In APridgeon/GFS3000AnalysR: GFS3000 csv Importer

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Quick guide

This is a quick quide on how to use the GFS3000AnalysR package to import GFS3000 .csv files easily into R.

First load the package.

library(GFS3000AnalysR)

Import files

Using a path to your file of interest (here a path to the example data set is used) use the import.single.GFS3000() function to import your data.

file - corresponds to the filepath
names - option to add a name column
time0s - option to add a column that has time in mins - with time 0 as your time of choice. Must be a string "yyyy-m-d H:M:S".

#Path to example dataset
path = system.file("extdata", "exampleData.csv",package = "GFS3000AnalysR")

#Import the data
dataframe = import.single.GFS3000(file = path, names = "Name", time0s = "2019-11-04 13:59:43")

If you had multiple runs in a single .csv file (with plants under different object numbers) you can still use import.single.GFS3000(). An example is shown below.

names - an optional list of names, where the first name corresponds to object 0001, the second to object 0002, etc...
time0s - an optional list of time0s ("yyyy-m-d H:M:S"), the first corresponds to object 0001, the second to object 0002, etc...

#Importing multiuple runs from a single .csv file
dataframe = import.single.GFS3000(file = path, 
                                  names = c("Name1","Name2"), 
                                  time0s = c("2019-11-04 13:59:43", "2019-11-04 15:59:43"))

If you had multiple runs over multiple files (a single run on each file) you can use the import.multiple.GFS3000 function. This reads all of the files and outputs them into one big file.

files - a list of file paths
names - a list of names for each file
time0s - an optional list of time0s ("yyyy-m-d H:M:S") for each file

path1= path
path2=path
path3=path

#Importing runs over multiple .csv files
dataframe = import.multiple.GFS3000(files = c(path1,path2,path3),
                                    names =  c("Name1","Name2","Name3"),
                                    time0s = c("2019-11-04 13:59:43", 
                                               "2019-11-05 13:59:43", 
                                               "2019-11-06 15:59:43"))

Change leaf area

If you want to change the leaf area of a run you can use the changeLeafArea() function.

dataframe - the dataframe of interest
leafArea - new leaf area in cm2
objectNo - the object number of the leaf you are changing

This function recalculates E, GH2O, A, and ci.

#Path to example dataset
path = system.file("extdata", "exampleData.csv",package = "GFS3000AnalysR")

#Import the data
dataframe = import.single.GFS3000(file = path, names = "Name", time0s = "2019-11-04 13:59:43")

#Change leaf area
dataframe = changeLeafArea(dataframe = dataframe,
                           leafArea = 1.74,
                           objectNo = 1)

Easy plotting of data

After import, the dataframe should be easily plotted using ggplot2 or your favourite method of visualising data in R. Here, graphs with time in mins (determined from the time0 import variable) or in the %Y-%m-%d %H:%M:%S date/ time format.

library(ggplot2)

ggplot(dataframe, aes(TimeNo, GH2O, color = Name)) +
  geom_point()

ggplot(dataframe, aes(DateTime, GH2O, color = Name)) +
  geom_point()