/// <summary>
/// 设置分级算法
/// </summary>
/// <param name="classProperties">栅格分级渲染属性</param>
/// <param name="classMethod">分级算法</param>
private static void SetClassMethod(IRasterClassifyUIProperties classProperties, string classMethod)
{
//分级方法初始化
IClassifyGEN pClassifyGen;
//判断分级方法，以获取分段点
switch (classMethod)
{
case "Equal Interval":
pClassifyGen = new EqualIntervalClass();
break;
case "Natural Breaks":
pClassifyGen = new NaturalBreaksClass();
break;
case "Quantile":
pClassifyGen = new QuantileClass();
break;
case "Geometrical Interval":
pClassifyGen = new GeometricalIntervalClass();
break;
default:
pClassifyGen = new NaturalBreaksClass();
break;
}
//获取分级算法UID
classProperties.ClassificationMethod = pClassifyGen.ClassID;
}
internal static void UsingRasterClassifyRendered1(IRasterLayer irasterLayer_0, int int_0, string string_0)
{
bool flag;
IRaster raster = irasterLayer_0.Raster;
IRasterClassifyColorRampRenderer o = new RasterClassifyColorRampRenderer();
IRasterRenderer renderer2 = o as IRasterRenderer;
renderer2.Raster = raster;
o.ClassField = string_0;
o.ClassCount = int_0;
IClassify classify = new EqualInterval() as IClassify;
UID classID = classify.ClassID;
IRasterClassifyUIProperties properties = o as IRasterClassifyUIProperties;
properties.ClassificationMethod = classID;
renderer2.Update();
IColorRamp ramp = ColorManage.CreateColorRamp();
ramp.Size = int_0;
ramp.CreateRamp(out flag);
IFillSymbol symbol = new SimpleFillSymbol();
for (int i = 0; i < o.ClassCount; i++)
{
symbol.Color = ramp.get_Color(i);
o.set_Symbol(i, symbol as ISymbol);
}
renderer2.Update();
irasterLayer_0.Renderer = o as IRasterRenderer;
Marshal.ReleaseComObject(o);
o = null;
}
public static void classifyRender(IRasterLayer rastlayer, string classMethod, int count, IColorRamp ramp)
{
try
{
IRasterBand band = GetBand(rastlayer);
if (band.Histogram == null)
{
band.ComputeStatsAndHist();
}
IRasterClassifyColorRampRenderer rasClassifyRender = new RasterClassifyColorRampRendererClass();
IRasterRenderer rasRender = rasClassifyRender as IRasterRenderer;
rasRender.Raster = rastlayer.Raster;
rasRender.Update();
int numClasses = count;
IClassify classify = null;
switch (classMethod)
{
case "等间距分级":
classify = new EqualIntervalClass();
break;
case "自然断点分级":
classify = new NaturalBreaksClass();
break;
}
classify.Classify(ref numClasses);
double[] Classes = classify.ClassBreaks as double[];
UID pUid = classify.ClassID;
IRasterClassifyUIProperties rasClassifyUI = rasClassifyRender as IRasterClassifyUIProperties;
rasClassifyUI.ClassificationMethod = pUid;
rasClassifyRender.ClassField = "Value";
rasClassifyRender.ClassCount = count;
rasRender.Update();
IColor pColor;
ISimpleFillSymbol pSym;
for (int j = 0; j < count; j++)
{
pColor = ramp.get_Color(j * (ramp.Size - 1) / (count - 1));
pSym = new SimpleFillSymbolClass();
pSym.Color = pColor;
rasClassifyRender.set_Symbol(j, (ISymbol)pSym);
rasClassifyRender.set_Break(j, rasClassifyRender.get_Break(j));
}
rasRender.Update();
rastlayer.Renderer = rasClassifyRender as IRasterRenderer;
}
catch
{
XtraMessageBox.Show("唯一值数量已达到限制（65536）");
}
}
/// <summary>
/// 获取分级渲染设置
/// </summary>
/// <param name="classField">字段</param>
/// <param name="classCount">类别总数</param>
/// <param name="classMethod">分级算法</param>
/// <returns></returns>
public IRasterClassifyColorRampRenderer GetRasterClassifyRenderer(string classField, int classCount,
string classMethod)
{
//先计算统计值，不然无法获取分类数据
CalculateRasterStatistics(rasterLayer);
IRasterClassifyColorRampRenderer pRClassRend = new RasterClassifyColorRampRendererClass();
//分级属性接口
IRasterClassifyUIProperties classProperties = pRClassRend as IRasterClassifyUIProperties;
//设置分级算法
SetClassMethod(classProperties, classMethod);
//字段
pRClassRend.ClassField = classField;
//类别总数
pRClassRend.ClassCount = classCount;
IRasterRenderer rasterRend = (IRasterRenderer)pRClassRend;
rasterRend.Raster = rasterLayer.Raster;
rasterRend.Update();
return(pRClassRend);
}
//public void RasterClassify(IRasterLayer rastlayer, string classMethod, int count, IColorRamp ramp,double minValue)
//{
// IRasterBand band = GetBand(rastlayer);
// if (band.Histogram == null)
// {
// band.ComputeStatsAndHist();
// }
// IRasterClassifyColorRampRenderer rasClassifyRender = new RasterClassifyColorRampRendererClass();
// IRasterRenderer rasRender = rasClassifyRender as IRasterRenderer;
// rasRender.Raster = rastlayer.Raster;
// rasRender.Update();
// int numClasses = count;
// IRasterHistogram pRasterHistogram = band.Histogram;
// double[] dblValues = pRasterHistogram.Counts as double[];
// int intValueCount = dblValues.GetUpperBound(0) + 1;
// double[] vValues = new double[intValueCount];
// IRasterStatistics pRasterStatistic = band.Statistics;
// //double dMaxValue = pRasterStatistic.Maximum;
// double dMaxValue = minValue;
// double dMinValue = pRasterStatistic.Minimum;
// double BinInterval = Convert.ToDouble((dMaxValue - dMinValue) / intValueCount);
// for (int i = 0; i < intValueCount; i++)
// {
// vValues[i] = i * BinInterval + pRasterStatistic.Minimum;
// }
// long[] longvalues = new long[dblValues.Length];
// for (int i = 0; i <= dblValues.Length - 1; i++)
// {
// longvalues[i] = long.Parse(Convert.ToString(dblValues[i]));
// }
// //IClassifyGEN classify = null;
// IClassify classify = null;
// switch (classMethod)
// {
// case "等间距分级":
// EqualInterval eqclassify = new EqualIntervalClass();
// eqclassify.Classify(vValues, longvalues, ref numClasses);
// classify = eqclassify as IClassify;
// break;
// case "自然断点分级":
// NaturalBreaks naclassify = new NaturalBreaksClass();
// naclassify.Classify(vValues, longvalues, ref numClasses);
// classify = naclassify as IClassify;
// break;
// }
// //switch (classMethod)
// //{
// // case "等间距分级":
// // classify = new EqualIntervalClass();
// // break;
// // case "自然断点分级":
// // classify = new NaturalBreaksClass();
// // break;
// //}
// //classify.Classify(vValues, longvalues, ref numClasses);
// double[] Classes = classify.ClassBreaks as double[];
// UID pUid = classify.ClassID;
// IRasterClassifyUIProperties rasClassifyUI = rasClassifyRender as IRasterClassifyUIProperties;
// rasClassifyUI.ClassificationMethod = pUid;
// rasClassifyRender.ClassCount = count;
// IColor pColor;
// ISimpleFillSymbol pSym;
// for (int j = 0; j < count; j++)
// {
// pColor = ramp.get_Color(j * (ramp.Size / count));
// pSym = new SimpleFillSymbolClass();
// pSym.Color = pColor;
// rasClassifyRender.set_Symbol(j, (ISymbol)pSym);
// rasRender.Update();
// if (Classes[j] == 0)
// {
// rasClassifyRender.set_Label(j, Classes[j].ToString() + "-" + Classes[j + 1].ToString("0.000"));
// rasRender.Update();
// }
// else
// {
// rasClassifyRender.set_Label(j, Classes[j].ToString("0.000") + "-" + Classes[j + 1].ToString("0.000"));
// rasRender.Update();
// }
// }
// rastlayer.Renderer = rasClassifyRender as IRasterRenderer;
public void RasterClassify(IRasterLayer rastlayer, string classMethod, int count, IColorRamp ramp)
{
try
{ //进行唯一值判断
IUniqueValues values = new UniqueValuesClass();
IRasterCalcUniqueValues unique = new RasterCalcUniqueValuesClass();
unique.AddFromRaster(rastlayer.Raster, 0, values);
int uniquecount = values.get_UniqueCount(0);
//计算统计图
IRasterBand band = GetBand(rastlayer);
if (band.Histogram == null)
{
band.ComputeStatsAndHist();
}
IRasterClassifyColorRampRenderer rasClassifyRender = new RasterClassifyColorRampRendererClass();
IRasterRenderer rasRender = rasClassifyRender as IRasterRenderer;
rasRender.Raster = rastlayer.Raster;
rasRender.Update();
int numClasses = count;
IRasterHistogram pRasterHistogram = band.Histogram;
double[] dblValues = pRasterHistogram.Counts as double[];
int intValueCount = dblValues.GetUpperBound(0) + 1;
double[] vValues = new double[intValueCount];
IRasterStatistics pRasterStatistic = band.Statistics;
double dMaxValue = pRasterStatistic.Maximum;
double dMinValue = pRasterStatistic.Minimum;
if (dMinValue == 0)
{
pRasterStatistic.IgnoredValues = pRasterStatistic.Minimum;
pRasterStatistic.Recalculate();
dMinValue = pRasterStatistic.Minimum;
}
double BinInterval = Convert.ToDouble((dMaxValue - dMinValue) / intValueCount);
for (int i = 0; i < intValueCount; i++)
{
vValues[i] = i * BinInterval + pRasterStatistic.Minimum;
}
long[] longvalues = new long[dblValues.Length];
for (int i = 0; i <= dblValues.Length - 1; i++)
{
longvalues[i] = long.Parse(Convert.ToString(dblValues[i]));
}
//IClassifyGEN classify = null;
IClassify classify = null;
switch (classMethod)
{
case "等间距分级":
EqualInterval eqclassify = new EqualIntervalClass();
eqclassify.Classify(vValues, longvalues, ref numClasses);
classify = eqclassify as IClassify;
break;
case "自然断点分级":
NaturalBreaks naclassify = new NaturalBreaksClass();
naclassify.Classify(vValues, longvalues, ref numClasses);
classify = naclassify as IClassify;
break;
}
#region
//switch (classMethod)
//{
// case "等间距分级":
// classify = new EqualIntervalClass();
// break;
// case "自然断点分级":
// classify = new NaturalBreaksClass();
// break;
//}
//classify.Classify(vValues, longvalues, ref numClasses);
#endregion
double[] Classes = classify.ClassBreaks as double[];
int n = Classes.Count();
double dn = Classes[0];
UID pUid = classify.ClassID;
IRasterClassifyUIProperties rasClassifyUI = rasClassifyRender as IRasterClassifyUIProperties;
rasClassifyUI.ClassificationMethod = pUid;
rasClassifyRender.ClassCount = count;
IColor pColor;
ISimpleFillSymbol pSym;
//排除数值
double[] exdouble = new double[2] {
0, Classes[0]
};
IRasterDataExclusion ex = rasClassifyRender as IRasterDataExclusion;
ex.ExcludeValues = exdouble;
ex.ExcludeColor = GET(255, 255, 255);
for (int j = 0; j < count; j++)
{
pColor = ramp.get_Color(j * (ramp.Size / count));
pSym = new SimpleFillSymbolClass();
pSym.Color = pColor;
rasClassifyRender.set_Symbol(j, (ISymbol)pSym);
rasRender.Update();
rasClassifyRender.set_Break(j, rasClassifyRender.get_Break(j));
rasClassifyRender.set_Label(j, Classes[j].ToString("0.000") + "-" + Classes[j + 1].ToString("0.000"));
rasRender.Update();
}
//IRasterProps rasterProps = (IRasterProps)rastlayer.Raster;
//rasterProps.NoDataValue = 0;
//IRasterDisplayProps props = rasClassifyRender as IRasterDisplayProps;
//props.NoDataColor = GET(255, 255, 255);
//rasRender.Update();
rastlayer.Renderer = rasClassifyRender as IRasterRenderer;
}
catch (Exception ex)
{
//MessageBox.Show(ex.ToString());
if (ex.ToString().Contains("唯一值过多"))
{
MessageBox.Show("唯一值数量已达到限制（65536）");
}
else
{
MessageBox.Show("还未计算唯一值，进行唯一值计算！");
}
}
//catch
//{
// MessageBox.Show("数据需要先计算统计值，请点击确定进行计算！");
//}
}
public void RasterClassify(IRasterLayer rastlayer, string classMethod, int count, IColorRamp ramp)
{
IRasterBand band = GetBand(rastlayer);
if (band.Histogram == null)
{
band.ComputeStatsAndHist();
}
IRasterClassifyColorRampRenderer rasClassifyRender = new RasterClassifyColorRampRendererClass();
IRasterRenderer rasRender = rasClassifyRender as IRasterRenderer;
rasRender.Raster = rastlayer.Raster;
rasRender.Update();
int numClasses = count;
IRasterHistogram pRasterHistogram = band.Histogram;
double[] dblValues = pRasterHistogram.Counts as double[];
int intValueCount = dblValues.GetUpperBound(0) + 1;
double[] vValues = new double[intValueCount];
IRasterStatistics pRasterStatistic = band.Statistics;
double dMaxValue = pRasterStatistic.Maximum;
double dMinValue = pRasterStatistic.Minimum;
if (dMinValue == 0)
{
pRasterStatistic.IgnoredValues = pRasterStatistic.Minimum;
pRasterStatistic.Recalculate();
dMinValue = pRasterStatistic.Minimum;
}
double BinInterval = Convert.ToDouble((dMaxValue - dMinValue) / intValueCount);
for (int i = 0; i < intValueCount; i++)
{
vValues[i] = i * BinInterval + pRasterStatistic.Minimum;
}
long[] longvalues = new long[dblValues.Length];
for (int i = 0; i <= dblValues.Length - 1; i++)
{
longvalues[i] = long.Parse(Convert.ToString(dblValues[i]));
}
//IClassifyGEN classify = null;
IClassify classify = null;
switch (classMethod)
{
case "等间距分级":
EqualInterval eqclassify = new EqualIntervalClass();
eqclassify.Classify(vValues, longvalues, ref numClasses);
classify = eqclassify as IClassify;
break;
case "自然断点分级":
NaturalBreaks naclassify = new NaturalBreaksClass();
naclassify.Classify(vValues, longvalues, ref numClasses);
classify = naclassify as IClassify;
break;
}
//switch (classMethod)
//{
// case "等间距分级":
// classify = new EqualIntervalClass();
// break;
// case "自然断点分级":
// classify = new NaturalBreaksClass();
// break;
//}
//classify.Classify(vValues, longvalues, ref numClasses);
double[] Classes = classify.ClassBreaks as double[];
UID pUid = classify.ClassID;
IRasterClassifyUIProperties rasClassifyUI = rasClassifyRender as IRasterClassifyUIProperties;
rasClassifyUI.ClassificationMethod = pUid;
rasClassifyRender.ClassCount = count;
IColor pColor;
ISimpleFillSymbol pSym;
for (int j = 0; j < count; j++)
{
IRasterProps rasterProps = (IRasterProps)rastlayer.Raster;
rasterProps.NoDataValue = 0;
pColor = ramp.get_Color(j * (ramp.Size / count));
pSym = new SimpleFillSymbolClass();
pSym.Color = pColor;
rasClassifyRender.set_Symbol(j, (ISymbol)pSym);
rasRender.Update();
rasClassifyRender.set_Break(j, rasClassifyRender.get_Break(j));
rasClassifyRender.set_Label(j, Classes[j].ToString("0.000") + "-" + Classes[j + 1].ToString("0.000"));
rasRender.Update();
}
rastlayer.Renderer = rasClassifyRender as IRasterRenderer;
}
public static void UsingRasterClassifyRendered(IRasterLayer irasterLayer_0, int int_0, string string_0)
{
try
{
bool flag;
IRaster raster = irasterLayer_0.Raster;
IRasterBand band = (raster as IRasterBandCollection).Item(0);
band.HasTable(out flag);
if (flag)
{
int num2;
bool flag2;
IRasterClassifyColorRampRenderer renderer = new RasterClassifyColorRampRenderer();
IRasterRenderer renderer2 = renderer as IRasterRenderer;
renderer2.Raster = raster;
ITable attributeTable = band.AttributeTable;
ITableHistogram tableHistogram = new BasicTableHistogram() as ITableHistogram;
tableHistogram.Field = string_0;
tableHistogram.Table = attributeTable;
ITableHistogram histogram = tableHistogram as ITableHistogram;
double maximum = (histogram as IStatisticsResults).Maximum;
IClassify classify = new EqualInterval() as IClassify;
(classify as IClassifyMinMax).Minimum = (histogram as IStatisticsResults).Minimum;
(classify as IClassifyMinMax).Maximum = (histogram as IStatisticsResults).Maximum;
int_0--;
classify.Classify(ref int_0);
object classBreaks = classify.ClassBreaks;
UID classID = classify.ClassID;
IRasterClassifyUIProperties properties = renderer as IRasterClassifyUIProperties;
properties.ClassificationMethod = classID;
renderer.ClassCount = int_0;
renderer.ClassField = string_0;
for (num2 = 0; num2 < int_0; num2++)
{
renderer.set_Break(num2, ((double[])classBreaks)[num2]);
}
IColorRamp ramp = ColorManage.CreateColorRamp();
ramp.Size = int_0;
ramp.CreateRamp(out flag2);
IFillSymbol symbol = new SimpleFillSymbol();
for (num2 = 0; num2 < renderer.ClassCount; num2++)
{
double num4;
symbol.Color = ramp.get_Color(num2);
renderer.set_Symbol(num2, symbol as ISymbol);
double num3 = ((double[])classBreaks)[num2];
if (num2 == (renderer.ClassCount - 1))
{
num4 = maximum;
}
else
{
num4 = ((double[])classBreaks)[num2 + 1];
}
renderer.set_Label(num2, num3.ToString() + "-" + num4.ToString());
}
renderer2.Update();
irasterLayer_0.Renderer = renderer as IRasterRenderer;
}
else
{
UsingRasterClassifyRendered1(irasterLayer_0, int_0, string_0);
}
}
catch (Exception exception)
{
CErrorLog.writeErrorLog(null, exception, "栅格渲染");
}
}
public void RasterClassify(IRasterLayer rastlayer, string classMethod, int count, IColorRamp ramp)
{
try
{
//计算统计图
IRasterBand band = GetBand(rastlayer);
if (band.Histogram == null)
{
band.ComputeStatsAndHist();
}
IRasterClassifyColorRampRenderer rasClassifyRender = new RasterClassifyColorRampRendererClass();
IRasterRenderer rasRender = rasClassifyRender as IRasterRenderer;
rasRender.Raster = rastlayer.Raster;
rasRender.Update();
int numClasses = count;
IRasterHistogram pRasterHistogram = band.Histogram;
double[] dblValues = pRasterHistogram.Counts as double[];
int intValueCount = dblValues.GetUpperBound(0) + 1;
double[] vValues = new double[intValueCount];
IRasterStatistics pRasterStatistic = band.Statistics;
double dMaxValue = pRasterStatistic.Maximum;
double dMinValue = pRasterStatistic.Minimum;
double BinInterval = Convert.ToDouble((dMaxValue - dMinValue) / intValueCount);
for (int i = 0; i < intValueCount; i++)
{
vValues[i] = i * BinInterval + pRasterStatistic.Minimum;
}
long[] longvalues = new long[dblValues.Length];
for (int i = 0; i <= dblValues.Length - 1; i++)
{
longvalues[i] = long.Parse(Convert.ToString(dblValues[i]));
}
//IClassifyGEN classify = null;
IClassify classify = null;
switch (classMethod)
{
case "等间距分级":
classify = new EqualIntervalClass();
break;
case "自然断点分级":
classify = new NaturalBreaksClass();
break;
}
classify.Classify(ref numClasses);
double[] Classes = classify.ClassBreaks as double[];
UID pUid = classify.ClassID;
IRasterClassifyUIProperties rasClassifyUI = rasClassifyRender as IRasterClassifyUIProperties;
rasClassifyUI.ClassificationMethod = pUid;
rasClassifyRender.ClassCount = count;
IColor pColor;
ISimpleFillSymbol pSym;
for (int j = 0; j < count; j++)
{
pColor = ramp.get_Color(j * (ramp.Size - 1) / (count - 1));
pSym = new SimpleFillSymbolClass();
pSym.Color = pColor;
rasClassifyRender.set_Symbol(j, (ISymbol)pSym);
rasRender.Update();
rasClassifyRender.set_Break(j, rasClassifyRender.get_Break(j));
//rasClassifyRender.set_Label(j, Classes[j].ToString("0.000") + "-" + Classes[j + 1].ToString("0.000"));
rasRender.Update();
}
//IRasterProps rasterProps = (IRasterProps)rastlayer.Raster;
//rasterProps.NoDataValue = 0;
//IRasterDisplayProps props = rasClassifyRender as IRasterDisplayProps;
//props.NoDataColor = GET(255, 255, 255);
//rasRender.Update();
rastlayer.Renderer = rasClassifyRender as IRasterRenderer;
}
catch
{
MessageBox.Show("唯一值数量已达到限制（65536）");
}
}
