Last active
September 23, 2024 04:51
-
-
Save Sonictherocketman/2a1c9ec1cd5bb2e80df6e22d7428f2bb to your computer and use it in GitHub Desktop.
A very crude galaxy simulator.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| """ | |
| Code by: | |
| Brian Schrader | |
| 09-21-2024 | |
| """ | |
| from datetime import datetime | |
| import logging | |
| import os.path | |
| import json | |
| import time | |
| import numpy as np | |
| from numpy.linalg import inv | |
| import matplotlib.pyplot as plt | |
| from matplotlib import animation | |
| from matplotlib import cm | |
| from matplotlib import colors | |
| from scipy.spatial.distance import euclidean | |
| logger = logging.getLogger(__name__) | |
| logging.basicConfig(level=logging.INFO) | |
| G = -6.6743 * 10e-11 | |
| R_ones = None # This value is just based on the size of the matrix given. | |
| # It doesn't change once the params are set. This is a cache. | |
| def R(P_n): | |
| P_n_T = P_n.T | |
| # This is from here: | |
| # https://stackoverflow.com/a/46700369 | |
| return np.linalg.norm(P_n_T - P_n_T[:,None], axis=-1) | |
| def A(P_n, GM): | |
| global R_ones | |
| G_M_P = GM * P_n | |
| R_cu = R(P_n) ** 3 | |
| if R_ones is None: | |
| R_ones = np.ones(R_cu.shape) | |
| R_recp = np.divide(R_ones, R_cu, out=np.zeros_like(R_ones), where=R_cu!=0) | |
| return G_M_P * np.sum(R_recp, axis=0) | |
| def P_V(P_n1, V_n1, GM, dt=1): | |
| a_n = A(P_n1, GM) | |
| V_n = V_n1 + a_n * dt | |
| P_n = P_n1 + V_n1 * dt + 0.5 * a_n * dt**2 | |
| return P_n, V_n | |
| def plot(Ps, limit, anim_step=10): | |
| logger.info('Plotting...') | |
| cmap = colors.ListedColormap(['black', 'lightgreen']) | |
| bounds = [0,1] | |
| norm = colors.BoundaryNorm(bounds, cmap.N) | |
| fig, ax = plt.subplots(subplot_kw={"projection": "3d"}) | |
| ax.set_title(f'P: Position t=0') | |
| ax.set_xlim([0, limit]) | |
| ax.set_ylim([0, limit]) | |
| ax.set_zlim([0, limit]) | |
| ax.grid(True) | |
| def update(args): | |
| t, P = args | |
| ax.clear() | |
| ax.set_xlim([-limit, limit]) | |
| ax.set_ylim([-limit, limit]) | |
| ax.set_zlim([-limit, limit]) | |
| ax.set_title(f'P: Position {t=}') | |
| plot = ax.scatter(P[0], P[1], P[2], s=1) | |
| return plot | |
| ani = animation.FuncAnimation( | |
| fig=fig, | |
| func=update, | |
| frames=list(enumerate(Ps))[::anim_step], | |
| interval=100, | |
| ) | |
| ts = datetime.now().strftime('%Y-%M-%d-%H-%M') | |
| ani.save(f'simulation-{ts}.m4v') | |
| plt.close() | |
| def simulate( | |
| P_0, | |
| V_0, | |
| M, | |
| steps, | |
| args=None, | |
| update_interval=100, | |
| ): | |
| logger.info('Running...') | |
| Ps = [P_0] | |
| V_prev = V_0 | |
| t = 0 | |
| GM = G * M | |
| start = t0 = time.time() | |
| for t in range(steps): | |
| P_t, V_t = P_V(Ps[-1], V_prev, GM) | |
| Ps.append(P_t) | |
| V_prev = V_t | |
| if t % update_interval == 0: | |
| logger.info(f'{t=}: d[{update_interval}] = {(time.time()-t0):.2f}s') | |
| t0 = time.time() | |
| logger.info( | |
| f'Simulation complete! ({t=} steps) - total time = {(time.time()-start):.2f}s' | |
| ) | |
| return Ps | |
| def main(n_nodes=1_500, p_scale=2e11, steps=100_000, v_scale=1e5, m_scale=2e30): | |
| logger.info(f'Settings: {n_nodes=}, {p_scale=}, {v_scale=}, {m_scale=}, {steps=}') | |
| P_0 = np.random.randint(-p_scale, p_scale, size=(3, n_nodes)) | |
| V_0 = np.random.randint(-v_scale, v_scale, size=(3, n_nodes)) | |
| M = m_scale * np.random.uniform(0.7, 10, size=n_nodes) | |
| Ps = simulate(P_0, V_0, M, steps) | |
| plot(Ps, p_scale * 1.2) | |
| if __name__ == '__main__': | |
| main() |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment