R=range
import time
import random
import math
def TwoDimensionalAllNearestNeighbourRandomised(d2,S,T,bucket_size,time_bound):
	S_size = len(S); T_size = len(T)
	if S_size == 0:return[]
	assert( T_size > 0 )
	nn = [set()for i in R(S_size)]
	for i in R(S_size):nn[i].add(0)
	line = [0]*T_size
	now = time.time()
	time_bound /= 1000
	while time.time() - now < time_bound:
		theta = random.randint( -1000 , 1000 ) * 0.00314
		dx = math.cos( theta ); dy = math.sin( theta )
		def proj( v ):return v[0] * dx + v[1] * dy
		for j in R(T_size):line[j] = [ proj( T[j] ) , j ]
		line.sort()
		line_ord = [0]*T_size
		for i in R(S_size):
			proj_i = [ proj( S[i] ) , 0 ]
			l , r = 0 , T_size
			while l + 1 < r:
				m = ( l + r ) >> 1
				if proj_i < line[m]:r = m
				else:l = m
			j_min = max( 0 , l - bucket_size )
			j_ulim = min( T_size , l + bucket_size + 1 )
			d_opt = d2( S[i] , T[next( iter( nn[i] ) )] )
			for j in R(j_min,j_ulim):
				d_temp = d2( S[i] , T[line[j][1]] )
				if d_opt > d_temp:
					d_opt = d_temp
					nn[i] = set(); nn[i].add( line[j][1] )
				elif d_opt == d_temp and not line[j][1] in nn[i]:
					nn[i].add( line[j][1] )
	return[list(nn[i])for i in R(S_size)]

def d2(u,v):return (u[0]-v[0])**2+(u[1]-v[1])**2

J=lambda:list(map(int,input().split()))
N,M,K=J()
N+=1
XY=[J()for i in R(N)]
AB=[J()for k in R(K)]
d=min(d2(XY[0],XY[i])for i in R(1,N))**0.5
ann1=TwoDimensionalAllNearestNeighbourRandomised(d2,AB,XY,1000,2000)
ann2=TwoDimensionalAllNearestNeighbourRandomised(d2,AB,XY,17,2000)
answer=sum(min(d2(XY[0],AB[k])**0.5,min(d+d2(XY[i],AB[k])**0.5 for i in ann1[k]+ann2[k]))for k in R(K))
print(answer*2)