python_solar_simulation/README.txt at master · TheDoktorr/python_solar_simulation · GitHub

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N-body solar system written in Python.
Andrew Hamill   39047415

Imports:
 matplotlib     - plotting
 numpy          - array maths
 os             - used to run terminal commands
 platform       - used to determine operating system
 pickle         - binary file storage

 spiceypy       - transformation matrices
 astrpoy        - gets data from specified ephemeris           - source: https://github.com/poliastro/poliastro/archive/main.zip
 poliastro      - gets mass constants for planetary bodies

If using a environment manager, packages such numpy and matplot can be installed via CLI or GUI,
  1) verify the correct environment is used,

    conda info --envs
    conda activate env-name

  2) list and install packages,

    conda list
    conda isntall pkg-name


Other packages can be obtained through pip, Python's package manager:
    pip install jplephem spiceypy
Poliastro must be obtained from Github,
    pip install https://github.com/poliastro/poliastro/archive/main.zip

File structure:
    Constants.py  and Particle.py
    - These handle mass constants, and the particle class used for all planetary bodies

    Setup.py
    - The main computation file, this handles class creation, initialising variables as well as user input for simulation parameters
        -> prompted when running Simulation.py as it contains a while loop
    - Also contains Kepler's 3rd law calculations as this occurs after the simulation has run

    Simulation.py
    - The main simulation loop, graphing and outputs. This is the file you run.
    - contains code and data saving used for graphs in the report, this is commented out as it's computationally expensive


Known issues:
- "Even when not re-running the simulation, I still have to enter simulation parameters?" - This was an oversight in implementation order causing the same `while True:` loop to run despite no intent to run the sim.
- Graphs included in sim file. - due to variable storage, they cannot be in their own file, as this would be dependent on Setup.py and Simulation.py, which creates circular dependencies.
- Kepler's law calculated outside of class - due to using post-sim. data, there's definitely a better way of doing this...
- .pkl cache file can become quite large, when doing long simulations (~ 1 GB)
- storing data for re-graphing can be very slow on low powered machnines - recommend commenting that out!

How to setup:
1) install necessary packages
1b) if using a lower powered computer (16GB ram recommended, 8GB min) comment out the code for saving data to a .pkl -> # save_pickle(data_store) on line 172 in Simulation.py
2) run Simulation.py
3) wait for ephemeris to download if not ran before
4) follow on screen dialogue