sglandry

# SC state transition data play

library(tidyverse)
library(readr)

data <- tibble(read_csv("12376.csv")) %>%
  select(timestamp, TimeStamp,Speed,ACC_State,HOLCA_State,HOLCA_Icon,StrgWhlTchSnsHndsOnStat,DMSIP_DrvrAttnStatAuth,Take_Steering_Msg,SWLB = StrgWhlLgtBarCmdLgtBrStat) %>%
  mutate_all(as.numeric) %>%
  mutate(Speed = Speed*2.237) #Converts meters per second to MPH

sglandry

library(tidyverse)
library(pbapply)

wd <- getwd() # get working directory
setwd(file.path(wd,"pupil detection")) # look in emotions_processed folder
files <- list.files() # 176 files

# read in and combine all files
allclips <- pblapply(files,function(x){
  read_csv(x) %>%

sglandry

# plot.me accepts an argument of a specific question title (Q) and analyzes then plots all the subquestions (speed and steering Q's for the same image)

# example usage: plot.me('14') to analyze questions that start with '14.'

plot.me <- function(Q){
  data %>%
    select(starts_with(Q),pauser2) %>% 
    rename(speed = ends_with(".2"), steer = ends_with(".3")) %>%
    pivot_longer(cols = c(speed,steer),names_to = "system") %>%
    group_by(pauser2,system) %>%

sglandry

library(progress)

pb <- progress_bar$new(
  format = "  Synchronizing with the matrix bleep blorp [:bar] :percent eta: :eta",
  total = length(unique(data$trip_id)), clear = FALSE, width= 60)
pdf("plots.pdf", onefile = TRUE)
for(trip in unique(data$trip_id)){
  pb$tick()
  theplot <- data %>%
    filter(trip_id == trip) %>%

sglandry

library(tidyverse);library(readxl);library(pbapply)

trips <- read_csv('//ctl-apett.mit.edu/agelab_data/AVT/trips.csv') %>% 
    mutate(trip_id=as.character(trip_id)) %>% 
    select(trip_id,vehicle_type,trip_label_share)

files.cpap <- list.files('//ctl-apett.mit.edu/agelab_data/AVT/annotation_projects/aa_cp_annotations/annotations','xlsx',full.names = T,recursive = T) %>% 
    enframe(NULL,'path') %>% 
    filter(!str_detect(path,'template|Copy|~|/_'))

sglandry

library(readr)
library(ggplot2)
library("reshape2", lib.loc="~/R/win-library/3.3")
library(googlesheets)
library(httpuv)
library(dplyr)
library(lme4)
library(lmerTest)
library("lme4", lib.loc="~/R/win-library/3.3")
setwd("C:/Users/sglan/Desktop/Dissertation stats")

sglandry

library(readr)
library(ggplot2)
library("reshape2", lib.loc="~/R/win-library/3.3")
library(googlesheets)
library(httpuv)
library(dplyr)
library("lme4", lib.loc="~/R/win-library/3.3")
setwd("C:/Users/sglan/Desktop/Dissertation stats")

get.se <- function(y) {

sglandry

library(readxl)
library(stringr)
library(reshape2)
library(ggplot2)
library(readr)

# Because these data are essentially quotations attached to lists of codes, 
# a function `list.to.matrix` was created to take a list with vector items of 
# different lengths and create a matrix with the same length of the list but to 
# have a width equal to the length of the longest vector item to accommodate all 

sglandry

library(ggplot2)
library(reshape2)

setwd("M:/mtucifs_home/Desktop/Trains/Study 2")
list.files()


SIMA1<- read.csv("M:/mtucifs_home/Desktop/Trains/Study 2/SIMA1.csv")
SIMA2<- read.csv("M:/mtucifs_home/Desktop/Trains/Study 2/SIMA2.csv")
SIMC1<- read.csv("M:/mtucifs_home/Desktop/Trains/Study 2/SIMC1.csv")

sglandry

path<-"//homedir.mtu.edu/home/Desktop/Trains/Study 2/newest/HRD Data/" ### home path
setwd(path)
subfolders<-dir()
path2<-"//homedir.mtu.edu/home/Desktop/Trains/Study 2/newest/cleaned/" ### destination folder for cleaned up HRD data
path3<-"//homedir.mtu.edu/home/Desktop/Trains/Study 2/newest/Newest (all)/" ### source folder for all DAQ CSV's
path4<-"//homedir.mtu.edu/home/Desktop/Trains/Study 2/newest/cleanmerged/"  ### destination folder for merged files
path5<-"//homedir.mtu.edu/home/Desktop/Trains/Study 2/newest/splitbyevents/" ##### destination folder for final merged files split by event

# loop through each sub folder
# loop through each test folder