Loading Packages
packages = c('scales', 'viridis', 'rmarkdown',
'lubridate', 'ggthemes',
'gridExtra', 'tidyverse', 'gganimate',
'readxl', 'knitr', 'patchwork',
'data.table', 'ViSiElse')
for (p in packages){
if(!require(p, character.only = T)){
install.packages(p)
}
library(p,character.only = T)
}
Select 2 Participants
all_fs <- list.files('./data/Activity_Logs/')
selected_ids <- c(0, 1)
df <- data.frame()
for (f in all_fs) {
tmp <- read_csv(paste0('./data/Activity_Logs/', f)) %>%
filter(participantId %in% selected_ids)
df <- rbind(df, tmp)
}
rm(tmp)
write_csv(df, './data/01behaviors.csv')
Load Data
df <- read_csv('./data/01behaviors.csv')
df$date <- date(df$timestamp)
paged_table(df)
timestamp <dttm> | currentLocation <chr> | |
|---|---|---|
| 2022-03-01 00:00:00 | POINT (-2724.6277665310454 6866.2081834436985) | |
| 2022-03-01 00:00:00 | POINT (-1526.9372331431534 5582.2951345645315) | |
| 2022-03-01 00:05:00 | POINT (-2724.6277665310454 6866.2081834436985) | |
| 2022-03-01 00:05:00 | POINT (-1526.9372331431534 5582.2951345645315) | |
| 2022-03-01 00:10:00 | POINT (-2724.6277665310454 6866.2081834436985) | |
| 2022-03-01 00:10:00 | POINT (-1526.9372331431534 5582.2951345645315) | |
| 2022-03-01 00:15:00 | POINT (-2724.6277665310454 6866.2081834436985) | |
| 2022-03-01 00:15:00 | POINT (-1526.9372331431534 5582.2951345645315) | |
| 2022-03-01 00:20:00 | POINT (-2724.6277665310454 6866.2081834436985) | |
| 2022-03-01 00:20:00 | POINT (-1526.9372331431534 5582.2951345645315) |
Daily Life Pattern
VisiElse cannot work as expected, so changing ggplot2 to
reveal the daily life patterns of participants 0 and 1.
display_dt = "2022-03-01"
one_day_behavior <- df %>%
filter(date == display_dt)
one_day_behavior$end_timestamp <- one_day_behavior$timestamp + minutes(5)
p1 <- ggplot()+
geom_segment(data=one_day_behavior,
mapping=aes(x=timestamp, xend=end_timestamp,
y=currentMode, yend = currentMode, color= currentMode),
size=6) +
facet_grid(.~participantId~.) +
theme(legend.position = 'right',
legend.title=element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
text = element_text(size=10)) +
labs(title="Daily Routines of Two Selected Participant (0 vs 1)",
subtitle=display_dt)
p2 <- ggplot()+
geom_segment(data=one_day_behavior,
mapping=aes(x=timestamp, xend=end_timestamp,
y=hungerStatus, yend = hungerStatus, color= hungerStatus),
size=6) +
facet_grid(.~participantId~.) +
theme(legend.position = 'right',
legend.title=element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
text = element_text(size=10))
p3 <- ggplot(data=one_day_behavior)+
geom_segment(mapping=aes(x=timestamp, xend=end_timestamp,
y=sleepStatus, yend = sleepStatus, color= sleepStatus),
size=6) +
facet_grid(.~participantId~.) +
theme(legend.position = 'right',
legend.title=element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
text = element_text(size=10))
p1/p2/p3
Heatmap for Each Status
Using heatmap to find the differences between these 2 participants.
wkday_levels <- c('Saturday', 'Friday', 'Thursday', 'Wednesday',
'Tuesday', 'Monday', 'Sunday')
df$weekday <- weekdays(df$timestamp)
df$hour <- hour(df$timestamp)
atHome_df1 <- df %>%
filter(currentMode == "AtHome" & participantId == 1) %>%
count(participantId, weekday, hour) %>%
ungroup() %>%
na.omit()
ref1 <- crossing(wkday_levels, 0:23) %>%
rename(weekday = wkday_levels, hour=`0:23`) %>%
merge(atHome_df1[,-1], by=c('weekday', 'hour'), all.x = TRUE) %>%
mutate(n = coalesce(n, 0), participantId=1)
atHome_df0 <- df %>%
filter(currentMode == "AtHome" & participantId == 0) %>%
count(participantId, weekday, hour) %>%
ungroup() %>%
na.omit()
ref0 <- crossing(wkday_levels, 0:23) %>%
rename(weekday = wkday_levels, hour=`0:23`) %>%
merge(atHome_df0[,-1], by=c('weekday', 'hour'), all.x = TRUE) %>%
mutate(n = coalesce(n, 0), participantId=0)
ref <- rbind(ref0, ref1)
ref <- ref %>%
mutate(weekday = factor(weekday, levels = wkday_levels),
hour = factor(hour, levels = 0:23))
ggplot(ref,
aes(hour,
weekday,
fill = n)) +
geom_tile(color = "white",
size = 0.1) +
theme_tufte(base_family = "Helvetica") + # remove the boundary
facet_wrap(~participantId, nrow = 2) +
coord_equal() +
scale_fill_gradient(name = "Freq. of AtHome",
low = "sky blue",
high = "dark blue") +
labs(x = NULL,
y = NULL,
title = "AtHome Patterns of the partipants (0 vs 1)") +
theme(axis.ticks = element_blank(),
plot.title = element_text(hjust = 0.5),
legend.title = element_text(size = 8),
legend.text = element_text(size = 6) )
Similarly, we can draw the heatmap for hungerStatus and sleepStatus
