R Knitr not printing model results to finle - r

Question

I have an R script that is generating a number of plots and well as assessing a few linear models. For some reason when I try to print out the plots and linear model statistics in a loop they don't end up in the file but when I remove the loop they get printed to file.
R/Knitr markup that doesn't work (desired lines to print with # I want this to print):
library('RODBC')
library('ggplot2')
library('dplyr')
library('reshape2')
con <- odbcConnect('yield_model')
sql <- "SELECT DISTINCT [grouping],[group],regionId,class,finalPk,avgArea,layer,runTime,random,name FROM dbo.pk p LEFT OUTER JOIN dred.dbo.yasMap y ON p.class = y.id WHERE random=1"
values <- sqlQuery(con,sql,stringsAsFactors = FALSE)
values$model = "NM"
groupings <- unique(select(values,regionId,class,layer))
groupings <- groupings[order(groupings$layer,groupings$regionId,groupings$class),]
for(i in 1:nrow(groupings)) {
data <- subset(values,regionId == groupings$regionId[i] & class == groupings$class[i] & layer == groupings$layer[i])
layer <- unique(select(data,layer))
region <- unique(select(data,regionId))
defectNo <- unique(select(data,class))
defectName <- unique(select(data,name))
count <- length(unique(data$avgArea))
average <- mean(data$finalPk)
myPlot <- ggplot(data=data,aes(x=avgArea,y=finalPk)) +
geom_point(size=4,color="red") +
ggtitle(paste("Defect=",defectName$name,"(", defectNo$class,"), Region=",region$regionId, ", Layer=", layer$layer,sep="")) +
geom_abline(intercept=average,slop=0,size=1,aes(color="mean"))
if(count > 1) {
myPlot <- myPlot + stat_smooth(method ="lm",formula = y ~ x, se = FALSE,size=1,aes(color="linear"))
}
if (count > 3) {
myPlot <- myPlot + stat_smooth(method = "lm", formula = y ~ log(x), se = FALSE, size=1, aes(color="log"))
myPlot <- myPlot + stat_smooth(method = "lm", formula = y ~ poly(x,2), se = FALSE, size=1, aes(color="poly"))
}
if(count > 1 & count < 4) {
myPlot <- myPlot + scale_colour_manual(name="",values=c("mean" = "orange","linear" = "green"))
} else if(count > 3) {
myPlot <- myPlot + scale_colour_manual(name="",values=c("mean" = "orange","linear" = "green","log" = "red","poly" = "blue"))
} else if (count == 2 | count == 3) {
}
plot(myPlot)
paste("Average Pk=",average,sep="") # I want this to print
if(count > 1) {
linMod <- lm(data$finalPk ~ data$avgArea)
coef(linMod) # I want this to print
summary(linMod) # I want this to print
}
if (count > 3) {
linModLog <- lm(data$finalPk ~ log(data$avgArea))
coef(linModLog) # I want this to print
summary(linModLog) # I want this to print
linModPoly <- lm(data$finalPk ~ poly(data$avgArea,2))
coef(linModPoly) # I want this to print
summary(linModPoly) # I want this to print
}
}
R/Knitr that does print:
library('RODBC')
library('ggplot2')
library('dplyr')
library('reshape2')
con <- odbcConnect('yield_model')
sql <- "SELECT DISTINCT [grouping],[group],regionId,class,finalPk,avgArea,layer,runTime,random,name FROM dbo.pk p LEFT OUTER JOIN dred.dbo.yasMap y ON p.class = y.id WHERE random=1"
values <- sqlQuery(con,sql,stringsAsFactors = FALSE)
values$model = "NM"
groupings <- unique(select(values,regionId,class,layer))
groupings <- groupings[order(groupings$layer,groupings$regionId,groupings$class),]
#for(i in 1:nrow(groupings)) {
i <- 1
data <- subset(values,regionId == groupings$regionId[i] & class == groupings$class[i] & layer == groupings$layer[i])
layer <- unique(select(data,layer))
region <- unique(select(data,regionId))
defectNo <- unique(select(data,class))
defectName <- unique(select(data,name))
count <- length(unique(data$avgArea))
average <- mean(data$finalPk)
myPlot <- ggplot(data=data,aes(x=avgArea,y=finalPk)) +
geom_point(size=4,color="red") +
ggtitle(paste("Defect=",defectName$name,"(", defectNo$class,"), Region=",region$regionId, ", Layer=", layer$layer,sep="")) +
geom_abline(intercept=average,slop=0,size=1,aes(color="mean"))
if(count > 1) {
myPlot <- myPlot + stat_smooth(method ="lm",formula = y ~ x, se = FALSE,size=1,aes(color="linear"))
}
if (count > 3) {
myPlot <- myPlot + stat_smooth(method = "lm", formula = y ~ log(x), se = FALSE, size=1, aes(color="log"))
myPlot <- myPlot + stat_smooth(method = "lm", formula = y ~ poly(x,2), se = FALSE, size=1, aes(color="poly"))
}
if(count > 1 & count < 4) {
myPlot <- myPlot + scale_colour_manual(name="",values=c("mean" = "orange","linear" = "green"))
} else if(count > 3) {
myPlot <- myPlot + scale_colour_manual(name="",values=c("mean" = "orange","linear" = "green","log" = "red","poly" = "blue"))
} else if (count == 2 | count == 3) {
}
plot(myPlot)
paste("Average Pk=",average,sep="") # I want this to print
if(count > 1) {
linMod <- lm(data$finalPk ~ data$avgArea)
coef(linMod) # I want this to print
summary(linMod) # I want this to print
}
if (count > 3) {
linModLog <- lm(data$finalPk ~ log(data$avgArea))
coef(linModLog) # I want this to print
summary(linModLog) # I want this to print
linModPoly <- lm(data$finalPk ~ poly(data$avgArea,2))
coef(linModPoly) # I want this to print
summary(linModPoly) # I want this to print
}
#}
My header values (I also tried with no results portion at all):
{r echo=FALSE,results='asis'}
Hopefully somebody has some advice for me. Appreciate the help!

Answer 1

Given that it's everything after the plot(myPlot) statement which is giving you problems in the loop, I'm thinking the answer here might apply to you.
Try adding a plot.new call after the plot(myPlot) statement