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`# 根据线拐点的表格坐标信息批量生成奥维地图轨迹####
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• 功能用途介绍：

  • 如何根据野外标记的坐标信息，在奥维地图上绘制轨迹和拐点标签
  • 优点：可以批量在奥维地图上标记多条轨迹路线，和标记拐点标签，并可修改点标签的大小、颜色，线的宽度。
  • 用途：可以根据野外调查的实际点位绘制工作轨迹，进行质量检查。

• 模块使用方法：

  • 运行环境：采用python编程语言，在PyCharm开发平台运行。

  • 前期准备：

    • Windows系统安装xlrd库：cmd.exe-->pip3 install xlrd

    • excel表格原始数据格式：

name xyh color width LineName Pnum a ln
101 113.823035001277,25.1556843733412,0 ff00ff80 2 L1 1 1 L1-
102 113.822375077267,25.1563570638673,0 ff00ff80 2 L1 2 2 L1-
103 113.82171504702,25.1570297539114,0 ff00ff80 2 L1 3 3 L1-
104 113.821055106587,25.1577023495313,0 ff00ff80 2 L1 4 4 L1-
201 113.82039506199,25.1583750348307,0 ff00ff80 2 L2 1 5 L2-
202 113.819735109284,25.1590477158692,0 ff00ff80 2 L2 2 6 L2-
203 113.819075050336,25.1597203964229,0 ff00ff80 2 L2 3 7 L2-
204 113.818415083279,25.160393072716,0 ff00ff80 2 L2 4 8 L2-
205 113.817755106973,25.1610656564729,0 ff00ff80 2 L2 5 9 L2-
301 113.817095026497,25.1617383299062,0 ff00ff80 2 L3 1 10 L3-
302 113.816435037913,25.1624109990793,0 ff00ff80 2 L3 2 11 L3-
401 113.815774943083,25.1630836677642,0 ff00ff80 2 L4 1 12 L4-
402 113.815114938074,25.1637562420257,0 ff00ff80 2 L4 2 13 L4-
403 113.814454828889,25.164428905961,0 ff00ff80 2 L4 3 14 L4-
404 113.813794811597,25.1651015656366,0 ff00ff80 2 L4 4 15 L4-
405 113.813134787128,25.1657742229374,0 ff00ff80 2 L4 5 16 L4-

• 模块运行：
  • 点击“运行”
  • 输入:输入Excel表格数据存储路径
  • 结果保存到模块目录下，文件名为：“ 坐标转奥维结果.kml”
  • 将“ line坐标转奥维地图线结果.kml”导入到奥维地图软件，即完成点位标记
    ‘‘‘

效果如下：

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• 研发团队：广核智造研发小组 组长：bisonQue 研发日期:2020年7月3日
  ‘‘‘
  import xlrd

行 Row 列 Column 这是Excel里面的规范表述!

便签绘制函数

def placemark(name, color, scale, xyh):
msg3 = ‘‘‘
%s%s ‘‘‘ % (
name, color, scale, xyh)
return msg3
# print(msg3)
# with open("坐标转奥维结果.kmz", "w+", encoding="utf-8") as f:
# f.write(msg3)

绘制多段线函数

def placemarkForLine(name, color, width, xyhlist):
msgLine = ‘‘‘< Placemark >< name > %s < / name > < Style > < LineStyle > < color > %s < / color > < width > %s < / width > < / LineStyle >< / Style >< LineString >< coordinates > %s< / coordinates >< / LineString >< / Placemark >
‘‘‘% (name, color, width, xyhlist)
msgLine =‘‘‘

%s

‘‘‘% (name, color, width, xyhlist)
return msgLine
# print(msg3)
# with open("坐标转奥维结果.kmz", "w+", encoding="utf-8") as f:
#     f.write(msg3)

def strcount(a): # a为字符串参数 字符串中的所有元素的出现次数
b = {} # 定义一个空字典
c = len(a) # 求出字符串的长度
i = 0
while i < c:
if a[i] in b:
b[a[i]] += 1
else:
b[a[i]] = 1
i += 1
# 遍历字典
# for item in b.items():
# print(item)
# b.pop(a[0])
print(b)
return b

def all_list(arr): # list中的count,获取所有元素的出现次数
result = {}
for i in set(arr):
result[i] = arr.count(i)
return result

main

if name == ‘main‘: # 主函数入库类似c的main函数
# read_xlrd(excelFile=excelFile) #执行函数
with open("line坐标转奥维地图线结果.kml", "w+", encoding="utf-8") as f:
msg1 = ‘‘‘OvitalMap_20200629_213234仁化项目奥维点‘‘‘
f.write(msg1.strip(‘\n‘))

    excelFile = ‘line.xls‘  # excle文件路径名称
    # excelFile = str(input("请输入Excel表格数据存储路径，例如：E:/2020仁化矿山调查项目2020年/RHZB.xls，输入完路径按回车键，路径为："))

    data = xlrd.open_workbook(excelFile)
    # 默认读取第1张sheet表
    table = data.sheet_by_index(0)  # 或者table = data.sheet_by_name(‘工作表1‘)

标记线上的拐点

    rowNum = 0
    colNum = 0
    Name = ""
    Xyh = ""
    Color = ""
    Scale = ""

    for rowNum in range(table.nrows):  # 每行地址循环
        # for colNum in range(table.ncols):
        for colNum in range(table.ncols):
            nameValue = table.row_values(rowNum)[colNum]
            if rowNum > 0 and colNum==0:
                Name= nameValue      #标签名字
            elif rowNum > 0 and colNum==1:
                Xyh = nameValue        #标签坐标
            elif rowNum > 0 and colNum==2:
                Color = nameValue     #标签颜色
            elif rowNum > 0 and colNum == 3:
                Scale = nameValue     #标签大小
            else:
                pass
        f.write(placemark(Name, Color,Scale, Xyh).strip(‘\n‘))

获取线名称放入列表

    xyzValue = ""
    res = ""
    a = []
    b = []
    list_l1 = []  # 用于提取线名称，按linename循环
    list_l2 = []  # 用于计算某条线出现的次数，终止循环
    for rowNum in range(table.nrows):  # 每行地址循环
        # for colNum in range(table.ncols):
        for colNum in range(table.ncols):
            nameValue = table.row_values(rowNum)[colNum]
            L = table.row_values
            if colNum == 7 and rowNum > 0:
                lname = L(rowNum)[7]
                list_l1.append(lname)
                list_l2.append(L(rowNum)[4])
    # 提取线段名称，用于判断
    # print("list_l1:", list_l1)  #list_l1: [‘L1-‘, ‘L1-‘, ‘L1-‘, ‘L1-‘, ‘L2-‘, ‘L2-‘, ‘L2-‘, ‘L2-‘, ‘L2-‘, ‘L3-‘, ‘L3-‘]
    # print("list_l2:", list_l2) #list_l2: [‘L1‘, ‘L1‘, ‘L1‘, ‘L1‘, ‘L2‘, ‘L2‘, ‘L2‘, ‘L2‘, ‘L2‘, ‘L3‘, ‘L3‘]
    dict_count= all_list(list_l2)
    # print("dict_count:",dict_count)  # {‘l3‘: 2, ‘l1‘: 5, ‘l2‘: 4}
    llist_l1 = set(list_l1)
    llist_l1 = list(set(list_l1))
    llist_l1.sort(key=list_l1.index)
    y = ‘‘.join(llist_l1)
    lineName = y.split(‘-‘)
    lineName.pop()  # 删掉最后一个空字符
    # print("lineName:",lineName)   #[‘l1‘, ‘l2‘, ‘l3‘]
    # print(len(lineName)) #3
    # for i in range(len(lineName)):
    # print(lineName[i])     #l1     l2         l3

绘制多段线

    for i in range(len(lineName)):  # len(lineName)循环次数是线的种类
        count=0
        j=0
        a = []
        for rowNum in range(table.nrows):  # 每行地址循环
            colNum = 1
            nameValue = table.row_values(rowNum)[colNum]
            L = table.row_values
            if L(rowNum)[4] == lineName[i] :
               count+=1
               j+=1
               res = L(rowNum)[1]
               a.append(res)
               a.append(" ")
               name=L(rowNum)[4]
               color=L(rowNum)[2]
               width=L(rowNum)[3]
        xyhlist=‘‘.join(a)
        f.write(placemarkForLine(name, color, width, xyhlist))

输出结尾部分

    msg2 = ‘‘‘</Folder></Document></kml>‘‘‘
    f.write(msg2.strip(‘\n‘))

python打印输出

with open("line坐标转奥维地图线结果.kml", "r", encoding="utf-8") as f1:
print(f1.read())
print("程序运行成功！结果保存到：line坐标转奥维地图线结果.kml")
############################ end ############################`

根据线拐点的表格坐标信息批量生成奥维地图轨迹

标签：工作表   values   ==   main   and   检查   loading   数据   mamicode   

原文地址：https://www.cnblogs.com/quezesheng/p/13228067.html