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117 lines
2.8 KiB
117 lines
2.8 KiB
source("readData.R")
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library(tidyverse)
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RPEData <-readNArpeData()
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games <- readGameRandChanges
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numDays <- max(RPEData$TimeSinceAugFirst)
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dayList <- 0:numDays
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workLoad <- c()
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averageWorkLoad <- c()
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for(day in dayList)
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{
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daylyActivities <- subset(RPEData, TimeSinceAugFirst == day)
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cat("day: ", day, "\n",sep="")
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cat("Activity count:", length(daylyActivities$DailyLoad), "\n", sep="")
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averageWorkLoad <- c(averageWorkLoad, mean(daylyActivities$SessionLoad, na.rm = T))
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workLoad <- c(workLoad, sum(daylyActivities$SessionLoad, na.rm = T))
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}
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fatigueFunction <- function(workLoad, index)
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{
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if(index == 1)
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{
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return(workLoad[1])
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}
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else
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{
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return(workLoad[index] + (exp(1)^(-1/15))*fatigueFunction(workLoad, index -1))
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}
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}
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smoothedWork <- c()
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for(day in dayList)
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{
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smoothedWork <- c(smoothedWork, fatigueFunction(workLoad, day + 1))
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}
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fatigueData <- readFatigueSums()
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dayNum <- max(fatigueData$TimeSinceAugFirst)
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dayList <- 0:dayNum
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slidingAverage <- c()
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window <- 21 - 1
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for(day in window:dayNum)
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{
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windowAverage <- mean(fatigueData$fatigueSum[c((day-window):day)], na.rm = T)
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slidingAverage <- c(slidingAverage, windowAverage)
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}
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smoothedFatigueData <- c()
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for(day in dayList)
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{
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smoothedFatigueData <- c(smoothedFatigueData, fatigueFunction(fatigueData$fatigueSum, day + 1))
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}
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plot(dayList, smoothedFatigueData)
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workTibble <- tibble(day = dayList, totalWork = workLoad,
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averageWorkLoad = averageWorkLoad,
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smoothedWork = smoothedWork,
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smoothedFatigueData = smoothedFatigueData)
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plot(workTibble$totalWork, fatigueData$fatigueSum[-1])
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workGraph <- ggplot(data = workTibble) +
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theme(plot.title = element_text(hjust = 0.5)) +
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ggtitle("Team's Smoothed Work") +
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geom_point(mapping = aes(x=day, y=smoothedWork)) +
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labs(x = "Days Since August First 2017", y = "Teams Training Work")+
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theme_bw()
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fatGraph <- ggplot(data = workTibble) +
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theme(plot.title = element_text(hjust = 0.5)) +
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ggtitle("Team's Percieved Fatigue") +
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geom_point(mapping = aes(x=day, y=smoothedFatigueData)) +
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labs(x = "Days Since August First 2017", y = "Teams Average Normalized Fatigue")+
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theme_bw()
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ggplot(data = workTibble) +
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theme(plot.title = element_text(hjust = 0.5)) +
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ggtitle("Team's Percieved Fatigue") +
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geom_point(mapping = aes(x=smoothedWork, y=smoothedFatigueData)) +
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labs(x = "Smoothed Work Per Day", y = "Teams Average Normalized Fatigue")+
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theme_bw()
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for(gameDay in games$Date)
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{
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fatGraph <- fatGraph + geom_vline(xintercept = gameDay, linetype="dotted",
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color = "blue", size=1.0)
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workGraph <- workGraph + geom_vline(xintercept = gameDay, linetype="dotted",
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color = "blue", size=1.0)
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}
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workGraph
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fatGraph
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