GPVPlot: SIMPLE AND EFFICIENT GRAPH GENERATION FOR GEOCHEMICAL DATA

Geologists collect a plethora of geochemical data from a variety of analytical sources. In petrologic and geochemical studies it is routine practice to plot these data on discrimination or "Harker" diagrams to facilitate the identification and interpretation of geochemical trends. While many graphing programs exist, some of which are intended specifically for geologists, none allow the user to quickly graph large, or numerous, data sets for analysis in a side-by-side one page view. GPVPlot is a command-line based program that accomplishes this, enabling geologists and geochemists to rapidly graph large quantities of geochemical data from multiple data sets saved and displayed as a PDF. The program streamlines the plotting process and eliminates the need to plot data individually, saving time and effort.

GPVPlot was written in the open-source languages Perl and gnuplot to maximize availability and customization. Through the computer’s terminal, the program prompts the user with a short series of questions from which a graphical output is generated as a PDF. The user can plot up to eight oxides from as many as ten data sets against a single x-axis variable. Once the user has specified the names of the data sets, the variables, and the range of data to plot (optional), the entire process from graphing the data to saving the graphs as images to embedding them on and displaying a PDF takes between 4 and 6 seconds. GPVPlot is designed to take .CSV files (as generated by a program such as Excel™) and .TXT files (of whitespace-separated values). The program input is flexible and will accept filenames with or without extensions. The program is very low-impact, consisting of only two files requiring ~11 KB of storage space. Because Perl is a Unix-based language, this program is optimized for use on Unix-based machines such as those running Linux and Mac OS X. The result is a compact, efficient, open-source program that rapidly graphs large volumes of geochemical data.