private Dictionary <string, SortedDictionary <string, double> > Stat <T>(IRasterDataProvider raster, string templateName, Dictionary <string, Func <T, bool> > multiFilter, bool weight, float weightZoom, string vectorTemplate) where T : struct, IConvertible
{
if (raster == null)
{
return(null);
}
if (raster == null)
{
return(null);
}
_perAreas = AreaCountHelper.CalcArea(raster.CoordEnvelope.Center.X, raster.CoordEnvelope.Center.Y, raster.ResolutionX, raster.ResolutionY) * Math.Pow(10, -6);
if (string.IsNullOrWhiteSpace(templateName))
{
return(StatRaster(raster, multiFilter, weight, weightZoom));
}
string tempFile = FindRasterFullname(templateName);
if (templateName == "China_LandRaster")
{
return(StatByRasterTemplate <T>(raster, tempFile, multiFilter, weight, weightZoom));
}
else
{
Dictionary <string, SortedDictionary <string, double> > statResult = StatByRasterTemplate <T>(raster, tempFile, multiFilter, weight, weightZoom, vectorTemplate);
//SortedDictionary<string, double> newDic = ToSSXLevel(statResult); //县级统计，向上推至省市级。
return(statResult);
}
}
public StatResultItem[] CountByVector(IRasterDataProvider raster, Dictionary <string, int[]> aoi, Func <T, bool> filter)
{
if (filter == null)
{
return(null);
}
if (aoi == null || aoi.Count == 0)
{
return(null);
}
double lon = raster.CoordEnvelope.Center.X;
double lat = raster.CoordEnvelope.Center.Y;
int count = 0;
List <StatResultItem> items = new List <StatResultItem>();
IRasterOperator <T> oper = new RasterOperator <T>();
foreach (string fea in aoi.Keys)
{
if (aoi[fea] == null)
{
count = 0;
}
else
{
count = oper.Count(raster, aoi[fea], filter);
}
StatResultItem it = new StatResultItem();
it.Name = fea;
double d = AreaCountHelper.CalcArea(lon, lat, raster.ResolutionX, raster.ResolutionY) * count * Math.Pow(10, -6);
it.Value = Math.Round(d, 3);
items.Add(it);
}
return(items != null?items.ToArray() : null);
}
public StatResultItem[] CountByVector(IRasterDataProvider raster, string shpFullname, string shpPrimaryField, Func <T, int, int> weight)
{
if (weight == null)
{
return(null);
}
if (String.IsNullOrEmpty(shpFullname))
{
return(null);
}
//step2:读取矢量
CodeCell.AgileMap.Core.Feature[] features = GetFeatures(shpFullname);
if (features == null || features.Length == 0)
{
return(null);
}
double lon = raster.CoordEnvelope.Center.X;
double lat = raster.CoordEnvelope.Center.Y;
//step3:矢量栅格化
Dictionary <string, Color> nameColors = new Dictionary <string, Color>();
using (Bitmap bitmap = VectorsToBitmap(raster, features, shpPrimaryField, out nameColors))
{
int[] aoi;
Color color;
int count;
string name;
List <StatResultItem> items = new List <StatResultItem>();
IRasterOperator <T> oper = new RasterOperator <T>();
foreach (Feature fea in features)
{
name = fea.GetFieldValue(shpPrimaryField);
if (String.IsNullOrEmpty(name))
{
continue;
}
color = nameColors[name];
aoi = GetAOIByFeature(bitmap, color);
if (aoi == null)
{
count = 0;
}
else
{
count = oper.Count(raster, aoi, weight);
}
StatResultItem it = new StatResultItem();
it.Name = name;
it.Code = fea.OID.ToString();
double d = AreaCountHelper.CalcArea(lon, lat, raster.ResolutionX, raster.ResolutionY) * count * Math.Pow(10, -6);
it.Value = Math.Round(d, 3);
items.Add(it);
}
return(items != null?items.ToArray() : null);
}
}
private static StatResultItem[] AreaStatCurrentRegion <T>(IRasterDataProvider prd, string title, Func <T, bool> filter)
{
RasterOperator <T> oper = new RasterOperator <T>();
int count = oper.Count(prd, null, filter);
StatResultItem sri = new StatResultItem();
sri.Name = "当前区域";
//精细面积计算
//sri.Value = oper.Area(prd, null, filter);
double lon = prd.CoordEnvelope.Center.X;
double lat = prd.CoordEnvelope.Center.Y;
sri.Value = Math.Round(count * AreaCountHelper.CalcArea(lon, lat, prd.ResolutionX, prd.ResolutionX) / Math.Pow(10, 6), 3);
return(new StatResultItem[] { sri });
}
/// <summary>
/// 基于栅格分类的统计
/// 输出按分类的覆盖面积
/// </summary>
/// <typeparam name="T">待统计数据类型</typeparam>
/// <param name="raster">待统计数据</param>
/// <param name="templateName">栅格分类模版（统计分类）,如县界\土地类型</param>
/// <param name="func">统计条件</param>
public SortedDictionary <string, double> Stat <T>(IRasterDataProvider raster, string templateName, Func <T, bool> func)
{
if (raster == null)
{
return(null);
}
_perAreas = AreaCountHelper.CalcArea(raster.CoordEnvelope.Center.X, raster.CoordEnvelope.Center.Y, raster.ResolutionX, raster.ResolutionY) * Math.Pow(10, -6);
string tempFile = FindRasterFullname(templateName);
if (templateName == "China_LandRaster")
{
return(StatRasterTemplate <T>(raster, tempFile, func));
}
else
{
SortedDictionary <string, double> statResult = StatRasterTemplate <T>(raster, tempFile, func);
SortedDictionary <string, double> newDic = ToSSXLevel(statResult);//县级统计，向上推至省市级。
return(newDic);
}
}
private StatResultItem[] CountByLandRaster(IRasterDataProvider raster, Func <T, int, int> weight)
{
IRasterDictionaryTemplate <byte> temp = RasterDictionaryTemplateFactory.CreateLandRasterTemplate();
Dictionary <byte, string> paris = temp.CodeNameParis;
if (paris == null)
{
return(null);
}
double lon = raster.CoordEnvelope.Center.X;
double lat = raster.CoordEnvelope.Center.Y;
IRasterOperator <T> oper = new RasterOperator <T>();
List <StatResultItem> items = new List <StatResultItem>();
int[] aoi;
int count;
foreach (string value in paris.Values)
{
aoi = temp.GetAOI(value, raster.CoordEnvelope.MinX, raster.CoordEnvelope.MaxX, raster.CoordEnvelope.MinY, raster.CoordEnvelope.MaxY, new Size(raster.Width, raster.Height));
if (aoi == null)
{
continue;
}
count = oper.Count(raster, aoi, weight);
if (count == 0)
{
continue;
}
StatResultItem it = new StatResultItem();
it.Name = value;
it.Value = count;
double d = AreaCountHelper.CalcArea(lon, lat, raster.ResolutionX, raster.ResolutionY) * count * Math.Pow(10, -6);
it.Value = Math.Round(d, 3);
items.Add(it);
}
return(items != null?items.ToArray() : null);
}
private SortedDictionary <string, StatAreaItem> StatTemplate <T>(IRasterDataProvider[] rasters, IRasterDataProvider tempRaster, Func <T, bool> func)
{
try
{
//01、计算所有输入栅格的的范围并集
CoordEnvelope maxEnv = UnionEnv(rasters);
//计算待统计栅格与分类栅格的相交区域,以创建相同的虚拟栅格
CoordEnvelope virtureEnv = maxEnv.Intersect(tempRaster.CoordEnvelope);
VirtualRasterHeader vHeader = VirtualRasterHeader.Create(virtureEnv, rasters[0].ResolutionX, rasters[0].ResolutionX);
List <VirtualRaster> vRasters = new List <VirtualRaster>();
for (int i = 0; i < rasters.Length; i++)
{
VirtualRaster vRaster = new VirtualRaster(rasters[i], vHeader);
vRasters.Add(vRaster);
}
VirtualRaster template = new VirtualRaster(tempRaster, vHeader);
int[] tdata = template.ReadData <int>(1, 0, 0, vHeader.Width, vHeader.Height);
//2、依据逻辑，计算初步统计结果,这一步对于大数据，可考虑分块处理
int calcLength = vHeader.Width * vHeader.Height * vRasters.Count;
int dataLength = vHeader.Width * vHeader.Height;
byte[] valueCalced = new byte[dataLength];
SortedDictionary <string, StatAreaItem> result = new SortedDictionary <string, StatAreaItem>();
for (int i = 0; i < vRasters.Count; i++)
{
T[] datas = vRasters[i].ReadData <T>(1, 0, 0, vHeader.Width, vHeader.Height);
for (int j = 0; j < dataLength; j++)
{
UpdateProgress((int)((j + (i * dataLength)) * 100f / calcLength), "正在计算统计数据");
if (func(datas[j]))
{
string key = tdata[j].ToString();
if (result.ContainsKey(key))//累计计数
{
result[key].GrandTotal += 1;
}
else
{
result.Add(key, new StatAreaItem()
{
GrandTotal = 1
});
}
if (valueCalced[j] == 0)//覆盖计数
{
valueCalced[j] = 1;
result[key].Cover += 1;
}
}
}
}
double perAreas = AreaCountHelper.CalcArea(vHeader.CoordEnvelope.Center.X, vHeader.CoordEnvelope.Center.Y, vHeader.ResolutionX, vHeader.ResolutionY) * Math.Pow(10, -6);
foreach (string key in result.Keys)
{
result[key].GrandTotal *= perAreas;
result[key].Cover *= perAreas;
}
return(result);
}
finally
{
UpdateProgress(100, "统计数据计算完毕");
}
}
/// <summary>
/// 覆盖面积：指的是覆盖到的面积，
/// 累计面积：即累计覆盖面积，相同区域不同时次的累计计算
/// </summary>
/// <typeparam name="T"></typeparam>
/// <param name="rasters"></param>
/// <param name="rasterTemplate"></param>
/// <param name="func"></param>
/// <returns></returns>
private SortedDictionary <string, StatAreaItem> StatTemplate <T>(IRasterDataProvider[] rasters, IRasterDataProvider typeRaster, Func <T, bool> func, bool isCombinSameDay)
{
try
{
//01、计算所有输入栅格的的范围并集
CoordEnvelope maxEnv = UnionEnv(rasters);
//计算待统计栅格与分类栅格的相交区域,以创建相同的虚拟栅格。
CoordEnvelope virtureEnv = maxEnv.Intersect(typeRaster.CoordEnvelope);
VirtualRasterHeader vHeader = VirtualRasterHeader.Create(virtureEnv, rasters[0].ResolutionX, rasters[0].ResolutionX);
VirtualRaster typelate = new VirtualRaster(typeRaster, vHeader);
int[] tdata = typelate.ReadData <int>(1, 0, 0, vHeader.Width, vHeader.Height);
//2、依据逻辑，计算初步统计结果,这一步对于大数据，可考虑分块处理
int calcLength = vHeader.Width * vHeader.Height * rasters.Length;
int dataLength = vHeader.Width * vHeader.Height;
byte[] valueCalced = new byte[dataLength];
SortedDictionary <string, StatAreaItem> result = new SortedDictionary <string, StatAreaItem>();
if (isCombinSameDay)
{
//预处理同天数据
Dictionary <DateTime, List <IRasterDataProvider> > dic = new Dictionary <DateTime, List <IRasterDataProvider> >();
foreach (IRasterDataProvider raster in rasters)
{
if (raster.DataIdentify.OrbitDateTime == DateTime.MinValue)
{
RasterIdentify identify = new RasterIdentify(raster.fileName);
raster.DataIdentify.OrbitDateTime = identify.OrbitDateTime;
}
List <IRasterDataProvider> lst;
if (dic.TryGetValue(raster.DataIdentify.OrbitDateTime, out lst))
{
dic[raster.DataIdentify.OrbitDateTime].Add(raster);
}
else
{
lst = new List <IRasterDataProvider>();
lst.Add(raster);
dic.Add(raster.DataIdentify.OrbitDateTime, lst);
}
}
foreach (DateTime dateKey in dic.Keys)
{
IRasterDataProvider[] rastersSameDay = dic[dateKey].ToArray();
if (rastersSameDay.Length == 1 || dateKey == DateTime.MinValue)
{
for (int i = 0; i < rastersSameDay.Length; i++)
{
VirtualRaster vRaster = new VirtualRaster(rastersSameDay[i], vHeader);
T[] datas = vRaster.ReadData <T>(1, 0, 0, vHeader.Width, vHeader.Height);
for (int j = 0; j < dataLength; j++)
{
UpdateProgress((int)((j + (i * dataLength)) * 100f / calcLength), "正在计算统计数据");
if (func(datas[j]))
{
string key = tdata[j].ToString();
if (result.ContainsKey(key))//累计计数
{
result[key].GrandTotal += 1;
}
else
{
result.Add(key, new StatAreaItem()
{
GrandTotal = 1
});
}
if (valueCalced[j] == 0)//覆盖计数
{
valueCalced[j] = 1;
result[key].Cover += 1;
}
}
}
}
}
else//同天数据处理,
{
byte[] sameDayCalced = new byte[vHeader.Width * vHeader.Height];
for (int i = 0; i < rasters.Length; i++)
{
VirtualRaster vRaster = new VirtualRaster(rasters[i], vHeader);
T[] datas = vRaster.ReadData <T>(1, 0, 0, vHeader.Width, vHeader.Height);
for (int j = 0; j < dataLength; j++)
{
UpdateProgress((int)((j + (i * dataLength)) * 100f / calcLength), "正在计算统计数据");
if (func(datas[j]))
{
if (sameDayCalced[j] == 0)//
{
sameDayCalced[j] = 1;
string key = tdata[j].ToString();
if (result.ContainsKey(key))//累计计数
{
result[key].GrandTotal += 1;
}
else
{
result.Add(key, new StatAreaItem()
{
GrandTotal = 1
});
}
if (valueCalced[j] == 0)//覆盖计数
{
valueCalced[j] = 1;
result[key].Cover += 1;
}
}
}
}
}
}
}
}
else
{
for (int i = 0; i < rasters.Length; i++)
{
VirtualRaster vRaster = new VirtualRaster(rasters[i], vHeader);
T[] datas = vRaster.ReadData <T>(1, 0, 0, vHeader.Width, vHeader.Height);
for (int j = 0; j < dataLength; j++)
{
UpdateProgress((int)((j + (i * dataLength)) * 100f / calcLength), "正在计算统计数据");
if (func(datas[j]))
{
string key = tdata[j].ToString();
if (result.ContainsKey(key))//累计计数
{
result[key].GrandTotal += 1;
}
else
{
result.Add(key, new StatAreaItem()
{
GrandTotal = 1
});
}
if (valueCalced[j] == 0)//覆盖计数
{
valueCalced[j] = 1;
result[key].Cover += 1;
}
}
}
}
}
double perAreas = AreaCountHelper.CalcArea(vHeader.CoordEnvelope.Center.X, vHeader.CoordEnvelope.Center.Y, vHeader.ResolutionX, vHeader.ResolutionY) * Math.Pow(10, -6);
foreach (string key in result.Keys)
{
result[key].GrandTotal *= perAreas;
result[key].Cover *= perAreas;
}
return(result);
}
finally
{
UpdateProgress(100, "统计数据计算完毕");
}
}
public RasterStatByRaster(Action <int, string> progressTracker)
{
_progressTracker = progressTracker;
_perAreas = AreaCountHelper.CalcArea(110, 35, 0.01, 0.01) * Math.Pow(10, -6);
}