Plotly: add_trace in a loop

19

votes

I'm trying to add_trace ad each loop, but I get only one plot with multiplies lines on over each other.

mean <- -0.0007200342
sd   <- 0.3403711
N=10
T=1
Delta = T/N

W = c(0,cumsum( sqrt(Delta) * rnorm(N, mean=mean, sd=sd)))
t <- seq(0,T, length=N+1)

p<-plot_ly(y=W, x=t)

for(i in 1:5){

  W <- c(0,cumsum( sqrt(Delta) * rnorm(N, mean=mean, sd=sd)))
  p<-add_trace(p, y=W)

}
print(p)

r plotggplot2plotly

My guess is a scoping issue. When defining y=W, W is first found within the environment of the plot. Directly using p<-add_trace(p, y=c(0,cumsum( sqrt(Delta) * rnorm(N, mean=mean, sd=sd)))) resolves the issue, but I imagine you are looking for a more general solution. – Axeman

Also interested in a solution here..seems to be a general plotly issue? I mean aforementioned solution works for this simple example, but not if you have big dataframes. As soon as you have soom loop variable or anything in the plotly call, it only takes the last loop variable... – MichiZH

7

votes

The plot_ly and add_trace functions have an evaluation = FALSE option that you can change to TRUE, which should fix the scope issues.

5

votes

Use evaluate = TRUE in add_trace.

2

votes

Nasty, but works:

mean <- -0.0007200342
sd   <- 0.3403711
N=10
T=1
Delta = T/N

W = c(0,cumsum( sqrt(Delta) * rnorm(N, mean=mean, sd=sd)))
t <- seq(0,T, length=N+1)


for(i in 1:5){

  W <- c(0,cumsum( sqrt(Delta) * rnorm(N, mean=mean, sd=sd)))

  assign(paste("W_",i,sep=""),W)
  assign(paste("Name_", i, sep=""), paste("Name",i,sep=""))
  if(i==1){
    pString<-"p<-plot_ly(x = t, y = W_1, name='W1')"
  } else {
    pString<-paste(pString, " %>% add_trace(x=t, y =",  eval(paste("W", i, sep="_")),", name=", eval(paste("Name", i, sep="_")), ")", sep="")
  }

}
eval(parse(text=pString))
print(p)

1

votes

I'd do this like this:

mean <- -0.0007200342
sd   <- 0.3403711
N=10
T=1
Delta = T/N

# a list with the trace Y values
Ws <- lapply(
  1:15,
  function(idx){
    c(0,cumsum( sqrt(Delta) * rnorm(N, mean=mean, sd=sd)))
  } 
)

# this could be a list with the trace X values, but is just a seq
t <- seq(0,T, length=N+1)

# a list with plotly compliant formatted objects
formattedW <- lapply(
  seq_along(Ws),
  function(idx, datasetY, datasetX){
    return(list( x = datasetX, y = datasetY[[idx]], type="scatter", mode = 'lines+markers'))
  },
  datasetX = t,
  datasetY = Ws
)

# Reduce the list of plotly compliant objs, starting with the plot_ly() value and adding the `add_trace` at the following iterations
Reduce(
  function(acc, curr){
    do.call(add_trace,c(list(p=acc),curr))
  },
  formattedW,
  init=plot_ly()
)

-3

votes

It is described here : http://www.r-graph-gallery.com/129-use-a-loop-to-add-trace-with-plotly/

save your plot in a variable, and then do add_trace :

p <- plotly(...)

p<- add_trace(p, ...)

Plotly: add_trace in a loop

5 Answers