arcpy开发实例之POI格网剖分聚类

# _*_ encoding: utf-8 _*_

import arcpy

arcpy.env.workspace = "d:/temp/poi_yuelu";

# 1. 生成格网（鱼网）

arcpy.management.CreateFishnet("d:/temp/poi_yuelu/grid.shp",'12560907 3264305','12560907 3286103',500,500,45,30,labels=False,geometry_type='POLYGON');

# 删除行政边界外的格网，以减少计算量

# 2. 空间关联计算每个单元格里的poi数量

arcpy.analysis.SpatialJoin("grid","poi_yuelu","d:/temp/poi_yuelu/grid_pcount.shp","JOIN_ONE_TO_ONE",match_option="COMPLETELY_CONTAINS");

#删除所有poi点数量为0的单元格，以减少计算量

with arcpy.da.UpdateCursor("grid_pcount","*","join_count=0") as cursor:

    for row in cursor:

        cursor.deleteRow();

# 3. 使用自然分类法，将单元格的poi数量划分为10个组

ys = [];

with arcpy.da.SearchCursor("grid_pcount","join_count") as cursor:

    for row in cursor:

        ys.append(row[0]);      

import jenkspy

breaks = jenkspy.jenks_breaks(ys, nb_class=10)

print breaks

#[1.0, 10.0, 25.0, 45.0, 69.0, 99.0, 138.0, 182.0, 240.0, 305.0, 401.0]

# 4. 根据breaks，为每个单元格设置分组号

with arcpy.da.UpdateCursor("grid_pcount",["join_count","pcount"]) as cursor:

    for row in cursor:

        if row[0]<breaks[1]:

            row[1]=1;

        elif row[0]>=breaks[1] and row[0]<breaks[2]:

            row[1] = 2;

        elif row[0]>=breaks[2] and row[0]<breaks[3]:

            row[1] = 3;

        elif row[0]>=breaks[3] and row[0]<breaks[4]:

            row[1] = 4;

        elif row[0]>=breaks[4] and row[0]<breaks[5]:

            row[1] = 5;

        elif row[0]>=breaks[5] and row[0]<breaks[6]:

            row[1] = 6;

        elif row[0]>=breaks[6] and row[0]<breaks[7]:

            row[1] = 7;

        elif row[0]>=breaks[7] and row[0]<breaks[8]:

            row[1] = 8;

        elif row[0]>=breaks[8] and row[0]<breaks[9]:

            row[1] = 9;

        elif row[0]>=breaks[9]:

            row[1] = 10;    

        cursor.updateRow(row);

# 6. 使用arcgis自带的hotarean分析工具

arcpy.stats.OptimizedHotSpotAnalysis("poi_yuelu","d:/temp/poi_hotarea.shp",

                                      Incident_Data_Aggregation_Method="COUNT_INCIDENTS_WITHIN_FISHNET_POLYGONS",

                                      Cell_Size="20 Meters");

# 六边形鱼网

arcpy.stats.OptimizedHotSpotAnalysis("poi_yuelu","d:/temp/poi_hotarea.shp",

                                      Incident_Data_Aggregation_Method="COUNT_INCIDENTS_WITHIN_HEXAGON_POLYGONS",

                                      Cell_Size="20 Meters");