growth-pH.R

#plotting growth curve with additional data encoded as the color fill of a geom_tile
# in this case, it is pH
library(ggplot2)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(growthcurver)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

load("growth.ph.rdata")

lb <- growth.ph %>% filter(medium=="lb")
nay <- growth.ph %>% filter(medium=="nay")
model.lb <- SummarizeGrowth(lb$time,lb$od)
model.nay <- SummarizeGrowth(nay$time,nay$od)
lb$model <- predict(model.lb$model)
nay$model <- predict(model.nay$model)
growth.ph <- rbind(lb,nay)

growth.ph %>% ggplot() + 
  geom_point(aes(x=time, y=od), alpha=1/2) + 
  geom_tile(aes(x=time, y=11, fill=pH), width=1.5) + 
  facet_grid(medium ~ .) + 
  scale_fill_gradient(low = "red",high = "green") +
  geom_line(aes(time,model), color="red", alpha=0.5)+
  theme_bw()

# the pH measurements are overlapping, therefore no alpha here

#or, to express the pH as the points' color
p <- growth.ph %>% ggplot() + 
    geom_point(aes(x=time, y=od, color=pH)) + 
    facet_grid(medium ~ .) + 
    geom_line(aes(time,model), color="red", alpha=0.5)+
    scale_color_gradient(low="red", high="green") +
    theme_bw()
p

#or, using plotly
ggplotly(p)

#enjoy!