I like dplyr's "progress_estimated" function but I can't figure out how to get a progress bar to work inside a dplyr chain. I've put a reproducible example with code at the bottom here.
I have a pretty big data.frame like this:
cdatetime latitude longitude
1 2013-01-11 06:40:00 CST 49.74697 -93.30951
2 2013-01-12 15:55:00 CST 49.74697 -93.30951
3 2013-01-07 20:30:00 CST 49.74697 -93.30951
and I'd like to calculate sunrise times for each date, using the libraries
library(dplyr)
library(StreamMetabolism)
I can get dplyr's progress_estimated bar to work within a loop, e.g.:
Ugly loop (works)
p <- progress_estimated(nrow(test))
for (i in 1:nrow(test)){
p$tick()$print()
datetime = as.POSIXct(substr(test$cdatetime[i], 1, 20), tz = "CST6CDT")
test$sunrise[i] <- sunrise.set(test$latitude[i], test$longitude[i], datetime, "CST6CDT", num.days = 1)[1,1]
}
but how can I nest it in my function, so I can avoid using a loop?
Prefer to use:
SunriseSet <- function(dataframe, timezone){
dataframe %>%
rowwise() %>%
mutate(# calculate the date-time using the correct timezone
datetime = as.POSIXct(substr(cdatetime, 1, 20), tz = timezone),
# Get the time of sunrise and sunset on this day, at the county midpoint
sunrise = sunrise.set(latitude, longitude, datetime, timezone, num.days = 1)[1,1])
}
How to get a progress bar here?
test2 <- SunriseSet(test, "CST6CDT")
Here's some example data:
test <- data.frame(cdatetime = rep("2013-01-11 06:40:00", 300),
latitude = seq(49.74697, 50.04695, 0.001),
longitude = seq(-93.30951, -93.27960, 0.0001))
Rather than using rowwise()
, perhaps try pairing the map*
functions from purrr
with progress_estimated()
. This answer follows the approach from https://rud.is/b/2017/03/27/all-in-on-r%E2%81%B4-progress-bars-on-first-post/.
First, wrap your function in another function that updates the progress bar:
SunriseSet <- function(lat, long, date, timezone, num.days, .pb = NULL) {
if (.pb$i < .pb$n) .pb$tick()$print()
sunrise.set(lat, long, date, timezone, num.days)
}
Then, iterate through your inputs with pmap
, or pmap_df
(to bind the outputs into a dataframe):
library(purrr)
pb <- progress_estimated(nrow(test), 0)
test2 <- test %>%
mutate(
sunrise = pmap_df(
list(
lat = latitude,
long = longitude,
date = as.character(cdatetime)
),
SunriseSet,
timezone = "CST6CDT", num.days = 1, .pb = pb
)$sunrise
)
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