From bf9c85f0e4641caea3fabae05bbadbeaff84997e Mon Sep 17 00:00:00 2001 From: jrtechs Date: Sat, 30 Mar 2019 15:07:38 -0400 Subject: [PATCH 1/5] Created graph showing moving average vs daily load. --- data_preparation/createWorkSequenceData.R | 11 +++++++++++ findings/SlidingAverageDailyLoad.png | Bin 0 -> 23209 bytes 2 files changed, 11 insertions(+) create mode 100644 findings/SlidingAverageDailyLoad.png diff --git a/data_preparation/createWorkSequenceData.R b/data_preparation/createWorkSequenceData.R index 859e120..81b785e 100644 --- a/data_preparation/createWorkSequenceData.R +++ b/data_preparation/createWorkSequenceData.R @@ -40,6 +40,8 @@ for(day in window:numDays) 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 +49,13 @@ plot(density(workLoad), main="Total Work Load Average") dataTibble <- tibble(TimeSinceAugFirst = window:numDays, slidingWorkAverage = slidingAverage) + +ggplot(data = dataTibble) + + theme(plot.title = element_text(hjust = 0.5)) + + ggtitle("Team's Total Daily Load Moving Average") + + geom_point(mapping = aes(x=TimeSinceAugFirst, y=slidingWorkAverage)) + + labs(x = "Days Since August Twenty First 2017", y = "Teams Total Daily Load")+ + theme_bw() + + write.csv(dataTibble, "cleaned/slidingWorkAverage.csv") \ No newline at end of file diff --git a/findings/SlidingAverageDailyLoad.png b/findings/SlidingAverageDailyLoad.png new file mode 100644 index 0000000000000000000000000000000000000000..6517a0b3a04663b3d56e20b4b57f61aca8271aad GIT binary patch literal 23209 zcmZ_0WmweD7dK2di*zlZbR)gA(jgtvNH;9qt)S9fOC#Nl5{oF!Qi3!~gOt+Ev*_=C z-OqJj*ZqPQ`<vAtfaxBO@axC#RsGproXvqN1XvrUn9mG&D4{w6t_|bWfi? zefI1bJv}`G0|O%?BNG!7Gcz*_3kxeND;padJ3BiE2L~r7Cl?nNH#avA56|=G&v|)y z`S|$w`S}F|1Ox>Ig@lBJg@r*NkcfzgsHmuzn3%Y@xP*j+q@<*jl+=qCFJ8WUDJ?B6 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slidingAverage <- c() -window <- 21 - 1 +window <- 7 - 1 for(day in window:numDays) { - print(length(workLoad[c((day-window):day)])) windowAverage <- mean(workLoad[c((day-window):day)]) - slidingAverage <- c(slidingAverage, windowAverage) } @@ -52,10 +50,10 @@ dataTibble <- tibble(TimeSinceAugFirst = window:numDays, slidingWorkAverage = sl ggplot(data = dataTibble) + theme(plot.title = element_text(hjust = 0.5)) + - ggtitle("Team's Total Daily Load Moving Average") + + ggtitle("Team's 7 Day Moving Average") + geom_point(mapping = aes(x=TimeSinceAugFirst, y=slidingWorkAverage)) + - labs(x = "Days Since August Twenty First 2017", y = "Teams Total Daily Load")+ + labs(x = "Days Since August Seventh 2017", y = "Teams Total Daily Load")+ theme_bw() -write.csv(dataTibble, "cleaned/slidingWorkAverage.csv") \ No newline at end of file +write.csv(dataTibble, "cleaned/slidingWorkAverageSevenDay.csv") \ No newline at end of file From 1dda04e6d70b86cf346973ca6da4ca3a631f753a Mon Sep 17 00:00:00 2001 From: jrtechs Date: Sat, 30 Mar 2019 16:01:25 -0400 Subject: [PATCH 3/5] created graphs for fatigue over time. --- data_preparation/createWorkSequenceData.R | 41 +++++++++++++++++++--- findings/Fatigue.png | Bin 0 -> 23769 bytes 2 files changed, 37 insertions(+), 4 deletions(-) create mode 100644 findings/Fatigue.png diff --git a/data_preparation/createWorkSequenceData.R b/data_preparation/createWorkSequenceData.R index 2fd7fe0..f202b22 100644 --- a/data_preparation/createWorkSequenceData.R +++ b/data_preparation/createWorkSequenceData.R @@ -16,8 +16,6 @@ averageWorkLoad <- c() for(day in dayList) { - total <- 0 - daylyActivities <- subset(RPEData, TimeSinceAugFirst == day) cat("day: ", day, "\n",sep="") cat("Activity count:", length(daylyActivities$DailyLoad), "\n", sep="") @@ -31,7 +29,7 @@ plot(dayList, workLoad, main="Daily Total Work Load") slidingAverage <- c() -window <- 7 - 1 +window <- 31 - 1 for(day in window:numDays) { windowAverage <- mean(workLoad[c((day-window):day)]) @@ -56,4 +54,39 @@ ggplot(data = dataTibble) + theme_bw() -write.csv(dataTibble, "cleaned/slidingWorkAverageSevenDay.csv") \ No newline at end of file + +write.csv(dataTibble, "cleaned/slidingWorkAverageSevenDay.csv") + + +################################ Wellness Data ################################### + +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) +} + +graphingTib <- tibble(slidingAverage = slidingAverage, days = window:dayNum) + +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() + +plot(density(slidingAverage)) +plot(window:dayNum, slidingAverage) + + + diff --git a/findings/Fatigue.png b/findings/Fatigue.png new file mode 100644 index 0000000000000000000000000000000000000000..4b4b205ee2a2ad9ee375507a6c6524c733682067 GIT binary patch literal 23769 zcmcG$byU<})Hez!sdRUPfP{cBbeF);AT5G4!qAOK4J{%)fOJWhw7`(c(9$);(A{}Q z{XOsd+;#uHYXNKKobTD^bN1PF_C8-CHGxXFI8-<&C@8op%JSMMD31UrC}<>DkB}`Z zsy-^n1{6&-T?OPAFNU|?iqWMX1sW@ct#VPR!uWn*JwXJ>!*>=_3K2PY>d7Z=y_=g+yhxp{baczJpG z`1oGDc)`!lFCZWwC@A>yx>FE6j4prELzsHCK%tgNh}qVnq1D^*ohH8nMLb#)*RsG*^usi~=@rKPQ{ zt)ru(tE;Q0r>C#4Z(v~X`t@r=Lqj7YBV%J@6B83tQ&TfDGjntEH*elpSXjJ$`_|IZ z(#p!}-Me?z*48#QHnz65c6N65_Vx}A4vvnFPEJnm-@kWuc6M=b0f9iSuC8uwZtm{x z9v&W^o}OM_Uf$l`K0ZFazP^5be*XUc0RaJlfq_9mK_5PR2o4VZ`0-;%NJwaCXjoWS zczAe3LBs;cVh>YAFG+S=N>y1M%M`i6#v#>U3)-@i9C zH8nRkx3sjhwzjslwY9gmcXV|8`0=B&v$LzKtGl}!3WfIc^z`=j_VxAk_xBGB3=9qq z{`~p#*RNkgLqjkaY&4Gc&WZvvYHE 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bytes findings/SmoothedWork.png | Bin 0 -> 64660 bytes 6 files changed, 461 insertions(+), 16 deletions(-) create mode 100644 data_preparation/cleaned/expSmoothWorkAndFatigueData.csv create mode 100644 findings/Rplot.png create mode 100644 findings/Rplot01.png create mode 100644 findings/SmoothedFatigue.png create mode 100644 findings/SmoothedWork.png diff --git a/data_preparation/cleaned/expSmoothWorkAndFatigueData.csv b/data_preparation/cleaned/expSmoothWorkAndFatigueData.csv new file mode 100644 index 0000000..df1b22e --- /dev/null +++ b/data_preparation/cleaned/expSmoothWorkAndFatigueData.csv @@ -0,0 +1,356 @@ +"","day","totalWork","averageWorkLoad","smoothedWork","smoothedFatigueData" +"1",0,4855,255.526315789474,4855,0.734457489003587 +"2",1,1380,138,5921.8864123285,1.17226558337237 +"3",2,6030,231.923076923077,11569.9661032971,1.37713723445689 +"4",3,7745,322.708333333333,18568.7841062135,2.14122117421005 +"5",4,15,15,17386.2272349068,2.07084549296884 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+"355",354,446,148.666666666667,46713.9484000605,NA diff --git a/data_preparation/createWorkSequenceData.R b/data_preparation/createWorkSequenceData.R index f202b22..21cb979 100644 --- a/data_preparation/createWorkSequenceData.R +++ b/data_preparation/createWorkSequenceData.R @@ -27,6 +27,92 @@ plot(dayList, averageWorkLoad, main="Average Work Load") plot(dayList, workLoad, main="Daily Total Work Load") + + + +fatigueFunction <- function(workLoad, index) +{ + if(index == 1) + { + return(workLoad[1]) + } + else + { + return(workLoad[index] + (exp(1)^(-1/15))*fatigueFunction(workLoad, index -1)) + } +} + +smoothedWork <- c() +for(day in dayList) +{ + smoothedWork <- c(smoothedWork, fatigueFunction(workLoad, day + 1)) +} + +plot(dayList, smoothedFatigue) + + + + + +fatigueData <- readFatigueSums() + +dayNum <- max(fatigueData$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$Date) +{ + fatGraph <- fatGraph + geom_vline(xintercept = gameDay, linetype="dotted", + color = "blue", size=1.0) + workGraph <- workGraph + geom_vline(xintercept = gameDay, linetype="dotted", + color = "blue", size=1.0) +} +workGraph +fatGraph + +write.csv(dataTibble, "cleaned/expSmoothWorkAndFatigueData.csv") + + + slidingAverage <- c() window <- 31 - 1 @@ -46,7 +132,7 @@ plot(density(workLoad), main="Total Work Load Average") dataTibble <- tibble(TimeSinceAugFirst = window:numDays, slidingWorkAverage = slidingAverage) -ggplot(data = dataTibble) + +workGraph <- ggplot(data = dataTibble) + theme(plot.title = element_text(hjust = 0.5)) + ggtitle("Team's 7 Day Moving Average") + geom_point(mapping = aes(x=TimeSinceAugFirst, y=slidingWorkAverage)) + @@ -54,37 +140,40 @@ ggplot(data = dataTibble) + theme_bw() +for(gameDay in games$Date) +{ + workGraph <- workGraph + geom_vline(xintercept = gameDay, linetype="dotted", + color = "blue", size=1.0) +} -write.csv(dataTibble, "cleaned/slidingWorkAverageSevenDay.csv") - +workGraph -################################ Wellness Data ################################### -fatigueData <- readFatigueSums() +write.csv(dataTibble, "cleaned/slidingWorkAverageSevenDay.csv") -dayNum <- max(fatigueData$TimeSinceAugFirst) -dayList <- 0:dayNum +################################ Wellness Data ################################### -slidingAverage <- c() -window <- 21 - 1 -for(day in window:dayNum) -{ - windowAverage <- mean(fatigueData$fatigueSum[c((day-window):day)], na.rm = T) - - slidingAverage <- c(slidingAverage, windowAverage) -} graphingTib <- tibble(slidingAverage = slidingAverage, days = window:dayNum) -ggplot(data = graphingTib) + +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$Date) +{ + fGraph <- fGraph + geom_vline(xintercept = gameDay, linetype="dotted", + color = "blue", size=1.0) +} + +fGraph + plot(density(slidingAverage)) plot(window:dayNum, slidingAverage) diff --git a/findings/Rplot.png b/findings/Rplot.png new file mode 100644 index 0000000000000000000000000000000000000000..a4cf8befd3f20a73296f486e101444ff39982fcb GIT binary patch literal 65447 zcmbTeWmJ}H*9H0z3WB77N+Y0jNGUB1(kD#>2?&A;NOvRBAt4}0 zob|Zh{hseT-@n5cd$`Bb_jO%stvTnK>kd;^l*Yj##X=wuII=Plst5$y0|Ww<2on_^ zd2&q20{>idlzHNeK;U*D|3mrww9pKJphn0_JW}^a+nROPyK#Jpv8yF2${Wlm&im5; z&K<>ShOtH!BJvs?zbKo{LJFDLoTze5$;~mHI#=Bqo7v}M;b_G8>JkL6MU!dhPR^h4 zzCh5F>IME>r4rr|c9%8ys^30MmWd~QC&nLN43j3fkczby?eG7+-dD+zf=BSP^9z+} zgW)k1HT6P*zb|5B8bLlIHbO*fgM5a@Mota8#<=6fGp1UvLmOhVFWucb%^rI-w&TUe zyW*j^oYt9wo~lhB)t@f31uXk+y?_6n9M^KSFTFH3b~IZuA^;8J{_xz~oT2ZDd0DH3 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