01_Load_data.R

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# Analysis of implant data from foxes for:
# Shapiro et al.
# Potential for real-time health and welfare monitoring in experimental rabies infection in red fox (Vulpes vulpes) 
# using implants
# 
# Script 1: Loads raw data from text files from implants and performs initial data processing and formatting 
#           Includes both temperature and activity data for each fox
# 
#
# The following outputs are used for downstream analysis: 
# df_0fae2, df_0fae_act2, df_0faf2, df_0faf_act2, df_0fb1.2, df_0fb1_act2, df_0fb0.2, df_0fb0_act2
# 
# 
# Script tested for R version 4.1.2
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# Load packages ####
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# Load packages (install first if necessary)
library(tidyverse)
library(data.table)
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####################################################################################################################
# Fox 0fae -- Temperature data ####
####################################################################################################################

# Identify all the text files with temperature data (ends with slo_1.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0fae

# Identify file names
fnames_0fae <- dir("0fae", pattern = "*.slo_1.iox.txt")

# Begin reading each temperature file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0fae" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0fae <- lapply(fnames_0fae, function (x){fread(x,skip="cpu-date", fill=T)})

# Create function for intial data formatting / processing
# This function will be called for the TEMPERATURE data for each fox                                    
text.proc.temp <- function(x){x %>%
    drop_na(`sto-id`) %>%
    select(`cpu-date`, `cpu-time`, V13) %>%
    rename(date=`cpu-date`,
           time=`cpu-time`,
           Temp = V13)}

# Reset the working directory to your project directory (normally one level up)
# Apply the function
list_0fae_proc <- lapply(list_0fae, text.proc.temp)


# Concatenate lists into one data frame
df_0fae <- map(list_0fae_proc, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0fae2 <- df_0fae %>%
  drop_na() %>%
  mutate(Temp = as.numeric(Temp),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  #mutate(date_time=ymd_hms(paste0(Jour, hour, min, sec)))
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  filter(Temp >= 36) %>%
  select(date_time, date_time_min, Temp, everything()) %>%
  arrange(date_time_min)
####################################################################################################################


####################################################################################################################
# Fox 0fae - Activity data ####
####################################################################################################################
# Identify all the text files for Activity data (ends with slo_2.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0fae
fnames_0fae_act <- dir("0fae", pattern = "*.slo_2.iox.txt")

# Create a list of all the files
# READ THIS: Note, had to set working directory one level down to "0fae" folder for this to work,
# even though this should not be necessary because path is called above

# Begin reading each activity file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0fae" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0fae_act <- lapply(fnames_0fae_act, function (x){fread(x,skip="cpu-date", fill=T)})

# Create function for intial data formatting / processing
# This function will be called for the ACTIVITY data for each fox
text.proc.act <- function(x){x %>%
    drop_na(`sto-id`) %>%
    select(`cpu-date`, `cpu-time`, V13) %>%
    rename(date=`cpu-date`,
           time=`cpu-time`,
           Activity = V13)}

# Reset the working directory to your project directory (normally one level up)
# Apply the function
list_0fae_proc_act <- lapply(list_0fae_act, text.proc.act)


# Concatenate lists into one data frame
df_0fae_act <- map(list_0fae_proc_act, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0fae_act2 <- df_0fae_act %>%
  drop_na() %>%
  mutate(Activity = as.numeric(Activity),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  select(date_time, date_time_min, Activity, everything()) %>%
  arrange(date_time_min)
####################################################################################################################


####################################################################################################################
# Fox 0fb0 - Temperature data ####
####################################################################################################################

# Identify all the text files with temperature data (ends with slo_1.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0fb0

# Identify file names
fnames_0fb0 <- dir("0fb0", pattern = "*.slo_1.iox.txt")

# Begin reading each temperature file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0fb0" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0fb0 <- lapply(fnames_0fb0, function (x){fread(x,skip="cpu-date", fill=T)})

# Reset the working directory to your project directory (normally one level up)
# Apply the text.proc.temp function format 
list_0fb0_proc <- lapply(list_0fb0, text.proc.temp)

# Concatenate lists into one data frame
df_0fb0 <- map(list_0fb0_proc, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0fb0.2 <- df_0fb0 %>%
  drop_na() %>%
  mutate(Temp = as.numeric(Temp),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  #mutate(date_time=ymd_hms(paste0(Jour, hour, min, sec)))
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  select(date_time, date_time_min, Temp, everything()) %>%
  filter(Temp>35) %>%
  arrange(date_time_min)
####################################################################################################################


####################################################################################################################
# Fox 0fb0 - Activity data ####
####################################################################################################################
# Identify all the text files for Activity data (ends with slo_2.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0fb0
fnames_0fb0_act <- dir("0fb0", pattern = "*.slo_2.iox.txt")

# Begin reading each activity file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0fb0" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0fb0_act <- lapply(fnames_0fb0_act, function (x){fread(x,skip="cpu-date", fill=T)})


# Reset the working directory to your project directory (normally one level up)
# Apply the text.proc.act function to format
list_0fb0_proc_act <- lapply(list_0fb0_act, text.proc.act)


# Concatenate lists into one data frame
df_0fb0_act <- map(list_0fb0_proc_act, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0fb0_act2 <- df_0fb0_act %>%
  drop_na() %>%
  mutate(Activity = as.numeric(Activity),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  select(date_time, date_time_min, Activity, everything()) %>%
  arrange(date_time_min)
####################################################################################################################


####################################################################################################################
# Fox 0faf -- Temperature data ####
####################################################################################################################
# Identify all the text files with temperature data (ends with slo_1.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0fae

# Identify file names
fnames_0faf <- dir("0faf", pattern = "*.slo_1.iox.txt")

# Begin reading each temperature file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0faf" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0faf <- lapply(fnames_0faf, function (x){fread(x,skip="cpu-date", fill=T)})

# Reset the working directory to your project directory (normally one level up)
# Apply the function text.proc.temp to format
list_0faf_proc <- lapply(list_0faf, text.proc.temp)

# Concatenate lists into one data frame
df_0faf <- map(list_0faf_proc, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0faf2 <- df_0faf %>%
  drop_na() %>%
  mutate(Temp = as.numeric(Temp),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  #mutate(date_time=ymd_hms(paste0(Jour, hour, min, sec)))
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  filter(Temp >= 36) %>%
  select(date_time, date_time_min, Temp, everything()) %>%
  arrange(date_time_min)
####################################################################################################################


####################################################################################################################
# Fox 0faf - Activity data ####
####################################################################################################################
# Identify all the text files for Activity data (ends with slo_2.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0faf
fnames_0faf_act <- dir("0faf", pattern = "*.slo_2.iox.txt")

# Begin reading each activity file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0faf" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0faf_act <- lapply(fnames_0faf_act, function (x){fread(x,skip="cpu-date", fill=T)})

# Reset the working directory to your project directory (normally one level up)
# Apply the function text.proc.act to function
list_0faf_proc_act <- lapply(list_0faf_act, text.proc.act)

# Concatenate lists into one data frame
df_0faf_act <- map(list_0faf_proc_act, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0faf_act2 <- df_0faf_act %>%
  drop_na() %>%
  mutate(Activity = as.numeric(Activity),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  #mutate(date_time=ymd_hms(paste0(Jour, hour, min, sec)))
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  select(date_time, date_time_min, Activity, everything()) %>%
  arrange(date_time_min)
####################################################################################################################


####################################################################################################################
# Fox 0fb1 -- Temperature data ####
####################################################################################################################

# Identify all the text files with temperature data (ends with slo_1.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0fb1

# Identify file names
fnames_0fb1 <- dir("0fb1", pattern = "*.slo_1.iox.txt")

# Begin reading each temperature file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0fb1" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0fb1 <- lapply(fnames_0fb1, function (x){fread(x,skip="cpu-date", fill=T)})

# Reset the working directory to your project directory (normally one level up)
# Apply the text.proc.temp function to format
list_0fb1_proc <- lapply(list_0fb1, text.proc.temp)

# Concatenate lists into one data frame
df_0fb1 <- map(list_0fb1_proc, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0fb1.2 <- df_0fb1 %>%
  drop_na() %>%
  mutate(Temp = as.numeric(Temp),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  filter(Temp >= 36) %>%
  select(date_time, date_time_min, Temp, everything()) %>%
  arrange(date_time_min)
####################################################################################################################


####################################################################################################################
# Fox 0fb1 -- Activity data ####
####################################################################################################################

# Identify all the text files for Activity data (ends with slo_2.iox.txt)
# READ THIS : Set the working directory to one level above wherever your files are for fox 0fb1
fnames_0fb1_act <- dir("0fb1", pattern = "*.slo_2.iox.txt")

# Begin reading each activity file in the list starting at character string 'cpu-date'
# Create list of read files
# READ THIS: Note, had to set working directory one level down to "0fb1" folder for this to work,
# even though this should not be necessary because path is called above
# May vary for each user
list_0fb1_act <- lapply(fnames_0fb1_act, function (x){fread(x,skip="cpu-date", fill=T)})

# Reset the working directory to your project directory (normally one level up)
# Apply the text.proc.act function to format
list_0fb1_proc_act <- lapply(list_0fb1_act, text.proc.act)

# Concatenate lists into one data frame
df_0fb1_act <- map(list_0fb1_proc_act, as.data.table) %>% 
  rbindlist()

# Format data (type, set date-times, etc)
df_0fb1_act2 <- df_0fb1_act %>%
  drop_na() %>%
  mutate(Activity = as.numeric(Activity),
         date = mdy(date)) %>%
  separate_wider_delim(time, delim=':',names=c('hour','min','sec')) %>%
  separate_wider_delim(date, delim='-',names=c('year','month','day')) %>%
  mutate(hour = as.numeric(hour),
         min = as.numeric(min),
         sec = as.integer(sec),
         year=as.numeric(year),
         month=as.numeric(month),
         day=as.numeric(day)) %>%
  mutate(date_time = make_datetime(year,month,day, hour, min, sec)) %>%
  mutate(date_time_min = make_datetime(year,month,day, hour, min)) %>%
  select(date_time, date_time_min, Activity, everything()) %>%
  arrange(date_time_min)
####################################################################################################################