我想计算两个数组中所有坐标对之间的距离。这是我写的一些代码:
def haversine(x,y):
"""
Calculate the great circle distance between two points
on the earth (specified in decimal degrees)
"""
# convert decimal degrees to radians
print(type(x))
lat1, lon1 = np.radians(x)
lat2, lon2 = np.radians(y)
# haversine formula
dlon = lon2 - lon1
dlat = lat2 - lat1
a = np.sin(dlat/2)**2 + np.cos(lat1) * np.cos(lat2) * np.sin(dlon/2)**2
c = 2 * np.arcsin(np.sqrt(a))
r = 6371 # Radius of earth in kilometers. Use 3956 for miles
return c * r
haversine = np.vectorize(haversine)
数组是gas_coords
和postal_coords
。请注意
type(postal_coords)
>>>numpy.ndarray
type(gas_coords)
>>>numpy.ndarray
并且每个数组都有两列。
当我尝试计算距离using scipy.spatial.distance.cdist
时,出现以下错误:
in haversine(x, y)
6 # convert decimal degrees to radians
7 print(type(x))
---->; 8 lat1,lon1 =np.radians(x)
9 lat2,lon2 = np.radians(y)
10
TypeError: 'numpy.float64' object is not iterable
haversine
似乎认为输入x
是浮点数而不是数组。即使我像haversine
一样将数组传递到haversine(np.zeros(2),np.zeros(2))
中,也会出现相同的问题。我应该注意,这仅在通过np.vectorize
进行矢量化之后才会发生。
从查看haversine
来看,参数没有任何改变。可能是什么原因导致错误?
这是一个最小的工作示例:
import numpy as np
from scipy.spatial.distance import cdist
gas_coords = np.array([[50, 80], [50, 81]])
postal_coords = np.array([[51, 80], [51, 81]])
cdist(postal_coords, gas_coords, metric = haversine)
>>>array([[ 111.19492664, 131.7804742 ],
[ 131.7804742 , 111.19492664]])
答案 0 :(得分:2)
给出所需的输出,可以通过不对body {
margin: 0;
}
h1, h2, h3, h4, h5, h6 {
font-family: Open Sans, sans-serif;
}
p {
font-family: Raleway, sans-serif;
}
li {
font-family: Raleway, sans-serif;
}
a {
font-family: Raleway, sans-serif;
text-decoration: none;
color: black;
}
nav {
background: whitesmoke;
position: relative;
height: 100%;
}
nav ul {
position: absolute;
margin: auto;
top: 0; left: 0; bottom: 0; right: 0;
list-style-type: none;
text-align: right;
margin-right: 30px;
}
nav li {
display: inline;
padding: 10px;
transition: background-color 0.4s ease-in-out 0s;
}
nav li:hover {
background-color: lightgrey;
}
函数进行向量化来避免错误,因为这会将标量传递给该函数(如上面的注释所述)。因此,您可以通过以下方式致电haversine
:
cdist