N Body Problem.ipynb

n-body-problem.ipynb

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        "<a href=\"https://colab.research.google.com/gist/tensorvijay/2c5d0cb7d3174438bf3e98aad18cd2b4/n-body-problem.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "code",
      "metadata": {
        "id": "eiKuAO6IS46Z"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from mpl_toolkits.mplot3d import Axes3D\n",
        "\n",
        "class Body():\n",
        "\n",
        "    \"\"\"\n",
        "    This class contains adjustable parameters as attributes. These\n",
        "    parameters include current and previous positions, velocities, and\n",
        "    accelerations.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(self, identifier, facecolor, position, mass=1, velocity=None, acceleration=None, notes=None):\n",
        "        \"\"\"\n",
        "        identifier:\n",
        "            type <str>\n",
        "\n",
        "        facecolor:\n",
        "            type <str>\n",
        "\n",
        "        position:\n",
        "            type <tuple / list / array>\n",
        "\n",
        "        mass:\n",
        "            type <int / float>\n",
        "\n",
        "        velocity:\n",
        "            type <tuple / list / array> or None\n",
        "\n",
        "        acceleration:\n",
        "            type <tuple / list / array> or None\n",
        "\n",
        "        notes:\n",
        "            type <str> or None\n",
        "        \"\"\"\n",
        "        self.identifier = identifier\n",
        "        self.facecolor = facecolor\n",
        "        self.position = np.array(position, dtype=float)\n",
        "        self.mass = mass\n",
        "        self.velocity = self.autocorrect_parameter(velocity)\n",
        "        self.acceleration = self.autocorrect_parameter(acceleration)\n",
        "        self._vector_position = [self.position]\n",
        "        self._vector_velocity = [self.velocity]\n",
        "        self._vector_acceleration = [self.acceleration]\n",
        "        self.notes = notes\n",
        "\n",
        "    def __str__(self):\n",
        "        res = ''\n",
        "        for key in ('identifier', 'vector_position'):\n",
        "            value = getattr(self, key)\n",
        "            text = '\\n .. {}:\\n\\t{}\\n'.format(key, value)\n",
        "            res += '{}'.format(text)\n",
        "        return res\n",
        "\n",
        "    def autocorrect_parameter(self, args):\n",
        "        \"\"\"\n",
        "        args:\n",
        "            type <tuple / list / array> or None\n",
        "        \"\"\"\n",
        "        if args is None:\n",
        "            return np.zeros(self.position.shape, dtype=float)\n",
        "        else:\n",
        "            return np.array(args, dtype=float)\n",
        "\n",
        "    @property\n",
        "    def vector_position(self):\n",
        "        return np.array(self._vector_position)\n",
        "\n",
        "    @property\n",
        "    def vector_velocity(self):\n",
        "        return np.array(self._vector_velocity)\n",
        "\n",
        "    @property\n",
        "    def vector_acceleration(self):\n",
        "        return np.array(self._vector_acceleration)\n",
        "\n",
        "    @property\n",
        "    def scalar_position(self):\n",
        "        return np.sqrt(np.sum(np.square(self.vector_position), axis=1))\n",
        "\n",
        "    @property\n",
        "    def scalar_velocity(self):\n",
        "        return np.sqrt(np.sum(np.square(self.vector_velocity), axis=1))\n",
        "\n",
        "    @property\n",
        "    def scalar_acceleration(self):\n",
        "        return np.sqrt(np.sum(np.square(self.vector_acceleration), axis=1))\n",
        "\n",
        "    def get_vector(self, parameter):\n",
        "        \"\"\"\n",
        "        parameter:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        attribute = 'vector_{}'.format(parameter)\n",
        "        return getattr(self, attribute)\n",
        "\n",
        "    def get_scalar(self, parameter):\n",
        "        \"\"\"\n",
        "        parameter:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        attribute = 'scalar_{}'.format(parameter)\n",
        "        return getattr(self, attribute)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ICfjnkFLTHn4"
      },
      "source": [
        "class GravitationalDynamics():\n",
        "\n",
        "    \"\"\"\n",
        "    This class contains methods to run a simulation of N bodies that interact\n",
        "    gravitationally over some time. Each body in the simulation keeps a record\n",
        "    of parameters (position, velocity, and acceleration) as time progresses.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(self, bodies, t=0, gravitational_constant=6.67e-11):\n",
        "        \"\"\"\n",
        "        bodies:\n",
        "            type <tuple / list / array>\n",
        "\n",
        "        t:\n",
        "            type <int / float>\n",
        "\n",
        "        gravitational_constant:\n",
        "            type <float>\n",
        "        \"\"\"\n",
        "        self._bodies = bodies\n",
        "        self.nbodies = len(bodies)\n",
        "        self.ndim = len(bodies[0].position)\n",
        "        self.t = t\n",
        "        self._moments = [t]\n",
        "        self.gravitational_constant = gravitational_constant\n",
        "        # self._collision_times = []\n",
        "\n",
        "    @property\n",
        "    def bodies(self):\n",
        "        return self._bodies\n",
        "\n",
        "    @property\n",
        "    def moments(self):\n",
        "        return np.array(self._moments)\n",
        "\n",
        "    def get_acceleration(self, ibody, jbody):\n",
        "        \"\"\"\n",
        "        ibody:\n",
        "            type <custom class: Body>\n",
        "\n",
        "        jbody:\n",
        "            type <custom class: Body>\n",
        "        \"\"\"\n",
        "        dpos = ibody.position - jbody.position\n",
        "        r = np.sum(dpos**2)\n",
        "        acc = -1 * self.gravitational_constant * jbody.mass * dpos / np.sqrt(r**3)\n",
        "        return acc\n",
        "\n",
        "    def update_accelerations(self):\n",
        "        for ith_body, ibody in enumerate(self.bodies):\n",
        "            ibody.acceleration *= 0\n",
        "            for jth_body, jbody in enumerate(self.bodies):\n",
        "                if ith_body != jth_body:\n",
        "                    acc = self.get_acceleration(ibody, jbody)\n",
        "                    ibody.acceleration += acc\n",
        "            ibody._vector_acceleration.append(np.copy(ibody.acceleration))\n",
        "\n",
        "    def update_velocities_and_positions(self, dt):\n",
        "        \"\"\"\n",
        "        dt:\n",
        "            type <int / float>\n",
        "        \"\"\"\n",
        "        for ith_body, ibody in enumerate(self.bodies):\n",
        "            ibody.velocity += ibody.acceleration * dt\n",
        "            ibody.position += ibody.velocity * dt\n",
        "            ibody._vector_velocity.append(np.copy(ibody.velocity))\n",
        "            ibody._vector_position.append(np.copy(ibody.position))\n",
        "\n",
        "    def simulate(self, dt, duration):\n",
        "        \"\"\"\n",
        "        dt:\n",
        "            type <int / float>\n",
        "\n",
        "        duration:\n",
        "            type <int / float>\n",
        "        \"\"\"\n",
        "        nsteps = int(duration / dt)\n",
        "        for ith_step in range(nsteps):\n",
        "            self.update_accelerations()\n",
        "            self.update_velocities_and_positions(dt)\n",
        "            self.t += dt\n",
        "            self._moments.append(self.t)\n",
        "            ## check collisions\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xw1g2jWFTuwo"
      },
      "source": [
        "class UnitConversions():\n",
        "\n",
        "    \"\"\"\n",
        "    This class contains methods to convert measurements from one unit to\n",
        "    another. Measurable quantities include distance, time, velocity, mass,\n",
        "    and acceleration. All values are scaled to their corresponding units\n",
        "    such that each base quantity measured in SI units has a value of 1.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(self):\n",
        "        self.distance_units = ('meter', 'kilometer', 'mile', 'Astronomical Unit', 'Light Year', 'parsec')\n",
        "        self.distance_values = (1, 1000, 1609, 1.496e11, 9.461e15, 3.086e16)\n",
        "        self.time_units = ('second', 'hour', 'day', 'year')\n",
        "        self.time_values = (1, 3600, 3600*24, 3600*24*365)\n",
        "        self.mass_units = ('gram', 'kilogram', 'lunar mass', 'earth mass', 'solar mass')\n",
        "        self.mass_values = (1/1000, 1, 7.3459e22, 5.9722e24, 1.988e30)\n",
        "        self.distance_conversion_factors = self.get_conversion_factors(self.distance_units, self.distance_values, base_unit='meter')\n",
        "        self.time_conversion_factors = self.get_conversion_factors(self.time_units, self.time_values, base_unit='second')\n",
        "        self.mass_conversion_factors = self.get_conversion_factors(self.mass_units, self.mass_values, base_unit='kilogram')\n",
        "\n",
        "    @staticmethod\n",
        "    def get_conversion_factors(units, values, base_unit):\n",
        "        \"\"\"\n",
        "        units:\n",
        "            type <tuple / list / array>\n",
        "\n",
        "        values:\n",
        "            type <tuple / list / array>\n",
        "\n",
        "        base_unit:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        res = {}\n",
        "        for outer_key, outer_value in zip(units, values):\n",
        "            if outer_key == base_unit:\n",
        "                res[outer_key] = dict(zip(units, values))\n",
        "            else:\n",
        "                res[outer_key] = {}\n",
        "                for inner_key, inner_value in zip(units, values):\n",
        "                    res[outer_key][inner_key] = inner_value / outer_value\n",
        "        return res\n",
        "\n",
        "    def convert_distance(self, distance, original_unit, prime_unit='meter'):\n",
        "        \"\"\"\n",
        "        distance:\n",
        "            type <int / float / array>\n",
        "\n",
        "        original_unit:\n",
        "            type <str>\n",
        "\n",
        "        prime_unit:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        conversion_factor = self.distance_conversion_factors[prime_unit][original_unit]\n",
        "        return distance * conversion_factor\n",
        "\n",
        "    def convert_time(self, time, original_unit, prime_unit='second'):\n",
        "        \"\"\"\n",
        "        time:\n",
        "            type <int / float / array>\n",
        "\n",
        "        original_unit:\n",
        "            type <str>\n",
        "\n",
        "        prime_unit:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        conversion_factor = self.time_conversion_factors[prime_unit][original_unit]\n",
        "        return time * conversion_factor\n",
        "\n",
        "    def convert_mass(self, mass, original_unit, prime_unit='kilogram'):\n",
        "        \"\"\"\n",
        "        mass:\n",
        "            type <int / float / array>\n",
        "\n",
        "        original_unit:\n",
        "            type <str>\n",
        "\n",
        "        prime_unit:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        conversion_factor = self.mass_conversion_factors[prime_unit][original_unit]\n",
        "        return mass * conversion_factor\n",
        "\n",
        "    def convert_velocity(self, distance, time, original_distance_unit, original_time_unit, prime_distance_unit='meter', prime_time_unit='second'):\n",
        "        \"\"\"\n",
        "        velocity:\n",
        "            type <int / float / array>\n",
        "\n",
        "        original_distance_unit:\n",
        "            type <str>\n",
        "\n",
        "        original_time_unit:\n",
        "            type <str>\n",
        "\n",
        "        prime_distance_unit:\n",
        "            type <str>\n",
        "\n",
        "        prime_time_unit:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        return self.convert_distance(distance, original_distance_unit, prime_distance_unit) / self.convert_time(time, original_time_unit, prime_time_unit)\n",
        "\n",
        "    def convert_acceleration(self, distance, time, original_distance_unit, original_time_unit, prime_distance_unit='meter', prime_time_unit='second'):\n",
        "        \"\"\"\n",
        "        velocity:\n",
        "            type <int / float / array>\n",
        "\n",
        "        original_distance_unit:\n",
        "            type <str>\n",
        "\n",
        "        original_time_unit:\n",
        "            type <str>\n",
        "\n",
        "        prime_distance_unit:\n",
        "            type <str>\n",
        "\n",
        "        prime_time_unit:\n",
        "            type <str>\n",
        "        \"\"\"\n",
        "        return self.convert_distance(distance, original_distance_unit, prime_distance_unit) / self.convert_time(time, original_time_unit, prime_time_unit)**2\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UCu6VBpRTaVJ"
      },
      "source": [
        "UC = UnitConversions()\n",
        "\n",
        "m_sun = UC.convert_mass(1, original_unit='solar mass', prime_unit='kilogram')\n",
        "Sun = Body(identifier='Sun', facecolor='yellow', mass=m_sun, position=[0, 0, 0])\n",
        "\n",
        "m_mercury = UC.convert_mass(0.05227, original_unit='earth mass', prime_unit='kilogram')\n",
        "d_mercury = UC.convert_distance(0.4392, original_unit='Astronomical Unit', prime_unit='meter')\n",
        "v_mercury = UC.convert_distance(106000, original_unit='mile', prime_unit='meter') / UC.convert_time(1, original_unit='hour', prime_unit='second')\n",
        "Mercury = Body(identifier='Mercury', facecolor='gray', mass=m_mercury, position=[d_mercury, 0, 0], velocity=[0, v_mercury, 0])\n",
        "\n",
        "m_earth = UC.convert_mass(1, original_unit='earth mass', prime_unit='kilogram')\n",
        "d_earth = UC.convert_distance(1, original_unit='Astronomical Unit', prime_unit='meter')\n",
        "v_earth = UC.convert_distance(66600, original_unit='mile', prime_unit='meter') / UC.convert_time(1, original_unit='hour', prime_unit='second')\n",
        "Earth = Body(identifier='Earth', facecolor='blue', mass=m_earth, position=[d_earth, 0, 0], velocity=[0, v_earth, 0])\n",
        "\n",
        "m_mars = UC.convert_mass(0.1704, original_unit='earth mass', prime_unit='kilogram')\n",
        "d_mars = UC.convert_distance(1.653, original_unit='Astronomical Unit', prime_unit='meter')\n",
        "v_mars = UC.convert_distance(53900, original_unit='mile', prime_unit='meter') / UC.convert_time(1, original_unit='hour', prime_unit='second')\n",
        "Mars = Body(identifier='Mars', facecolor='darkred', mass=m_mars, position=[0, d_mars, 0], velocity=[v_mars, 0, 0])\n",
        "\n",
        "bodies = [Sun, Mercury, Earth, Mars]\n",
        "dt = UC.convert_time(2, original_unit='day', prime_unit='second')\n",
        "duration = UC.convert_time(10, original_unit='year', prime_unit='second')\n",
        "\n",
        "GD = GravitationalDynamics(bodies)\n",
        "GD.simulate(dt, duration)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
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        "outputId": "aa1091ee-8b0c-48d2-a066-8b26b7308725"
      },
      "source": [
        "fig = plt.figure(figsize=(11, 7))\n",
        "ax_left = fig.add_subplot(1, 2, 1, projection='3d')\n",
        "ax_left.set_title('3-D Position')\n",
        "ax_right = fig.add_subplot(1, 2, 2)\n",
        "ax_right.set_title('Displacement vs Time')\n",
        "ts = UC.convert_time(GD.moments, original_unit='second', prime_unit='year')\n",
        "xticks = np.arange(max(ts)+1).astype(int)\n",
        "\n",
        "for body in GD.bodies:\n",
        "    vector = body.get_vector('position')\n",
        "    vector_coordinates = UC.convert_distance(vector, original_unit='meter', prime_unit='Astronomical Unit')\n",
        "    scalar = body.get_scalar('position')\n",
        "    scalar_coordinates = UC.convert_distance(scalar, original_unit='meter', prime_unit='Astronomical Unit')\n",
        "    ax_left.scatter(*vector_coordinates.T, marker='.', c=body.facecolor, label=body.identifier)\n",
        "    ax_right.scatter(ts, scalar_coordinates, marker='.', c=body.facecolor, label=body.identifier)\n",
        "ax_right.set_xticks(xticks)\n",
        "ax_right.grid(color='k', linestyle=':', alpha=0.3)\n",
        "fig.subplots_adjust(bottom=0.3)\n",
        "fig.legend(loc='lower center', mode='expand', ncol=len(GD.bodies))\n",
        "plt.show()\n",
        "plt.close(fig)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "id": "tv5Aa_pOlhtV",
        "outputId": "d4c038d8-9349-41b0-c2f3-ffe8a03aef62"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from mpl_toolkits.mplot3d import Axes3D\n",
        "\n",
        "class Body():\n",
        "    \"\"\"\n",
        "    This class contains adjustable parameters as attributes. These\n",
        "    parameters include current and previous positions, velocities, and\n",
        "    accelerations.\n",
        "    \"\"\"\n",
        "    def __init__(self,\n",
        "                 id, facecolor, pos,\n",
        "                 mass=1, vel=None, acc=None):\n",
        "        self.id = id\n",
        "        self.facecolor = facecolor\n",
        "        self.pos = np.array(pos, dtype=float)\n",
        "        self.mass = mass\n",
        "        self.vel = self.autocorrect_parameter(vel)\n",
        "        self.acc = self.autocorrect_parameter(acc)\n",
        "        self.vector_pos = [self.pos]\n",
        "        self.vector_vel = [self.vel]\n",
        "        self.vector_acc = [self.acc]\n",
        "\n",
        "    def autocorrect_parameter(self, args):\n",
        "        if args is None:\n",
        "            return np.zeros(self.pos.shape, dtype=float)\n",
        "        return np.array(args, dtype=float)\n",
        "\n",
        "    def scalar_pos(self):\n",
        "        return np.sqrt(np.sum(np.square(self.vector_pos), axis=1))\n",
        "\n",
        "class GravitationalDynamics():\n",
        "    \"\"\"\n",
        "    This class contains methods to run a simulation of N bodies that interact\n",
        "    gravitationally over some time. Each body in the simulation keeps a record\n",
        "    of parameters (pos, vel, and acc) as time progresses.\n",
        "    \"\"\"\n",
        "    def __init__(self, bodies, t=0, gravitational_constant=6.67e-11):\n",
        "        self.bodies = bodies\n",
        "        self.nbodies = len(bodies)\n",
        "        self.ndim = len(bodies[0].pos)\n",
        "        self.t = t\n",
        "        self.moments = [t]\n",
        "        self.gravitational_constant = gravitational_constant\n",
        "\n",
        "    def get_acc(self, ibody, jbody):\n",
        "        dpos = ibody.pos - jbody.pos\n",
        "        r = np.sum(dpos**2)\n",
        "        acc = -1 * self.gravitational_constant * jbody.mass \\\n",
        "            * dpos / np.sqrt(r**3)\n",
        "        return acc\n",
        "\n",
        "    def update_accelerations(self):\n",
        "        for ith_body, ibody in enumerate(self.bodies):\n",
        "            ibody.acc *= 0\n",
        "            for jth_body, jbody in enumerate(self.bodies):\n",
        "                if ith_body != jth_body:\n",
        "                    acc = self.get_acc(ibody, jbody)\n",
        "                    ibody.acc += acc\n",
        "            ibody.vector_acc.append(np.copy(ibody.acc))\n",
        "\n",
        "    def update_velocities_and_positions(self, dt):\n",
        "        for ibody in self.bodies:\n",
        "            ibody.vel += ibody.acc * dt\n",
        "            ibody.pos += ibody.vel * dt\n",
        "            ibody.vector_vel.append(np.copy(ibody.vel))\n",
        "            ibody.vector_pos.append(np.copy(ibody.pos))\n",
        "\n",
        "    def simulate(self, dt, duration):\n",
        "        nsteps = int(duration / dt)\n",
        "        for ith_step in range(nsteps):\n",
        "            self.update_accelerations()\n",
        "            self.update_velocities_and_positions(dt)\n",
        "            self.t += dt\n",
        "            self.moments.append(self.t)\n",
        "\n",
        "# Masses\n",
        "SOLAR_MASS = 1.988e30\n",
        "EARTH_MASS = 5.9722e24\n",
        "\n",
        "# Distances\n",
        "ASTRO_UNIT = 1.496e11\n",
        "MILE = 1609\n",
        "\n",
        "# Durations\n",
        "HOUR = 3600\n",
        "DAY = 24 * HOUR\n",
        "YEAR = 365 * DAY\n",
        "\n",
        "def main():\n",
        "    m_sun = 1 * SOLAR_MASS\n",
        "\n",
        "    sun = Body('Sun', 'yellow', [0, 0, 0], m_sun)\n",
        "\n",
        "    m_mercury = 0.05227 * EARTH_MASS\n",
        "    d_mercury = 0.4392 * ASTRO_UNIT\n",
        "    v_mercury = (106_000 * MILE) / (1 * HOUR)\n",
        "    mercury = Body('Mercury', 'gray',\n",
        "                   [d_mercury, 0, 0], m_mercury,\n",
        "                   [0, v_mercury, 0])\n",
        "\n",
        "    m_earth = 1 * EARTH_MASS\n",
        "    d_earth = 1 * ASTRO_UNIT\n",
        "    v_earth = (66_600 * MILE) / (1 * HOUR)\n",
        "    earth = Body('Earth', 'blue', [d_earth, 0, 0], m_earth, [0, v_earth, 0])\n",
        "\n",
        "    m_mars = 0.1704 * EARTH_MASS\n",
        "    d_mars = 1.653 * ASTRO_UNIT\n",
        "    v_mars = (53_900 * MILE) / (1 * HOUR)\n",
        "    mars = Body('Mars', 'darkred', [0, d_mars, 0], m_mars, [v_mars, 0, 0])\n",
        "\n",
        "    bodies = [sun, mercury, earth, mars]\n",
        "    dt = 2 * DAY\n",
        "    duration = 10 * YEAR\n",
        "\n",
        "    gd = GravitationalDynamics(bodies)\n",
        "    gd.simulate(dt, duration)\n",
        "\n",
        "    fig = plt.figure(figsize=(11, 7))\n",
        "    ax_left = fig.add_subplot(1, 2, 1, projection='3d')\n",
        "    ax_left.set_title('3-D Position')\n",
        "    ax_right = fig.add_subplot(1, 2, 2)\n",
        "    ax_right.set_title('Displacement vs Time')\n",
        "\n",
        "    ts = np.array(gd.moments) / YEAR\n",
        "    xticks = np.arange(max(ts)+1).astype(int)\n",
        "\n",
        "    for body in gd.bodies:\n",
        "        vector = np.array(body.vector_pos)\n",
        "        vector_coordinates = vector / ASTRO_UNIT\n",
        "\n",
        "        scalar = body.scalar_pos()\n",
        "        scalar_coordinates = scalar / ASTRO_UNIT\n",
        "        ax_left.scatter(*vector_coordinates.T, marker='.',\n",
        "                        c=body.facecolor, label=body.id)\n",
        "        ax_right.scatter(ts, scalar_coordinates, marker='.',\n",
        "                         c=body.facecolor, label=body.id)\n",
        "        ax_right.set_xticks(xticks)\n",
        "        ax_right.grid(color='k', linestyle=':', alpha=0.3)\n",
        "        fig.subplots_adjust(bottom=0.3)\n",
        "        fig.legend(loc='lower center', mode='expand', ncol=len(gd.bodies))\n",
        "    plt.show()\n",
        "    plt.close(fig)\n",
        "\n",
        "if __name__ == '__main__':\n",
        "    main()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}