plot.capthist(secr)
plot.capthist()所属R语言包：secr
Plot Detection Histories
图检测历史记录
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Display a plot of detection (capture) histories over a map of the detectors.
显示图探测器的检测（捕获）的历史图。
用法----------Usage----------
## S3 method for class 'capthist'
plot(x, rad = 5,
hidetraps = FALSE, tracks = FALSE,
title = TRUE, subtitle = TRUE, add = FALSE, varycol = TRUE,
icolours = NULL, randcol = FALSE,
lab1cap = FALSE, laboffset = 4, ncap = FALSE,
splitocc = NULL, col2 = "green",
type = "petal",
cappar = list(cex = 1.3, pch = 16, col = "blue"),
trkpar = list(col = "blue", lwd = 1),
labpar = list(cex = 0.7, col = "black"), ...)
参数----------Arguments----------
参数：x
an object of class capthist
一个对象的类capthist
参数：rad
radial displacement of dot indicating each capture event from the detector location (used to separate overlapping points)
点指示每个捕捉事件检测器位置（用于分离重叠点的径向位移）
参数：hidetraps
logical indicating whether trap locations should be displayed
逻辑陷阱的位置是否应显示
参数：tracks
logical indicating whether consecutive locations of individual animals should be joined by a line
逻辑说明的连续位置的动物个体是否应加入行
参数：title
logical or character string for title
为标题的逻辑或字符串
参数：subtitle
logical or character string for subtitle
逻辑或字符串字幕
参数：add
logical for whether to add to existing plot
逻辑是否添加到现有的图
参数：varycol
logical for whether to distinguish individuals by colour
符合逻辑的，是否按颜色区分个人
参数：icolours
vector of individual colours (when varycol = TRUE), or colour scale (non-petal plots)
矢量种颜色（时varycol= TRUE），或颜色规模（非花瓣图）
参数：randcol
logical to use random colours (varycol = TRUE)
合理使用随机颜色（varycol= TRUE）
参数：lab1cap
logical for whether to label the first capture of each animal
逻辑是否将第一次捕捉每一个动物
参数：laboffset
distance by which to offset labels from points
从点距离，以抵消标签
参数：ncap
logical to display the number of detections per trap per occasion
显示每陷阱每一次的检测逻辑
参数：splitocc
optional occasion from which second colour is to be used
可选的场合，从该第二颜色是要使用
参数：col2
second colour (used with splitocc)
第二个颜色（使用splitocc）
参数：type
character string ("petal", "n.per.detector" or "n.per.cluster")
字符串（“花瓣”中，“n.per.detector”或“n.per.cluster”）
参数：cappar
list of named graphical parameters for detections (passed to par)
名为图形参数检测（传递到par）
参数：trkpar
list of named graphical parameters for tracks (passed to par)
名为图形参数的曲目（传递到par）
参数：labpar
list of named graphical parameters for labels (passed to par)
名为图形参数的标签（传递到par）
参数：...
arguments to be passed to lines if tracks are plotted
参数被传递到lines如果轨迹绘制
Details
详细信息----------Details----------
By default, a "petal" plot is generated in the style of Density (Efford 2007) using eqscplot from the MASS library. If type = "n.per.detector" or type = "n.per.cluster" the result is a colour-coded plot of the number of individuals at each unit, pooled over occasions.
默认情况下，“花瓣”的图中生成密度的风格（Efford 2007）eqscplotMASS库。如果type = "n.per.detector"或type = "n.per.cluster"的结果是个人在每个单元的数量超过场合，汇集颜色编码的图。
If title = FALSE no title is displayed; if title = TRUE, the session identifer is used for the title.
如果title= FALSE不显示标题，如果title= TRUE，会话标识符作为标题。
If subtitle = FALSE no subtitle is displayed; if subtitle = TRUE, the subtitle gives the numbers of occasions, detections and individuals.
如果subtitle = FALSE没有字幕显示;如果subtitle= TRUE，字幕的情况下，检测和个人提供的数字。
If x is a multi-session capthist object then a separate plot is produced for each session. Use par(mfrow = c(nr, nc)) to allow a grid of plots to be displayed simultaneously (nr rows x nc columns).
如果x是一个的多届capthist对象，然后一个单独的图为每个会话。使用par(mfrow = c(nr, nc))允许同时显示的网格图（NR行x的NC列）。
These arguments are used only for petal plots: rad, tracks, varycol, randcol, lab1cap, laboffset, ncap, splitocc, col2, trkpar, and labpar.
这些参数仅用于花瓣图：rad，tracks，varycol，randcol，lab1cap，laboffset，ncap splitocc，col2，trkpar和labpar。
If icolours = NULL and varycol = TRUE then a vector of colours is generated automatically as terrain.colors((nrow(x)+1) * 1.5). If there are too few values in icolours for the number of individuals then colours will be re-used.
如果icolours = NULL和varycol = TRUE的颜色，矢量自动生成terrain.colors（（NROW（X）+1）* 1.5）。如果有中的值太少icolours的个体数量的颜色将被重新使用。
值----------Value----------
For type = "petal", the number of detections in x. For type = "n.per.detector" or type = "n.per.cluster", a dataframe with data for a legend (see Examples).
对于type = "petal"，在x的检测次数。对于type = "n.per.detector"或type = "n.per.cluster"，一个数据框，一个传奇的数据（见例）。
参考文献----------References----------
explicit capture–recapture. Department of Zoology, University of Otago, Dunedin, New Zealand. http://www.otago.ac.nz/density
参见----------See Also----------
capthist
capthist
实例----------Examples----------
demotrap <- make.grid()
tempcapt <- sim.capthist(demotrap,
popn = list(D = 5, buffer = 50),
detectpar = list(g0 = 0.15, sigma = 30))
plot(tempcapt, border = 10, rad = 3, tracks = TRUE,
lab1cap = TRUE, laboffset = 2.5)
## type = n.per.cluster[＃类型n.per.cluster]
## generate some captures[＃产生一些捕获。]
testregion <- data.frame(x = c(0,2000,2000,0),
y = c(0,0,2000,2000))
popn <- sim.popn (D = 10, core = testregion, buffer = 0,
model2D = "hills", details = list(hills = c(-2,3)))
t1 <- make.grid(nx = 1, ny = 1)
t1.100 <- make.systematic (cluster = t1, spacing = 100,
region = testregion)
capt <- sim.capthist(t1.100, popn = popn, noccasions = 1)
## now plot captures ...[＃图捕获...]
temp <- plot(capt, title = "Individuals per cluster",
type = "n.per.cluster", hidetraps = FALSE,
gridlines = FALSE, cappar = list(cex = 1.5))
## Not run: [＃不运行：]
## add legend; click on map to place top left corner[，＃添加传说;点击图左上角放置]
legend (locator(1), pch = 21, pt.bg = temp$colour,
pt.cex = 1.3, legend = temp$legend, cex = 0.8)
## End(Not run)[＃（不执行）]
## Not run: [＃不运行：]
## try varying individual colours - requires RColorBrewer[＃尝试不同的个人色彩 - RColorBrewer]
require(RColorBrewer)
plot(infraCH[[2]], icolours = brewer.pal(12, 'Set3'), tracks = T,
bg = 'black', cappar = list(cex = 2), border = 10, rad = 2,
gridlines=F)
## End(Not run)[＃（不执行）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-30 00:00:43
