I am trying to calculate the sum of distances between every uninfected point and an infected point
我使用此数据对感染状态的个体进行了随机绘图。frame：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | structure(list(xcoord = c(22L, 38L, 46L, 86L, 66L, 97L, 51L, 87L, 24L, 45L, 61L, 96L, 91L, 90L, 49L, 17L, 25L, 7L, 6L, 74L, 76L, 94L, 27L, 99L, 39L, 83L, 40L, 41L, 9L, 84L, 88L, 63L, 43L, 12L, 93L, 1L, 54L, 13L, 33L, 68L, 20L, 64L, 85L, 3L, 28L, 19L, 23L, 81L, 79L, 5L, 78L, 56L, 8L, 26L, 73L, 37L, 71L, 14L, 11L, 55L), ycoord = c(8L, 35L, 77L, 5L, 68L, 22L, 62L, 86L, 85L, 91L, 74L, 71L, 11L, 1L, 34L, 76L, 13L, 57L, 10L, 29L, 14L, 47L, 80L, 45L, 83L, 56L, 17L, 70L, 55L, 51L, 6L, 46L, 16L, 58L, 18L, 72L, 54L, 38L, 41L, 73L, 69L, 33L, 100L, 50L, 37L, 65L, 25L, 90L, 20L, 95L, 88L, 19L, 67L, 42L, 78L, 53L, 15L, 96L, 66L, 84L), infectionstatus = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c(NA, -60L), class ="data.frame") |
我想做的是计算每个未感染个体与被感染个体之间的距离。这样一来，一旦我在每个未感染点和被感染点之间保持距离，就可以使用此信息根据该信息来发展成为被感染功能的可能性。如何计算每个未感染点与一个感染点之间的距离？
如果数据集较小，则可以使用
1 2 3 4 5 6 7 8 9 10 11 12 13 | i <- x$infectionstatus == 1 tt <- outer(x$xcoord[i], x$xcoord[!i],"-")^2 + outer(x$ycoord[i], x$ycoord[!i],"-")^2 sqrt(apply(tt, 2, min)) # [1] 81.884064 57.271284 56.603887 42.755117 35.000000 25.179357 # [7] 45.541190 39.623226 79.649231 65.855903 42.638011 24.083189 #[13] 36.124784 46.173586 46.840154 82.280010 76.922038 87.572827 #[19] 95.462034 26.907248 37.589892 74.686009 5.385165 65.734314 #[25] 14.212670 61.773781 57.775427 85.375641 10.770330 41.436699 #[31] 31.016125 59.682493 82.734515 29.017236 96.301610 40.607881 #[37] 81.498466 61.294372 36.769553 77.201036 33.105891 53.758720 #[43] 91.049437 66.753277 77.129761 74.330344 44.922155 30.886890 #[49] 101.118742 44.011362 47.201695 88.294960 68.183576 37.443290 #[55] 57.314920 39.408121 93.813645 85.146932 53.758720 |
1 2 3 4 5 6 7 8 9 | # Calculate the pairwase distance matrix for every individual to the rest. if (!require("rdist")) { install.packages("rdist"); require("rdist") } distances <- pdist(data[,1:2], metric ="euclidean") # dataframe position of the infected individual. position_infected_individual <- which(data[,3]==1) # distances from this infected individual to the rest (we eliminate the distance from itself that is 0) dist_from_infected <- distances[-(position_infected_individual),position_infected_individual] |