PressureFile").ToString();
if (string.IsNullOrEmpty(pressureFile) || !File.Exists(pressureFile))
{
PrintInfo("获取气压场文件失败。");
return(null);
}
//进行光学厚度与沙尘粒子有效半径计算需要文件：1、原始影像数据；2、查算表数据；3、太阳高度角数据
List <RasterMaper> inputRms = new List <RasterMaper>();
List <RasterMaper> outputRms = new List <RasterMaper>();
try
{
//当前影像（待判识文件）
RasterMaper rm = new RasterMaper(_argumentProvider.DataProvider, bandNos);
inputRms.Add(rm);
//判识结果文件
IRasterDataProvider dblvPrd = GeoDataDriver.Open(dblvFile) as IRasterDataProvider;
RasterMaper dblvRm = new RasterMaper(dblvPrd, new int[] { 1 });
inputRms.Add(dblvRm);
//太阳天顶角文件
IRasterDataProvider angleDataPrd = GeoDataDriver.Open(angleFile) as IRasterDataProvider;
RasterMaper anglerm = new RasterMaper(angleDataPrd, new int[] { 1 });
inputRms.Add(anglerm);
//土地类型文件
IRasterDataProvider landTypeDataPrd = GeoDataDriver.Open(landTypeFile) as IRasterDataProvider;
RasterMaper landTypeRm = new RasterMaper(landTypeDataPrd, new int[] { 1 });
inputRms.Add(landTypeRm);
//温度场文件
IRasterDataProvider tempDataPrd = GeoDataDriver.Open(landTypeFile) as IRasterDataProvider;
RasterMaper tempRm = new RasterMaper(tempDataPrd, new int[] { 1 });
inputRms.Add(tempRm);
//气压场文件
IRasterDataProvider pressureDataPrd = GeoDataDriver.Open(pressureFile) as IRasterDataProvider;
RasterMaper pressureRm = new RasterMaper(tempDataPrd, new int[] { 1 });
inputRms.Add(pressureRm);
RasterIdentify ri = new RasterIdentify(_argumentProvider.DataProvider.fileName);
ri.ProductIdentify = "DST";
ri.IsOutput2WorkspaceDir = true;
IRasterDataProvider htRaster = CreateOutRaster(ri, dblvPrd, "0DHT");
RasterMaper htRm = new RasterMaper(htRaster, new int[] { 1 });
outputRms.Add(htRm);
IRasterDataProvider optRaster = CreateOutRaster(ri, dblvPrd, "0OPT");
RasterMaper optRm = new RasterMaper(optRaster, new int[] { 1 });
outputRms.Add(optRm);
//栅格数据映射
RasterMaper[] fileIns = inputRms.ToArray();
RasterMaper[] fileOuts = outputRms.ToArray();
//创建处理模型
RasterProcessModel <short, float> rfr = new RasterProcessModel <short, float>();
rfr.SetRaster(fileIns, fileOuts);
#region
rfr.RegisterCalcModel(new RasterCalcHandler <short, float>((rvInVistor, rvOutVistor, aoi) =>
{
int landType;
float t1 = 0, t2 = 0;
if (rvInVistor[0].RasterBandsData[0] != null)
{
int length = rvInVistor[0].RasterBandsData[0].Length;
for (int i = 0; i < length; i++)
{
if (rvInVistor[1].RasterBandsData[0][i] == 1)
{
if (rvInVistor[4].RasterBandsData[0][i] > 263)
{
t1 = rvInVistor[4].RasterBandsData[0][i] - 3;
t2 = rvInVistor[4].RasterBandsData[0][i] + 3;
}
if (rvInVistor[4].RasterBandsData[0][i] < rvInVistor[0].RasterBandsData[0][i])
{
t1 = rvInVistor[0].RasterBandsData[0][i];
t2 = rvInVistor[0].RasterBandsData[0][i] + 5;
}
//for(int m=0;m<)
landType = rvInVistor[3].RasterBandsData[0][i];
//water
if (landType == 0 || landType >= 17)
{
}
//desert
else if (landType == 16)
{
}
else
{
}
}
}
}
}));
#endregion
rfr.Excute();
FileExtractResult htResult = new FileExtractResult("0DHT", htRaster.fileName, true);
htResult.SetDispaly(false);
FileExtractResult optResult = new FileExtractResult("0OPT", optRaster.fileName, true);
optResult.SetDispaly(false);
ExtractResultArray resultArray = new ExtractResultArray(_subProductDef.Identify);
resultArray.Add(htResult);
resultArray.Add(optResult);
return(resultArray);
}
finally
{
for (int i = 1; i < inputRms.Count; i++)
{
if (inputRms[i].Raster != null)
{
inputRms[i].Raster.Dispose();
}
}
foreach (RasterMaper rm in outputRms)
{
if (rm.Raster != null)
{
rm.Raster.Dispose();
}
}
}
}
private IExtractResult ModisAlgorithm()
{
int middleInfraredNo, farInfrared1No, farInfrared2No;
IBandNameRaster bandNameRaster = _argumentProvider.DataProvider as IBandNameRaster;
middleInfraredNo = TryGetBandNo(bandNameRaster, "MiddleInfrared");
farInfrared1No = TryGetBandNo(bandNameRaster, "FarInfrared1");
farInfrared2No = TryGetBandNo(bandNameRaster, "FarInfrared2");
if (middleInfraredNo == -1 || farInfrared1No == -1 || farInfrared2No == -1)
{
PrintInfo("获取波段序号失败,可能是波段映射表配置错误或判识算法波段参数配置错误。");
return(null);
}
int[] bandNos = new int[] { middleInfraredNo, farInfrared1No, farInfrared2No };
if (_argumentProvider.GetArg("BinaryFile") == null)
{
PrintInfo("获取判识结果文件失败。");
return(null);
}
string dblvFile = _argumentProvider.GetArg("BinaryFile").ToString();
if (string.IsNullOrEmpty(dblvFile) || !File.Exists(dblvFile))
{
PrintInfo("获取判识结果文件失败。");
return(null);
}
float mbtd = (float)_argumentProvider.GetArg("mbtd");
float mbt = (float)_argumentProvider.GetArg("mbt");
int ntype = Int32.Parse(_argumentProvider.GetArg("ntype").ToString());
//获取查找表参数
LookupTableArgument argument = new LookupTableArgument();
//进行光学厚度与沙尘粒子有效半径计算需要文件：1、原始影像数据；2、查算表数据
List <RasterMaper> inputRms = new List <RasterMaper>();
List <RasterMaper> outputRms = new List <RasterMaper>();
try
{
//当前影像（待判识文件）
RasterMaper rm = new RasterMaper(_argumentProvider.DataProvider, bandNos);
inputRms.Add(rm);
IRasterDataProvider dblvPrd = GeoDataDriver.Open(dblvFile) as IRasterDataProvider;
RasterMaper dblvRm = new RasterMaper(dblvPrd, new int[] { 1 });
inputRms.Add(dblvRm);
RasterIdentify ri = new RasterIdentify(_argumentProvider.DataProvider.fileName);
ri.ProductIdentify = "DST";
ri.IsOutput2WorkspaceDir = true;
IRasterDataProvider reRaster = CreateOutRaster(ri, dblvPrd, "0DRE");
RasterMaper reRm = new RasterMaper(reRaster, new int[] { 1 });
outputRms.Add(reRm);
IRasterDataProvider optRaster = CreateOutRaster(ri, dblvPrd, "0OPT");
RasterMaper optRm = new RasterMaper(optRaster, new int[] { 1 });
outputRms.Add(optRm);
IRasterDataProvider denRaster = CreateOutRaster(ri, dblvPrd, "DDEN");
RasterMaper denRm = new RasterMaper(denRaster, new int[] { 1 });
outputRms.Add(denRm);
//栅格数据映射
RasterMaper[] fileIns = inputRms.ToArray();
RasterMaper[] fileOuts = outputRms.ToArray();
//创建处理模型
RasterProcessModel <short, float> rfr = new RasterProcessModel <short, float>();
rfr.SetRaster(fileIns, fileOuts);
#region
rfr.RegisterCalcModel(new RasterCalcHandler <short, float>((rvInVistor, rvOutVistor, aoi) =>
{
int nindex;
double ocdiff = 0, mindiff = 0, den = 0, gcon;
float den0, rpsize = 0, rpsize0, rpmin = 0.01f, rpmax = 100;
double sgma = 2.0, sgdust = 2.5e-12;
double dr = (Math.Log10(rpmax) - Math.Log10(rpmin)) / 100;
if (rvInVistor[0].RasterBandsData[0] != null)
{
int length = rvInVistor[0].RasterBandsData[0].Length;
for (int i = 0; i < length; i++)
{
if (rvInVistor[1].RasterBandsData[0][i] == 1)
{
float bt31 = rvInVistor[0].RasterBandsData[1][i] / 10f;
float btd3132 = (rvInVistor[0].RasterBandsData[1][i] - rvInVistor[0].RasterBandsData[2][i]) / 10f;
float btd2931 = (rvInVistor[0].RasterBandsData[0][i] - rvInVistor[0].RasterBandsData[1][i]) / 10f;
for (int m = 0; m < 50; m++)
{
for (int n = 0; n < 29; n++)
{
ocdiff = Math.Pow(btd3132 - argument.Cbtd3132[m, n], 2) + Math.Pow((btd2931 - argument.Cbtd2931[m, n]), 2) * mbtd
+ Math.Pow((bt31 - argument.Cbt31[m, n]), 2) * mbt;
if (ocdiff < mindiff || (m == 0 && n == 0))
{
mindiff = ocdiff;
rvOutVistor[0].RasterBandsData[0][i] = argument.Dref[n];
rvOutVistor[1].RasterBandsData[0][i] = argument.Dopt[m];
}
}
}
//计算rvOutVistor[2].RasterBandsData[0][i]载沙量
if (rvOutVistor[0].RasterBandsData[0][i] <= 1)
{
nindex = (int)(rvOutVistor[0].RasterBandsData[0][i] * 10);
}
else
{
nindex = (int)(rvOutVistor[0].RasterBandsData[0][i]) + 9;
}
den0 = rvOutVistor[1].RasterBandsData[0][i] / argument.Ext55[nindex - 1];
double ravg = Calravg(rvOutVistor[1].RasterBandsData[0][i], sgma);
double tcv = 0;
rpsize = rpmin;
for (int j = 0; j < 100; j++)
{
//源代码中未定义type为1,2所需变量初始值
den = DType(ntype, rpsize, 0, 0, 0, 0, 0, 0, 0, den0, ravg, sgma);
rpsize0 = rpsize;
rpsize = (float)Math.Pow(10, (Math.Log10(rpsize) + dr));
gcon = 4f / 3 * Math.PI * Math.Pow(rpsize0, 3) * den * (rpsize - rpsize0);
tcv += gcon;
}
float value = (float)((tcv * sgdust * 1.0e+9 * 10));
rvOutVistor[2].RasterBandsData[0][i] = value > 50f ? 50f : value;
}
}
}
}));
#endregion
rfr.Excute();
FileExtractResult reResult = new FileExtractResult("0DRE", reRaster.fileName, true);
reResult.SetDispaly(false);
FileExtractResult optResult = new FileExtractResult("0OPT", optRaster.fileName, true);
optResult.SetDispaly(false);
FileExtractResult denResult = new FileExtractResult("DDEN", denRaster.fileName, true);
ExtractResultArray resultArray = new ExtractResultArray(_subProductDef.Identify);
resultArray.Add(reResult);
resultArray.Add(optResult);
//生成载沙量
resultArray.Add(denResult);
return(resultArray);
}
finally
{
for (int i = 1; i < inputRms.Count; i++)
{
if (inputRms[i].Raster != null)
{
inputRms[i].Raster.Dispose();
}
}
foreach (RasterMaper rm in outputRms)
{
if (rm.Raster != null)
{
rm.Raster.Dispose();
}
}
}
}
private IExtractResult MicroVisSNWSDAlgorithm(Action <int, string> progressTracker)
{
string inputSDFileName = _argumentProvider.GetArg("RasterSDFile").ToString();
if (string.IsNullOrEmpty(inputSDFileName) || !File.Exists(inputSDFileName))
{
PrintInfo("缺少微波雪深文件");
return(null);
}
string inputCLDSNWFileName = "";
string inputVISNWFileName = "";
string identify = "";
string[] snowfname = GetStringArray("RasterVISNWFiles");
if (progressTracker != null)
{
progressTracker(1, "开始计算");
}
if (snowfname == null || snowfname.Length <= 0)
{
PrintInfo("请选可见光雪判识文件！");
return(null);
}
if (snowfname.Length == 1)
{
inputVISNWFileName = snowfname[0];
}
else
{
identify = "SNDB";
IFileExtractResult vissnowFilename = ComposeVISSNW(snowfname, identify);
inputVISNWFileName = vissnowFilename.FileName;
}
progressTracker(20, "计算完成20%");
string[] cloudfname = GetStringArray("RasterCLDSNWFiles");
if (cloudfname == null || cloudfname.Length <= 0)
{
PrintInfo("请选可见光云判识文件！");
return(null);
}
if (cloudfname.Length == 1)
{
inputCLDSNWFileName = cloudfname[0];
}
else
{
identify = "0CLM";
IFileExtractResult viscldFilename = ComposeVISSNW(cloudfname, identify);
inputCLDSNWFileName = viscldFilename.FileName;
}
progressTracker(50, "计算完成50%");
if (string.IsNullOrEmpty(inputVISNWFileName) || !File.Exists(inputVISNWFileName) || string.IsNullOrEmpty(inputCLDSNWFileName) || !File.Exists(inputCLDSNWFileName))
{
PrintInfo("缺少可见光雪或者云判识文件");
return(null);
}
else
{
IExtractResultArray array = new ExtractResultArray("融合雪深");
IFileExtractResult visFilename = ComputeVIS(inputVISNWFileName, inputCLDSNWFileName);
array.Add(visFilename);
progressTracker(70, "计算完成70%");
string visSNWfilename = visFilename.FileName;
IFileExtractResult microvisfilename = ComputeSD(inputSDFileName, visSNWfilename);
array.Add(microvisfilename);
//中值滤波
Int16 smoothwindow = 5;
string microvisName = microvisfilename.FileName;
IFileExtractResult midSDFilterResult = ComputerMid(microvisName, smoothwindow);//滤波
array.Add(midSDFilterResult);
progressTracker(100, "计算完成");
return(array);
}
}
private IExtractResult JuPingAnalysisAlgorithm(Action <int, string> progressTracker)
{
string[] inputCurrentFiles = null; //= ExportManager.GetInstance().List.ToArray();//GetStringArray("RasterCurrentFile"); 由查询那里获得
string[] inputHistoryFiles = null;
List <string> list1 = ExportManager.GetInstance().List; //得到的是从数据库里查询出来的周期数据
StatisticResultManager manager = StatisticResultManager.GetInstance();
List <StatisticResult> list = manager.List;
List <string> list2 = manager.GetFilePathFromList(); //得到的是基于数据查询的数据又做的统计数据
regionNames = _argumentProvider.GetArg("regionNames") as string;
//处理后的数据，用它来出专题图
List <string> afterProcessfiles = new List <string>();
#region 获得目标区域
aoiContainer = new GeoDo.RSS.Core.VectorDrawing.AOIContainerLayer();
string fieldName;
string shapeFilename;
int fieldIndex = -1;
List <string> fieldValues = new List <string>();
string regionsname = "";
using (frmStatSubRegionTemplates frm = new frmStatSubRegionTemplates())
{
frm.listView1.MultiSelect = true;
if (frm.ShowDialog() == DialogResult.OK)
{
Feature[] fets = frm.GetSelectedFeatures();
fets = frm.GetStatFeatures(out fieldName, out shapeFilename, out fieldIndex);
if (fets == null)
{
aoiContainer = null;
regionsname = "全国";
}
else
{
string chinafieldValue = fets[0].GetFieldValue(fieldIndex);
if (chinafieldValue == "中国")
{
aoiContainer = null;
regionsname = "全国";
}
else
{
foreach (Feature fet in fets)
{
fieldValues.Add(fet.GetFieldValue(fieldIndex)); //获得选择区域名称
aoiContainer.AddAOI(fet);
}
foreach (string region in fieldValues)
{
regionsname += region;
}
if (regionsname.Contains("西藏") && regionsname.Contains("青海"))
{
regionsname = "青藏地区";
}
if (!string.IsNullOrEmpty(regionNames))
{
regionsname = regionNames.Trim();
}
}
}
}
else
{
return(null);
}
}
#endregion
Regex DataReg = new Regex(@"(?<year>\d{4})", RegexOptions.Compiled);
//处理后的数据存储路径
string savePath = _argumentProvider.GetArg("HistoryDataSave") as string;
string jpsavepath = savePath + "\\" + "距平分析";
if (!System.IO.Directory.Exists(jpsavepath))//如果不存在这个路径
{
System.IO.Directory.CreateDirectory(jpsavepath);
}
//参数设置
List <string> paraset = _argumentProvider.GetArg("paraSet") as List <string>;
string[] paras = paraset.ToArray();
List <string> jpfiles = new List <string>();//存放相减的距平分析文件
string date = "";
string jupingfile = "";
IExtractResultArray array = new ExtractResultArray("距平分析");
string Nostr = ""; //排除非选择的轨道数据
if (paras[0] == "Ascend")
{
Nostr = "_D_";
}
if (paras[0] == "Descend")
{
Nostr = "_A_";
}
if (paras[1] == "winter") // inputCurrentFiles = manager.GetFilePathFromList() 冬季的数所是统计出来的。
{ // inputHistoryFiles 需要再重新计算一次 *** 这是多对一计算距平
//比如说要算2000-2013年冬季的距平，需要先分别算出每年冬季的值，用这些值算总的均值。再分别用每年冬季减去总冬季值。
List <string> files = new List <string>();
foreach (string file in list2)
{
if (!Path.GetFileName(file).Contains(Nostr))
{
files.Add(file);
}
}
inputCurrentFiles = files.ToArray();
string outHistoryFile = jpsavepath + "\\" + Path.GetFileNameWithoutExtension(inputCurrentFiles[0]).Substring(0, 14) + "_" + paras[2] + ".dat";
SNWParaStat snwStat = new SNWParaStat();
snwStat.SNWParaAvgStat(inputCurrentFiles, 0.1f, outHistoryFile);
List <string> temphistory = new List <string>();
temphistory.Add(outHistoryFile);
inputHistoryFiles = temphistory.ToArray();
if (inputCurrentFiles == null || inputCurrentFiles.Length < 0 || inputHistoryFiles == null || inputHistoryFiles.Length < 0)
{
PrintInfo("缺少分析文件");
return(null);
}
foreach (string inputCurrentFile in inputCurrentFiles)
{
Regex DataReg2 = new Regex(@"(?<year>\d{4})_(?<month>\d{2})_(?<year>\d{4})_(?<month>\d{1})", RegexOptions.Compiled);
Match m = DataReg2.Match(inputCurrentFile); //提取每年冬季的时间
string year = "";
if (m.Success)
{
year = m.Value;
}
jupingfile = JuPinComputer(inputCurrentFile, inputHistoryFiles[0], jpsavepath);
string hdrfile = Path.GetDirectoryName(jupingfile) + "\\" + Path.GetFileNameWithoutExtension(jupingfile) + ".hdr";
FileInfo fi = new FileInfo(jupingfile);
string newjpfile = Path.Combine(jpsavepath, Path.GetFileNameWithoutExtension(jupingfile) + "_" + year.Substring(0, 4) + ".dat");
string newhdrfile = Path.Combine(jpsavepath, Path.GetFileNameWithoutExtension(jupingfile) + "_" + year.Substring(0, 4) + ".hdr");
fi.MoveTo(newjpfile);
FileInfo fihdr = new FileInfo(hdrfile);
fihdr.MoveTo(newhdrfile);
jpfiles.Add(newjpfile);
}
}
else
{ //例 2013年11月上旬-2013年11月下旬分别与1987-2013年11月上中下旬 同期比较 一对一计算距平
inputCurrentFiles = list1.ToArray();
inputHistoryFiles = list2.ToArray();
if (inputCurrentFiles == null || inputCurrentFiles.Length < 0 || inputHistoryFiles == null || inputHistoryFiles.Length < 0)
{
PrintInfo("缺少分析文件");
return(null);
}
if ((inputCurrentFiles.Length) * 2 != inputHistoryFiles.Length)
{
MessageBox.Show("当年数据与同期数据不对应");
return(null);
}
foreach (string inputCurrentFile in inputCurrentFiles)
{
//先假设选择的是旬数据 MWS_MWSD_China_Xun_0SD_A_2011_1_avg.dat
// 则同期旬数据 MWS_MWSD_China_Xun_0SD_A_1989_2011_1_avg.dat
string cfile = Path.GetFileNameWithoutExtension(inputCurrentFile);
Match m = DataReg.Match(cfile);
if (m.Success)
{
date = m.Value; //根据年4个数字来拆分字符串
}
string bhalf = cfile.Substring(0, cfile.IndexOf(date));
string ahalf = cfile.Substring(cfile.IndexOf(date) + 4, cfile.Length - 4 - cfile.IndexOf(date));
foreach (string inputHistoryFile in inputHistoryFiles)
{
string aa = Path.GetFileNameWithoutExtension(inputHistoryFile);
if (aa.Contains(bhalf) && aa.Contains(ahalf) && aa.Contains(date) && !aa.Contains(Nostr))
{
jupingfile = JuPinComputer(inputCurrentFile, inputHistoryFile, jpsavepath);
jpfiles.Add(jupingfile);
break;
}
}
}
}
#region 距平的文件在jpfiles 中，下面是裁切和平滑处理
MulRegionsClip muticlip = new MulRegionsClip(); //裁切
MWSSmoothHelp smooth = new MWSSmoothHelp(); //平滑
//创建专题图路径
gxdsave = jpsavepath + "\\" + regionsname + "\\" + "专题图";
if (!System.IO.Directory.Exists(gxdsave))//如果不存在这个路径
{
System.IO.Directory.CreateDirectory(gxdsave);
}
//创建平滑路径
string smoothsave = jpsavepath + "\\" + regionsname + "\\" + "平滑";
if (!System.IO.Directory.Exists(smoothsave))
{
System.IO.Directory.CreateDirectory(smoothsave);
}
//创建平滑\\中值
string filtersave = smoothsave + "\\" + "中值";
if (!System.IO.Directory.Exists(filtersave))
{
System.IO.Directory.CreateDirectory(filtersave);
}
if (aoiContainer == null)
{
//只做中值处理
foreach (string infile in jpfiles)
{
// 先判断这个文件是否存在，存在了就不做
string filterfile = filtersave + "\\" + Path.GetFileName(infile);
if (!File.Exists(filterfile))
{
filterfile = smooth.ComputerMid(infile, 5, filtersave);
}
afterProcessfiles.Add(filterfile);
toBarfiles.Add(infile);
}
}
else
{
// 裁切 // 中值 // 插值
string clipsave = jpsavepath + "\\" + regionsname + "\\" + "裁切";
if (!System.IO.Directory.Exists(clipsave))//如果不存在这个路径
{
System.IO.Directory.CreateDirectory(clipsave);
}
string bilisave = smoothsave + "\\" + "插值";
if (!System.IO.Directory.Exists(bilisave))
{
System.IO.Directory.CreateDirectory(bilisave);
}
foreach (string infile in jpfiles)
{
string newclipfile = clipsave + "\\" + Path.GetFileName(infile).Replace("China", regionsname);
if (!File.Exists(newclipfile))
{
string clipfile = muticlip.MutiRegionsClip(infile, aoiContainer, clipsave);
string hdrfile = Path.GetDirectoryName(clipfile) + "\\" + Path.GetFileNameWithoutExtension(clipfile) + ".hdr";
//重命名
string newhdrfile = Path.Combine(Path.GetDirectoryName(clipfile), Path.GetFileNameWithoutExtension(infile).Replace("China", regionsname) + ".hdr");
FileInfo fi = new FileInfo(clipfile);
fi.MoveTo(newclipfile);
FileInfo fihdr = new FileInfo(hdrfile);
fihdr.MoveTo(newhdrfile);
}
toBarfiles.Add(newclipfile); //加上裁切后的文件
//中值、插值
string filterfile = smooth.ComputerMid(newclipfile, 5, filtersave);
string bilifile = smooth.Bilinear(filterfile, 10, bilisave);
afterProcessfiles.Add(bilifile);
}
}
#endregion
//出专题图
#region
IExtractResultArray results = new ExtractResultArray("");
foreach (string arguments in afterProcessfiles.ToArray())
{
string product = "";
if (arguments.Contains("MWSD"))
{
product = "雪深";
_argumentProvider.SetArg("OutFileIdentify", "JPDI");
}
if (arguments.Contains("MSWE"))
{
product = "雪水当量";
_argumentProvider.SetArg("OutFileIdentify", "JPEI");
}
//解析文件名确定专题图名称
string filename = Path.GetFileNameWithoutExtension(arguments);
if (paras[1] == "usual")
{
Regex DataReg1 = new Regex(@"(?<year>\d{4})_(?<year>\d{4})", RegexOptions.Compiled);
Match m = DataReg1.Match(filename);
string year = "";
if (m.Success)
{
year = m.Value;
}
//提取年至avg之间的字符
string filetime = filename.Substring(filename.IndexOf(year), filename.Length - 3 - filename.IndexOf(year));
string[] mxchars = filetime.Split(new char[] { '_' });
string mx = "";//月+旬
if (filename.Contains("Xun"))
{
if (mxchars[3] == "1")
{
mx = mxchars[2] + "月" + "上旬";
}
if (mxchars[3] == "2")
{
mx = mxchars[2] + "月" + "中旬";
}
if (mxchars[3] == "3")
{
mx = mxchars[2] + "月" + "下旬";
}
}
if (filename.Contains("Month"))
{
mx = mxchars[2] + "月";
}
imgname = year.Substring(5, 4) + "年" + mx + regionsname + product + "距平分布图(" + paras[2] + "年)";
}
if (paras[1] == "winter")
{
imgname = Path.GetFileNameWithoutExtension(arguments).Substring(Path.GetFileNameWithoutExtension(arguments).Length - 4, 4) + "年" + "冬季" + regionsname + product + "距平分布图(" + paras[2] + "年)";
}
_argumentProvider.SetArg("SelectedPrimaryFiles", arguments);
_argumentProvider.SetArg("fileOpenArgs", arguments);
FileExtractResult result = ThemeGraphyResult(null) as FileExtractResult;
//增加矢量
string autopath = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, @"SystemData\ProductArgs\MWS\shppath.txt");
string shpFile = "";
if (File.Exists(autopath))
{
FileStream fauto = new FileStream(autopath, FileMode.Open, FileAccess.Read);
StreamReader rauto = new StreamReader(fauto, Encoding.GetEncoding("gb2312"));
shpFile = rauto.ReadLine();
rauto.Close();
fauto.Close();
}
else
{
shpFile = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, @"数据引用\基础矢量\行政区划\线\中国边界_线.shp");
}
CreateMcd(shpFile);
_shpFile = shpFile;
_gxdFile = (result as FileExtractResult).FileName;
AddShpToGxd();
string newresultfile = Path.Combine(gxdsave, Path.GetFileNameWithoutExtension(arguments) + ".gxd");
FileInfo fi = new FileInfo(result.FileName);
if (!File.Exists(newresultfile))
{
fi.MoveTo(newresultfile);
}
else
{
FileInfo fi1 = new FileInfo(newresultfile);
fi1.Delete();
}
IFileExtractResult res = new FileExtractResult(_subProductDef.Identify, newresultfile, false);
results.Add(res);
}
#endregion
return(results);
}
private IExtractResult EVIAlgorithm1(Action <int, string> progressTracker)
{
int bands = _argumentProvider.DataProvider.BandCount;
if (bands == 0 || bands == 1)
{
PrintInfo("请选择正确的局地文件进行计算。");
return(null);
}
if (_argumentProvider.GetArg("Visible") == null)
{
PrintInfo("参数\"Visible\"为空。");
return(null);
}
IBandNameRaster bandNameRaster = _argumentProvider.DataProvider as IBandNameRaster;
int bandV = TryGetBandNo(bandNameRaster, "Visible");
if (_argumentProvider.GetArg("NearInfrared") == null)
{
PrintInfo("参数\"NearInfrared\"为空。");
return(null);
}
int bandN = TryGetBandNo(bandNameRaster, "NearInfrared");
if (_argumentProvider.GetArg("Blue") == null)
{
PrintInfo("参数\"Blue\"为空。");
return(null);
}
int bandB = TryGetBandNo(bandNameRaster, "Blue");
if (bandV < 1 || bandB < 1 || bandN < 1 || bandV > bands || bandB > bands || bandN > bands)
{
PrintInfo("获取波段序号失败,可能是波段映射表配置错误或判识算法波段参数配置错误。");
return(null);
}
int bandMid = TryGetBandNo(bandNameRaster, "MiddInfrared"); //中红外
int bandFar = TryGetBandNo(bandNameRaster, "FarInfrared11"); //远红外
if (_argumentProvider.GetArg("Visible_Zoom") == null)
{
PrintInfo("参数\"Visible_Zoom\"为空。");
return(null);
}
double visibleZoom = (double)_argumentProvider.GetArg("Visible_Zoom");
if (_argumentProvider.GetArg("NearInfrared_Zoom") == null)
{
PrintInfo("参数\"NearInfrared_Zoom\"为空。");
return(null);
}
double nearInfrared = (double)_argumentProvider.GetArg("NearInfrared_Zoom");
if (_argumentProvider.GetArg("Blue_Zoom") == null)
{
PrintInfo("参数\"Blue_Zoom\"为空。");
return(null);
}
double blueZoom = (double)_argumentProvider.GetArg("Blue_Zoom");
double middZoom = (double)_argumentProvider.GetArg("MiddInfrared_Zoom");
double farZoom = (double)_argumentProvider.GetArg("FarInfrared11_Zoom");
int[] bandNos = new int[] { bandV, bandN, bandB, bandMid, bandFar };
double[] bandZoom = new double[] { visibleZoom, nearInfrared, blueZoom, middZoom, farZoom };
float NearInfraredCLMMin = float.Parse(_argumentProvider.GetArg("NearInfraredCLMMin").ToString());
float FarInfrared11CLMMax = float.Parse(_argumentProvider.GetArg("FarInfrared11CLMMax").ToString());
float FarInfrared1112CLMMin = float.Parse(_argumentProvider.GetArg("FarInfrared1112CLMMin").ToString());
float[] cloudyArgs = new float[] { NearInfraredCLMMin, FarInfrared11CLMMax, FarInfrared1112CLMMin };
Int16 defCloudy = (Int16)_argumentProvider.GetArg("defCloudy");
float zoom = (ushort)_argumentProvider.GetArg("resultZoom");
zoom = zoom == 0f ? 1000 : zoom;
string[] aois = _argumentProvider.GetArg("AOITemplate") as string[];
string aoiTemplate = (aois == null || aois.Length == 0) ? null : aois[0];
string[] inputFiles = GetStringArray("RasterFile");
if (inputFiles == null || inputFiles.Length == 0)
{
PrintInfo("没有设置输入数据");
return(null);
}
bool isFitterCloud;
if (!bool.TryParse(_argumentProvider.GetArg("isFilterCloudy").ToString(), out isFitterCloud))
{
PrintInfo("是否过滤云参数设置不正确！");
return(null);
}
IExtractResultArray results = new ExtractResultArray("EVI");
foreach (string inputFile in inputFiles)
{
//计算RVI
IExtractResult ret = CalcEVIAlgorithm1(inputFile, bandNos, zoom, bandZoom, cloudyArgs, defCloudy, isFitterCloud, aoiTemplate, progressTracker);
if (ret != null)
{
results.Add(ret as IExtractResultBase);
}
}
return(results);
}
private IExtractResult DataVal(ValArguments args)
{
//分波长，每个波长多时次进行验证（前提各时次地理位置相同）
//2,3,4
IVectorFeatureDataReader reader = AeronetDataReaderFactory.GetVectorFeatureDataReader(args.FileNamesToVal[0], new object[] { "LEV20" });
Dictionary <string, List <AslDataSet> >[] fieldValue = new Dictionary <string, List <AslDataSet> >[] { new Dictionary <string, List <AslDataSet> > {
},
new Dictionary <string, List <AslDataSet> > {
}, new Dictionary <string, List <AslDataSet> > {
} }; ///分别为470,550,650波长，每个字典分别为站点名为关键字，值为观测站点值的时间序列
foreach (string item in args.FileNamesForVal)
{
RasterIdentify rid = new RasterIdentify(item);
using (IRasterDataProvider dataPrd2Val = GeoDataDriver.Open(item) as IRasterDataProvider)
{
//470
for (int bandNo = 2; bandNo < 5; bandNo++)
{
string description = dataPrd2Val.GetRasterBand(bandNo).Description;
string key = Regex.Match(description, pattern).ToString();
int bandLength = Int32.Parse(key);
int fieldIndex = 0;
//求验证数据中的Field
for (int i = 5; i < 20; i++)
{
if (bandLength >= GetBandLength(reader.Fields[i]) &&
bandLength < GetBandLength(reader.Fields[i - 1]))
{
fieldIndex = i;
break;
}
}
//验证数据中在范围内时间内的Feature
string timeString = rid.OrbitDateTime.ToString("dd:MM:yyyy");
string t3 = rid.OrbitDateTime.ToString("yyyy/MM/dd");
Feature[] feature4Vals = GetValFeature(reader.Features, dataPrd2Val.CoordEnvelope, timeString);
foreach (Feature fet in feature4Vals)
{
//已存在该站点
string location = fet.FieldValues[0];
double value4Val = StringToDouble(fet.FieldValues, fieldIndex);
if (value4Val == -9999)
{
continue;
}
double value2Val = ReadDataValueInRaster(dataPrd2Val, fet.Geometry.Envelope.MinX, fet.Geometry.Envelope.MinY, bandNo);
if (value2Val < 0)//去除无效值
{
continue;
}
if (fieldValue[bandNo - 2].ContainsKey(location))
{
fieldValue[bandNo - 2][location].Add(new AslDataSet(t3, new double[] { value2Val, value4Val }));
}
else
{
fieldValue[bandNo - 2].Add(location, new List <AslDataSet> {
new AslDataSet(t3, new double[] { value2Val, value4Val })
});
}
}
}
}
}
IExtractResultArray array = new ExtractResultArray("统计表格");
//生成结果
if (args.CreatScatter)
{
for (int i = 0; i < fieldValue.Length; i++)
{
foreach (string key in fieldValue[i].Keys)
{
List <string[]> rowList = new List <string[]>();
foreach (AslDataSet set in fieldValue[i][key])
{
rowList.Add(new string[] { set.DateString, set.SiteValue[0].ToString(), set.SiteValue[1].ToString() });
}
string[][] rows = rowList.ToArray();
IStatResult result = new StatResult("站点名称:" + key + "波长:" + GetBandLength(i), new string[] { "时间", "待验证ASL", "Aeronet LST" }, rows);
string title = "气溶胶产品数据对比";
string filename = GetOutputFileName(args.FileNamesForVal, "SCAT", key, GetBandLength(i));
try
{
using (StatResultToChartInExcelFile excelControl = new StatResultToChartInExcelFile())
{
excelControl.Init(masExcelDrawStatType.xlXYScatter);
excelControl.Add(title, result, true, 1, false, result.Columns[1], result.Columns[2]);
if (!filename.ToUpper().EndsWith(".XLSX"))
{
filename += ".XLSX";
}
excelControl.SaveFile(filename);
IFileExtractResult res = new FileExtractResult("SCAT", filename);
array.Add(res);
}
}
catch (Exception ex)
{
}
}
}
}
if (args.CreatTimeSeq)
{
for (int i = 0; i < fieldValue.Length; i++)
{
foreach (string key in fieldValue[i].Keys)
{
List <string[]> rowList = new List <string[]>();
foreach (AslDataSet set in fieldValue[i][key])
{
rowList.Add(new string[] { set.DateString, set.SiteValue[0].ToString(), set.SiteValue[1].ToString() });
}
string[][] rows = rowList.ToArray();
IStatResult result = new StatResult("站点名称:" + key + "波长:" + GetBandLength(i), new string[] { "时间", "待验证ASL", "Aeronet LST" }, rows);
string title = "气溶胶产品数据对比";
string filename = GetOutputFileName(args.FileNamesForVal, "SEQD", key, GetBandLength(i));
try
{
using (StatResultToChartInExcelFile excelControl = new StatResultToChartInExcelFile())
{
excelControl.Init(masExcelDrawStatType.xlLineMarkers);
excelControl.Add(title, result, true, 0, true, result.Columns[0], "ASL");
if (!filename.ToUpper().EndsWith(".XLSX"))
{
filename += ".XLSX";
}
excelControl.SaveFile(filename);
IFileExtractResult res = new FileExtractResult("SEQD", filename);
array.Add(res);
}
}
catch (Exception ex)
{
}
}
}
}
return(array);
}
private IExtractResult EVIAlgorithm2(Action <int, string> progressTracker)
{
int bands = _argumentProvider.DataProvider.BandCount;
if (bands == 0 || bands == 1)
{
PrintInfo("请选择正确的局地文件进行计算。");
return(null);
}
if (_argumentProvider.GetArg("Visible") == null)
{
PrintInfo("参数\"Visible\"为空。");
return(null);
}
IBandNameRaster bandNameRaster = _argumentProvider.DataProvider as IBandNameRaster;
int bandV = TryGetBandNo(bandNameRaster, "Visible");
if (_argumentProvider.GetArg("NearInfrared") == null)
{
PrintInfo("参数\"NearInfrared\"为空。");
return(null);
}
int bandN = TryGetBandNo(bandNameRaster, "NearInfrared");
if (_argumentProvider.GetArg("Blue") == null)
{
PrintInfo("参数\"Blue\"为空。");
return(null);
}
int bandB = TryGetBandNo(bandNameRaster, "Blue");
if (bandV < 1 || bandB < 1 || bandN < 1 || bandV > bands || bandB > bands || bandN > bands)
{
PrintInfo("获取波段序号失败,可能是波段映射表配置错误或判识算法波段参数配置错误。");
return(null);
}
if (_argumentProvider.GetArg("Visible_Zoom") == null)
{
PrintInfo("参数\"Visible_Zoom\"为空。");
return(null);
}
double visibleZoom = (double)_argumentProvider.GetArg("Visible_Zoom");
if (_argumentProvider.GetArg("NearInfrared_Zoom") == null)
{
PrintInfo("参数\"NearInfrared_Zoom\"为空。");
return(null);
}
double nearInfrared = (double)_argumentProvider.GetArg("NearInfrared_Zoom");
if (_argumentProvider.GetArg("Blue_Zoom") == null)
{
PrintInfo("参数\"Blue_Zoom\"为空。");
return(null);
}
double blueZoom = (double)_argumentProvider.GetArg("Blue_Zoom");
int[] bandNos = new int[] { bandV, bandN, bandB, };
double[] bandZoom = new double[] { visibleZoom, nearInfrared, blueZoom };
Dictionary <string, string> dic = Obj2Dic(_argumentProvider.GetArg("ArgumentSetting"));
string nearVisiableMinStr = dic.ContainsKey("NearVisableMin") ? dic["NearVisableMin"] : string.Empty;
string nearVisiableMaxStr = dic.ContainsKey("NearVisableMax") ? dic["NearVisableMax"] : string.Empty;
string visibleMinStr = dic.ContainsKey("VisibleMin") ? dic["VisibleMin"] : string.Empty;
float nearVisiableMin = float.Parse(nearVisiableMinStr);
float nearVisiableMax = float.Parse(nearVisiableMaxStr);
float visibleMin = float.Parse(visibleMinStr);
float[] cloudyArgs = new float[] { visibleMin, nearVisiableMax, nearVisiableMin };
Int16 defCloudy = (Int16)_argumentProvider.GetArg("defCloudy");
float zoom = (ushort)_argumentProvider.GetArg("resultZoom");
zoom = zoom == 0f ? 1000 : zoom;
string[] aois = _argumentProvider.GetArg("AOITemplate") as string[];
string aoiTemplate = (aois == null || aois.Length == 0) ? null : aois[0];
string[] inputFiles = GetStringArray("RasterFile");
if (inputFiles == null || inputFiles.Length == 0)
{
PrintInfo("没有设置输入数据");
return(null);
}
bool isFitterCloud;
if (!bool.TryParse(_argumentProvider.GetArg("isFilterCloudy").ToString(), out isFitterCloud))
{
PrintInfo("是否过滤云参数设置不正确！");
return(null);
}
IExtractResultArray results = new ExtractResultArray("EVI");
foreach (string inputFile in inputFiles)
{
//计算RVI
IExtractResult ret = CalcEVIAlgorithm2(inputFile, bandNos, zoom, bandZoom, cloudyArgs, defCloudy, isFitterCloud, aoiTemplate, progressTracker);
if (ret != null)
{
results.Add(ret as IExtractResultBase);
}
}
return(results);
}
private IExtractResult SnowPrdAlgorithm()
{
string inputFileName = _argumentProvider.DataProvider.fileName;
if (string.IsNullOrEmpty(inputFileName) || !File.Exists(inputFileName))
{
return(null);
}
int[] bandNos = CheckBandNos();
if (bandNos == null || bandNos.Length < 10)
{
PrintInfo("获取波段序号失败,可能是波段映射表配置错误或判识算法波段参数配置错误。");
return(null);
}
double[] sdParas = GetSDPara();
if (sdParas == null)
{
PrintInfo("雪深计算参数为空。");
return(null);
}
//查找参数数据
string argFileDir = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "SystemData\\ProductArgs\\SNW\\SnowArgFile");
string fileNameBare = Path.Combine(argFileDir, "china_bares.dat");
string filenameGrass = Path.Combine(argFileDir, "china_grass.dat");
string filenameForest = Path.Combine(argFileDir, "china_forest.dat");
string filenameFarmhand = Path.Combine(argFileDir, "china_farmhand.dat");
string filenameDensity = Path.Combine(argFileDir, "china_snow_density.dat");
if (!File.Exists(filenameDensity))
{
return(null);
}
//1、查找是否存在各土地类型百分比文件（4个），不存在则生成
string bareFracFile = Path.ChangeExtension(fileNameBare, "_frac.dat");
string grassFracFile = Path.ChangeExtension(filenameGrass, "_frac.dat");
string forestFracFile = Path.ChangeExtension(filenameForest, "_frac.dat");
string farmhandFracFile = Path.ChangeExtension(filenameFarmhand, "_frac.dat");
string[] argFiles = new string[] { bareFracFile, grassFracFile, forestFracFile, farmhandFracFile };
foreach (string file in argFiles)
{
string sumFile = null;
if (!File.Exists(file))
{
//计算
//1)生成SummaryFile（不存在）
sumFile = GetArgSummaryFile(fileNameBare, filenameGrass, filenameForest, filenameFarmhand);
//2)计算某个百分比文件
ComputeFracFile(sumFile, file);
}
}
//2、计算雪深、雪水当量
//雪深
IExtractResultArray array = new ExtractResultArray("雪深当量");
IFileExtractResult depthResult = ComputeSnowDepth(inputFileName, bandNos, argFiles, sdParas);
//雪水当量
if (!File.Exists(filenameDensity))
{
return(null);
}
string depthFileName = (depthResult as FileExtractResult).FileName;
if (!File.Exists(depthFileName))
{
return(null);
}
IFileExtractResult sweResult = ComputeSnowSWE(filenameDensity, depthFileName);
array.Add(depthResult);
array.Add(sweResult);
return(array);
}
private IExtractResult StatProcentRaster <T>(string fname, Dictionary <string, Func <short, bool> > filters, Action <int, string> progressTracker)
{
string statString = AreaStatProvider.GetAreaStatItemFileName("行政区划");
SortedDictionary <string, double[][]> srcResult = RasterStatFactory.StatPercent <short>(fname, statString, filters, progressTracker);
//删除为空的AOI区域以及计算百分比
SortedDictionary <string, double[][]> statResult = new SortedDictionary <string, double[][]>();
//区间个数
int regionCount = filters.Keys.Count;
foreach (string key in srcResult.Keys)
{
if (srcResult[key] == null)
{
continue;
}
else
{
int zeroCount = 0;
double[][] value = new double[regionCount][];
for (int i = 0; i < regionCount; i++)
{
value[i] = new double[] { srcResult[key][i][0], srcResult[key][i][0] / srcResult[key][i][1] * 100 };
if (value[i][0] == 0)
{
zeroCount++;
}
}
//如果全为0，也不添加
if (zeroCount < regionCount)
{
statResult.Add(key, value);
}
}
}
if (statResult.Count == 0)
{
return(null);
}
string productName = _subProductDef.ProductDef.Name;
string title = productName + "行政区划";
string subTitle = GetSubTitle(fname);
string[] colDescs = new string[] { "面积", "百分比" };
IStatResult[] results = DicToStatResult(statResult, filters.Keys.ToArray(), subTitle, colDescs);
if (results == null)
{
return(null);
}
string outFileIdentify = GetStringArgument("OutFileIdentify");
string[] outFileIdentifys = new string[] { outFileIdentify, outFileIdentify.Substring(1) + "P" };
string productIdentify = _subProductDef.ProductDef.Identify;
IExtractResultArray array = new ExtractResultArray("LST");
string filename = null;
for (int i = 0; i < results.Length; i++)
{
if (i >= outFileIdentifys.Length)
{
break;
}
filename = StatResultToFile(new string[] { fname }, results[i], productIdentify, outFileIdentifys[i], title + colDescs[i] + "统计", null, 1, false, 1);
array.Add(new FileExtractResult(outFileIdentify, filename));
}
return(array);
}
public override IExtractResult Make(Action <int, string> progressTracker)
{
if (!CheckArguments())
{
return(null);
}
Dictionary <DateTime, List <string> > orderedFiles = GroupByOrbitDate();
if (orderedFiles.Count == 0)
{
return(null);
}
object obj = _argumentProvider.GetArg("ThemeGraphyGenerator");
if (obj == null)
{
return(null);
}
IThemeGraphGenerator tgg = obj as IThemeGraphGenerator;
List <string> rdpList = new List <string>();//按照日期生成的多个日最大合成数据
//每天生成一个最大日合成图
foreach (DateTime time in orderedFiles.Keys)
{
RasterMoasicProcesser processer = new RasterMoasicProcesser();
List <IRasterDataProvider> srcdata = new List <IRasterDataProvider>();
try
{
foreach (string item in orderedFiles[time])
{
IRasterDataProvider rdp = GeoDataDriver.Open(item) as IRasterDataProvider;
if (rdp != null)
{
srcdata.Add(rdp);
}
}
string fileName = null;
IFileNameGenerator generator = GetFileNameGenerator();
if (generator == null)
{
fileName = string.Empty;
}
else
{
fileName = generator.NewFileName(CreatRasterIndetifyId(orderedFiles[time].ToArray(), "SNW", "MAXI", GetDataIdentify(), ".LDF", null));
}
using (IRasterDataProvider dstPrd = processer.Moasic <Int16>(srcdata.ToArray(), "LDF", fileName, false, null, "MAX", null, (srcValue, dstValue) => { return(srcValue > dstValue ? srcValue : dstValue); }))
{
if (dstPrd != null)
{
rdpList.Add(dstPrd.fileName);
}
}
}
finally
{
foreach (IRasterDataProvider rdp in srcdata)
{
rdp.Dispose();
}
srcdata.Clear();
}
}
string templatName = GetStringArgument("ThemeGraphTemplateName");
string colorTabelName = GetColorTableName("colortablename");
IExtractResultArray resultArray = new ExtractResultArray("MAXI");
foreach (string file in rdpList)
{
tgg.Generate(file, templatName, null, null, "MAXI", colorTabelName);
string resultFilename = tgg.Save();
if (string.IsNullOrEmpty(resultFilename))
{
continue;
}
resultArray.Add(new FileExtractResult("MAXI", resultFilename));
}
if (resultArray != null)
{
return(resultArray);
}
return(null);
}
public override IExtractResult MakeExtProduct(IPixelIndexMapper piexd, Action <int, string> progressTracker)
{
object obj = _argumentProvider.GetArg("ucAnlysisTool");
UCAnlysisTool ucAnlysisTool = null;
if (obj != null)
{
ucAnlysisTool = obj as UCAnlysisTool;
}
else
{
return(null);
}
IRasterDataProvider sourceraster = _argumentProvider.DataProvider as IRasterDataProvider;
RasterIdentify rid = new RasterIdentify(_argumentProvider.DataProvider.fileName);
rid.ProductIdentify = _subProductDef.ProductDef.Identify;
rid.SubProductIdentify = _subProductDef.Identify;
string tempFile = rid.ToWksFullFileName(".dat");
string outFileName = Path.Combine(Path.GetDirectoryName(tempFile), Path.GetFileNameWithoutExtension(tempFile) + GetExtInfo(ucAnlysisTool.cmbType.Text) + ".ldf");
IExtractResultArray array = new ExtractResultArray("BAG");
bool onlyTxt = bool.Parse(_argumentProvider.GetArg("OnlyTxt").ToString());
if (!onlyTxt)
{
int totalLength = 0;
//原始影像raster
List <RasterMaper> listRaster = new List <RasterMaper>();
RasterMaper rmsoure = new RasterMaper(sourceraster, GetBandArray(sourceraster.BandCount));
int totalbandcount = sourceraster.BandCount;
listRaster.Add(rmsoure);
try
{
using (IRasterDataProvider outRaster = CreateOutM_BandRaster(outFileName, listRaster.ToArray(), totalbandcount))
{
//波段总数
RasterMaper[] fileIns = listRaster.ToArray();
RasterMaper[] fileOuts = new RasterMaper[] { new RasterMaper(outRaster, GetBandArray(totalbandcount)) };
//创建处理模型
RasterProcessModel <UInt16, UInt16> rfr = null;
rfr = new RasterProcessModel <UInt16, UInt16>(progressTracker);
rfr.SetRaster(fileIns, fileOuts);
rfr.SetFeatureAOI(_argumentProvider.AOIs);
rfr.RegisterCalcModel(new RasterCalcHandler <UInt16, UInt16>((rvInVistor, rvOutVistor, aoi) =>
{
int dataLength = rvOutVistor[0].SizeY * rvOutVistor[0].SizeX;
if (rvInVistor[0].RasterBandsData == null || rvInVistor[0].RasterBandsData[0] == null)
{
totalLength += dataLength;
return;
}
for (int index = 0; index < dataLength; index++)
{
if (_argumentProvider.AOI.Contains(totalLength + index))
{
for (int i = 0; i < totalbandcount; i++)
{
rvOutVistor[0].RasterBandsData[i][index] = rvInVistor[0].RasterBandsData[i][index];
}
}
}
totalLength += dataLength;
}
));
//执行
rfr.Excute(0);
}
string dstfilename = outFileName.Replace(".ldf", ".dat");
if (File.Exists(dstfilename))
{
File.Delete(dstfilename);
}
File.Move(outFileName, dstfilename);
FileExtractResult res = new FileExtractResult("BAG", dstfilename, true);
res.SetDispaly(false);
array.Add(res);
}
finally
{
}
}
if (!string.IsNullOrEmpty(ucAnlysisTool.txtInfos.Text))
{
string txtFile = outFileName.Replace(".ldf", ".txt");
File.WriteAllLines(txtFile, ucAnlysisTool.WriteText, Encoding.Unicode);
FileExtractResult resTxt = new FileExtractResult("BAG", txtFile, true);
resTxt.SetDispaly(false);
array.Add(resTxt);
}
return(array);
}
private IExtractResult ComputeByCurrentRaster(IRasterDataProvider currPrd, Action <int, string> progressTracker)
{
float curNDVI = 0f;
currPrd = currPrd != null ? currPrd : _argumentProvider.DataProvider;
if (currPrd == null)
{
return(null);
}
IBandNameRaster bandNameRaster = _argumentProvider.DataProvider as IBandNameRaster;//
int VisibleCH = TryGetBandNo(bandNameRaster, "RedBand");
int NearInfraredCH = TryGetBandNo(bandNameRaster, "NirBand");
int FarInfrared11CH = TryGetBandNo(bandNameRaster, "FarBand");
double VisibleZoom = (double)_argumentProvider.GetArg("RedBand_Zoom");
double NearInfraredZoom = (double)_argumentProvider.GetArg("NirBand_Zoom");
double FarInfrared11Zoom = (double)_argumentProvider.GetArg("FarBand_Zoom");
bool isAutoCloud = (bool)_argumentProvider.GetArg("isAutoCloud");
bool isAppCloud = (bool)_argumentProvider.GetArg("isAppCloud");
if (VisibleCH == -1 || NearInfraredCH == -1 || (isAutoCloud && FarInfrared11CH == -1))
{
PrintInfo("获取波段序号失败,可能是波段映射表配置错误或判识算法波段参数配置错误。");
return(null);
}
string normalizationFile = string.Empty;
AngleParModel angleArg = _argumentProvider.GetArg("Angle") as AngleParModel;
if (angleArg != null && angleArg.ApplyN)
{
if (string.IsNullOrEmpty(angleArg.FileAsatA) || !File.Exists(angleArg.FileAsatA) ||
string.IsNullOrEmpty(angleArg.FileAsatZ) || !File.Exists(angleArg.FileAsatZ) ||
string.IsNullOrEmpty(angleArg.FileAsunA) || !File.Exists(angleArg.FileAsunA) ||
string.IsNullOrEmpty(angleArg.FileAsunZ) || !File.Exists(angleArg.FileAsunZ) ||
string.IsNullOrEmpty(angleArg.FileLandConvery) || !File.Exists(angleArg.FileLandConvery))
{
PrintInfo("归一化处理所需的角度信息、土地覆盖信息填写不正确或不存在,请检查...");
return(null);
}
normalizationFile = NormalizationProcess(currPrd, progressTracker);
if (string.IsNullOrEmpty(normalizationFile) || !File.Exists(normalizationFile))
{
PrintInfo("归一化处理失败");
return(null);
}
}
bool normalizationSuccess = angleArg != null && angleArg.ApplyN &&
!string.IsNullOrEmpty(normalizationFile) && File.Exists(normalizationFile) ? true : false;
float NearInfraredCLMMin = float.Parse(_argumentProvider.GetArg("NearInfraredCLMMin").ToString());
float FarInfrared11CLMMax = float.Parse(_argumentProvider.GetArg("FarInfrared11CLMMax").ToString());
float FarInfrared11WaterMin = float.Parse(_argumentProvider.GetArg("FarInfrared11WaterMin").ToString());
float NDVIWaterMax = float.Parse(_argumentProvider.GetArg("NDVIWaterMax").ToString());
Int16 defCloudy = (Int16)_argumentProvider.GetArg("defCloudy");
Int16 defWater = (Int16)_argumentProvider.GetArg("defWater");
Int16 InvaildValue = (Int16)_argumentProvider.GetArg("InvaildValue");
int cloudCH = (int)_argumentProvider.GetArg("CLMBand");
string clmFile = GetClmFile(currPrd);
bool isSetMinMax = (bool)_argumentProvider.GetArg("isSetMinMax");
float ndviMax = (float)_argumentProvider.GetArg("NDVIMax");
float ndviMin = (float)_argumentProvider.GetArg("NDVIMin");
float ndviCalcMax = float.MinValue;
float ndviCalcMin = float.MaxValue;
float PNVIZoom = (float)_argumentProvider.GetArg("PNVIZoom");
//输入文件准备
List <RasterMaper> rms = new List <RasterMaper>();
IRasterDataProvider currRaster = null;
IRasterDataProvider clmPrd = null;
IRasterDataProvider ndviPrd = null;
IFileExtractResult pviFile = null;
IExtractResultArray array = new ExtractResultArray("DRT");
if (progressTracker != null)
{
progressTracker.Invoke(normalizationSuccess ? 77 : 0, "计算改进型垂直干旱指数");
}
try
{
currRaster = normalizationSuccess ? GeoDataDriver.Open(normalizationFile) as IRasterDataProvider : currPrd;
if (!normalizationSuccess && (currRaster.BandCount < VisibleCH || currRaster.BandCount < NearInfraredCH || (isAutoCloud && currRaster.BandCount < FarInfrared11CH)))
{
PrintInfo("请选择正确的数据进行垂直干旱指数计算。");
return(null);
}
RasterMaper rmCurr = normalizationSuccess ? new RasterMaper(currRaster, new int[] { 1, 2, 3 }) :
new RasterMaper(currRaster, new int[] { VisibleCH, NearInfraredCH, FarInfrared11CH });
rms.Add(rmCurr);
bool isContainClm = false;
if (isAppCloud && !string.IsNullOrEmpty(clmFile) && File.Exists(clmFile))
{
clmPrd = GeoDataDriver.Open(clmFile) as IRasterDataProvider;
if (clmPrd.BandCount < cloudCH)
{
PrintInfo("请选择正确的云数据通道进行计算。");
return(null);
}
RasterMaper clmRm = new RasterMaper(clmPrd, new int[] { cloudCH });
rms.Add(clmRm);
isContainClm = true;
}
bool isContainNDVI = false;
string ndviFile = string.Empty;
string[] ndviFiles = GetStringArray("SelectedPrimaryFiles");
if (ndviFiles == null || ndviFiles.Length == 0 || string.IsNullOrEmpty(ndviFiles[0]) || !File.Exists(ndviFiles[0]))
{
isContainNDVI = false;
}
else
{
isContainNDVI = true;
ndviFile = ndviFiles[0];
}
int ndviCH = (int)_argumentProvider.GetArg("NDVIBand");
double ndviZoom = (double)_argumentProvider.GetArg("NDVIBand_Zoom");
if (isContainNDVI && !string.IsNullOrEmpty(ndviFile))
{
ndviPrd = GeoDataDriver.Open(ndviFile) as IRasterDataProvider;
if (ndviPrd.BandCount < ndviCH)
{
PrintInfo("请选择正确的植被指数数据通道进行计算。");
return(null);
}
RasterMaper ndviRm = new RasterMaper(ndviPrd, new int[] { ndviCH });
rms.Add(ndviRm);
isContainNDVI = true;
}
//输出文件准备（作为输入栅格并集处理）
string outFileName = GetFileName(new string[] { currRaster.fileName }, _subProductDef.ProductDef.Identify, "PNVI", ".dat", null);
using (IRasterDataProvider outRaster = CreateOutRaster(outFileName, rms.ToArray()))
{
//栅格数据映射
RasterMaper[] fileIns = rms.ToArray();
RasterMaper[] fileOuts = new RasterMaper[] { new RasterMaper(outRaster, new int[] { 1 }) };
//创建处理模型
RasterProcessModel <Int16, Int16> rfr = null;
rfr = new RasterProcessModel <Int16, Int16>(progressTracker);
rfr.SetRaster(fileIns, fileOuts);
rfr.RegisterCalcModel(new RasterCalcHandler <Int16, Int16>((rvInVistor, rvOutVistor, aoi) =>
{
int dataLength = rvOutVistor[0].SizeY * rvOutVistor[0].SizeX;
for (int index = 0; index < dataLength; index++)
{
Int16 visiableValue = rvInVistor[0].RasterBandsData[0][index];
Int16 nearInfraredValue = rvInVistor[0].RasterBandsData[1][index];
Int16 farInfraredVale = rvInVistor[0].RasterBandsData[2][index];
curNDVI = isContainNDVI ? (float)(rvInVistor[2 - (isContainClm ? 0 : 1)].RasterBandsData[0][index] / ndviZoom) : GetNDVI(nearInfraredValue, visiableValue);
if (visiableValue == 0 && nearInfraredValue == 0)
{
rvOutVistor[0].RasterBandsData[0][index] = InvaildValue;
}
else if (isContainClm && rvInVistor[1].RasterBandsData[0][index] != 0)
{
rvOutVistor[0].RasterBandsData[0][index] = defCloudy;
}
else if (isAutoCloud && (nearInfraredValue / NearInfraredZoom > NearInfraredCLMMin && farInfraredVale / FarInfrared11Zoom < FarInfrared11CLMMax))
{
rvOutVistor[0].RasterBandsData[0][index] = defCloudy;
}
else
{
if (farInfraredVale / FarInfrared11Zoom > FarInfrared11WaterMin && curNDVI < NDVIWaterMax)
{
rvOutVistor[0].RasterBandsData[0][index] = defWater;
}
else
{
rvOutVistor[0].RasterBandsData[0][index] = (Int16)(curNDVI * PNVIZoom);
if (curNDVI > ndviCalcMax)
{
ndviCalcMax = curNDVI;
}
else if (curNDVI < ndviCalcMin)
{
ndviCalcMin = curNDVI;
}
}
}
}
}));
//执行
rfr.Excute();
pviFile = new FileExtractResult(_subProductDef.Identify, outFileName, true);
pviFile.SetDispaly(false);
if (normalizationSuccess)
{
FileExtractResult nrsb = new FileExtractResult(_subProductDef.Identify, normalizationFile, true);
nrsb.SetDispaly(false);
array.Add(nrsb);
}
_argumentProvider.SetArg("CursorInfo:Image-NDVIMax", ndviCalcMax);
_argumentProvider.SetArg("CursorInfo:Image-NDVIMin", ndviCalcMin);
array.Add(pviFile);
}
}
finally
{
if (clmPrd != null)
{
clmPrd.Dispose();
}
if (ndviPrd != null)
{
ndviPrd.Dispose();
}
}
FileExtractResult mpdiFile = null;
if (File.Exists(pviFile.FileName))
{
mpdiFile = CalcMPDI(pviFile.FileName, ndviCalcMin, ndviCalcMax, currRaster, normalizationSuccess, progressTracker);
if (mpdiFile != null)
{
array.Add(mpdiFile);
}
}
return(array);
}
private IExtractResult TSTATAlgorithmStat(string outId, SubProductInstanceDef instance, Dictionary <string, Func <short, bool> > filters, Action <int, string> progressTracker)
{
string[] files = GetStringArray("SelectedPrimaryFiles");
IStatResult temp = null;
List <string> colums = new List <string>();
List <string[]> rowTemp = new List <string[]>();
IStatResult dstResult = null;
RasterIdentify rid = null;
string dateStr = _argumentProvider.GetArg("tostringtype").ToString();
int fileIndex = 0;
float step = 90f / files.Length;
try
{
if (outId == "CCAR")
{
foreach (string file in files)
{
if (progressTracker != null)
{
progressTracker.Invoke((int)Math.Ceiling(fileIndex * step), "正在统计第[" + fileIndex + "]个文件,请稍后...");
}
temp = StatRasterToStatResult <short>(instance, new string[] { file }, filters, progressTracker);
rid = new RasterIdentify(file);
foreach (string[] cols in temp.Rows)
{
cols[0] = rid.OrbitDateTime.ToString(dateStr);
rowTemp.Add(cols);
}
if (colums.Count == 0)
{
colums.AddRange(temp.Columns);
}
}
rowTemp.Sort((before, last) => before.First().CompareTo(last.First()));
dstResult = new StatResult(null, colums.ToArray(), rowTemp.ToArray());
if (progressTracker != null)
{
progressTracker.Invoke(95, "正在写入统计信息,请稍后...");
}
return(new FileExtractResult("LST", StatResultToFile(files, dstResult, "LST", "T" + outId.Substring(0, 3), "", "", 1, false)));
}
if (instance.AOIProvider == "省级行政区划" || instance.AOIProvider == "土地利用类型")
{
string statVector = instance.AOIProvider == "省级行政区划" ? "行政区划" : "土地利用类型";
string title;
string[] colDescs;
IStatResult[] tempArray = null;
IStatResult[] dstResultArray = null;
List <string> tempList = null;
foreach (string file in files)
{
fileIndex++;
if (progressTracker != null)
{
progressTracker.Invoke((int)Math.Ceiling(fileIndex * step), "正在统计第[" + fileIndex + "]个文件,请稍后...");
}
tempArray = StatProcentRasterToStatResult(file, statVector, filters, null, out title, out colDescs, true);
if (dstResultArray == null)
{
dstResultArray = new IStatResult[tempArray.Length];
}
rid = new RasterIdentify(file);
for (int i = 0; i < dstResultArray.Length; i++)
{
try
{
foreach (string[] cols in tempArray[i].Rows)
{
tempList = new List <string>();
tempList.AddRange(cols);
tempList.Insert(1, rid.OrbitDateTime.ToString(dateStr));
rowTemp.Add(tempList.ToArray());
}
if (colums.Count == 0)
{
tempList = new List <string>();
tempList.AddRange(tempArray[i].Columns);
tempList.Insert(1, "日期");
colums.AddRange(tempList.ToArray());
}
if (dstResultArray[i] == null)
{
dstResultArray[i] = new StatResult(null, colums.ToArray(), rowTemp.ToArray());
}
else
{
List <string[]> tempRowsFromArray = new List <string[]>();
tempRowsFromArray.AddRange(dstResultArray[i].Rows);
tempRowsFromArray.AddRange(rowTemp.ToArray());
StringArrayComparer comparer = new StringArrayComparer(true);
tempRowsFromArray.Sort(comparer);
dstResultArray[i] = new StatResult(null, colums.ToArray(), tempRowsFromArray.ToArray());
}
}
finally
{
colums.Clear();
rowTemp.Clear();
}
}
}
if (progressTracker != null)
{
progressTracker.Invoke(95, "正在写入统计信息,请稍后...");
}
string outFileIdentify = GetStringArgument("OutFileIdentify");
string[] outFileIdentifys = new string[] { "T" + outFileIdentify.Substring(0, 3), "T" + outFileIdentify.Substring(0, 2) + "P" };
IExtractResultArray array = new ExtractResultArray("LST");
for (int i = 0; i < dstResultArray.Length; i++)
{
List <RowDisplayDef> rowRulers = new List <RowDisplayDef>();
List <int> displayRowNum = new List <int>();
int count = -1;
string befStr = dstResultArray[i].Rows[0].First();
for (int row = 0; row < dstResultArray[i].Rows.Length; row++)
{
count++;
if (dstResultArray[i].Rows[row].First() == befStr)
{
displayRowNum.Add(count + 3);
continue;
}
AddRowRuler(ref rowRulers, displayRowNum, dstResultArray[i].Rows[row - 1][0], true, false, false);
displayRowNum.Clear();
befStr = dstResultArray[i].Rows[row].First();
displayRowNum.Add(count + 3);
}
AddRowRuler(ref rowRulers, displayRowNum, befStr, true, false, false);
array.Add(new FileExtractResult("LST", StatResultToFile(files, dstResultArray[i], "LST", outFileIdentifys[i], "", "", 1, rowRulers, 3, (dstResultArray[i].Columns.Length - 2))));
}
return(array);
}
}
finally
{
if (progressTracker != null)
{
progressTracker.Invoke(100, "完成统计分析!");
}
}
PrintInfo("指定的算法\"" + instance.Name + "\"没有实现。");
return(null);
}
private IExtractResult HistoryDataLayoutAlgorithm(Action <int, string> progressTracker)
{
//1.获取到数据
List <string> list = ExportManager.GetInstance().List; //这个针对查询出来的数据出专题图
string[] inputfiles = list.ToArray();
//再加一上基于 同期统计数据的专题图，如果是冬季的，还要再计算一次
StatisticResultManager manager = StatisticResultManager.GetInstance();
List <string> list2 = manager.GetFilePathFromList(); //得到的是基于数据查询的数据又做的统计数据
if (list2.Count != 0)
{
inputfiles = list2.ToArray();
period = "yes";
Match m = DataReg2.Match(inputfiles[0]);
if (m.Success)
{
Iswinter = "yes";
}
}
//处理后的数据存储路径
string savePath = _argumentProvider.GetArg("HistoryDataSave") as string;
regioNames = _argumentProvider.GetArg("regionNames") as string;
string orbitType = _argumentProvider.GetArg("OrbitType") as string;
string Str = null;
if (orbitType == "Ascend")
{
Str = "_A_";
}
if (orbitType == "Descend")
{
Str = "_D_";
}
//同期统计计算传出来的文件没有分升降轨，这里进行区分
List <string> fnamelist = new List <string>();
foreach (string file in inputfiles)
{
if (Path.GetFileName(file).Contains(Str))
{
fnamelist.Add(file);
}
}
inputfiles = fnamelist.ToArray();
//处理后的数据，用它来出专题图
List <string> afterProcessfiles = new List <string>();
//(插一步，通过这个原始选择的文件名时间信息把专题图名称确定)
//2.确定选择区域，没有选或者中国区域不要用裁，如果是其地区首先裁切，并且放到指定文件夹下
aoiContainer = new GeoDo.RSS.Core.VectorDrawing.AOIContainerLayer();
MulRegionsClip muticlip = new MulRegionsClip(); //裁切
MWSSmoothHelp smooth = new MWSSmoothHelp(); //平滑
string regionsname = "";
#region 获得目标区域
aoiContainer = new GeoDo.RSS.Core.VectorDrawing.AOIContainerLayer();
string fieldName;
string shapeFilename;
int fieldIndex = -1;
List <string> fieldValues = new List <string>();
using (frmStatSubRegionTemplates frm = new frmStatSubRegionTemplates())
{
frm.listView1.MultiSelect = true;
if (frm.ShowDialog() == DialogResult.OK)
{
Feature[] fets = frm.GetSelectedFeatures();
fets = frm.GetStatFeatures(out fieldName, out shapeFilename, out fieldIndex);
if (fets == null)
{
aoiContainer = null;
regionsname = "全国";
}
else
{
string chinafieldValue = fets[0].GetFieldValue(fieldIndex);
if (chinafieldValue == "中国")
{
aoiContainer = null;
regionsname = "全国";
}
else
{
foreach (Feature fet in fets)
{
fieldValues.Add(fet.GetFieldValue(fieldIndex)); //获得选择区域名称
aoiContainer.AddAOI(fet);
}
foreach (string region in fieldValues)
{
regionsname += region;
}
if (regionsname.Contains("西藏") && regionsname.Contains("青海"))
{
regionsname = "青藏地区";
}
if (!string.IsNullOrEmpty(regioNames))
{
regionsname = regioNames.Trim();
}
}
}
}
else //没有点击确定，返回空
{
return(null);
}
}
#endregion
if (aoiContainer == null)
{
//不用裁切,只做中值滤波的平滑处理。
regionsname = "全国";
foreach (string infile in inputfiles)
{
//创建专题图路径
gxdsave = savePath + "\\" + regionsname + "\\" + "专题图";
if (!System.IO.Directory.Exists(gxdsave))//如果不存在这个路径
{
System.IO.Directory.CreateDirectory(gxdsave);
}
//创建平滑路径
string smoothsave = savePath + "\\" + regionsname + "\\" + "平滑";
if (!System.IO.Directory.Exists(smoothsave))
{
System.IO.Directory.CreateDirectory(smoothsave);
}
//创建平滑\\中值
string filtersave = smoothsave + "\\" + "中值";
if (!System.IO.Directory.Exists(filtersave))
{
System.IO.Directory.CreateDirectory(filtersave);
}
string filterfile = smooth.ComputerMid(infile, 5, filtersave);
string hdrfile = Path.GetDirectoryName(filterfile) + "\\" + Path.GetFileNameWithoutExtension(filterfile) + ".hdr";
afterProcessfiles.Add(filterfile);
}
}
else
{
//创建裁切路径
string clipsave = savePath + "\\" + regionsname + "\\" + "裁切";
if (!System.IO.Directory.Exists(clipsave))//如果不存在这个路径
{
System.IO.Directory.CreateDirectory(clipsave);
}
//创建专题图路径
gxdsave = savePath + "\\" + regionsname + "\\" + "专题图";
if (!System.IO.Directory.Exists(gxdsave))//如果不存在这个路径
{
System.IO.Directory.CreateDirectory(gxdsave);
}
//创建平滑路径
string smoothsave = savePath + "\\" + regionsname + "\\" + "平滑";
if (!System.IO.Directory.Exists(smoothsave))
{
System.IO.Directory.CreateDirectory(smoothsave);
}
//创建平滑\\中值
string filtersave = smoothsave + "\\" + "中值";
if (!System.IO.Directory.Exists(filtersave))
{
System.IO.Directory.CreateDirectory(filtersave);
}
//创建平滑\\插值
string bilisave = smoothsave + "\\" + "插值";
if (!System.IO.Directory.Exists(bilisave))
{
System.IO.Directory.CreateDirectory(bilisave);
}
foreach (string infile in inputfiles)
{
//加一个条件判断要处理的数据是否已经存在，如果存就不用再做
string newclipfile = Path.Combine(clipsave, Path.GetFileName(infile).Replace("China", regionsname));
if (!File.Exists(newclipfile))
{
string clipfile = muticlip.MutiRegionsClip(infile, aoiContainer, clipsave);
string hdrfile = Path.GetDirectoryName(clipfile) + "\\" + Path.GetFileNameWithoutExtension(clipfile) + ".hdr";
//重命名
string newhdrfile = Path.Combine(Path.GetDirectoryName(clipfile), Path.GetFileNameWithoutExtension(infile).Replace("China", regionsname) + ".hdr");
FileInfo fi = new FileInfo(clipfile);
fi.MoveTo(newclipfile);
FileInfo fihdr = new FileInfo(hdrfile);
fihdr.MoveTo(newhdrfile);
}
//裁切后要对数据中值、插值
string filterfile = smooth.ComputerMid(newclipfile, 5, filtersave);
string bilifile = smooth.Bilinear(filterfile, 10, bilisave);
afterProcessfiles.Add(bilifile);
}
}
//把处理后的afterProcessfiles.ToArray()数组文件名标识变为“HFSD”或“HFWE”。
foreach (string file in afterProcessfiles.ToArray())
{
string hdrfile = Path.GetDirectoryName(file) + "\\" + Path.GetFileNameWithoutExtension(file) + ".hdr";
string newfile = "";
string newhdr = "";
if (file.Contains("MWSD"))
{
newfile = file.Replace("MWSD", "HFSD");
newhdr = hdrfile.Replace("MWSD", "HFSD");
}
if (file.Contains("MSWE"))
{
newfile = file.Replace("MSWE", "HFWE");
newhdr = hdrfile.Replace("MSWE", "HFWE");
}
FileInfo fi = new FileInfo(file);
if (!File.Exists(newfile))
{
fi.MoveTo(newfile);
}
FileInfo fihdr = new FileInfo(hdrfile);
if (!File.Exists(newhdr))
{
fihdr.MoveTo(newhdr);
}
imgfiles.Add(newfile);
}
IExtractResultArray results = new ExtractResultArray("");
foreach (string arguments in imgfiles.ToArray())
{
string product = "";
if (arguments.Contains("HFSD"))
{
_argumentProvider.SetArg("OutFileIdentify", "HSDI");
product = "雪深";
}
if (arguments.Contains("HFWE"))
{
_argumentProvider.SetArg("OutFileIdentify", "HSWI");
product = "雪水当量";
}
//解析文件名确定专题图名称
string filename = Path.GetFileNameWithoutExtension(arguments);
if (period == "yes") //同期统计的
{
if (Iswinter == "yes")
{
Match m = DataReg2.Match(filename);
string year = "";
if (m.Success)
{
year = m.Value;
}
imgname = year.Substring(0, 4) + "年" + "冬季" + regionsname + product + "分布图";
}
else
{
Regex DataReg1 = new Regex(@"(?<year>\d{4})_(?<year>\d{4})", RegexOptions.Compiled);
Match m = DataReg1.Match(filename);
string year = "";
if (m.Success)
{
year = m.Value;
}
//提取年至avg之间的字符
string filetime = filename.Substring(filename.IndexOf(year), filename.Length - 3 - filename.IndexOf(year));
string[] mxchars = filetime.Split(new char[] { '_' });
string mx = "";//月+旬
if (filename.Contains("Xun"))
{
if (mxchars[3] == "1")
{
mx = mxchars[2] + "月" + "上旬";
}
if (mxchars[3] == "2")
{
mx = mxchars[2] + "月" + "中旬";
}
if (mxchars[3] == "3")
{
mx = mxchars[2] + "月" + "下旬";
}
}
if (filename.Contains("Month"))
{
mx = mxchars[2] + "月";
}
imgname = year + "年" + mx + regionsname + product + "分布图";
}
}
else
{
Regex DataReg = new Regex(@"(?<year>\d{4})", RegexOptions.Compiled);
Match m = DataReg.Match(filename);
string year = "";
if (m.Success)
{
year = m.Value;
}
//提取年至avg之间的字符
string filetime = filename.Substring(filename.IndexOf(year), filename.Length - 3 - filename.IndexOf(year));
string[] mxchars = filetime.Split(new char[] { '_' });
string mx = "";//月+旬
if (filename.Contains("Xun"))
{
if (mxchars[2] == "1")
{
mx = mxchars[1] + "月" + "上旬";
}
if (mxchars[2] == "2")
{
mx = mxchars[1] + "月" + "中旬";
}
if (mxchars[2] == "3")
{
mx = mxchars[1] + "月" + "下旬";
}
}
if (filename.Contains("Month"))
{
mx = mxchars[1] + "月";
}
if (filetime.Contains("Season"))
{
mx = mxchars[1] + "季度";
}
imgname = year + "年" + mx + regionsname + product + "分布图";
}
_argumentProvider.SetArg("SelectedPrimaryFiles", arguments);
_argumentProvider.SetArg("fileOpenArgs", arguments);
FileExtractResult result = ThemeGraphyResult(null) as FileExtractResult;
//增加矢量
string autopath = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, @"SystemData\ProductArgs\MWS\shppath.txt");
string shpFile = "";
if (File.Exists(autopath))
{
FileStream fauto = new FileStream(autopath, FileMode.Open, FileAccess.Read);
StreamReader rauto = new StreamReader(fauto, Encoding.GetEncoding("gb2312"));
shpFile = rauto.ReadLine();
rauto.Close();
fauto.Close();
}
else
{
shpFile = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, @"数据引用\基础矢量\行政区划\线\中国边界_线.shp");
}
CreateMcd(shpFile);
_shpFile = shpFile;
_gxdFile = (result as FileExtractResult).FileName;
AddShpToGxd();
FileInfo fi = new FileInfo(result.FileName);
string newresultfile = Path.Combine(gxdsave, Path.GetFileNameWithoutExtension(arguments) + ".gxd");
if (!File.Exists(newresultfile))
{
fi.MoveTo(newresultfile);
}
else
{
FileInfo fi1 = new FileInfo(newresultfile);
fi1.Delete();
}
IFileExtractResult res = new FileExtractResult(_subProductDef.Identify, newresultfile, false);
results.Add(res);
}
return(results);
}
private IExtractResult FRAREAlgorithm(Action <int, string> progressTracker)
{
AngleParModel model = _argumentProvider.GetArg("anglesettings") as AngleParModel;
double glintmax = double.Parse(_argumentProvider.GetArg("glint").ToString());
//band
int angleband = (int)_argumentProvider.GetArg("angle");
//zoom
float anglezoom = float.Parse(_argumentProvider.GetArg("angle_Zoom").ToString());
string rasterfile = _argumentProvider.DataProvider.fileName;
IRasterDataProvider outRaster = null;
List <RasterMaper> rms = new List <RasterMaper>();
try
{
IRasterDataProvider sunzinRaster = RasterDataDriver.Open(model.FileAsunZ) as IRasterDataProvider;
RasterMaper brmsunz = new RasterMaper(sunzinRaster, new int[] { angleband });
rms.Add(brmsunz);
IRasterDataProvider sunainRaster = RasterDataDriver.Open(model.FileAsunA) as IRasterDataProvider;
RasterMaper brmsuna = new RasterMaper(sunainRaster, new int[] { angleband });
rms.Add(brmsuna);
IRasterDataProvider satzinRaster = RasterDataDriver.Open(model.FileAsatZ) as IRasterDataProvider;
RasterMaper brmsatz = new RasterMaper(satzinRaster, new int[] { angleband });
rms.Add(brmsatz);
IRasterDataProvider satainRaster = RasterDataDriver.Open(model.FileAsatA) as IRasterDataProvider;
RasterMaper brmsata = new RasterMaper(satainRaster, new int[] { angleband });
rms.Add(brmsata);
RasterIdentify ri = GetRasterIdentifyID(rasterfile);
ri.SubProductIdentify = "FRAM";
string outFileName = ri.ToWksFullFileName(".dat");
IPixelIndexMapper result = null;
IPixelFeatureMapper <Int16> resultTag = null;
int totalDatalength = 0;
Dictionary <int, FireAngleFeature> listfeature = new Dictionary <int, FireAngleFeature>();
outRaster = CreateOutRaster(outFileName, rms.ToArray());
result = PixelIndexMapperFactory.CreatePixelIndexMapper("FIR", outRaster.Width, outRaster.Height, outRaster.CoordEnvelope, outRaster.SpatialRef);
//栅格数据映射
RasterMaper[] fileIns = rms.ToArray();
RasterMaper[] fileOuts = new RasterMaper[] { new RasterMaper(outRaster, new int[] { 1 }) };
//创建处理模型
RasterProcessModel <Int16, UInt16> rfr = null;
rfr = new RasterProcessModel <Int16, UInt16>(progressTracker);
rfr.SetRaster(fileIns, fileOuts);
rfr.RegisterCalcModel(new RasterCalcHandler <Int16, UInt16>((rvInVistor, rvOutVistor, aoi) =>
{
int dataLength = rvOutVistor[0].SizeY * rvOutVistor[0].SizeX;
for (int index = 0; index < dataLength; index++)
{
double asunz = rvInVistor[0].RasterBandsData[0][index] / anglezoom;
double asuna = rvInVistor[1].RasterBandsData[0][index] / anglezoom;
double asatz = rvInVistor[2].RasterBandsData[0][index] / anglezoom;
double asata = rvInVistor[3].RasterBandsData[0][index] / anglezoom;
double glintangle = Math.Acos(Math.Sin(asunz) * Math.Sin(asatz) * Math.Cos(asuna - asata) + Math.Cos(asunz) * Math.Cos(asatz));
if (glintangle != 0)
{
if (glintangle * 180 / Math.PI < glintmax)
{
result.Put(totalDatalength + index);
}
//增加像元信息显示
FireAngleFeature feature = new FireAngleFeature();
feature.SunZ = asunz;
feature.SunA = asuna;
feature.SatZ = asatz;
feature.SatA = asata;
feature.Glint = Math.Round(glintangle * 180 / Math.PI, 2);
listfeature.Add(totalDatalength + index, feature);
}
rvOutVistor[0].RasterBandsData[0][index] = Convert.ToUInt16(glintangle * 180 * anglezoom / Math.PI);
}
totalDatalength += dataLength;
}));
//执行
rfr.Excute();
result.Tag = new FireAngleCollection("耀斑角信息", listfeature);
IExtractResultArray array = new ExtractResultArray("FIR");
array.Add(result);
FileExtractResult angleresult = new FileExtractResult(ri.SubProductIdentify, outFileName);
angleresult.SetDispaly(false);
array.Add(angleresult);
return(array);
}
finally
{
foreach (RasterMaper rm in rms)
{
rm.Raster.Dispose();
}
if (outRaster != null)
{
outRaster.Dispose();
}
}
}