# 
# Written by:
# -- 
# John L. Weatherwax                2009-04-21
# 
# email: wax@alum.mit.edu
# 
# Please send comments and especially bug reports to the
# above email address.
# 
#-----

save_plots = F

#
# EPage 140
#

DF = read.csv( "../../Data/tumor_size.csv", header=TRUE )

DF_long = reshape( DF, varying=c( "Days_11", "Days_13", "Days_15", "Days_17" ), v.names=c( "size" ), timevar="days", idvar="Mouse", direction="long" )
rownames(DF_long) = NULL
DF_long[DF_long$days==1,2] = 11
DF_long[DF_long$days==2,2] = 13
DF_long[DF_long$days==3,2] = 15
DF_long[DF_long$days==4,2] = 17

if( save_plots ){ postscript("../../WriteUp/Graphics/Chapter6/tgim_spaghetti_plot.eps", onefile=FALSE, horizontal=FALSE) }
interaction.plot(DF_long$days, DF_long$Mouse, DF_long$size, xlab="days", ylab="size", main="spaghetti plot of tumor size by mouse", legend=F)
if( save_plots ){ dev.off() }

# Fit a linear model:
#
m = lm( size ~ days, data=DF_long )
summary(m)

if( save_plots ){ postscript("../../WriteUp/Graphics/Chapter6/tgim_linear_fit.eps", onefile=FALSE, horizontal=FALSE) }
par(mfrow=c(1,2))
plot( DF_long$days, DF_long$size )
abline(m)
plot(m, which=1)
par(mfrow=c(1,1))
if( save_plots ){ dev.off() }

# Try a lograthmic transformation of size:
#
DF_long$lsize = log(DF_long$size)
m2 = lm( lsize ~ days, data=DF_long )
summary(m2)

if( save_plots ){ postscript("../../WriteUp/Graphics/Chapter6/tgim_linear_N_log_fit.eps", onefile=FALSE, horizontal=FALSE) }
plot( DF_long$days, DF_long$size )
abline(m, col='red')
days = unique(DF_long$days)
y_hat = exp( predict( m2, newdata=data.frame(days=days) ) )
points( days, y_hat, type='l', col='green' )
if( save_plots ){ dev.off() }

# Fit a linear model on each mouse separately:
#
all_coeffs = data.frame()
for( mi in 1:10 ){
    mm = lm( size ~ days, data=DF_long[ DF_long$Mouse==mi, ] )
    mc = coef(mm)
    F = data.frame( mouse=mi, intercept=mc[1], slope=mc[2] )
    rownames(F) = NULL
    all_coeffs = rbind( all_coeffs, F )
}
all_coeffs = all_coeffs[ order(all_coeffs$slope), ]
print(all_coeffs)