Python，用于计算字典中的坐标差_Python_List_Dictionary

Python，用于计算字典中的坐标差

python list dictionary

Python，用于计算字典中的坐标差,python,list,dictionary,Python,List,Dictionary,用于计算2个坐标的现有函数。例如，它可以计算这两个城市之间的距离（52.22,21.01）和（52.40,16.92）输出为： Distance is: 278.82127298 km. 现在，对于城市列表，我想计算任意两个城市之间的距离。数据以字典形式提供，我可以访问坐标： cities = { "Ahmedabad":"23.02579,72.58727", "Bengaluru":"12.97194,77.59369", "Chennai":"13.08784,80.27847", "

用于计算2个坐标的现有函数。例如，它可以计算这两个城市之间的距离（52.22,21.01）和（52.40,16.92）

输出为：

Distance is: 278.82127298 km.

现在，对于城市列表，我想计算任意两个城市之间的距离。数据以字典形式提供，我可以访问坐标：

cities = {
"Ahmedabad":"23.02579,72.58727",
"Bengaluru":"12.97194,77.59369",
"Chennai":"13.08784,80.27847",
"Delhi":"28.65195,77.23149",
"Hyderabad":"17.38405,78.45636",
"Kanpur":"26.46523,80.34975",
"Kolkata":"22.56263,88.36304",
"Mumbai":"19.07283,72.88261",
"Pune":"18.51957,73.85535",
"Surat":"21.19594,72.83023"}

for c, o in cities.items():
    lat = o.split(",")[0]
    lon = o.split(",")[1]

如何计算字典中任意两个城市之间的所有距离

谢谢。

如果用户输入两个城市名称，您只需执行以下操作：

def dist_two_cities(city1,city2):
    lat1 = cities[city1].split(",")[0]
    lon1 = cities[city1].split(",")[0]

    lat2 = cities[city2].split(",")[0]
    lon2 = cities[city2].split(",")[0]

    return cor_dist_calculator(lat1, lat2, lon1, lon2)

而且，如果您想为所有人随机计算，您可以循环。

如果用户提供两个城市名称作为输入，您只需执行以下操作：

def dist_two_cities(city1,city2):
    lat1 = cities[city1].split(",")[0]
    lon1 = cities[city1].split(",")[0]

    lat2 = cities[city2].split(",")[0]
    lon2 = cities[city2].split(",")[0]

    return cor_dist_calculator(lat1, lat2, lon1, lon2)

而且，如果你想对所有人进行随机计算，你可以进行循环。

你已经完成了大部分工作。这只是从用户那里获取输入并根据您的需要对其进行格式化的问题

if __name__ == "__main__":
    city1, city2 = input("Enter the name of the city seperated by comma\n").split(',')

    lat1, long1 = cities.get(city1.strip()).split(',')
    lat2, long2 = cities.get(city2.strip()).split(',')

    cor_dist_calculator(radians(float(lat1)), radians(float(lat2)), radians(float(long1)), radians(float(long2)))

你已经做了大部分事情。这只是从用户那里获取输入并根据您的需要对其进行格式化的问题

if __name__ == "__main__":
    city1, city2 = input("Enter the name of the city seperated by comma\n").split(',')

    lat1, long1 = cities.get(city1.strip()).split(',')
    lat2, long2 = cities.get(city2.strip()).split(',')

    cor_dist_calculator(radians(float(lat1)), radians(float(lat2)), radians(float(long1)), radians(float(long2)))

代码

from math import sin, cos, sqrt, atan2, radians
import json

def cor_dist_calculator(lat1, lat2, lon1, lon2):
    R = 6373.0
    dlon = lon2 - lon1
    dlat = lat2 - lat1
    a = sin(dlat / 2)**2 + cos(lat1) * cos(lat2) * sin(dlon / 2)**2
    c = 2 * atan2(sqrt(a), sqrt(1 - a))
    distance = R * c
    return distance # Change to return result instead of printing

cities = {
  "Ahmedabad":"23.02579,72.58727",
  "Bengaluru":"12.97194,77.59369",
  "Chennai":"13.08784,80.27847",
  "Delhi":"28.65195,77.23149",
  "Hyderabad":"17.38405,78.45636",
  "Kanpur":"26.46523,80.34975",
  "Kolkata":"22.56263,88.36304",
  "Mumbai":"19.07283,72.88261",
  "Pune":"18.51957,73.85535",
  "Surat":"21.19594,72.83023"
}

result = { } # result cache

for c1, o1 in cities.items():
  for c2, o2 in cities.items():
    if c1 == c2: # Skip distance to itself
      continue
    if c1 not in result:
      result[c1] = {}
    if c2 not in result:
      result[c2] = {}
    if c2 in result[c1]: # Skip calculation if result exists
      continue
    lat1, lon1 = o1.split(",")
    lat2, lon2 = o2.split(",")
    lat1, lon1, lat2, lon2 = float(lat1), float(lon1), float(lat2), float(lon2)
    dist = cor_dist_calculator(radians(lat1), radians(lat2), radians(lon1), radians(lon2))
    result[c1][c2] = dist
    result[c2][c1] = dist

# Use JSON to pretty print
print(json.dumps(result, sort_keys=True, indent=4))

输出

{
    "Ahmedabad": {
        "Bengaluru": 1236.9685147466164,
        "Chennai": 1371.5560941922058,
        "Delhi": 779.3993196898124,
        "Hyderabad": 876.7339794841921,
        "Kanpur": 872.2163865213793,
        "Kolkata": 1617.7373028708505,
        "Mumbai": 440.75405570398016,
        "Pune": 518.2729673252524,
        "Surat": 205.06784688939214
    },
    "Bengaluru": {
        "Ahmedabad": 1236.9685147466164,
        "Chennai": 291.2228040150677,
        "Delhi": 1744.487772289504,
        "Hyderabad": 499.41428330226853,
        "Kanpur": 1528.1728332155533,
        "Kolkata": 1560.4315624298629,
        "Mumbai": 844.9020405056748,
        "Pune": 735.3744543489997,
        "Surat": 1045.3221688709566
    },
    "Chennai": {
        "Ahmedabad": 1371.5560941922058,
        "Bengaluru": 291.2228040150677,
        "Delhi": 1759.6662314194639,
        "Hyderabad": 516.3080888651748,
        "Kanpur": 1487.983445250212,
        "Kolkata": 1356.9170709394425,
        "Mumbai": 1033.058314823502,
        "Pune": 914.9401253270859,
        "Surat": 1199.443950315355
    },
    "Delhi": {
        "Ahmedabad": 779.3993196898124,
        "Bengaluru": 1744.487772289504,
        "Chennai": 1759.6662314194639,
        "Hyderabad": 1259.5527686310922,
        "Kanpur": 392.0259915147513,
        "Kolkata": 1304.8787459771033,
        "Mumbai": 1153.348591508457,
        "Pune": 1178.1906584531494,
        "Surat": 940.4321887894869
    },
    "Hyderabad": {
        "Ahmedabad": 876.7339794841921,
        "Bengaluru": 499.41428330226853,
        "Chennai": 516.3080888651748,
        "Delhi": 1259.5527686310922,
        "Kanpur": 1028.7605594631257,
        "Kolkata": 1184.4860919672817,
        "Mumbai": 618.0416762200242,
        "Pune": 502.9490477553323,
        "Surat": 726.9427844409639
    },
    "Kanpur": {
        "Ahmedabad": 872.2163865213793,
        "Bengaluru": 1528.1728332155533,
        "Chennai": 1487.983445250212,
        "Delhi": 392.0259915147513,
        "Hyderabad": 1028.7605594631257,
        "Kolkata": 919.5167629722739,
        "Mumbai": 1123.0549698313646,
        "Pune": 1106.9736378339578,
        "Surat": 963.370481325532
    },
    "Kolkata": {
        "Ahmedabad": 1617.7373028708505,
        "Bengaluru": 1560.4315624298629,
        "Chennai": 1356.9170709394425,
        "Delhi": 1304.8787459771033,
        "Hyderabad": 1184.4860919672817,
        "Kanpur": 919.5167629722739,
        "Mumbai": 1654.6687139324506,
        "Pune": 1575.6823437947044,
        "Surat": 1609.718084142609
    },
    "Mumbai": {
        "Ahmedabad": 440.75405570398016,
        "Bengaluru": 844.9020405056748,
        "Chennai": 1033.058314823502,
        "Delhi": 1153.348591508457,
        "Hyderabad": 618.0416762200242,
        "Kanpur": 1123.0549698313646,
        "Kolkata": 1654.6687139324506,
        "Pune": 119.49195110246427,
        "Surat": 236.21650702410025
    },
    "Pune": {
        "Ahmedabad": 518.2729673252524,
        "Bengaluru": 735.3744543489997,
        "Chennai": 914.9401253270859,
        "Delhi": 1178.1906584531494,
        "Hyderabad": 502.9490477553323,
        "Kanpur": 1106.9736378339578,
        "Kolkata": 1575.6823437947044,
        "Mumbai": 119.49195110246427,
        "Surat": 316.4157942067634
    },
    "Surat": {
        "Ahmedabad": 205.06784688939214,
        "Bengaluru": 1045.3221688709566,
        "Chennai": 1199.443950315355,
        "Delhi": 940.4321887894869,
        "Hyderabad": 726.9427844409639,
        "Kanpur": 963.370481325532,
        "Kolkata": 1609.718084142609,
        "Mumbai": 236.21650702410025,
        "Pune": 316.4157942067634
    }
}

代码

from math import sin, cos, sqrt, atan2, radians
import json

def cor_dist_calculator(lat1, lat2, lon1, lon2):
    R = 6373.0
    dlon = lon2 - lon1
    dlat = lat2 - lat1
    a = sin(dlat / 2)**2 + cos(lat1) * cos(lat2) * sin(dlon / 2)**2
    c = 2 * atan2(sqrt(a), sqrt(1 - a))
    distance = R * c
    return distance # Change to return result instead of printing

cities = {
  "Ahmedabad":"23.02579,72.58727",
  "Bengaluru":"12.97194,77.59369",
  "Chennai":"13.08784,80.27847",
  "Delhi":"28.65195,77.23149",
  "Hyderabad":"17.38405,78.45636",
  "Kanpur":"26.46523,80.34975",
  "Kolkata":"22.56263,88.36304",
  "Mumbai":"19.07283,72.88261",
  "Pune":"18.51957,73.85535",
  "Surat":"21.19594,72.83023"
}

result = { } # result cache

for c1, o1 in cities.items():
  for c2, o2 in cities.items():
    if c1 == c2: # Skip distance to itself
      continue
    if c1 not in result:
      result[c1] = {}
    if c2 not in result:
      result[c2] = {}
    if c2 in result[c1]: # Skip calculation if result exists
      continue
    lat1, lon1 = o1.split(",")
    lat2, lon2 = o2.split(",")
    lat1, lon1, lat2, lon2 = float(lat1), float(lon1), float(lat2), float(lon2)
    dist = cor_dist_calculator(radians(lat1), radians(lat2), radians(lon1), radians(lon2))
    result[c1][c2] = dist
    result[c2][c1] = dist

# Use JSON to pretty print
print(json.dumps(result, sort_keys=True, indent=4))

输出

{
    "Ahmedabad": {
        "Bengaluru": 1236.9685147466164,
        "Chennai": 1371.5560941922058,
        "Delhi": 779.3993196898124,
        "Hyderabad": 876.7339794841921,
        "Kanpur": 872.2163865213793,
        "Kolkata": 1617.7373028708505,
        "Mumbai": 440.75405570398016,
        "Pune": 518.2729673252524,
        "Surat": 205.06784688939214
    },
    "Bengaluru": {
        "Ahmedabad": 1236.9685147466164,
        "Chennai": 291.2228040150677,
        "Delhi": 1744.487772289504,
        "Hyderabad": 499.41428330226853,
        "Kanpur": 1528.1728332155533,
        "Kolkata": 1560.4315624298629,
        "Mumbai": 844.9020405056748,
        "Pune": 735.3744543489997,
        "Surat": 1045.3221688709566
    },
    "Chennai": {
        "Ahmedabad": 1371.5560941922058,
        "Bengaluru": 291.2228040150677,
        "Delhi": 1759.6662314194639,
        "Hyderabad": 516.3080888651748,
        "Kanpur": 1487.983445250212,
        "Kolkata": 1356.9170709394425,
        "Mumbai": 1033.058314823502,
        "Pune": 914.9401253270859,
        "Surat": 1199.443950315355
    },
    "Delhi": {
        "Ahmedabad": 779.3993196898124,
        "Bengaluru": 1744.487772289504,
        "Chennai": 1759.6662314194639,
        "Hyderabad": 1259.5527686310922,
        "Kanpur": 392.0259915147513,
        "Kolkata": 1304.8787459771033,
        "Mumbai": 1153.348591508457,
        "Pune": 1178.1906584531494,
        "Surat": 940.4321887894869
    },
    "Hyderabad": {
        "Ahmedabad": 876.7339794841921,
        "Bengaluru": 499.41428330226853,
        "Chennai": 516.3080888651748,
        "Delhi": 1259.5527686310922,
        "Kanpur": 1028.7605594631257,
        "Kolkata": 1184.4860919672817,
        "Mumbai": 618.0416762200242,
        "Pune": 502.9490477553323,
        "Surat": 726.9427844409639
    },
    "Kanpur": {
        "Ahmedabad": 872.2163865213793,
        "Bengaluru": 1528.1728332155533,
        "Chennai": 1487.983445250212,
        "Delhi": 392.0259915147513,
        "Hyderabad": 1028.7605594631257,
        "Kolkata": 919.5167629722739,
        "Mumbai": 1123.0549698313646,
        "Pune": 1106.9736378339578,
        "Surat": 963.370481325532
    },
    "Kolkata": {
        "Ahmedabad": 1617.7373028708505,
        "Bengaluru": 1560.4315624298629,
        "Chennai": 1356.9170709394425,
        "Delhi": 1304.8787459771033,
        "Hyderabad": 1184.4860919672817,
        "Kanpur": 919.5167629722739,
        "Mumbai": 1654.6687139324506,
        "Pune": 1575.6823437947044,
        "Surat": 1609.718084142609
    },
    "Mumbai": {
        "Ahmedabad": 440.75405570398016,
        "Bengaluru": 844.9020405056748,
        "Chennai": 1033.058314823502,
        "Delhi": 1153.348591508457,
        "Hyderabad": 618.0416762200242,
        "Kanpur": 1123.0549698313646,
        "Kolkata": 1654.6687139324506,
        "Pune": 119.49195110246427,
        "Surat": 236.21650702410025
    },
    "Pune": {
        "Ahmedabad": 518.2729673252524,
        "Bengaluru": 735.3744543489997,
        "Chennai": 914.9401253270859,
        "Delhi": 1178.1906584531494,
        "Hyderabad": 502.9490477553323,
        "Kanpur": 1106.9736378339578,
        "Kolkata": 1575.6823437947044,
        "Mumbai": 119.49195110246427,
        "Surat": 316.4157942067634
    },
    "Surat": {
        "Ahmedabad": 205.06784688939214,
        "Bengaluru": 1045.3221688709566,
        "Chennai": 1199.443950315355,
        "Delhi": 940.4321887894869,
        "Hyderabad": 726.9427844409639,
        "Kanpur": 963.370481325532,
        "Kolkata": 1609.718084142609,
        "Mumbai": 236.21650702410025,
        "Pune": 316.4157942067634
    }
}

我建议将这一行添加到def下方的计算器中：

lat1, lat2, lon1, lon2 = radians(lat1), radians(lat2), radians(lon1), radians(lon2)

因此，您可以轻松地以度为单位输入坐标

然后，用两个城市的组合建立一个列表（以避免计算城市到自身或城市1-city2和城市2-city1的距离）：

现在res包含：

[('Ahmedabad', 'Bengaluru', 157.22689337854425), ('Ahmedabad', 'Chennai', 248.52555085450666), ('Ahmedabad', 'Delhi', 675.9491465155114), ('Ahmedabad', 'Hyderabad', 675.9491465155114), ......

如果需要两个方向上的距离（相同：），请将

itertools.compositions

更改为

itertools.permutations

使用

permutations

可以如下方式获取信息：

city1 = "Surat"
city2 = "Bengaluru"
print ([ cities for cities in res if cities[0] == city1 and cities[1] == city2])