Multi-File Data Visualization with Gnuplot: Efficient Plotting Methods for Time Series and Sequence Numbers

Introduction

In the fields of scientific computing and data analysis, Gnuplot serves as a powerful plotting tool widely used in various data visualization scenarios. In practical applications, researchers often need to plot time series data from multiple sources on the same graph for comparative analysis. This article, based on a typical user case, provides an in-depth discussion of the correct implementation methods for multi-file plotting in Gnuplot.

Problem Analysis

The user encountered a syntax error while attempting to plot data from six text files using Gnuplot. Each file contains two columns of data: the first column represents time (in seconds, as floating-point numbers), and the second column contains sequence numbers. The user aimed to visualize the time-sequence number relationship from all six files in a single chart.

The original code contained a critical syntax error:

plot "print_1012720" using 1:2 title "Flow 1", \
plot "print_1058167" using 1:2 title "Flow 2", \
plot "print_193548"  using 1:2 title "Flow 3", \ 
plot "print_401125"  using 1:2 title "Flow 4", \
plot "print_401275"  using 1:2 title "Flow 5", \
plot "print_401276"  using 1:2 title "Flow 6"

The error message indicated: "plot.plt", line 24: undefined variable: plot. This occurred because Gnuplot interpreted the second and subsequent plot keywords as variable names rather than plotting commands.

Correct Solution

The corrected plot command should use commas to separate multiple data sources, with the plot keyword used only once at the beginning:

plot "print_1012720" using 1:2 title "Flow 1", \
     "print_1058167" using 1:2 title "Flow 2", \
     "print_193548"  using 1:2 title "Flow 3", \ 
     "print_401125"  using 1:2 title "Flow 4", \
     "print_401275"  using 1:2 title "Flow 5", \
     "print_401276"  using 1:2 title "Flow 6"

Complete Configuration Analysis

The complete Gnuplot script configuration is as follows:

set terminal png
set output 'akamai.png'

set xdata time
set timefmt "%S"
set xlabel "time"

set autoscale

set ylabel "highest seq number"
set format y "%s"

set title "seq number over time"
set key reverse Left outside
set grid

set style data linespoints

plot "print_1012720" using 1:2 title "Flow 1", \
     "print_1058167" using 1:2 title "Flow 2", \
     "print_193548"  using 1:2 title "Flow 3", \ 
     "print_401125"  using 1:2 title "Flow 4", \
     "print_401275"  using 1:2 title "Flow 5", \
     "print_401276"  using 1:2 title "Flow 6"

Explanation of configuration items:

• set terminal png: Sets output format to PNG image
• set output 'akamai.png': Specifies output filename
• set xdata time and set timefmt "%S": Configures X-axis as time format using seconds as unit
• set style data linespoints: Sets data points to be connected by lines with point markers displayed
• set key reverse Left outside: Places legend outside the chart on the left side

Advanced Techniques: Automated Plotting

For large numbers of data files, Gnuplot's for loops can be used to achieve automated plotting:

# Method 1: Using filename lists
filenames = "print_1012720 print_1058167 print_193548 print_401125 print_401275 print_401276"
titles = "Flow 1 Flow 2 Flow 3 Flow 4 Flow 5 Flow 6"

plot for [i=1:6] word(filenames, i) using 1:2 title word(titles, i) with linespoints

# Method 2: Using formatted filenames
filename(n) = sprintf("print_%d", [1012720, 1058167, 193548, 401125, 401275, 401276][n])
plot for [i=1:6] filename(i-1) using 1:2 title sprintf("Flow %d", i) with linespoints

Usage Scenarios for replot Command

In interactive sessions, the replot command can be used to gradually add data series:

plot "print_1012720" using 1:2 title "Flow 1"
replot "print_1058167" using 1:2 title "Flow 2"
replot "print_193548" using 1:2 title "Flow 3"
# Continue adding other files...

It's important to note that replot is primarily useful for interactive windows and has limited effectiveness when generating static images like PNG files.

Best Practice Recommendations

1. File Naming Conventions: Use meaningful filenames to facilitate management and automated processing

2. Data Preprocessing: Ensure consistent time formats across all data files to avoid parsing errors

3. Legend Management: When dealing with multiple data series, properly set legend position and style to avoid obscuring data

4. Error Debugging: When encountering syntax errors, carefully examine command structure, particularly the use of line continuation characters in multi-line commands

Conclusion

By correctly using Gnuplot's plot command syntax, users can efficiently visualize data from multiple files in a single chart. The solutions provided in this article not only address specific syntax errors but also introduce advanced techniques such as automated plotting and interactive operations, offering a comprehensive reference for multi-file data visualization to researchers and data analysts.