我有以下代码,它当前对一个列表运行for循环
data3 = []
x=0
while x<len(river_df_list):
for line in river_df_list[x]:
try:
distance = haversine(river_df_list[x][0],river_df_list[x][1],df1_list[0][4],df1_list[0][3])
data3.append(distance)
x=x+1
except IndexError:
pass
df1_list[0].append(data3.index(min(data3))) 其中haversine函数是:
def haversine(lon1, lat1, lon2, lat2):
"""
Calculate the great circle distance between two points
on the earth (specified in decimal degrees)
"""
# convert decimal degrees to radians
lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
# haversine formula
dlon = lon2 - lon1
dlat = lat2 - lat1
a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
c = 2 * asin(sqrt(a))
r = 6371 # Radius of earth in kilometers. Use 3956 for miles
return c * rriver_df_list (缩写)如下所示:
[[151.7753278, -32.90526725, 'HUNTER RIVER']
[151.77526830000002, -32.90610052, 'HUNTER RIVER']
[151.775397, -32.90977754, 'HUNTER RIVER']
[151.775578, -32.91202941, 'HUNTER RIVER']
[151.77586340000002, -32.91508789, 'HUNTER RIVER']
[151.7764116, -32.91645856, 'HUNTER RIVER']
[151.7773432, -32.91905274, 'HUNTER RIVER']
[151.7784225, -32.91996844, 'HUNTER RIVER']
[151.780565, -32.92181352, 'HUNTER RIVER']
[151.7807739, -32.92183623, 'HUNTER RIVER']
[151.78591709999998, -32.92187872, 'HUNTER RIVER']]df1_list (缩写)如下所示:
[[5, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '14/08/2015']
[6, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '15/08/2015']
[7, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '16/08/2015']
[8, 'A69-1601-27466', 'Golden perch', -35.5065473, 144.4488804, '17/08/2015']]目前,当我在顶部运行代码时,我能够遍历river_df_list并对df1_list中的第一个点应用半正弦函数。最后,代码将data3中出现最小值的索引附加到df1_list中,因此它现在看起来如下所示:
[5, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '14/08/2015',324110 ]
[6, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '15/08/2015']
[7, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '16/08/2015']
[8, 'A69-1601-27466', 'Golden perch', -35.5065473, 144.4488804, '17/08/2015']我想要做的是更改顶部的while / for循环,以比较df1_list的每个点上的所有river_df_list点,并将索引附加到df1_list的末尾,因此,最终所需的输出将是:
[[5, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '14/08/2015',324110 ]
[6, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '15/08/2015',32440]
[7, 'A69-1601-27466', 'Golden perch', -35.495479100000004, 144.45295380000002, '16/08/2015',31110]
[8, 'A69-1601-27466', 'Golden perch', -35.5065473, 144.4488804, '17/08/2015',35479]]我该怎么做呢?
发布于 2018-12-13 11:11:48
这应该是可行的:
for x in df1_list:
data3 = []
for y in river_df_list:
distance = haversine(y[0],y[1],x[4],x[3])
data3.append(distance)
x.append(data3.index(min(data3)))因为您需要每个点都与其他点相关联,所以您使用嵌套循环并同时处理这两个点。对于df1中的每个数组,您将遍历所有的river_df,获取哈弗正弦并将其保存到data3中。然后,在进入df1中的下一个数组之前,您将从data3获取最小值并将其附加到该数组上。它正在处理你给出的玩具数据。
编辑:此外,data3看起来非常昂贵(在时间和内存上),而且没有必要,因为你只想要最小的索引。这将消除它:
from sys import maxsize
for x in df1_list:
min_distance = [maxsize, 0]
for i, y in enumerate(river_df_list):
distance = haversine(y[0],y[1],x[4],x[3])
if distance < min_distance[0]:
min_distance = [distance, i]
x.append(min_distance[1])我使用maxsize,因为我不知道这些距离有多大。如果它们永远不会大于1000000,你可以直接使用它。
https://stackoverflow.com/questions/53752888
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