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dataProcessing.R
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dataProcessing.R
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#Library Loading ----
library(tidyverse)
#library(anytime)
#library(plyr)
#library(dplyr)
#library(readr)
library(lubridate)
library(geosphere)
#to remove all variables when needed
#rm(list=ls())
#Data Loading ----
# PGdf1 <- read.csv(file = 'raw/gps/post/PinPoint 80378 2020-11-09 10-57-44.csv', header = TRUE)
# PGdf2 <- read.csv(file = 'raw/gps/post/PinPoint 80379 2020-11-09 13-05-18.csv', header = TRUE)
# PGdf3 <- read.csv(file = 'raw/gps/post/PinPoint 80380 2020-11-09 13-18-22.csv', header = TRUE)
# PGdf4 <- read.csv(file = 'raw/gps/post/PinPoint 80381 2020-11-09 13-48-25.csv', header = TRUE)
# PGdf5 <- read.csv(file = 'raw/gps/post/PinPoint 80382 2020-11-09 12-11-25.csv', header = TRUE)
# PGdf6 <- read.csv(file = 'raw/gps/post/PinPoint 80383 2020-11-09 11-31-51.csv', header = TRUE)
# PGdf7 <- read.csv(file = 'raw/gps/post/PinPoint 80384 2020-11-05 15-35-36.csv', header = TRUE)
# PGdf8 <- read.csv(file = 'raw/gps/post/PinPoint 80385 2020-11-05 13-28-27.csv', header = TRUE)
# PGdf9 <- read.csv(file = 'raw/gps/post/PinPoint 80386 2020-11-09 15-35-23.csv', header = TRUE)
# PGdf10 <- read.csv(file = 'raw/gps/post/PinPoint 80387 2020-11-09 11-45-02.csv', header = TRUE)
# PGdf11 <- read.csv(file = 'raw/gps/post/PinPoint 80388 2020-11-09 14-28-51.csv', header = TRUE)
# PGdf12 <- read.csv(file = 'raw/gps/post/PinPoint 80389 2020-11-09 10-05-18.csv', header = TRUE)
# PGdf13 <- read.csv(file = 'raw/gps/post/PinPoint 80390 2020-11-05 14-37-10.csv', header = TRUE)
# PGdf14 <- read.csv(file = 'raw/gps/post/PinPoint 80391 2020-11-09 12-39-21.csv', header = TRUE)
PGdf1 <- read.csv(file = 'raw/gps/pre/PreGPS1.csv', header = TRUE)
PGdf2 <- read.csv(file = 'raw/gps/pre/PreGPS2.csv', header = TRUE)
PGdf3 <- read.csv(file = 'raw/gps/pre/PreGPS3.csv', header = TRUE)
PGdf4 <- read.csv(file = 'raw/gps/pre/PreGPS4.csv', header = TRUE)
PGdf5 <- read.csv(file = 'raw/gps/pre/PreGPS5.csv', header = TRUE)
PGdf6 <- read.csv(file = 'raw/gps/pre/PreGPS6.csv', header = TRUE)
PGdf7 <- read.csv(file = 'raw/gps/pre/PreGPS7.csv', header = TRUE)
PGdf8 <- read.csv(file = 'raw/gps/pre/PreGPS8.csv', header = TRUE)
PGdf9 <- read.csv(file = 'raw/gps/pre/PreGPS9.csv', header = TRUE)
PGdf10 <- read.csv(file = 'raw/gps/pre/PreGPS10.csv', header = TRUE)
PGdf11 <- read.csv(file = 'raw/gps/pre/PreGPS11.csv', header = TRUE)
PGdf12 <- read.csv(file = 'raw/gps/pre/PreGPS12.csv', header = TRUE)
# PGdf13 <- read.csv(file = 'raw/gps/post/PinPoint 80390 2020-11-05 14-37-10.csv', header = TRUE)
# PGdf14 <- read.csv(file = 'raw/gps/post/PinPoint 80391 2020-11-09 12-39-21.csv', header = TRUE)
#Calling MST Conversion Functions ----
PGdf1 <- mstConversion(PGdf1)
PGdf2 <- mstConversion(PGdf2)
PGdf3 <- mstConversion(PGdf3)
PGdf4 <- mstConversion(PGdf4)
PGdf5 <- mstConversion(PGdf5)
PGdf6 <- mstConversion(PGdf6)
PGdf7 <- mstConversion(PGdf7)
PGdf8 <- mstConversion(PGdf8)
PGdf9 <- mstConversion(PGdf9)
PGdf10 <- mstConversion(PGdf10)
PGdf11 <- mstConversion(PGdf11)
PGdf12 <- mstConversion(PGdf12)
# PGdf13 <- mstConversion(PGdf13)
# PGdf14 <- mstConversion(PGdf14)
#Calling Analyze Fix Functions ----
RPGdf1 <- analyzeFixes(PGdf1)
RPGdf2 <- analyzeFixes(PGdf2)
RPGdf3 <- analyzeFixes(PGdf3)
RPGdf4 <- analyzeFixes(PGdf4)
RPGdf5 <- analyzeFixes(PGdf5)
RPGdf6 <- analyzeFixes(PGdf6)
RPGdf7 <- analyzeFixes(PGdf7)
RPGdf8 <- analyzeFixes(PGdf8)
RPGdf9 <- analyzeFixes(PGdf9)
RPGdf10 <- analyzeFixes(PGdf10)
RPGdf11 <- analyzeFixes(PGdf11)
RPGdf12 <- analyzeFixes(PGdf12)
# RPGdf13 <- analyzeFixes(PGdf13)
# RPGdf14 <- analyzeFixes(PGdf14)
#Data Output ----
# write.csv(RPGdf1, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost1GPS.csv", row.names = FALSE)
# write.csv(RPGdf2, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost2GPS.csv", row.names = FALSE)
# write.csv(RPGdf3, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost3GPS.csv", row.names = FALSE)
# write.csv(RPGdf4, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost4GPS.csv", row.names = FALSE)
# write.csv(RPGdf5, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost5GPS.csv", row.names = FALSE)
# write.csv(RPGdf6, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost6GPS.csv", row.names = FALSE)
# write.csv(RPGdf7, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost7GPS.csv", row.names = FALSE)
# write.csv(RPGdf8, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost8GPS.csv", row.names = FALSE)
# write.csv(RPGdf9, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost9GPS.csv", row.names = FALSE)
# write.csv(RPGdf10, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost10GPS.csv", row.names = FALSE)
# write.csv(RPGdf11, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost11GPS.csv", row.names = FALSE)
# write.csv(RPGdf12, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost12GPS.csv", row.names = FALSE)
# write.csv(RPGdf13, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost13GPS.csv", row.names = FALSE)
# write.csv(RPGdf14, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost14GPS.csv", row.names = FALSE)
write.csv(RPGdf1, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre1GPS.csv", row.names = FALSE)
write.csv(RPGdf2, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre2GPS.csv", row.names = FALSE)
write.csv(RPGdf3, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre3GPS.csv", row.names = FALSE)
write.csv(RPGdf4, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre4GPS.csv", row.names = FALSE)
write.csv(RPGdf5, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre5GPS.csv", row.names = FALSE)
write.csv(RPGdf6, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre6GPS.csv", row.names = FALSE)
write.csv(RPGdf7, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre7GPS.csv", row.names = FALSE)
write.csv(RPGdf8, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre8GPS.csv", row.names = FALSE)
write.csv(RPGdf9, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre9GPS.csv", row.names = FALSE)
write.csv(RPGdf10, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre10GPS.csv", row.names = FALSE)
write.csv(RPGdf11, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre11GPS.csv", row.names = FALSE)
write.csv(RPGdf12, "F:/Development/Projects/Research/TeamBeef/workingProject/output/pre/APre12GPS.csv", row.names = FALSE)
# write.csv(RPGdf13, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost13GPS.csv", row.names = FALSE)
# write.csv(RPGdf14, "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost14GPS.csv", row.names = FALSE)
#Loading in Post ----
df1 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost1GPS.csv", header = TRUE)
#df2 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost2GPS.csv", header = TRUE)
df3 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost3GPS.csv", header = TRUE)
df4 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost4GPS.csv", header = TRUE)
df5 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost5GPS.csv", header = TRUE)
df6 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost6GPS.csv", header = TRUE)
#df7 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost7GPS.csv", header = TRUE)
df8 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost8GPS.csv", header = TRUE)
df9 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost9GPS.csv", header = TRUE)
df10 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost10GPS.csv", header = TRUE)
df11 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost11GPS.csv", header = TRUE)
df12 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost12GPS.csv", header = TRUE)
df13 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost13GPS.csv", header = TRUE)
df14 <- read.csv(file = "F:/Development/Projects/Research/TeamBeef/workingProject/output/post/APost14GPS.csv", header = TRUE)
#Post Avg ----
preAvg1 <- removePercent(df1)
preAvg1 <- collarAvg(preAvg1, 30378)
#preAvg2 <- removePercent(df2)
#preAvg2 <- collarAvg(preAvg2, 30380)
preAvg3 <- removePercent(df3)
preAvg3 <- collarAvg(preAvg3, 30380)
preAvg4 <- removePercent(df4)
preAvg4 <- collarAvg(preAvg4, 30381)
preAvg5 <- removePercent(df5)
preAvg5 <- collarAvg(preAvg5, 30382)
preAvg6 <- removePercent(df6)
preAvg6 <- collarAvg(preAvg6, 30383)
#preAvg7 <- removePercent(df7)
#preAvg7 <- collarAvg(preAvg7, 30384)
preAvg8 <- removePercent(df8)
preAvg8 <- collarAvg(preAvg8, 30385)
preAvg9 <- removePercent(df9)
preAvg9 <- collarAvg(preAvg9, 30386)
preAvg10 <- removePercent(df10)
preAvg10 <- collarAvg(preAvg10, 30387)
preAvg11 <- removePercent(df11)
preAvg11 <- collarAvg(preAvg11, 30388)
preAvg12 <- removePercent(df12)
preAvg12 <- collarAvg(preAvg12, 30389)
preAvg13 <- removePercent(df13)
preAvg13 <- collarAvg(preAvg13, 30390)
preAvg14 <- removePercent(df14)
preAvg14 <- collarAvg(preAvg14, 30391)
avgPostGPS <- rbind(preAvg1,preAvg3,preAvg4,preAvg5,preAvg6,preAvg8,preAvg9,preAvg10,preAvg11,preAvg12,preAvg13,preAvg14)
avgPostGPSn6 <- rbind(preAvg1,preAvg3,preAvg4,preAvg5,preAvg8,preAvg9,preAvg10,preAvg11,preAvg12,preAvg13,preAvg14)
#Avg of GPS Pre----
preAvg1 <- removePercent(RPGdf1)
preAvg1 <- collarAvg(preAvg1, 30379)
preAvg2 <- removePercent(RPGdf2)
preAvg2 <- collarAvg(preAvg2, 30380)
preAvg3 <- removePercent(RPGdf3)
preAvg3 <- collarAvg(preAvg3, 30381)
preAvg4 <- removePercent(RPGdf4)
preAvg4 <- collarAvg(preAvg4, 30382)
preAvg5 <- removePercent(RPGdf5)
preAvg5 <- collarAvg(preAvg5, 30384)
preAvg6 <- removePercent(RPGdf6)
preAvg6 <- collarAvg(preAvg6, 30385)
preAvg7 <- removePercent(RPGdf7)
preAvg7 <- collarAvg(preAvg7, 30386)
preAvg8 <- removePercent(RPGdf8)
preAvg8 <- collarAvg(preAvg8, 30387)
preAvg9 <- removePercent(RPGdf9)
preAvg9 <- collarAvg(preAvg9, 30388)
preAvg10 <- removePercent(RPGdf10)
preAvg10 <- collarAvg(preAvg10, 30389)
preAvg11 <- removePercent(RPGdf11)
preAvg11 <- collarAvg(preAvg11, 30390)
preAvg12 <- removePercent(RPGdf12)
preAvg12 <- collarAvg(preAvg12, 30391)
avgPreGPS <- rbind(preAvg1,preAvg2,preAvg3,preAvg4,preAvg5,preAvg6,preAvg7,preAvg8,preAvg9,preAvg10,preAvg11,preAvg12)
avgPreGPSn6 <- rbind(preAvg1,preAvg2,preAvg3,preAvg4,preAvg5,preAvg7,preAvg8,preAvg9,preAvg10,preAvg11,preAvg12)
#Avg of GPS Print----
write.csv(avgPreGPS, "F:/Development/Projects/Research/TeamBeef/workingProject/output/avgPreGPS.csv", row.names = FALSE)
write.csv(avgPreGPSn6, "F:/Development/Projects/Research/TeamBeef/workingProject/output/avgPreGPSn6.csv", row.names = FALSE)
write.csv(avgPostGPS, "F:/Development/Projects/Research/TeamBeef/workingProject/output/avgPostGPS.csv", row.names = FALSE)
write.csv(avgPostGPSn6, "F:/Development/Projects/Research/TeamBeef/workingProject/output/avgPostGPSn6.csv", row.names = FALSE)
#Histogram Time ----
#Working Tests Distance----
# testData <- read.csv(file = 'Data/GPS/testGPS.csv', header = TRUE)
# yot <- mstConversion(yot)
#
# testGPS1 <- testData[90,]
# testGPS2 <- testData[91,]
#
# avgSpeed <- speedFromGPS(PGdf1[(142),], PGdf1[10000,])
#
#
# new <- speedFromGPS(testGPS1, testGPS2)
#
# #Working Test Proximity Selc
# #need to extract before converting to MST
# yot <- filter(tempData, Fix %in% c("GPS Schedule"))
#
# #Testing Functions ----
#tempData <- PGdf1[PGdf1$Fix == "GPS Schedule", ]
# # "Proximity GPS Schedule")
# for(i in 2:nrow(tempData)) {
# speed <- speedFromGPS(tempData[i-1,], tempData[i,])
#
# print(speed)
# }
# #
# # tempData <- mstConversion(tempData)
# test <- analyzeFixes(tempData)
# # tempData <- tempData
# #
# #
# # #testing why inf speed, if can't figure out will just set to 0
# # speedFromGPS(tempData[169,], tempData[170,])
# #
# # yot <- TRUE
#Functions ----
mstConversion <- function(data)
{
#remove if wanted to analyze Schedulde and Proximity together, will remove when fixed up.
data <- data[data$Fix == "GPS Schedule", ]
tempDate <- strptime(data$GMT, "%Y-%m-%d %H:%M", tz = "GMT")
tempData <- with_tz(tempDate, "America/Edmonton")
data$GMT <- tempData
return(data)
}
indexGPSZero <- function(dataInput)
{
#selects the data within the headers specified in the argument
tempData <- dataInput %>% select(Latitude, Longitude, Altitude)
#checks the headers specified if a 0 is within
tempData <- tempData[tempData$Latitude == 0 | tempData$Longitude == 0 | tempData$Altitude == 0, ]
#previous loads as char, type cast to numeric for later use
dataOutput <- as.numeric(rownames(tempData))
return(dataOutput)
}
indexCopyFrame5 <- function(dataInput, index)
{
#set the same structure as the input dataframe
copyFrame <- dataInput[0, ]
#runs the length of the index vector
for(i in 1:length(index))
{
#checks if it is not out of bounds
if (index[i] >= 3)
#appends the specifed index of the input data, to bottom of copyFrame
copyFrame <- rbind(copyFrame, dataInput[index[i] - 2,])
if (index[i] >= 2)
copyFrame <- rbind(copyFrame, dataInput[index[i] - 1,])
copyFrame <- rbind(copyFrame, dataInput[index[i],])
if (index[i] <= (nrow(dataInput) - 1))
copyFrame <- rbind(copyFrame, dataInput[index[i] + 1,])
if (index[i] <= (nrow(dataInput) - 2))
copyFrame <- rbind(copyFrame, dataInput[index[i] + 2,])
#for sake of formatting, adds a row of NA
copyFrame[nrow(copyFrame) + 1,] <- NA
}
return(copyFrame)
}
indexCopyFrame6 <- function(dataInput, index)
{
#set the same structure as the input dataframe
copyFrame <- dataInput[0, ]
#runs the length of the index vector
for(i in 1:length(index))
{
#checks if it is not out of bounds
if (index[i] >= 3)
#appends the specifed index of the input data, to bottom of copyFrame
copyFrame <- rbind(copyFrame, dataInput[index[i] - 2,])
if (index[i] >= 2)
copyFrame <- rbind(copyFrame, dataInput[index[i] - 1,])
copyFrame <- rbind(copyFrame, dataInput[index[i],])
if (index[i] <= (nrow(dataInput) - 1))
copyFrame <- rbind(copyFrame, dataInput[index[i] + 1,])
if (index[i] <= (nrow(dataInput) - 2))
copyFrame <- rbind(copyFrame, dataInput[index[i] + 2,])
if (index[i] <= (nrow(dataInput) - 3))
copyFrame <- rbind(copyFrame, dataInput[index[i] + 3,])
#for sake of formatting, adds a row of NA
copyFrame[nrow(copyFrame) + 1,] <- NA
}
return(copyFrame)
}
analyzeFixes <- function(data)
{
#2020-07-13 for pre/post switch over 2020-06-18,
dates <- seq(as.Date("2020-06-18"), as.Date("2020-07-13"), by="days")
copyFrame <- data.frame(Dates=character(0), Expected_Fixes=numeric(0), On_Time_Fix=numeric(0),
No_Fix=numeric(0), Early_Fix=numeric(0), Late_Fix=numeric(0), Avg_Speed_Day=numeric(0),
Avg_Speed_Night=numeric(0), Out_of_Bounds=numeric(0), Per_No_Fix=character(0), Per_Missing_Fix=character(0))
for(i in 1:length(dates))
{
dateCounter <- 0
noFix <- 0
lateFix <- 0
earlyFix <- 0
Fix <- 0
differenceTime <- 0
firstCheck <- TRUE
dateStart <- 0
dateEnd <- 0
perNo <- 0
perMiss <- 0
expectedFix <- 0
avgSpeedDay <- 0
avgSpeedNight <- 0
speedcounterD <- 0
speedcounterN <- 0
speedEvent <- TRUE
outOfBounds <- 0
day <- FALSE
night <- FALSE
for(j in 2:(nrow(data)-1))
{
if(as.Date(data$GMT[j]) == dates[i]) { #same day
differenceTime <- as.numeric((data$GMT[j] - data$GMT[j - 1]), units ="mins")
speedCheck <- speedFromGPS(data[(j-1),], data[j,])
if(speedCheck > 10)
speedEvent <- FALSE
daytime <- format(data$GMT[j], format = "%H")
if(daytime == "06") {
day <- TRUE
night <- FALSE
}
else if(daytime == "20") {
night <- TRUE
day <- FALSE
}
if(data$Latitude[j] == 0 | data$Longitude[j] == 0 | data$Altitude[j] == 0) {
noFix <- noFix + 1
}
else if(3 < differenceTime && differenceTime < 7 & speedEvent) { #fix
Fix <- Fix + 1
if(day) {
avgSpeedDay <- avgSpeedDay + speedFromGPS(data[(j-1),], data[j,])
speedcounterD <- speedcounterD + 1
}
else if(night) {
avgSpeedNight <- avgSpeedNight + speedFromGPS(data[(j-1),], data[j,])
speedcounterN <- speedcounterN + 1
}
}
else if(3 >= differenceTime & speedEvent) { #early
earlyFix <- earlyFix + 1
if(day) {
avgSpeedDay <- avgSpeedDay + speedFromGPS(data[(j-1),], data[j,])
speedcounterD <- speedcounterD + 1
}
else if(night) {
avgSpeedNight <- avgSpeedNight + speedFromGPS(data[(j-1),], data[j,])
speedcounterN <- speedcounterN + 1
}
}
else if(differenceTime <= 7 & speedEvent) { #late
lateFix <- lateFix + 1
if(day) {
avgSpeedDay <- avgSpeedDay + speedFromGPS(data[(j-1),], data[j,])
speedcounterD <- speedcounterD + 1
}
else if(night) {
avgSpeedNight <- avgSpeedNight + speedFromGPS(data[(j-1),], data[j,])
speedcounterN <- speedcounterN + 1
}
}
else if(!speedEvent) {
outOfBounds <- outOfBounds + 1
speedEvent <- TRUE
}
if(firstCheck) { #first
dateStart <- data$GMT[j]
firstCheck <- FALSE
}
else if(TRUE) { #last
dateEnd <- data$GMT[j]
}
dateCounter <- dateCounter + 1
}
}
rowDate <- as.character(dates[i])
if(dateCounter == 0) {
holdFrame <- data.frame(rowDate, expectedFix, Fix, noFix, earlyFix, lateFix, avgSpeedDay, avgSpeedNight, outOfBounds, perNo, perMiss)
copyFrame <- rbind(copyFrame, holdFrame)
}
else {
periodDate <- as.interval(dateStart, dateEnd)
if (i == 1) {
expectedFix <- ceiling( periodDate / minutes(5) )
}
else if (i == length(dates)) {
expectedFix <- ceiling( periodDate / minutes(5) )
}
else {
expectedFix <- 288
}
perNo <- (noFix / (lateFix + earlyFix + Fix)) * 100
perNo <- paste(perNo, "%")
perMiss <- ((expectedFix - (lateFix + earlyFix + Fix)) / expectedFix) * 100
perMiss <- paste(perMiss, "%")
avgSpeedDay <- avgSpeedDay / speedcounterD
avgSpeedNight <- avgSpeedNight / speedcounterN
holdFrame <- data.frame(rowDate, expectedFix, Fix, noFix, earlyFix, lateFix, avgSpeedDay, avgSpeedNight, outOfBounds, perNo, perMiss)
copyFrame <- rbind(copyFrame, holdFrame)
}
}
colnames(copyFrame) <- c("Date", "Expected_Fixes", "On_Time_Fix", "No_fix", "Early_Fix", "Late_Fix", "Avg_Speed_Day", "Avg_Speed_Night", "Out_of_Bounds", "Percent_No_Fix_to_Total", "Per_Missing__to_Expected_Fix")
return(copyFrame)
}
speedFromGPS <- function(p1, p2)
{
p1GPS <- p1 %>% select(Latitude, Longitude)
p2GPS <- p2 %>% select(Latitude, Longitude)
p1GPS <- p1GPS[c('Longitude', "Latitude")]
p2GPS <- p2GPS[c('Longitude', "Latitude")]
distance <- distGeo(p1GPS, p2GPS)
time <- as.numeric((p2$GMT - p1$GMT), units ="secs")
speed <- abs(distance / time)
if(speed == Inf)
speed <- 0
return(speed)
}
removePercent <- function(data)
{
data$Percent_No_Fix_to_Total <- as.numeric(gsub("[\\%,]", "", data$Percent_No_Fix_to_Total))
data$Percent_No_Fix_to_Total <- data$Percent_No_Fix_to_Total / 100
data$Per_Missing__to_Expected_Fix <- as.numeric(gsub("[\\%,]", "", data$Per_Missing__to_Expected_Fix))
data$Per_Missing__to_Expected_Fix <- data$Per_Missing__to_Expected_Fix / 100
data <- transform(data, Per_Good_Fixes = data$On_Time_Fix / (data$No_fix + data$Early_Fix + data$On_Time_Fix))
data$Out_of_Bounds <- data$Out_of_Bounds / (data$No_fix + data$Early_Fix + data$On_Time_Fix)
data[] <- lapply(data, function(x) replace(x, !is.finite(x), 1))
return(data)
}
collarAvg <- function(data, ID)
{
copyFrame <- data.frame(ID=numeric(0),Per_Good_Fixes=numeric(0), Percent_No_Fix_to_Total=numeric(0), Per_Missing__to_Expected_Fix=numeric(0), Per_Out_of_Bounds=numeric(0))
goodFixes <- mean(data$Per_Good_Fixes)
noFix <- data[data$Percent_No_Fix_to_Total < 5,]
noFix <- mean(noFix$Percent_No_Fix_to_Total)
missingFix <- data[data$Per_Missing__to_Expected_Fix < 5,]
missingFix <- mean(missingFix$Per_Missing__to_Expected_Fix)
outFix <- mean(data$Out_of_Bounds)
holdFrame <- data.frame(ID, goodFixes, noFix, missingFix, outFix)
copyFrame <- rbind(copyFrame, holdFrame)
colnames(copyFrame) <- c("ID", "Per_Good_Fix_to_Exp", "Per_No_Fix_to_Total","Per_Missing_Fix_to_Total","Per_Out_of_Bounds_Fix")
return(copyFrame)
}