oscarlocator/find_overlap_passes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ephem\n",
    "\n",
    "philly = ephem.Observer()\n",
    "philly.lon, philly.lat = '-75.16961', '39.92435'\n",
    "\n",
    "portland = ephem.Observer()\n",
    "portland.lon, portland.lat = '-122.68092', '45.50901'\n",
    "\n",
    "fo_29 = ephem.readtle(\n",
    "    \"JAS-2 (FO-29)\",\n",
    "    \"1 24278U 96046B   19132.42991715  .00000011  00000-0  48833-4 0  9994\",\n",
    "    \"2 24278  98.5319 290.9039 0349934 336.8182  21.7496 13.53090691122769\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "philly.date = '2019/5/12'\n",
    "portland.date = '2019/5/12'\n",
    "\n",
    "def next_n_passses(location, sat, n):\n",
    "    passes = []\n",
    "    for i in range(n):\n",
    "        info = location.next_pass(sat)\n",
    "        passes.append((info[0], info[4], info[3]))\n",
    "        location.date = info[4] + 0.01\n",
    "    return passes\n",
    "\n",
    "philly_passes = next_n_passses(philly, fo_29, 20)\n",
    "portland_passes = next_n_passses(portland, fo_29, 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overlap!\n",
      "2019/5/12 00:10:59 2019/5/12 00:23:07\n",
      "2019/5/12 00:09:52 2019/5/12 00:30:50\n",
      "0.9643829464912415 6:18:04.0 61:33:22.3\n",
      "overlap!\n",
      "2019/5/12 08:35:52 2019/5/12 08:53:00\n",
      "2019/5/12 08:45:29 2019/5/12 08:55:52\n",
      "1.2769035622477531 78:39:18.9 5:29:38.7\n",
      "overlap!\n",
      "2019/5/12 10:24:19 2019/5/12 10:36:32\n",
      "2019/5/12 10:25:41 2019/5/12 10:42:03\n",
      "0.3876809626817703 8:48:42.3 31:01:27.2\n",
      "overlap!\n",
      "2019/5/12 21:28:51 2019/5/12 21:49:59\n",
      "2019/5/12 21:34:01 2019/5/12 21:40:30\n",
      "1.4334367364645004 83:18:54.0 1:11:06.4\n",
      "overlap!\n",
      "2019/5/12 23:14:45 2019/5/12 23:32:03\n",
      "2019/5/12 23:15:04 2019/5/12 23:34:39\n",
      "0.17535218596458435 18:16:17.0 28:19:05.9\n",
      "overlap!\n",
      "2019/5/13 07:41:14 2019/5/13 07:57:51\n",
      "2019/5/13 07:55:31 2019/5/13 07:59:13\n",
      "0.6650917669758201 38:36:50.8 0:30:25.8\n",
      "overlap!\n",
      "2019/5/13 09:26:37 2019/5/13 09:42:48\n",
      "2019/5/13 09:32:31 2019/5/13 09:46:39\n",
      "0.2721569836139679 29:40:06.1 14:04:29.7\n",
      "overlap!\n",
      "2019/5/13 22:19:08 2019/5/13 22:39:15\n",
      "2019/5/13 22:20:55 2019/5/13 22:36:46\n",
      "0.5122278779745102 40:32:54.0 11:11:59.4\n",
      "overlap!\n",
      "2019/5/14 00:05:49 2019/5/14 00:18:37\n",
      "2019/5/14 00:04:52 2019/5/14 00:25:53\n",
      "0.8954902663826942 7:07:52.2 58:26:20.3\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "overlap_count = 0\n",
    "for o_rise, o_set, o_max in philly_passes:\n",
    "    for t_rise, t_set, t_max in portland_passes:\n",
    "        if t_rise < o_set and t_set > o_rise:\n",
    "            overlap_count += 1\n",
    "            print(\"overlap!\")\n",
    "            print(o_rise, o_set)\n",
    "            print(t_rise, t_set)\n",
    "            print(abs(o_max - t_max), o_max, t_max)\n",
    "\n",
    "print(overlap_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
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