original_codes/original_daily_acticity_wrap_plot.R

In nasserdr/digyRhythm: Analyzing Animal's Rhythmicity

#libraries
library(ggplot2)
library(magrittr)
library(lubridate)
library(dplyr)

#Example
data("df516b_2")
df <- df516b_2
activity <- names(df)[2]
activity_alias <- 'Motion Index'
start <- "2020-05-01" #year-month-day
end <- "2020-08-13" #year-month-day
save <- 'sample_results/daily_activity_wrap' #if NULL, don't save the image
ncols <- 3
sampling_rate <- 15



#Function starts here
start <- lubridate::date(start)
end <- lubridate::date(end)

df$date <- lubridate::date(df$datetime)
data_to_plot <- df %>% filter(date >= start) %>% filter(date <= end)

data_to_plot$time <- format(data_to_plot$datetime, format = "%H:%M", tz = "CET")



# days <- unique(data_to_plot$date)
# l <- ceiling(length(days)/ncols)

# batch1 <- data_to_plot %>% filter(data_to_plot$date <= days[l])
# batch2 <- data_to_plot %>% filter(data_to_plot$date > days[l])

time2 = rep(1:(24*60/sampling_rate), length(unique(data_to_plot$date)))
data_to_plot$time2 <- time2[1:dim(data_to_plot)[1]]

avg_plot <- ggplot(data_to_plot, aes(
  x = time2,
  y = !!as.name(activity)))+
  geom_area() +
  facet_wrap(~date, ncol = ncols) +
  ggtitle(paste(activity_alias, "(", data_to_plot$date[1], "-", last(data_to_plot$date),")")) +
  xlab("Time") +
  theme(
    axis.text = element_text(color = 'black'),
    panel.background = element_rect(fill = "white"),
    legend.key = element_rect(fill = "white"),
    legend.key.width= unit(0.5, "cm"),
    legend.justification="left",
    legend.key.size = unit(7, "pt"),
    strip.background = element_blank(),
    strip.text.x = element_blank(),
    axis.title.y=element_blank(),
    axis.text.y=element_blank(),
    axis.ticks.y=element_blank(),
    axis.line=element_blank(),
    plot.title = element_text(hjust = 0.5),
    legend.position=c(0.05,0.89)) +
  scale_x_continuous(
    breaks = seq(sampling_rate - 2, 24*60/sampling_rate - sampling_rate+4, length.out = 4),
    labels = c("03:00", "09:00", "15:00", "21:00")
  )


print(avg_plot)