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Merge branch 'master' of https://github.com/PerryXDeng/wheatyeeters

master
PerryXDeng 5 years ago
parent
b77dc26a2d 1fd8828ae1
commit
87c5fff44f
10 changed files with 5855 additions and 6 deletions
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  1. +356
    -0
      data_preparation/cleaned/expSmoothWorkAndFatigueData.csv
  2. +350
    -0
      data_preparation/cleaned/slidingWorkAverageSevenDay.csv
  3. +5012
    -0
      data_preparation/cleaned/time_series_normalized_wellness_menstruation.csv
  4. +137
    -6
      data_preparation/createWorkSequenceData.R
  5. BIN
      findings/Fatigue.png
  6. BIN
      findings/Rplot.png
  7. BIN
      findings/Rplot01.png
  8. BIN
      findings/SlidingAverageDailyLoad.png
  9. BIN
      findings/SmoothedFatigue.png
  10. BIN
      findings/SmoothedWork.png

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data_preparation/cleaned/expSmoothWorkAndFatigueData.csv View File

@ -0,0 +1,356 @@
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"321",326,6522.42857142857
"322",327,6418.42857142857
"323",328,6350.71428571429
"324",329,6802.14285714286
"325",330,6798.57142857143
"326",331,6805
"327",332,6575.28571428571
"328",333,5883.14285714286
"329",334,6155.28571428571
"330",335,6258.14285714286
"331",336,5507.57142857143
"332",337,5044
"333",338,5049.71428571429
"334",339,4775.14285714286
"335",340,4217.28571428571
"336",341,3945.14285714286
"337",342,3879.42857142857
"338",343,3874.28571428571
"339",344,3343.28571428571
"340",345,3329
"341",346,3255.42857142857
"342",347,2469.71428571429
"343",348,2478.28571428571
"344",349,2441.14285714286
"345",350,1511.85714285714
"346",351,1720
"347",352,1720
"348",353,1363.57142857143
"349",354,1483.57142857143

+ 5012
- 0
data_preparation/cleaned/time_series_normalized_wellness_menstruation.csv
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View File


+ 137
- 6
data_preparation/createWorkSequenceData.R View File

@ -16,8 +16,6 @@ averageWorkLoad <- c()
for(day in dayList)
{
total <- 0
daylyActivities <- subset(RPEData, TimeSinceAugFirst == day)
cat("day: ", day, "\n",sep="")
cat("Activity count:", length(daylyActivities$DailyLoad), "\n", sep="")
@ -29,17 +27,103 @@ plot(dayList, averageWorkLoad, main="Average Work Load")
plot(dayList, workLoad, main="Daily Total Work Load")
slidingAverage <- c()
fatigueFunction <- function(workLoad, index)
{
if(index == 1)
{
return(workLoad[1])
}
else
{
return(workLoad[index] + (exp(1)^(-1/15))*fatigueFunction(workLoad, index -1))
}
}
smoothedWork <- c()
for(day in dayList)
{
smoothedWork <- c(smoothedWork, fatigueFunction(workLoad, day + 1))
}
plot(dayList, smoothedFatigue)
fatigueData <- readFatigueSums()
dayNum <- max(fatigueData$TimeSinceAugFirst)
dayList <- 0:dayNum
slidingAverage <- c()
window <- 21 - 1
for(day in window:dayNum)
{
windowAverage <- mean(fatigueData$fatigueSum[c((day-window):day)], na.rm = T)
slidingAverage <- c(slidingAverage, windowAverage)
}
smoothedFatigueData <- c()
for(day in dayList)
{
smoothedFatigueData <- c(smoothedFatigueData, fatigueFunction(fatigueData$fatigueSum, day + 1))
}
plot(dayList, smoothedFatigueData)
workTibble <- tibble(day = dayList, totalWork = workLoad,
averageWorkLoad = averageWorkLoad,
smoothedWork = smoothedWork,
smoothedFatigueData = smoothedFatigueData)
workGraph <- ggplot(data = workTibble) +
theme(plot.title = element_text(hjust = 0.5)) +
ggtitle("Team's Smoothed Work") +
geom_point(mapping = aes(x=day, y=smoothedWork)) +
labs(x = "Days Since August First 2017", y = "Teams Training Work")+
theme_bw()
fatGraph <- ggplot(data = workTibble) +
theme(plot.title = element_text(hjust = 0.5)) +
ggtitle("Team's Percieved Fatigue") +
geom_point(mapping = aes(x=day, y=smoothedFatigueData)) +
labs(x = "Days Since August First 2017", y = "Teams Average Normalized Fatigue")+
theme_bw()
for(gameDay in games$Date)
{
fatGraph <- fatGraph + geom_vline(xintercept = gameDay, linetype="dotted",
color = "blue", size=1.0)
workGraph <- workGraph + geom_vline(xintercept = gameDay, linetype="dotted",
color = "blue", size=1.0)
}
workGraph
fatGraph
write.csv(dataTibble, "cleaned/expSmoothWorkAndFatigueData.csv")
slidingAverage <- c()
window <- 31 - 1
for(day in window:numDays)
{
print(length(workLoad[c((day-window):day)]))
windowAverage <- mean(workLoad[c((day-window):day)])
slidingAverage <- c(slidingAverage, windowAverage)
}
plot(window:numDays, slidingAverage, main="Sliding Average")
plot(density(slidingAverage), main="Sliding Average Density")
plot(density(workLoad), main="Total Work Load Average")
@ -47,4 +131,51 @@ plot(density(workLoad), main="Total Work Load Average")
dataTibble <- tibble(TimeSinceAugFirst = window:numDays, slidingWorkAverage = slidingAverage)
write.csv(dataTibble, "cleaned/slidingWorkAverage.csv")
workGraph <- ggplot(data = dataTibble) +
theme(plot.title = element_text(hjust = 0.5)) +
ggtitle("Team's 7 Day Moving Average") +
geom_point(mapping = aes(x=TimeSinceAugFirst, y=slidingWorkAverage)) +
labs(x = "Days Since August Seventh 2017", y = "Teams Total Daily Load")+
theme_bw()
for(gameDay in games$Date)
{
workGraph <- workGraph + geom_vline(xintercept = gameDay, linetype="dotted",
color = "blue", size=1.0)
}
workGraph
write.csv(dataTibble, "cleaned/slidingWorkAverageSevenDay.csv")
################################ Wellness Data ###################################
graphingTib <- tibble(slidingAverage = slidingAverage, days = window:dayNum)
fGraph <- ggplot(data = graphingTib) +
theme(plot.title = element_text(hjust = 0.5)) +
ggtitle("Team's Average Normalized Fatigue") +
geom_point(mapping = aes(x=days, y=slidingAverage)) +
labs(x = "Days Since August Twenty First 2017", y = "Teams Average Normalized Fatigue")+
theme_bw()
for(gameDay in games$Date)
{
fGraph <- fGraph + geom_vline(xintercept = gameDay, linetype="dotted",
color = "blue", size=1.0)
}
fGraph
plot(density(slidingAverage))
plot(window:dayNum, slidingAverage)

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