Modifying objects in loops in R, and other speed pitfalls

speed.r

# =============================================
# Modifying a data frame in place
# =============================================

library(ggplot2)
str(diamonds)

# Modify data frame in place, in loop
# This is super, super slow
system.time({
  d <- diamonds
  for (i in 1:length(d$carat)) d$carat[i] <- i
})

# Modify separate vector in loop, then assign back into data frame
system.time({
  d <- diamonds
  carat <- d$carat
  for (i in 1:length(carat)) carat[i] <- i

  d$carat <- carat
})

# Modify separate, growing vector in loop, then assign back into data frame
system.time({
  d <- diamonds
  carat <- numeric()
  for (i in 1:nrow(d)) carat[i] <- i

  d$carat <- carat
})

# Use within() to modify data frame
system.time({
  d <- within(diamonds, {
    for (i in 1:length(carat)) carat[i] <- i
  })
})

# Converting data frame to list and doing assignment is much faster
system.time({
  d <- as.list(diamonds)
  for (i in 1:length(d$carat)) d$carat[i] <- i
  d <- as.data.frame(d)
})

# Vectorized assignment
system.time({
  d <- diamonds
  d$carat <- 1:length(d$carat)
})


# =============================================
# For loops, lapply, and vapply
# =============================================

# Grow a vector in place with a for loop
system.time({
  v <- numeric()
  for (i in 1:1e5) v[i] <- i*2
})

# lapply (returns list - need to convert to atomic vector)
system.time({
  v <- lapply(1:1e5, function(x) x*2)
  v <- unlist(v)
})



# Modify pre-allocated vector in place with a for loop
# Note this is 10x larger than previous examples
system.time({
  v <- numeric(1e6)
  for (i in 1:1e6) v[i] <- i*2
})

# lapply (returns list - need to convert to atomic vector)
system.time({
  v <- lapply(1:1e6, function(x) x*2)
  v <- unlist(v)
})

# vapply (returns atomic vector)
system.time({
  v <- vapply(1:1e6, function(x) x*2, FUN.VALUE = numeric(1))
})

# vectorized computation
system.time({
  v <- (1:1e6) * 2
})


# =============================================
# Modifying lists in place
# =============================================

# Grow a list in place with a for loop
system.time({
  v <- list()
  for (i in 1:1e5) v[[i]] <- i*2
})

# lapply
system.time({
  v <- lapply(1:1e5, function(x) x*2)
})


# Modify pre-allocated list in place with a for loop
system.time({
  v <- as.list(numeric(1e5))
  for (i in 1:1e5) v[[i]] <- i*2
})

# Modify pre-allocated vector in place with a for loop
system.time({
  v <- numeric(1e5)
  for (i in 1:1e5) v[[i]] <- i*2
})