csv2sa.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9784abe4-7d83-421f-97bb-78dc82965db5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import rebound\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "f5e15f09-0894-40c8-b236-cdb0161aafd7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created Simulationarchive for random <rebound.simulationarchive.Simulationarchive object at 0x143596640, nblobs=24941, reb_version=4.4.5>\n",
      "Created Simulationarchive for resonant <rebound.simulationarchive.Simulationarchive object at 0x143596940, nblobs=102497, reb_version=4.4.5>\n"
     ]
    }
   ],
   "source": [
    "for set in [\"random\", \"resonant\"]:\n",
    "    dataset = np.genfromtxt(set+\"/clean_initial_conditions.csv\", delimiter=\",\", skip_header=1)\n",
    "    sim = rebound.Simulation()\n",
    "    for i in range(4): sim.add()\n",
    "    sim.G=4*np.pi**2\n",
    "    for r, d in enumerate(dataset):\n",
    "        for i in range(4):\n",
    "            sim.particles[i].m = d[1+i*7]\n",
    "            sim.particles[i].xyz = d[2+i*7:5+i*7]\n",
    "            sim.particles[i].vxyz = d[5+i*7:8+i*7]\n",
    "        sim.save_to_file(set+\"/clean_initial_conditions.bin\", delete_file=(r==0))\n",
    "    sa = rebound.Simulationarchive(set+\"/clean_initial_conditions.bin\")\n",
    "    print(\"Created Simulationarchive for\", set, sa)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15a6c2d1-fa49-4541-b68f-e6a44dc9a210",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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