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{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "from collections import namedtuple\n", "from math import degrees\n", "\n", "import cartopy.crs as ccrs\n", "import cartopy.feature as cfeature\n", "import ephem\n", "import matplotlib.pyplot as plt\n", "\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", ")\n", "\n", "lakes = cfeature.NaturalEarthFeature('physical', 'lakes', '50m', facecolor=\"none\")\n", "countries = cfeature.NaturalEarthFeature('cultural', 'admin_0_countries', '50m', facecolor=\"none\")\n", "states = cfeature.NaturalEarthFeature('cultural', 'admin_1_states_provinces_lines', '50m', facecolor=\"none\")" ] }, { "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)\n", "\n", "best_overlap = {\"score\": 10000}\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", " score = abs(o_max - t_max)\n", " if best_overlap[\"score\"] > score:\n", " best_overlap = {\n", " \"score\": score,\n", " \"rise\": o_rise\n", " }" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "Point = namedtuple('Point', 'lats lons')\n", "ground_track = Point([], [])\n", "for i in range(300):\n", " t = best_overlap['rise'] - 0.01 + i/10000.0\n", " fo_29.compute(t)\n", " ground_track.lats.append(degrees(fo_29.sublat))\n", " ground_track.lons.append(degrees(fo_29.sublong))\n", "\n", "begin = best_overlap['rise'] - 0.01\n", "philly.date = begin\n", "philly_pass = philly.next_pass(fo_29)\n", "fo_29.compute(philly_pass[0])\n", "philly_aos = Point(degrees(fo_29.sublat), degrees(fo_29.sublong))\n", "\n", "fo_29.compute(philly_pass[2])\n", "philly_max = Point(degrees(fo_29.sublat), degrees(fo_29.sublong))\n", "\n", "fo_29.compute(philly_pass[4])\n", "philly_los = Point(degrees(fo_29.sublat), degrees(fo_29.sublong))\n", "\n", "\n", "portland.date = begin\n", "portland_pass = portland.next_pass(fo_29)\n", "fo_29.compute(portland_pass[0])\n", "portland_aos = Point(degrees(fo_29.sublat), degrees(fo_29.sublong))\n", "\n", "fo_29.compute(portland_pass[2])\n", "portland_max = Point(degrees(fo_29.sublat), degrees(fo_29.sublong))\n", "\n", "fo_29.compute(portland_pass[4])\n", "portland_los = Point(degrees(fo_29.sublat), degrees(fo_29.sublong))" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "<Figure size 792x612 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "proj = ccrs.AzimuthalEquidistant(\n", " central_longitude=-95,\n", " central_latitude=35,\n", ")\n", "geodetic = ccrs.Geodetic()\n", "\n", "fig = plt.figure(figsize=(11, 8.5))\n", "ax = fig.add_axes([0.1, 0.1, 0.9, 0.9], projection=proj)\n", "ax.set_extent([-140, -50, 5, 85], ccrs.Geodetic())\n", "ax.coastlines(resolution='50m', color=\"grey\", linewidth=0.5, alpha=0.5)\n", "ax.add_feature(lakes, edgecolor=\"grey\", linewidth=0.5, alpha=0.5)\n", "ax.add_feature(states, edgecolor=\"grey\", linewidth=0.5, alpha=0.3, dashes='--')\n", "ax.add_feature(countries, edgecolor=\"grey\", linewidth=0.5, alpha=0.4, dashes='--')\n", "\n", "\n", "ax.plot(ground_track.lons, ground_track.lats, 'k', lw=1, alpha=1, transform=geodetic)\n", "ax.plot([degrees(philly.lon), philly_aos.lons], [degrees(philly.lat), philly_aos.lats], 'k--', lw=0.5, transform=geodetic)\n", "ax.plot([degrees(philly.lon), philly_max.lons], [degrees(philly.lat), philly_max.lats], transform=geodetic)\n", "ax.plot([degrees(philly.lon), philly_los.lons], [degrees(philly.lat), philly_los.lats], 'k--', lw=0.5, transform=geodetic)\n", "\n", "ax.plot([degrees(portland.lon), portland_aos.lons], [degrees(portland.lat), portland_aos.lats], 'k--', lw=0.5, transform=geodetic)\n", "ax.plot([degrees(portland.lon), portland_max.lons], [degrees(portland.lat), portland_max.lats], transform=geodetic)\n", "ax.plot([degrees(portland.lon), portland_los.lons], [degrees(portland.lat), portland_los.lats], 'k--', lw=0.5, transform=geodetic)\n", "\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2}
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