在多个多边形之间构建成本最低的路径的Python脚本：如何提高速度？

我创建了一个python程序，它使用ArcGIS的函数“CostPath”在shapefile“selected_patches.shp”中包含的几个多边形之间自动构建最小成本路径（LCP）。我的python程序似乎可以工作，但速度太慢了。我必须建造275493个LCP。不幸的是，我不知道如何加速我的程序（我是Python编程语言和ArcGIS的初学者）。或者，是否有其他解决方案可以使用ArcGIS快速计算多个多边形之间的最小成本路径（我使用ArcGIS 10.1）？这是我的密码：

# Import system modules
 import arcpy
 from arcpy import env
 from arcpy.sa import *

arcpy.CheckOutExtension("Spatial")

 # Overwrite outputs
 arcpy.env.overwriteOutput = True

 # Set the workspace
 arcpy.env.workspace = "C:\Users\LCP"

 # Set the extent environment
 arcpy.env.extent = "costs.tif"


rowsInPatches_start = arcpy.SearchCursor("selected_patches.shp") 

for rowStart in rowsInPatches_start:        

ID_patch_start = rowStart.getValue("GRIDCODE") 

expressionForSelectInPatches_start = "GRIDCODE=%s" % (ID_patch_start) ## Define SQL expression for the fonction Select Layer By Attribute

# Process: Select Layer By Attribute in Patches_start
arcpy.MakeFeatureLayer_management("selected_patches.shp", "Selected_patch_start", expressionForSelectInPatches_start)

 # Process: Cost Distance
outCostDist=CostDistance("Selected_patch_start", "costs.tif", "", "outCostLink.tif")

# Save the output 
outCostDist.save("outCostDist.tif")

rowsInSelectedPatches_end = arcpy.SearchCursor("selected_patches.shp") 

for rowEnd in rowsInSelectedPatches_end:

    ID_patch_end = rowEnd.getValue("GRIDCODE") 

    expressionForSelectInPatches_end = "GRIDCODE=%s" % (ID_patch_end) ## Define SQL expression for the fonction Select Layer By Attribute

    # Process: Select Layer By Attribute in Patches_end
    arcpy.MakeFeatureLayer_management("selected_patches.shp", "Selected_patch_end", expressionForSelectInPatches_end)

    # Process: Cost Path
    outCostPath = CostPath("Selected_patch_end", "outCostDist.tif", "outCostLink.tif", "EACH_ZONE","FID")

    # Save the output
    outCostPath.save('P_' +  str(int(ID_patch_start)) + '_' + str(int(ID_patch_end)) + ".tif")

    # Writing in file .txt
    outfile=open('P_' +  str(int(ID_patch_start)) + '_' + str(int(ID_patch_end)) + ".txt", "w")
    rowsTxt = arcpy.SearchCursor('P_' +  str(int(ID_patch_start)) + '_' + str(int(ID_patch_end)) + ".tif")
    for rowTxt in rowsTxt:
        value = rowTxt.getValue("Value")
        count = rowTxt.getValue("Count")
        pathcost = rowTxt.getValue("PATHCOST")
        startrow = rowTxt.getValue("STARTROW")
        startcol = rowTxt.getValue("STARTCOL")
        print value, count, pathcost, startrow, startcol
        outfile.write(str(value) + " " + str(count) + " " + str(pathcost) + " " + str(startrow) + " " + str(startcol) + "\n")
    outfile.close()

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非常感谢你的帮助。

< p>写磁盘到计算成本的速度可能是一个瓶颈，考虑添加一个线程来处理所有的写入。

这：

可以通过使rowsText成为全局变量，并让线程从rowsText写入磁盘，将其转换为线程函数。 完成所有处理后，您可以拥有一个额外的全局布尔值，这样当您完成编写所有内容并关闭线程时，您的线程函数可以结束

我当前使用的线程函数示例：

import threading
class ThreadExample:
   def __init__(self):
      self.receiveThread = None

   def startRXThread(self):
      self.receiveThread = threading.Thread(target = self.receive)
      self.receiveThread.start()

   def stopRXThread(self):
      if self.receiveThread is not None:
         self.receiveThread.__Thread__stop()
         self.receiveThread.join()
         self.receiveThread = None

   def receive(self):
       while true:
          #do stuff for the life of the thread
          #in my case, I listen on a socket for data
          #and write it out

因此，对于您的情况，您可以向thread类添加一个类变量

self.rowsTxt

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然后更新您的receive以检查self.rowsText，如果它不是空的，请像我在上面从您那里获取的代码片段中那样处理它。处理后，将self.rowsText设置回无。您可以使用main函数更新threads self.rowsTxt，因为它获取了rowsTxt。考虑使用一个类似于Self.RoStxt的缓冲区列表，这样您就不会错过写入任何东西。

< P>最快的更改，您可以使其显著提高速度，即切换到（例如，代码> ARCYP.DA.SKCHCURSORE（））/>代码>。为了说明这一点，我在前一段时间运行了一个基准测试，以查看数据访问游标与旧游标相比的性能

附图显示了新da方法UpdateCursor与旧UpdateCursor方法的基准测试结果。基本上，基准测试执行以下工作流：

创建随机点（10、100、1000、10000、100000）

从正态分布中随机抽取样本，并向新样本添加值 带有光标的随机点属性表中的列

对新场景和新场景的每个随机点场景运行5次迭代 旧的UpdateCursor方法，并将平均值写入列表

绘制结果

---

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非常感谢亚伦的回答。我不知道它是否正确，但在上面的代码中，我用arcpy.da.SearchCursor（“selected_patches.shp”）替换了

中的rowsInPatches\u start=arcpy.SearchCursor（“selected_patches.shp”），（“*”）作为rowsInPatches\u start:

和

ID_patch\u start=rowStart.getValue（“GRIDCODE”）

by

ID_patch\u start=int（rowStart[3]）

。不幸的是，我不知道为什么我的脚本还太长。谢谢你的帮助。

self.rowsTxt

import arcpy, os, numpy, time
arcpy.env.overwriteOutput = True

outws = r'C:\temp'
fc = os.path.join(outws, 'randomPoints.shp')

iterations = [10, 100, 1000, 10000, 100000]
old = []
new = []

meanOld = []
meanNew = []

for x in iterations:
    arcpy.CreateRandomPoints_management(outws, 'randomPoints', '', '', x)
    arcpy.AddField_management(fc, 'randFloat', 'FLOAT')

    for y in range(5):

        # Old method ArcGIS 10.0 and earlier
        start = time.clock()

        rows = arcpy.UpdateCursor(fc)

        for row in rows:
            # generate random float from normal distribution
            s = float(numpy.random.normal(100, 10, 1))
            row.randFloat = s
            rows.updateRow(row)

        del row, rows

        end = time.clock()
        total = end - start
        old.append(total)

        del start, end, total

        # New method 10.1 and later
        start = time.clock()

        with arcpy.da.UpdateCursor(fc, ['randFloat']) as cursor:
            for row in cursor:
                # generate random float from normal distribution
                s = float(numpy.random.normal(100, 10, 1))
                row[0] = s
                cursor.updateRow(row)

        end = time.clock()
        total = end - start
        new.append(total)
        del start, end, total
    meanOld.append(round(numpy.mean(old),4))
    meanNew.append(round(numpy.mean(new),4))

#######################
# plot the results

import matplotlib.pyplot as plt
plt.plot(iterations, meanNew, label = 'New (da)')
plt.plot(iterations, meanOld, label = 'Old')
plt.title('arcpy.da.UpdateCursor -vs- arcpy.UpdateCursor')
plt.xlabel('Random Points')
plt.ylabel('Time (minutes)')
plt.legend(loc = 2)
plt.show()