Absolutely cannot figure out why the error is coming even though there are no self edges.
Below is a reproducible code. Any help would be great
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$desc = "3 axes --9 nodes -- 11 edges"
sumHPD(test3, chk.sm.pt = TRUE)
The code is giving self edges and the the plot is not rendering plotHive(test3) showing
Error in calcCurveGrob(x,x$debug) : end points must not be identical
In your code the position of the nodes of the axis (radius) are all set to 50. Hence there are overlapping points (3 on axis 1, 4 on axes 2 and 2 on axis 3).
A correct definition of radius solves the problem.
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$desc = "3 axes --9 nodes -- 11 edges"
sumHPD(test3, chk.sm.pt = TRUE)
plotHive(test3)
Related
I am generating a landscape pattern that evolves over time. The problem with the code is that I have clearly defined a window for the object bringing up the error but the window is not being recognised. I also do not see how any points are falling outside of the window, or how that would make a difference.
library(spatstat)
library(dplyr)
# Define the window
win <- owin(c(0, 100), c(0, 100))
# Define the point cluster
cluster1 <- rMatClust(kappa = 0.0005, scale = 0.1, mu = 20,
win = win, center = c(5,5))
# define the spread of the points
spread_rate <- 1
new_nests_per_year<-5
years<-10
# Plot the initial cluster
plot(win, main = "Initial cluster")
points(cluster1, pch = 20, col = "red")
newpoints<-list()
# Loop for n years
for (i in 1:years) {
# Generate new points that spread from the cluster
newpoints[[1]] <-rnorm(new_nests_per_year, mean = centroid.owin(cluster1)$y, sd = spread_rate)
newpoints[[2]] <-rnorm(new_nests_per_year, mean = centroid.owin(cluster1)$x, sd = spread_rate)
# Convert the list to a data frame
newpoints_df <- data.frame(newpoints)
# Rename the columns of the data frame
colnames(newpoints_df) <- c("x", "y")
# Combine the new points with the existing points
cluster1_df <- data.frame(cluster1)
newtotaldf<-bind_rows(cluster1_df,newpoints_df)
cluster1<-as.ppp(newtotaldf, x = newtotaldf$x, y = newtotaldf$y,
window = win)
# Plot the updated cluster
plot(win, main = paste("Cluster after year", i))
points(cluster1, pch = 20, col = "red")
}
However, when I run line:
cluster1<-as.ppp(newtotaldf, x = newtotaldf$x, y = newtotaldf$y,
window = win)
I recieve the error:
Error: x,y coords given but no window specified
Why would this be the case?
In your code, if you use the command W = win it should solve the issue. I also believe you can simplify the command without specifying x and y:
## ...[previous code]...
cluster1 <- as.ppp(newtotaldf, W = win)
plot(win)
points(cluster1, pch = 20, col = "red")
I want to make a 2 box plots with y being weight and x being the before and after. so two different boxplot will be displayed at the same time.
`rats_before = data.frame(
rat_num = paste0(rep("rat number",200),1:200),
weight = rweibull(200,shape= 10,scale = 20))
rats_after = data.frame(
rat_num = paste0(rep("rat number",200),1:200),
weight = rweibull(200,shape= 9,scale = 21))
rats = merge(rats_before,rats_after, by = c("rat_num"))`
i know the next part is not even close but it will give you a idea of what im trying to do.
rat_boxplot = qplot(y = weight, x = (rats_after, rats_before), geom = "boxplot", data = rats)
Or, if you want to do this in base R -
rats_before = data.frame(
rat_num = paste0(rep("rat number",200),1:200),
weight = rweibull(200,shape= 10,scale = 20))
rats_after = data.frame(
rat_num = paste0(rep("rat number",200),1:200),
weight = rweibull(200,shape= 9,scale = 21))
rats <- rbind(rats_before, rats_after)
rats$type <- c(rep("before", nrow(rats_before)), rep("after", nrow(rats_after)))
rats$type <- factor(rats$type)
rats$type <- relevel(rats$type, ref = 2)
boxplot(weight ~ type, data = rats)
You can add a column to each df ans userbind which will bind the rows of the two df instead of merge you can use. Then you simply have to use the aes of a ggplot.
rats_before$condition = "before"
rats_after$condition = "after"
rats = rbind(rats_before,rats_after)
ggplot(rats)+geom_boxplot(aes(condition,weight))
Hope I understood your question.
Tom
I'm plotting decision trees built with partykit in ggparty, and struggling to rotate the tree branches around branch nodes- as in, change the order they are displayed. I'm hoping to plot a tree with the branches displayed in an order according to the values of the terminal nodes. This would be somewhat comparable to using reorder() in a standard ggplot geom.
For instance, outlined below using the WeatherPlay data from the ggparty vignette, can the branches of this tree be rotated so that terminal node geom_bar() plots are displayed in increasing order of proportion "yes"? In this case, this would mean "sunny", then "rainy", then "overcast".
For my project I'll have terminal nodes with boxplots, but I'm guessing that the method for rotating branches is modular and can be repurposed.
## Playing with default WeatherPlay data as demonstrated in ggparty examples here:
# https://cran.r-project.org/web/packages/ggparty/vignettes/ggparty-graphic-partying.html
library(partykit)
library(ggparty)
data("WeatherPlay", package = "partykit")
sp_o <- partysplit(1L, index = 1:3)
sp_h <- partysplit(3L, breaks = 75)
sp_w <- partysplit(4L, index = 1:2)
pn <- partynode(1L, split = sp_o, kids = list(
partynode(2L, split = sp_h, kids = list(
partynode(3L, info = "yes"),
partynode(4L, info = "no"))),
partynode(5L, info = "yes"),
partynode(6L, split = sp_w, kids = list(
partynode(7L, info = "yes"),
partynode(8L, info = "no")))))
py <- party(pn, WeatherPlay)
# Node plots
n1 <- partynode(id = 1L, split = sp_o, kids = lapply(2L:4L, partynode))
t2 <- party(n1,
data = WeatherPlay,
fitted = data.frame(
"(fitted)" = fitted_node(n1, data = WeatherPlay),
"(response)" = WeatherPlay$play,
check.names = FALSE),
terms = terms(play ~ ., data = WeatherPlay)
)
t2 <- as.constparty(t2)
# Plot tree
ggparty(t2) +
geom_edge() +
geom_edge_label() +
geom_node_splitvar() +
geom_node_plot(gglist = list(geom_bar(aes(x = "", fill = play),
position = position_fill()),
xlab("play")),
# draw only one label for each axis
shared_axis_labels = TRUE,
# draw line between tree and legend
legend_separator = TRUE
)
In the following igraph there are dates to be plotted as marks on the x-axis. Below I provided an example. As the dates are specified in the label matrix they are formatted into an atomic value. How do I get the dates on the x-axis to be displayed in a regular date format?
library(igraph)
nodes=data.frame(
c(0,1,2,3),
c("A","B","C","D")
)
colnames(nodes) = c("id","name")
links = data.frame(
c(0,0,1,2),
c(1,2,3,3)
)
colnames(links) = c("from","to")
layout = matrix(
c(as.Date('2010-01-01'),1, as.Date('2010-01-02'),1, as.Date('2010-01-02'),2, as.Date('2010-01-06'),1), byrow = TRUE, nrow=4
)
net = graph.data.frame(links, vertices = nodes)
plot.igraph(
net, xaxt="n",layout=layout,axes=TRUE,asp=0, rescale=FALSE,xlim=c(as.Date('2010-01-01'),as.Date('2010-01-06')),ylim=c(1,2)
)
You can replace the axis by your own values as explained here.
Using your code, it gives:
layout <- data.frame(Date = as.Date(c('2010-01-01','2010-01-02','2010-01-02','2010-01-06')), value = c(1,2,1,1))
plot.igraph(
net,
layout = layout,
rescale = FALSE,
axis = FALSE,
asp = 0,
xlim = as.Date(c('2010-01-01', '2010-01-06')),
ylim = c(1,2)
)
axis(1, at = as.numeric(layout$Date), labels = layout$Date, cex.axis = 0.9)
axis(2, at = 1:max(layout$value), labels = 1:max(layout$value))
I created a Sankey diagram using the plotly package.
Please look at below example. I tried to make five streams, 1_6_7, 2_6_7, and so on. But two of five links between 6 and 7 disappeared. As far as I see, plotly allows to make only three or less links between two nodes.
Can I remove this restrictions ? Any help would be greatly appreciated.
Here is an example code and the outputs:
d <- expand.grid(1:5, 6, 7)
node_label <- 1:max(d)
node_colour <- scales::alpha(RColorBrewer::brewer.pal(7, "Set2"), 0.8)
link_source_nodeind <- c(d[,1], d[,2]) - 1
link_target_nodeind <- c(d[,2], d[,3]) - 1
link_value <- rep(100, nrow(d) * 2)
link_label <- rep(paste(d[,1], d[,2], d[,3], sep = "_"), 2)
link_colour <- rep(scales::alpha(RColorBrewer::brewer.pal(5, "Set2"), 0.2), 2)
p <- plotly::plot_ly(type = "sankey",
domain = c(x = c(0,1), y = c(0,1)),
orientation = "h",
node = list(label = node_label,
color = node_colour),
link = list(source = link_source_nodeind,
target = link_target_nodeind,
value = link_value,
label = link_label,
color = link_colour))
p