This R package performs data parsing and analysis tools useful to the University of Maryland Balloon Payload Program (UMDBPP).
R is a versatile scripting language designed for statistics and graphing. It is very similar to MATLAB in the way it approaches data structures; however, I think R is much easier to use and understand.
Click here if you are already familiar with MATLAB, and would like to learn analagous commands in R
If you have not installed R, you can download it from here.
Once you have installed R, running it will open a console window in which you can type commands.
Install the devtools package by running the following command:
install.packages("devtools")
Now you can use devtools to install this package directly from GitHub:
devtools::install_github("UMDBPP/BalloonDataAnalysis")
Load the package using the following command:
library(BalloonDataAnalysis)
In R, to view documentation and usage instructions of a specific command or package, use help(name_of_command) (or precede the command with a question mark ?name_of_command). For example, to view all documentation for this package, run
help(package = "BalloonDataAnalysis")
To view documentation for a specific function once the package is loaded, either run help(function_name), or just ?function_name
The main function in this library is read.payload. It imports data from the log formats of several sources (currently LINK-TLM, CellTracker, preparsed APRS, and IRENE) into useable and standardized data structures in R, adjusts timestamps to local time, and also calculates ascent rates, ground speeds, and downrange distances for CellTracker logs. It also recalulates LINK-TLM ascent rates and ground speeds by callsign to improve accuracy.
The function takes a string file path to the logfile, and also requires that you specify the source (payload) of the log, as well as the flight number, if it is not already in the name of the file. You can optionally specify start and end times, and read.payload will discard entries outside those times and return a truncated dataset.
In the case of LINK-TLM, whose logs can be either .json or .txt, either format will work.
For example, to import LINK-TLM data from NS57, run
NS57.Coord <- read.payload("NS57LaunchData.txt", data_source = "LINK-TLM", start_time = "07:50:31", end_time = "09:27:34")
BalloonDataAnalysis::read.payload(logfile, data_source, flight_number = NULL, flight_date = NULL, start_time = NULL, end_time = NULL, timezone = Sys.timezone())
BalloonDataAnalysis::join.interpolate(data_1, data_2, by = c("DateTime", "Data_Source", "Flight"), exclude = NULL)
BalloonDataAnalysis::map.points(location_data, zoom = 10)