函数认为我正在通过一个浮点

我想计算两个数组中所有坐标对之间的距离。以下是我写的一些代码:

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)

阵列是 gas_coords 和 postal_coords .注意

type(postal_coords)
>>>numpy.ndarray

type(gas_coords)
>>>numpy.ndarray

每个数组都有两列。

当我试图计算距离时 using scipy.spatial.distance.cdist 我得到以下错误:

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 是浮点而不是数组。即使当我将数组传递到 哈弗斯林 喜欢 haversine(np.zeros(2),np.zeros(2)) 同样的问题也出现了。我应该注意到,这只发生在矢量化通过 np.vectorize .

从看 哈弗斯林 ,参数不会以任何方式更改。导致错误的原因是什么?

下面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]])