https://github.com/mogankumar/bird-flock-simulation-with-pyspark

A PySpark-based bird flock simulation modeling alignment, cohesion, and separation forces with a leader guiding the flock. Efficiently handles large-scale simulations and generates a visualized GIF of the flock’s movement.
https://github.com/mogankumar/bird-flock-simulation-with-pyspark

argparse matplotlib numpy pyspark python3

Last synced: about 2 months ago
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A PySpark-based bird flock simulation modeling alignment, cohesion, and separation forces with a leader guiding the flock. Efficiently handles large-scale simulations and generates a visualized GIF of the flock’s movement.

• Host: GitHub
• URL: https://github.com/mogankumar/bird-flock-simulation-with-pyspark
• Owner: Mogankumar
• Created: 2025-01-09T18:50:27.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-09T20:06:25.000Z (over 1 year ago)
• Last Synced: 2025-06-02T19:43:44.863Z (about 1 year ago)
• Topics: argparse, matplotlib, numpy, pyspark, python3
• Language: Python
• Homepage:
• Size: 14.1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Bird Flock Simulation with PySpark

This project simulates the behavior of a flock of birds using PySpark for parallel computation. The simulation involves updating the positions and velocities of a group of birds based on forces like alignment, separation, and cohesion. Additionally, a leader bird guides the flock. The simulation results in a visualization and a GIF representing the flock’s behavior over time.

**Features**

	•	Simulates bird flock movement using rules of flocking:

	•	Cohesion: Birds are attracted to the nearest bird within a specific distance.

	•	Separation: Birds maintain a minimum distance to avoid collisions.

	•	Following the leader: Birds follow the leader bird as it moves in a circular path.

	•	Uses PySpark for distributed computation to handle large numbers of birds efficiently.

	•	Visualizes the simulation and generates a compressed GIF.

**How It Works**

	1.	Initialization:

  	•	Random positions and velocities are assigned to the birds.

  	•	A leader bird’s trajectory is defined as a circular path.

	2.	Computation:

  	•	For each frame of the simulation:

  	•	Forces such as cohesion, separation, and alignment are computed for each bird relative to its neighbors.

  	•	The birds’ velocities are updated based on the computed forces, and their positions are updated using the velocities.

	3.	Visualization:

  	•	The simulation is visualized using Matplotlib.

  	•	A GIF of the simulation is created using helper functions.