循環ltraj類？

-1

道歉，如果這不是最好的論壇來詢問這個問題。循環ltraj類？

有沒有人能夠循環/迭代，雖然在類ltraj（adehabitatlt）的多個GPS領域的個人？

我一直在試圖爲多個人計算Prox（https://cran.r-project.org/web/packages/wildlifeDI/vignettes/wildlifeDI-vignette.pdf），但我正在努力如何循環ltraj類，因爲它與數據框（我習慣於）不同。

在此先感謝。

install.packages('wildlifeDI', dependencies=TRUE) 
library(wildlifeDI) 
library(adehabitatLT) 
chupacabra <- structure(list(CollarID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L), .Label = c("A4116F", "A4117M", "A4118F"), class =  "factor"), 
DateTime = structure(c(1433653200, 1433667600, 1433682060, 
1433682300, 1433682600, 1433682900, 1433683200, 1433683500, 
1433683800, 1433684100, 1433684400, 1433684700, 1433685000, 
1433685300, 1433685600, 1433685900, 1433686200, 1433686500, 
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1433688300, 1433688600, 1433688900, 1433689200, 1433689500, 
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1433714700, 1433715000, 1433715300, 1433715600, 1433715900, 
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1433725200, 1433653200, 1433667660, 1433682060, 1433682300, 
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1433721000, 1433721300, 1433721600, 1433721900, 1433722200, 
1433722500, 1433722800, 1433723100, 1433723400, 1433723700, 
1433724000, 1433724300, 1433724600, 1433724900, 1433725200, 
1433653249, 1433667666, 1433682089, 1433682349, 1433682632, 
1433682936, 1433683234, 1433683536, 1433683837, 1433684144, 
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1433687448, 1433687736, 1433688034, 1433688337, 1433688649, 
1433688936, 1433689236, 1433689531, 1433689827, 1433690139, 
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1433691941, 1433692236, 1433692535, 1433692833, 1433693129, 
1433693434, 1433693735, 1433694028, 1433694373, 1433694642, 
1433694931, 1433695234, 1433695542, 1433695831, 1433696148, 
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1433719837, 1433720136, 1433720431, 1433720736, 1433721031, 
1433721336, 1433721640, 1433721946, 1433722236, 1433722528, 
1433722842, 1433723137, 1433723434, 1433723730, 1433724035, 
1433724370, 1433724634, 1433724936, 1433725236), class = c("POSIXct", 
"POSIXt"), tzone = ""), UTM_X = c(636979.2503, 636977.6583, 
637402.4471, 637400.3063, 637402.3105, 637407.1977, 637406.3305, 
637408.2991, 637407.1907, 637407.8414, 637406.7617, 637407.1614, 
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627502.6326, 627430.6781, 627408.8845, 627357.5049, 627406.0466, 
627427.1382, 636666.3215, 636629.7032, 637179.9041, 637187.7067, 
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637366.5627, 637340.7274, 637357.5505, 637350.709, 637349.689 
), UTM_Y = c(3365828.581, 3365826.066, 3364992.673, 3364991.006, 
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3365438.852, 3365412.317, 3365406.363)), .Names = c("CollarID", 
"DateTime", "UTM_X", "UTM_Y"), row.names = c(NA, -267L), class = "data.frame")

註釋掉不正確轉型

# chupacabra$DateTime <-as.POSIXct(strptime(chupacabra$DateTime, format='%m/%d/%Y %H:%M:%S'),origin='1970-01-01') 

chupacabra2<-as.ltraj(chupacabra[, c("UTM_X","UTM_Y")], date=chupacabra$DateTime,id=chupacabra$CollarID, typeII=TRUE) 

monster1<-chupacabra2[1] #extract the first chupacabra 

monster2<-chupacabra2[2] #extract the second chupacabra 

proxdf <-Prox(monster1,monster2, tc=0.5*60,dc=210, local =TRUE)

這裏的chupcabras的樣本，我們一直在跟蹤。我們想檢查一下他們彼此互動的頻率。這個數據集有3個人（但我們有許多更多的chupcabras），並且將動物/生物1乘1來計算接近度是低效的。我想做一個for循環（對於我唯一的ID，也許）但我不明白當數據是ltraj格式時如何做到這一點。任何援助將不勝感激。

來源

2016-03-01 ecologist55

不是任何人爲我做我的工作的請求。僅僅要求過去有人通過ltraj循環。 – ecologist55

在仔細觀察原始數據的時間圖之後，我認爲您對用於確定位置值「同時性」的時間間隔的選擇應該加倍。這意味着你只需要整整60秒來分隔「相鄰」時間值。它大大增加了在「Prox（）」結果中顯示的時間戳的數量。似乎很清楚，意圖是以5分鐘的間隔記錄數據。你也應該考慮刪除你對我的問題的評論。 –

刪除錯誤地重新格式化日期時間值的有害代碼後，我繪製了3個2動物組合的「軌跡」。顯然animal1不與動物2相互作用，因爲它們的範圍是不相交的。動物1和動物3看起來確實互動，因爲大約一半通過他們的共同作客它們具有大致相同的軌跡：

plot(chupacabra2[[1]]$x, chupacabra2[[1]]$y, type="l", 
     xlim=range(c(chupacabra2[[1]]$x, chupacabra2[[3]]$x)), 
     ylim= range(c(chupacabra2[[1]]$y, chupacabra2[[3]]$y))) 
lines(chupacabra2[[3]]$x, chupacabra2[[3]]$y, col="red")

這似乎在proxdf13爲：

> monster1<-chupacabra2[1] 
> 
> monster3<-chupacabra2[3] 
> 
> proxdf13 <-Prox(monster1,monster3, tc=0.5*60,dc=210, local =TRUE) 
> proxdf13 
        date  prox 
1 2015-06-07 06:01:00 549.074863 
2 2015-06-07 07:20:00 104.169909 
3 2015-06-07 08:10:00 6.205875 
4 2015-06-07 09:05:00 14.409016 
5 2015-06-07 09:20:00 11.189309 
6 2015-06-07 15:40:00 6.481131 
7 2015-06-07 16:25:00 4.259042 
8 2015-06-07 17:15:00 10.648210 
9 2015-06-07 17:35:00 4.181297 
10 2015-06-07 17:41:00 7.574566

所以「相互作用」（可能）意味着「沿着15個距離單位連續超過2天」。因此，一個自然的功能要考慮的是rle：

> rle(proxdf13$prox < 15) 
Run Length Encoding 
    lengths: int [1:2] 2 8 
    values : logi [1:2] FALSE TRUE 
> RL13 <- rle(proxdf13$prox < 15) 
> max(RL13$lengths [ RL13$values]) 
[1] 8

和測試，這是否是比一些值，比如2？

所以這是處理單個雙向動物 - 動物組合的方法。下面提問者的評論暗示我可能在後面的材料中失去了他。要獲得一個序列的2路組合使用combn：

> combn(1:3, 2) 
    [,1] [,2] [,3] 
[1,] 1 1 2 
[2,] 2 3 3

即一個矩陣，將使用以生成用於使用來自「ltraj」對象一次拉動兩個單動物「彈道」 dataframes的指標值每列分開。當使用apply函數時，它可以循環遍歷矩陣的行或列，並使用2作爲索引值指定apply指定列。

所以把所有這些組合起來（使用適用於遍歷combn -result的列索引，以獲得組合雙向）：

(max.days.prox <- apply(combn(seq(length(chupacabra2)), 2), 2, 
          # loops over columns of the "combinations matrix" 
          function(x) { 
           proxcomb <- Prox(chupacabra2[ x[1] ], chupacabra2[ x[2] ], 
               tc=0.5*60,dc=210, local =TRUE) 
           RLcomb <- rle(proxcomb$prox < 15) 
           Interact.days <- max(RLcomb$lengths [ RLcomb$values]) } )) 
# [1] -Inf 8 -Inf

我們rbind，要的結果看的項目興趣：

> rbind(combn(seq(length(chupacabra2)), 2) , max.days.prox) 
       [,1] [,2] [,3] 
       1 1 2 
       2 3 3 
max.days.prox -Inf 8 -Inf

所以只有動物1和動物3的配對提供了互動的證據。這將推廣到更大的ltraj實例 - 對象

來源

2016-03-01 23:44:36

欣賞你對此的努力，但這不能回答這個問題（如何通過ltraj類循環）。主持人 - 隨時刪除此帖子。 – ecologist55

您在此評論中有錯誤。我對所呈現的對象「打圈」，以提供所有可能的雙向組合。請求刪除答案的提問者是_not_本網站的工作原理 –

謝謝您擴展您的出色答案！ – ecologist55

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