R 蜂巢图中的自边误差
即使没有自边缘,也绝对无法找出错误产生的原因。R 蜂巢图中的自边误差,r,networking,plot,hive,R,Networking,Plot,Hive,即使没有自边缘,也绝对无法找出错误产生的原因。 下面是一个可复制的代码。任何帮助都会很好 library(HiveR) nodes = data.frame(id = 1:9, lab = c("A","B","C","E","F","G","H","I","J"), axis = c(1,1,1,2,3,2,2,2,3), radius = rep(50,9),size = rep(10,9), color = c("yellow","yellow","yellow", "green",
下面是一个可复制的代码。任何帮助都会很好
library(HiveR)
nodes = data.frame(id = 1:9, lab = c("A","B","C","E","F","G","H","I","J"),
axis = c(1,1,1,2,3,2,2,2,3), radius = rep(50,9),size = rep(10,9),
color = c("yellow","yellow","yellow", "green","red","green","green","green","red"))
edges = data.frame(id1 = c(1,2,3,4,5,4,1,9,8,6,1),id2 = c(2,3,4,1,9,9,9,8,7,7,6),
weight = rep(1,11),
color = c(rep("green",7), rep("red",4)))
test3 <- ranHiveData(nx = 3)
test3$nodes = nodes
test3$edges = edges
test3$edges$color <- as.character(test3$edges$color)
test3$edges$id1 <- as.integer(test3$edges$id1)
test3$edges$id2 <- as.integer(test3$edges$id2)
test3$nodes$color <- as.character(test3$nodes$color)
test3$nodes$lab <- as.character(test3$nodes$lab)
test3$nodes$axis = as.integer(test3$nodes$axis)
test3$nodes$id = as.integer(test3$nodes$id)
test3$nodes$radius = as.numeric(test3$nodes$radius)
test3$nodes$size = as.numeric(test3$nodes$size)
test3$edges$weight = as.numeric(test3$edges$weight)
test3$desc = "3 axes --9 nodes -- 11 edges"
sumHPD(test3, chk.sm.pt = TRUE)
库(HiveR)
节点=数据帧(id=1:9,lab=c(“A”、“B”、“c”、“E”、“F”、“G”、“H”、“I”、“J”),
轴=c(1,1,1,2,3,2,2,3),半径=rep(50,9),尺寸=rep(10,9),
颜色=c(“黄色”、“黄色”、“黄色”、“绿色”、“红色”、“绿色”、“绿色”、“绿色”、“红色”))
边=数据帧(id1=c(1,2,3,4,5,4,1,9,8,6,1),id2=c(2,3,4,1,9,9,9,8,7,6),
重量=代表(1,11),
颜色=c(代表(“绿色”,7),代表(“红色”,4)))
test3在代码中,轴节点的位置(半径
)都设置为50
因此存在重叠点(轴1上有3个,轴2上有4个,轴3上有2个)。
正确定义半径
可以解决此问题。
library(HiveR)
# radius has been changed !
nodes = data.frame(id = 1:9, lab = c("A","B","C","E","F","G","H","I","J"),
axis = c(1,1,1,2,3,2,2,2,3), radius = c(1,2,3,1,1,2,3,4,2),size = rep(1,9),
color = c("yellow","yellow","yellow", "green","red","green","green","green","red"))
edges = data.frame(id1 = c(1,2,3,4,5,4,1,9,8,6,1),id2 = c(2,3,4,1,9,9,9,8,7,7,6),
weight = rep(1,11),
color = c(rep("green",7), rep("red",4)))
test3 <- ranHiveData(nx = 3)
test3$nodes = nodes
test3$edges = edges
test3$edges$color <- as.character(test3$edges$color)
test3$edges$id1 <- as.integer(test3$edges$id1)
test3$edges$id2 <- as.integer(test3$edges$id2)
test3$nodes$color <- as.character(test3$nodes$color)
test3$nodes$lab <- as.character(test3$nodes$lab)
test3$nodes$axis = as.integer(test3$nodes$axis)
test3$nodes$id = as.integer(test3$nodes$id)
test3$nodes$radius = as.numeric(test3$nodes$radius)
test3$nodes$size = as.numeric(test3$nodes$size)
test3$edges$weight = as.numeric(test3$edges$weight)
test3$desc = "3 axes --9 nodes -- 11 edges"
sumHPD(test3, chk.sm.pt = TRUE)
plotHive(test3)
库(HiveR)
#半径已更改!
节点=数据帧(id=1:9,lab=c(“A”、“B”、“c”、“E”、“F”、“G”、“H”、“I”、“J”),
轴=c(1,1,1,2,3,2,2,3),半径=c(1,2,3,1,1,2,3,4,2),尺寸=rep(1,9),
颜色=c(“黄色”、“黄色”、“黄色”、“绿色”、“红色”、“绿色”、“绿色”、“绿色”、“红色”))
边=数据帧(id1=c(1,2,3,4,5,4,1,9,8,6,1),id2=c(2,3,4,1,9,9,9,8,7,6),
重量=代表(1,11),
颜色=c(代表(“绿色”,7),代表(“红色”,4)))
测试3