/// <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;
        }
Exemple #2
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        private void classify()
        {
            if (layer2Symbolize == null)
            {
                return;
            }
            IFeatureClass featureClass = layer2Symbolize.FeatureClass;
            ITable        pTable       = (ITable)featureClass;

            ITableHistogram pTableHistogram = new BasicTableHistogramClass();
            IBasicHistogram pHistogram      = (IBasicHistogram)pTableHistogram;

            pTableHistogram.Field = strRendererField;
            if (strNormalizeField.ToLower() != "none")
            {
                pTableHistogram.NormField = strNormalizeField;
            }
            pTableHistogram.Table = pTable;
            object dataFrequency;
            object dataValues;

            pHistogram.GetHistogram(out dataValues, out dataFrequency);
            //下面是分级方法,用于根据获得的值计算得出符合要求的数据
            //根据条件计算出Classes和ClassesCount,numDesiredClasses为预定的分级数目
            IClassifyGEN pClassify = new NaturalBreaksClass();

            switch (strClassifyMethod)
            {
            case "等间隔分类":
                pClassify = new EqualIntervalClass();
                break;

            //case "预定义间隔分类":
            //    pClassify = new DefinedIntervalClass();
            //    break;
            case "分位数分类":
                pClassify = new QuantileClass();
                break;

            case "自然裂点分类":
                pClassify = new NaturalBreaksClass();
                break;

            case "标准差分类":
                pClassify = new StandardDeviationClass();
                break;

            case "几何间隔分类":
                pClassify = new GeometricalIntervalClass();
                break;

            default:
                break;
            }
            int numDesiredClasses = gClassCount;

            pClassify.Classify(dataValues, dataFrequency, ref numDesiredClasses);
            gClassbreaks = (double[])pClassify.ClassBreaks;
        }
Exemple #3
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        private void btnClassiFy_Click(object sender, EventArgs e)
        {
            ITable pTable = this.pLayer as ITable;

            object dataValues;
            object dataFrequency;

            //以下代码用TableHistogram和BasicHistogram统计出Table某一字段的值和值的频率
            ITableHistogram pTableHistogram;

            pTableHistogram       = new BasicTableHistogramClass();
            pTableHistogram.Table = pTable;                       //需传入一个ITable
            pTableHistogram.Field = this.cbbClassBreakField.Text; //统计的字段
            IBasicHistogram pBasicHistogram;

            pBasicHistogram = pTableHistogram as IBasicHistogram;
            pBasicHistogram.GetHistogram(out dataValues, out dataFrequency);//关键

            //以下代码用IClassifyGEN和EqualInterval对象,基于分段数目,生成各段的临界值,并放在一个数组当中
            IClassifyGEN pClassifyGEN;

            switch (this.cbbClassBreaksMethod.SelectedIndex)
            {
            case 0:
                pClassifyGEN = new EqualIntervalClass();
                break;

            case 1:
                pClassifyGEN = new GeometricalIntervalClass();
                break;

            case 2:
                pClassifyGEN = new NaturalBreaksClass();
                break;

            case 3:
                pClassifyGEN = new QuantileClass();
                break;

            default:
                pClassifyGEN = new EqualIntervalClass();
                break;
            }
            //double[] classes;
            int classCount = int.Parse(this.cbbClassBreaksCount.Text);

            pClassifyGEN.Classify(dataValues, dataFrequency, ref classCount); //用到了上面ITableHistogram生成的值和值频率数组,关键!!!!!!
            this.classBreaks = pClassifyGEN.ClassBreaks as double[];          //注意,此对象下标从1开始(我觉得0为最开头,所以临界值从1开始有意义),关键!!!!!!

            this.lsvClassBreaksSymbol.Items.Clear();
            string currentRange;

            for (int i = 0; i < classCount; i++)
            {
                currentRange = this.classBreaks[i].ToString() + " ~ " + this.classBreaks[i + 1].ToString();
                this.lsvClassBreaksSymbol.Items.Add(currentRange);
                this.lsvClassBreaksSymbol.Items[i].SubItems.Add(currentRange);
            }
        }
Exemple #4
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        private void classify()
        {
            if (layer2Symbolize == null)
            {
                return;
            }
            IFeatureClass   featureClass    = layer2Symbolize.FeatureClass;
            ITable          pTable          = featureClass as ITable;
            ITableHistogram pTableHistogram = new BasicTableHistogramClass();
            IBasicHistogram pHistogram      = pTableHistogram as IBasicHistogram;

            pTableHistogram.Field = strRendererField;
            if (strNormalizeField.ToLower() != "none")
            {
                pTableHistogram.NormField = strNormalizeField;
            }
            pTableHistogram.Table = pTable;
            object dataFrequency;
            object dataValues;

            pHistogram.GetHistogram(out dataValues, out dataFrequency);
            IClassifyGEN pClassify = new NaturalBreaksClass();

            switch (strClassifyMethod)
            {
            case "Equal Interval":
                pClassify = new EqualIntervalClass();
                break;

            case "Quantile":
                pClassify = new QuantileClass();
                break;

            case "Natural Breaks":
                pClassify = new NaturalBreaksClass();
                break;

            case "Geometrical Interval":
                pClassify = new GeometricalIntervalClass();
                break;

            default:
                break;
            }
            int numDesiredClass = gClassCount;

            pClassify.Classify(dataValues, dataFrequency, ref numDesiredClass);
            gClassbreaks = (double[])pClassify.ClassBreaks;
        }
 private void classify()
 {
     if (layer2Symbolize == null) return;
     IFeatureClass featureClass = layer2Symbolize.FeatureClass;
     ITable pTable = (ITable)featureClass;
     ITableHistogram pTableHistogram = new BasicTableHistogramClass();
     IBasicHistogram pHistogram = (IBasicHistogram)pTableHistogram;
     pTableHistogram.Field = strRendererField;
     if (strNormalizeField.ToLower() != "none")
         pTableHistogram.NormField = strNormalizeField;
     pTableHistogram.Table = pTable;
     object dataFrequency;
     object dataValues;
     pHistogram.GetHistogram(out dataValues, out dataFrequency);
     //下面是分级方法,用于根据获得的值计算得出符合要求的数据
     //根据条件计算出Classes和ClassesCount,numDesiredClasses为预定的分级数目
     IClassifyGEN pClassify = new NaturalBreaksClass();
     switch (strClassifyMethod)
     {
         case "等间隔分类":
             pClassify = new EqualIntervalClass();
             break;
         //case "预定义间隔分类":
         //    pClassify = new DefinedIntervalClass();
         //    break;
         case "分位数分类":
             pClassify = new QuantileClass();
             break;
         case "自然裂点分类":
             pClassify = new NaturalBreaksClass();
             break;
         //case "标准差分类":
         //    pClassify = new StandardDeviationClass();
         //    break;
         case "几何间隔分类":
             pClassify = new GeometricalIntervalClass();
             break;
         default:
             break;
     }
     int numDesiredClasses = gClassCount;
     pClassify.Classify(dataValues, dataFrequency, ref numDesiredClasses);
     gClassbreaks = (double[])pClassify.ClassBreaks;
 }
Exemple #6
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        private void btnClassiFy_Click(object sender, EventArgs e)
        {
            ITable pTable = this.pLayer as ITable;

            object dataValues;
            object dataFrequency;

            //以下代码用TableHistogram和BasicHistogram统计出Table某一字段的值和值的频率
            ITableHistogram pTableHistogram;
            pTableHistogram = new BasicTableHistogramClass();
            pTableHistogram.Table = pTable;//需传入一个ITable
            pTableHistogram.Field = this.cbbClassBreakField.Text;//统计的字段
            IBasicHistogram pBasicHistogram;
            pBasicHistogram = pTableHistogram as IBasicHistogram;
            pBasicHistogram.GetHistogram(out dataValues, out dataFrequency);//关键

            //以下代码用IClassifyGEN和EqualInterval对象,基于分段数目,生成各段的临界值,并放在一个数组当中
            IClassifyGEN pClassifyGEN;
            switch (this.cbbClassBreaksMethod.SelectedIndex)
            {
                case 0:
                    pClassifyGEN = new EqualIntervalClass();
                    break;
                case 1:
                    pClassifyGEN = new GeometricalIntervalClass();
                    break;
                case 2:
                    pClassifyGEN = new NaturalBreaksClass();
                    break;
                case 3:
                    pClassifyGEN = new QuantileClass();
                    break;
                default:
                    pClassifyGEN = new EqualIntervalClass();
                    break;
            }
            //double[] classes;
            int classCount = int.Parse(this.cbbClassBreaksCount.Text);
            pClassifyGEN.Classify(dataValues, dataFrequency, ref classCount);//用到了上面ITableHistogram生成的值和值频率数组,关键!!!!!!
            this.classBreaks = pClassifyGEN.ClassBreaks as double[];//注意,此对象下标从1开始(我觉得0为最开头,所以临界值从1开始有意义),关键!!!!!!

            this.lsvClassBreaksSymbol.Items.Clear();
            string currentRange;
            for (int i = 0; i < classCount; i++)
            {
                currentRange = this.classBreaks[i].ToString() + " ~ " + this.classBreaks[i + 1].ToString();
                this.lsvClassBreaksSymbol.Items.Add(currentRange);
                this.lsvClassBreaksSymbol.Items[i].SubItems.Add(currentRange);
            }
        }