calculate TDEE based on body mass and calories

#Set input files
nutfile = "nutrition.txt"
weifile = "weight.txt"

#Ser smoothing parameters (from 0 to 2)
smoothparam <- 1.1
smoothparammacros <- 0.6

#Load libraries
require("plyr")

#Read data files
#Tab-delimited text files
#
#nutrition file
#accepts multiple meals per day
#
#columns:
#Date (dd/mm/yyyy)
#Calories (number)
#Fat (numeric, grams)
#Carbohydrates (numeric, grams)
#Protein (numeric, grams)
#
#weight file
#accepts multiple measurements per day
#
#columns:
#Date (dd/mm/yyyy)
#Body.Fat.. (body fat %)
#Weight (body mass, kilograms)

nut <- read.table(nutfile, header = T, sep = "\t")
wei <- read.table(weifile, header = T, sep = "\t")

#Sum up all meals in each day
nutd <- ddply(nut,
              .(Date),
              summarise,
              Calories = sum(Calories),
              Fat = sum(Fat),
              Carbohydrates = sum(Carbohydrates),
              Protein = sum(Protein),
              PFat = 100 * (sum(Fat) * 9)/sum(Calories),
              PCarbohydrates = 100 * (sum(Carbohydrates) * 4)/sum(Calories),
              PProtein = 100 * (sum(Protein) * 4)/sum(Calories),
              .progress = "text")

#Convert date to date format
nutd$RDate <- as.Date(as.character(nutd$Date), "%d/%m/%Y")
#order by date
nutd <- nutd[order(nutd$RDate), ]
#calculate number of days
nutd$Days <- as.numeric(nutd$RDate - nutd$RDate[1])
#remove rows with missing values
nutd <- nutd[complete.cases(nutd), ]

#Average multiple weight/bf measurements in each day
weid <- ddply(wei,
              .(Date),
              summarise,
              Weight = mean(Weight),
              Body.Fat = mean(Body.Fat..),
              .progress = "text")
#Convert date to date format
weid$RDate <- as.Date(as.character(weid$Date), "%d/%m/%Y")
#order by date
weid <- weid[order(weid$RDate), ]
#calculate number of days
weid$Days <- as.numeric(weid$RDate - weid$RDate[1])
#remove rows with missing values
weid <- weid[complete.cases(weid), ]

#calculate the max number of days and create day sequence
newt <- max(nutd$Days, weid$Days)
newdays <- c(1:newt)

#fit smoothing spline to calories
MCalories <- smooth.spline(nutd$Days, nutd$Calories, spar = smoothparam)
Caloriesmod <- predict(MCalories, nutd$Days)
nutd$Caloriesmod <- Caloriesmod$y

#fit smoothing spline to body mass and calculate deficit
MWeight <- smooth.spline(weid$Days, weid$Weight, spar = smoothparam)
Weightmod <- predict(MWeight, newdays)
WeightmodD <- predict(MWeight, weid$Days, deriv = 1)
#7700kcal per kilo of fat
weid$def <- WeightmodD$y * 7700

#calculate TDEE for all days
completecal <- predict(MCalories, newdays)$y
completedef <- predict(MWeight, newdays, deriv = 1)$y * 7700
TDEE <- completecal - completedef

#Fit body fat spline
MBody.Fat <- smooth.spline(weid$Days, weid$Body.Fat, spar = smoothparam)
BFmod <- predict(MBody.Fat, newdays)
#Fit nutrient splines
MFat <- smooth.spline(nutd$Days, nutd$PFat, spar = smoothparammacros)
MCarb <- smooth.spline(nutd$Days, nutd$PCarbohydrates, spar = smoothparammacros)
MProt <- smooth.spline(nutd$Days, nutd$PProtein, spar = smoothparammacros)
Fatmod <- predict(MFat, newdays)
Carbmod <- predict(MCarb, newdays)
Protmod <- predict(MProt, newdays)

#Make plot

png( filename = "Rplot.png", width = 666, height = 500, units = "px")
par(mfrow = c(2, 3))

plot(weid$Weight ~ weid$Days, xlab = "", ylab = "", ylim = c(90, 160),
     xlim = c(0, newt))
par(new = T)
plot(Weightmod$y ~ Weightmod$x, type = "l", xlab = "days", ylab = "body mass [kg]",
     ylim = c(90, 160), col = "red", xlim = c(0, newt))
plot(weid$Body.Fat ~ weid$Days, xlab = "", ylab = "", ylim = c(10, 60),
     xlim = c(0, newt))
par(new = T)
plot(BFmod$y ~ BFmod$x, type = "l", xlab = "days", ylab = "body fat [%]",
     ylim = c(10, 60), col = "red", xlim = c(0, newt))

plot(Fatmod$y ~ newdays, type = "l", xlab = "days", ylab = "calories from [%]",
     col = "red", ylim = c(0, 100), xlim = c(0, newt))
par(new = T)
plot(Carbmod$y ~ newdays, type = "l", xlab = "", ylab = "", col = "blue",
     ylim = c(0, 100), xlim = c(0, newt))
par(new = T)
plot(Protmod$y ~ newdays, type = "l", xlab = "", ylab = "", col = "darkgreen",
     ylim = c(0, 100), xlim = c(0, newt))
text(20, 90, "Fat", col = "red", adj = c(0, 0))
text(20, 80, "Carbohydrates", col = "blue", adj = c(0, 0))
text(20, 70, "Protein", col = "darkgreen", adj = c(0, 0))

plot(nutd$Calories ~ nutd$Days, xlab = "", ylab = "", ylim = c(1000, 4000),
     xlim = c(0, newt))
par(new = T)
plot(completecal ~ newdays, type = "l", xlab = "days", ylab = "calories consumed",
     ylim = c(1000, 4000), col = "red", xlim = c(0, newt))
plot(completedef ~ newdays, type = "l", xlab = "days", ylab = "deficit to explain mass loss",
     ylim = c(-2000, 0), xlim = c(0, newt))
plot(TDEE ~ newdays, type = "l", xlab = "days", ylab = "TDEE to explain mass loss",
     ylim = c(1000, 4000), xlim = c(0, newt))
dev.off()