make_lights and geom_lights fail with reversed light cycle

[matiasandina]

This

fed_df %>% 
  recalculate_pellets() %>% 
  ggplot(aes(Pi_Time, pellets)) + 
  geom_lights(lights_off_hour = 7, lights_on_hour = 19)+
  geom_step() +
  scale_x_datetime(breaks = dt_breaks , date_labels = "%d\n%H")

and

fed_df %>% 
  recalculate_pellets() %>% 
  ggplot(aes(Pi_Time, pellets)) + 
  geom_lights(lights_off_hour = 7, lights_on_hour = 19)+
  geom_step() +
  scale_x_datetime(breaks = dt_breaks , date_labels = "%d\n%H")

produce the same plot

When they should produce opposite shading patterns. I'm not sure whether the error is in the calculation itself or in the way ggplot treats geom_rect() internals.

[matiasandina]

Related, if there is only one day in the recording, geom_lights() is not made to go to -Inf or Inf. It ends up going from min(lights_on, lights_off) to max(lights_on, lights_off)

[matiasandina]

library(tidyverse)
library(fed3)
theme_set(theme(text = element_text(size = 16)))
fw_files <- list.files("/home/matias/Experiments/pilots/long_term/MLA127/FED_data/fedwatcher/2023/08/", 
                       recursive = T,
                       full.names = T)
fw_df <- map(fw_files, function(tt) read_fed(tt, lib_version = "fw")) %>%
  bind_rows()
#> Warning: One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)

min_dt <- min(fw_df$Pi_Time)

# Normal cycle
fw_df %>% 
  filter(lubridate::day(Pi_Time) < 8) %>% 
  recalculate_pellets() %>% 
  ggplot(aes(Pi_Time, pellets)) +
  geom_lights() +
  geom_step() +
  scale_x_datetime(breaks = "6 hours", date_labels = "%H")

# Fake reversed cycle
fw_df %>% 
  filter(lubridate::day(Pi_Time) < 8) %>% 
  recalculate_pellets() %>% 
  ggplot(aes(Pi_Time, pellets)) +
  geom_lights(lights_off_hour = 7, lights_on_hour = 19) +
  geom_step() +
  scale_x_datetime(breaks = "6 hours", date_labels = "%H")

# Less than a day
fw_df %>% 
  filter(lubridate::day(Pi_Time) == 8) %>% 
  recalculate_pellets() %>% 
  ggplot(aes(Pi_Time, pellets)) +
  geom_lights(lights_off_hour = 19, lights_on_hour = 7) +
  geom_step() +
  scale_x_datetime(breaks = "6 hours", date_labels = "%H")

^{Created on 2023-08-11 with reprex v2.0.2}