Tmp_phone

import numpy as np
from io import StringIO
from scipy.spatial import distance_matrix

input = """8 3 3
3 -2 10
-1 1 15
-1 4 10
3 2 20
4 3 20
-3 -4 25
2 -3 15
0 2 10
"""

# Parse Input:
f_inp = np.loadtxt(StringIO(input))
n, p, d = f_inp[0]
n = int(n) # number of cities should be integer
p = int(p) # number of choosed cities should be integer
xy = f_inp[1:, 0:2]
pop = f_inp[1:, 2]

# Greedy Algorithm
choice_lst = []
sum_pop = 0
distance = distance_matrix(xy, xy)

for i in range(p):
    weighted_pop = (distance <= d)*pop
    weighted_sum = weighted_pop.sum(axis=1)
    choice = np.argmax(weighted_sum) # argmax gives the best choice: Greedy
    covered = np.flatnonzero(weighted_pop[choice]) # cities in that choice
    pop[covered] = 0 # Zeros the city already covered
    sum_pop += weighted_sum[choice] # Total num pop
    choice_lst.append(choice+1)

# Output
choice_str = " ".join([str(x) for x in choice_lst])
print("%s %d"%(choice_str,sum_pop))