Print elapsed and remaining time in iterative processes.

Description

set_loop_timechecker returns a function that records and prints processing time in iterative processes.

Usage

set_loop_timechecker(
  n_iter,
  overwrite = TRUE,
  timestep = 0.5,
  show_timestamp = TRUE,
  verbose = TRUE
)

Arguments

Details

Provided with the number of iterations, this function creates a function named loop_timechecker which records and prints processing time in iterative process. In actual usage, it is recommended to call this function and creating loop_timechecker right before the iteration process, and place the loop_timechecker at the end of the iteration process.

If you want to keep all printed records in your console, please set overwrite = FALSE.

The timestep argument determines the frequency of updating printed information since too fast updates will decrease visibility.

Value

A function loop_timechecker. When placed at the end of the iterations, it records and prints the progress of iteration, elapsed time, and predicted remaining time. You can add arbitrary strings to the printed messages by using char_pre and char_post arguments.

See Also

set_step_timechecker

Examples

iters <- 1:1000
ans <- NULL
tc <- set_loop_timechecker(length(iters))
for (i in iters) {
  ans <- c(ans, i)
  Sys.sleep(0.002)
  tc()
}

# For multiple loops, overwrite and char_pre arguments can be used for readability
iters1 <- 1:3
iters2 <- 1:100
ans <- NULL
tc1 <- set_loop_timechecker(length(iters1), overwrite = FALSE)
for (i in iters1) {
  tc2 <- set_loop_timechecker(length(iters2))
  for (j in iters2) {
    ans <- c(ans, i * j)
    Sys.sleep(0.004)
    tc2(char_pre = '-- ')
  }
  tc1()
}

# char_pre or char_post can also be used to check name of current process
iters <- paste0('case', LETTERS[1:10])
tc <- set_loop_timechecker(length(iters))
for (i in iters) {
  Sys.sleep(1)
  tc(char_post = paste0('  Processing ', i))
}

Print elapsed and remaining time in each code block.

Description

set_step_timechecker returns a function that records and prints processing time in each code block.

Usage

set_step_timechecker(
  char_pre = "",
  char_post = "",
  show_timestamp = TRUE,
  verbose = TRUE
)

Arguments

Details

This function creates a function named step_timechecker which records and prints processing time in code blocks. The created function step_timechecker should be placed at the head of each code block with its name. Also, this function should be placed at the end of all steps with no argument.

Value

A function step_timechecker. When placed at the head of each code block, it records and prints the progress and elapsed time. An argument step_name, a string representing the name of the steps, should be provided. Otherwise, the function judges that it is the end of the measurement. An argument print_done can also be used if you do not wish to add message when the process of the step ends.

See Also

set_loop_timechecker

Examples

f <- function() {

  tc <- set_step_timechecker()

  tc('Simulation')
  df <- data.frame(x = 1:10, y = 1:10 + rnorm(10))
  Sys.sleep(2)

  tc('Data augumentation')
  df$x2 <- df$x ^ 2
  df$x3 <- df$x ^ 3
  Sys.sleep(3)

  tc('Regression')
  lmres <- lm(y ~ ., df)
  Sys.sleep(4)

  tc()
  coef(lmres)

}
ans <- f()

# when you place set_loop_timechecker in a loop,
# argument char_pre can be used for readability
tcl <- set_loop_timechecker(3, overwrite = FALSE)
for (i in 1:3) {

  tc <- set_step_timechecker(char_pre = '  ')

  tc('Simulation')
  df <- data.frame(x = 1:10, y = 1:10 + rnorm(10))
  Sys.sleep(2)

  tc('Data augumentation')
  df$x2 <- df$x ^ 2
  df$x3 <- df$x ^ 3
  Sys.sleep(3)

  tc('Regression')
  lmres <- lm(y ~ ., df)
  Sys.sleep(4)

  tc()
  tcl()

}

# when you place set_loop_timechecker inside a step in set_step_timechecker,
# argument print_done can be used for readability
f2 <- function() {

  tc <- set_step_timechecker()

  tc('Simulation')
  n <- 10
  df <- data.frame(x = 1:n, y = 1:n + rnorm(10))
  Sys.sleep(2)

  tc('Data augumentation', print_done = FALSE)
  tcl <- set_loop_timechecker(n)
  for (i in seq_len(n)) {
    df$x2[i] <- df$x[i] ^ 2
    df$x3[i] <- df$x[i] ^ 3
    Sys.sleep(0.2)
    tcl(char_pre = '- ')
  }

  tc('Regression')
  lmres <- lm(y ~ ., df)
  Sys.sleep(4)

  tc()
  coef(lmres)

}
ans <- f2()