PhotosynQ helps you to make your plant research more efficient. For an advanced analysis, this package allows to pull data from projects right into R. We recommend to use it with RStudio.
If you don’t already have, install RStudio and R first.
Download the latest release of the PhotosynQ R package.
Select the file indicated as Source code (tar.gz)
. This is
the format required by RStudio.
Package Archive File (.tgz; .tar-gz)
For users that already have a development environment, devtools provides an easy installation from the GitHub repository.
install.packages("devtools")
devtools::install_github("PhotosynQ/PhotosynQ-R")
Create a list of data frames in a single step from the data of a
Project. Each frame in the list represents one measurement protocol. A
user account for PhotosynQ is required to access the data. You will
find the ID
of your project on the project
page.
::login("john.doe@domain.com")
PhotosynQ<- 1556
ID <- PhotosynQ::getProject(ID) dfs
The flagged measurements are included in the dataset
and most likely needs to be removed for further analysis. You can use
the filter()
function of the dplyr
library to
remove the flagged measurement from the data frame. You might want to
use the same function to select a subset of measurement from your data
frame.
# Select a Protocol from the List of Data Frames
<- dfs$`Protocol Name`
df
# View the Protocol Output
View(df)
# Filter out flagged data
library(dplyr)
<- filter(df, status == "submitted") df_filtered
<- "john.doe@domain.com"
email <- PhotosynQ::login(email) login
::logout() PhotosynQ
<- 1556
ID <- PhotosynQ::getProjectInfo(ID) project_info
<- 1556
ID <- PhotosynQ::getProjectData(ID)
project_data
# Use raw data
<- FALSE
processed_data <- PhotosynQ::getProjectData(ID, processed_data) project_data
<- PhotosynQ::createDataframe(project_info, project_data) dataframe