progress_bar_test.R

library(nycflights13)
library(tidyverse)
library(stringr)
# devtools::install_github("ismayc/infer")
library(infer)
set.seed(2017)
fli_small <- flights %>% 
  na.omit() %>% 
  sample_n(size = 10000) %>% 
  mutate(half_year = case_when(
    between(month, 1, 6) ~ "h1",
    between(month, 7, 12) ~ "h2"
  )) %>% 
  mutate(day_hour = case_when(
    between(hour, 1, 12) ~ "morning",
    between(hour, 13, 24) ~ "not morning"
  )) %>% 
  select(arr_delay, dep_delay, half_year, 
         day_hour, origin, carrier)

test <- fli_small %>%
  specify(response = arr_delay) %>% # alt: arr_delay ~ NULL (or arr_delay ~ 1)
  hypothesize(null = "point", mu = 50)

# dplyr::progress_estimated way
# Suggested at https://stackoverflow.com/questions/42725428/how-to-add-progress-bar-inside-dplyr-chain-in-r
print_tick_function <- function(x, p) {
  p$tick()$print()
  data.frame(x)
}

generate_progress <- function(dataframe, ...){
  p <- progress_estimated(nrow(dataframe))
  dataframe %>% 
    rowwise() %>% 
    do(print_tick_function(., p)) %>% 
    generate(...)
}

calculate_progress <- function(dataframe, ...){
  p <- progress_estimated(nrow(dataframe))
  dataframe %>% 
    rowwise() %>% 
    do(print_tick_function(., p)) %>%   
    calculate(...)
}

# Way, way slower likely due to the rowwise and do()
fli_small %>%
  specify(response = arr_delay) %>% # alt: arr_delay ~ NULL (or arr_delay ~ 1)
  hypothesize(null = "point", mu = 50) %>% 
  generate_progress(reps = 5, type = "bootstrap") %>% 
  calculate_progress(stat = "mean") -> mean_temp

fli_small %>%
  specify(response = arr_delay) %>% # alt: arr_delay ~ NULL (or arr_delay ~ 1)
  hypothesize(null = "point", mu = 50) %>% 
  generate(reps = 5, type = "bootstrap") %>% 
  calculate(stat = "mean") -> mean_temp

# Any way to do this without converting to rowwise()?

# Seems like it will really only work with *apply() and map_* functions
# or with for() loops where you can specify how many iterations it goes over