PopG

This project includes a helper script to compile and run the Java application from the command line.

Requirements

• Java JDK installed (javac and java available in PATH)

Run the program

From the project root:

./run.sh

To start a new run immediately at startup (without opening the New Run settings form), use:

./run.sh -n

To auto-save a plot screenshot after a run finishes and then exit the app, use:

./run.sh -n -p=out/plot.png

The script will:

1. Compile src/PopGUserInterface.java into the out/ directory.
2. Run the main class popg.PopGUserInterface.

Run with a JSON defaults file

You can pass a JSON file path to preload default input values.

./run.sh path/to/defaults.json

You can combine it with -n to load defaults and immediately execute the New Run flow:

./run.sh path/to/defaults.json -n

You can also combine defaults, auto-run, and screenshot capture:

./run.sh path/to/defaults.json -n -p=out/plot.png

If the file can be read, any recognized fields in the JSON will override the built-in defaults from initInputVals().

Build an executable JAR

From the project root:

./build.sh

This generates PopG.jar in the project root.

Run the JAR from the command line

java -jar PopG.jar

You can pass the same optional arguments as run.sh:

java -jar PopG.jar -n
java -jar PopG.jar path/to/defaults.json
java -jar PopG.jar path/to/defaults.json -n
java -jar PopG.jar path/to/defaults.json -n -p=out/plot.png

CLI options:

• -n: start a New Run immediately at startup.
• -p=path/to/file.png: after a run finishes, save a plot screenshot to the given path and close the application. Requires -n.

Supported JSON keys (all optional):

• popSize: initial population size.
• fitGenAA: fitness value for genotype AA.
• fitGenAa: fitness value for genotype Aa.
• fitGenaa: fitness value for genotype aa.
• mutAa: mutation rate from allele A to a.
• mutaA: mutation rate from allele a to A.
• migRate: migration rate between populations.
• initFreq: initial frequency of allele A.
• genRun: number of generations to simulate.
• numPop: number of populations in the simulation.
• genSeed: whether to generate a random seed automatically.
• randSeed: explicit random seed value (used when genSeed is false).

Example JSON

{
  "popSize": 250,
  "fitGenAA": 0.95,
  "fitGenAa": 1.0,
  "fitGenaa": 1.05,
  "mutAa": 0.001,
  "mutaA": 0.002,
  "migRate": 0.01,
  "initFreq": 0.4,
  "genRun": 200,
  "numPop": 15,
  "genSeed": false,
  "randSeed": 42
}