positions.ipynb

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   "id": "ceb2afd1-71a7-4f2f-bdca-e2def9933387",
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    "tags": []
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/chris/python/miniconda3/envs/helio4/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "#import heliopy.data.spice as spicedata\n",
    "import copy\n",
    "#import heliopy.spice as spice\n",
    "import datetime\n",
    "from datetime import timedelta\n",
    "import astrospice\n",
    "from astrospice.net.reg import RemoteKernel, RemoteKernelsBase\n",
    "import astropy.units as u\n",
    "from astropy.time import Time, TimeDelta\n",
    "import astropy\n",
    "import sunpy\n",
    "from sunpy.time import parse_time\n",
    "from sunpy.coordinates import get_horizons_coord\n",
    "import os\n",
    "from heliocats import data as hd\n",
    "from bs4 import BeautifulSoup\n",
    "import cdflib\n",
    "from cdflib import epochs_astropy\n",
    "import urllib.request\n",
    "from urllib.request import urlopen\n",
    "import matplotlib.dates as mdates\n",
    "#importlib.reload(hd)\n",
    "\n",
    "from sunpy.coordinates import HeliographicStonyhurst, HeliocentricEarthEcliptic\n",
    "#import warnings\n",
    "\n",
    "import importlib\n",
    "\n",
    "wind_path = 'data/newdata/wind/'"
   ]
  },
  {
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   "id": "fb744215-e558-457a-b1ff-675d04c4563d",
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   "source": [
    "__all__ = ['BepiPredict']\n",
    "\n",
    "\n",
    "class BepiPredict(RemoteKernelsBase):\n",
    "    body = 'mpo'\n",
    "    type = 'predict'\n",
    "\n",
    "    def get_remote_kernels(self):\n",
    "        \"\"\"\n",
    "        Returns\n",
    "        -------\n",
    "        list[RemoteKernel]\n",
    "        \"\"\"\n",
    "        page = urlopen('https://naif.jpl.nasa.gov/pub/naif/BEPICOLOMBO/kernels/spk/')\n",
    "        soup = BeautifulSoup(page, 'html.parser')\n",
    "\n",
    "        kernel_urls = []\n",
    "        for link in soup.find_all('a'):\n",
    "            href = link.get('href')\n",
    "            if href is not None and href.startswith('bc'):\n",
    "                fname = href.split('/')[-1]\n",
    "                matches = self.matches(fname)\n",
    "                if matches:\n",
    "                    kernel_urls.append(\n",
    "                        RemoteKernel(f'https://naif.jpl.nasa.gov/pub/naif/BEPICOLOMBO/kernels/spk/{href}', *matches[1:]))\n",
    "\n",
    "        return kernel_urls\n",
    "\n",
    "    @staticmethod\n",
    "    def matches(fname):\n",
    "        \"\"\"\n",
    "        Check if the given filename matches the pattern of this kernel.\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        matches : bool\n",
    "        start_time : astropy.time.Time\n",
    "        end_time : astropy.time.Time\n",
    "        version : int\n",
    "        \"\"\"\n",
    "        # Example filename: bc_mpo_fcp_00154_20181020_20251102_v01.bsp \n",
    "        fname = fname.split('_')\n",
    "        if (len(fname) != 7 or\n",
    "                fname[0] != 'bc' or\n",
    "                fname[1] != 'mpo' or\n",
    "                fname[2] != 'fcp'):\n",
    "            return False\n",
    "\n",
    "        start_time = Time.strptime(fname[4], '%Y%m%d')\n",
    "        end_time = Time.strptime(fname[5], '%Y%m%d')\n",
    "        version = int(fname[6][1:3])\n",
    "        return True, start_time, end_time, version\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "faf75a9b-b800-41e4-a8a8-3457c3e1249b",
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   "source": [
    "def wind_positions_heeq(start_year, path=wind_path):\n",
    "    \n",
    "    end = datetime.datetime.utcnow().date()\n",
    "\n",
    "    files = os.listdir(wind_path)\n",
    "    files.sort()\n",
    "    data_files = [os.path.join(wind_path, f) for f in files]\n",
    "            \n",
    "    for i in np.arange(start_year, end.year+1, 1):\n",
    "        \n",
    "        #this is the path for the predicted orbits of Wind (predicted up to Sept. 30th 2023), GSE-coordinates in km\n",
    "        data_url = f'https://spdf.gsfc.nasa.gov/pub/data/wind/orbit/pre_or/{i}/'\n",
    "        soup = BeautifulSoup(urlopen(data_url), 'html.parser')\n",
    "        for link in soup.find_all('a'):\n",
    "            href = link.get('href')\n",
    "            if href is not None and href.startswith('wi_or_pre_'):\n",
    "                filename = href.split('/')[-1]\n",
    "                fname = filename.split('_')\n",
    "                date = fname[3]\n",
    "                version = int(fname[4][1:3])\n",
    "                \n",
    "                if np.size(data_files)>0:\n",
    "                    for i in range(1, len(data_files)):\n",
    "                        fname_loc = data_files[i].split('_')\n",
    "                        date_loc = fname_loc[3]\n",
    "                        version_loc = int(fname_loc[4][1:3])\n",
    "                        if date == date_loc and version != version_loc:\n",
    "                            os.remove(data_files[i])\n",
    "                            print('Deleted', data_files[i])\n",
    "                \n",
    "                if os.path.isfile(f\"{path}{filename}\") == True:\n",
    "                    print(f'{filename} has already been downloaded.')\n",
    "                \n",
    "                else:\n",
    "                    urllib.request.urlretrieve(data_url+href, f\"{path}{filename}\")\n",
    "                    print(f'Successfully downloaded {filename}')\n",
    "\n",
    "\n",
    "    files1 = os.listdir(wind_path)\n",
    "    files1.sort()\n",
    "    data_files1 = [os.path.join(wind_path, f) for f in files1]\n",
    "    \n",
    "    time_wind=np.zeros(0,dtype=[('time',object)])\n",
    "    gse_x=np.zeros(0)\n",
    "    gse_y=np.zeros(0)\n",
    "    gse_z=np.zeros(0)\n",
    "\n",
    "    for i in np.arange(1,len(data_files1)):\n",
    "        wind_data = cdflib.CDF(data_files1[i])\n",
    "\n",
    "        gse=wind_data.varget('GSE_POS')\n",
    "        gse_x1=gse[:,0]*u.km.to(u.au)\n",
    "        gse_y1=gse[:,1]*u.km.to(u.au)\n",
    "        gse_z1=gse[:,2]*u.km.to(u.au)\n",
    "\n",
    "        gse_x=np.append(gse_x,gse_x1)\n",
    "        gse_y=np.append(gse_y,gse_y1)\n",
    "        gse_z=np.append(gse_z,gse_z1)\n",
    "\n",
    "        time_wind_epoch=wind_data.varget('Epoch')\n",
    "\n",
    "        time_wind_datetime=parse_time(epochs_astropy.CDFAstropy.convert_to_astropy(time_wind_epoch, format=None)).datetime\n",
    "        time_wind=np.append(time_wind,time_wind_datetime)\n",
    "    \n",
    "    #get Earth coordinates in HEE using astrospice\n",
    "    #dt = 10min, because cdf-files have a 10min resolution as well\n",
    "    dt = TimeDelta(10 * u.minute)\n",
    "    \n",
    "    times = Time(np.arange(Time(time_wind[0]), Time(time_wind[-1])+dt, dt))\n",
    "    coords_earth = astrospice.generate_coords('Earth', times)\n",
    "    coords_earth_hee = coords_earth.transform_to(HeliocentricEarthEcliptic())\n",
    "    [earth_hee_x, earth_hee_y, earth_hee_z] = hd.sphere2cart(coords_earth_hee.distance.to(u.au).value, np.deg2rad(-coords_earth_hee.lat.value+90), np.deg2rad(coords_earth_hee.lon.value))\n",
    "    \n",
    "    wind = np.zeros(np.size(time_wind),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    wind = wind.view(np.recarray)\n",
    "    wind.time = time_wind\n",
    "    wind.x = earth_hee_x - gse_x\n",
    "    wind.y = earth_hee_y - gse_y\n",
    "    wind.z = earth_hee_z + gse_z\n",
    "    \n",
    "    wind = convert_HEE_to_HEEQ(wind)\n",
    "    \n",
    "    [wind.r, wind.lat, wind.lon] = hd.cart2sphere(wind.x, wind.y, wind.z)\n",
    "    \n",
    "    return wind"
   ]
  },
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   "source": [
    "def convert_HEE_to_HEEQ(sc_in):\n",
    "    '''\n",
    "    for Wind positions: convert HEE to HAE to HEEQ\n",
    "    '''\n",
    "\n",
    "    print('conversion HEE to HEEQ')                                \n",
    "    \n",
    "    sc=copy.deepcopy(sc_in)\n",
    "    \n",
    "    jd=np.zeros(len(sc))\n",
    "    mjd=np.zeros(len(sc))\n",
    "        \n",
    "\n",
    "    for i in np.arange(0,len(sc)):\n",
    "\n",
    "        jd[i]=parse_time(sc.time[i]).jd\n",
    "        mjd[i]=float(int(jd[i]-2400000.5)) #use modified julian date    \n",
    "        \n",
    "       \n",
    "        w_hee=[sc.x[i],sc.y[i],sc.z[i]]\n",
    "        \n",
    "        #HEE to HAE        \n",
    "        \n",
    "        #define T00 and UT\n",
    "        T00=(mjd[i]-51544.5)/36525.0          \n",
    "        dobj=sc.time[i]\n",
    "        UT=dobj.hour + dobj.minute / 60. + dobj.second / 3600. #time in UT in hours   \n",
    "\n",
    "        #lambda_sun in Hapgood, equation 5, here in rad\n",
    "        M=np.radians(357.528+35999.050*T00+0.04107*UT)\n",
    "        LAMBDA=280.460+36000.772*T00+0.04107*UT        \n",
    "        lambda_sun=np.radians( (LAMBDA+(1.915-0.0048*T00)*np.sin(M)+0.020*np.sin(2*M)) )\n",
    "        \n",
    "        #S-1 Matrix equation 12 hapgood 1992, change sign in lambda angle for inversion HEE to HAE instead of HAE to HEE\n",
    "        c, s = np.cos(-(lambda_sun+np.radians(180))), np.sin(-(lambda_sun+np.radians(180)))\n",
    "        Sm1 = np.array(((c,s, 0), (-s, c, 0), (0, 0, 1)))\n",
    "        w_hae=np.dot(Sm1,w_hee)\n",
    "\n",
    "        #HAE to HEEQ\n",
    "        \n",
    "        iota=np.radians(7.25)\n",
    "        omega=np.radians((73.6667+0.013958*((mjd[i]+3242)/365.25)))                      \n",
    "        theta=np.arctan(np.cos(iota)*np.tan(lambda_sun-omega))                       \n",
    "                      \n",
    "    \n",
    "        #quadrant of theta must be opposite lambda_sun minus omega; Hapgood 1992 end of section 5   \n",
    "        #get lambda-omega angle in degree mod 360 and theta in degrees\n",
    "        lambda_omega_deg=np.mod(np.degrees(lambda_sun)-np.degrees(omega),360)\n",
    "        theta_node_deg=np.degrees(theta)\n",
    "\n",
    "\n",
    "        ##if the 2 angles are close to similar, so in the same quadrant, then theta_node = theta_node +pi           \n",
    "        if np.logical_or(abs(lambda_omega_deg-theta_node_deg) < 1, abs(lambda_omega_deg-360-theta_node_deg) < 1): theta=theta+np.pi                                                                                                          \n",
    "        \n",
    "        #rotation around Z by theta\n",
    "        c, s = np.cos(theta), np.sin(theta)\n",
    "        S2_1 = np.array(((c,s, 0), (-s, c, 0), (0, 0, 1)))\n",
    "\n",
    "        #rotation around X by iota  \n",
    "        iota=np.radians(7.25)\n",
    "        c, s = np.cos(iota), np.sin(iota)\n",
    "        S2_2 = np.array(( (1,0,0), (0,c, s), (0, -s, c)) )\n",
    "                \n",
    "        #rotation around Z by Omega  \n",
    "        c, s = np.cos(omega), np.sin(omega)\n",
    "        S2_3 = np.array( ((c,s, 0), (-s, c, 0), (0, 0, 1)) )\n",
    "        \n",
    "        #matrix multiplication to go from HAE to HEEQ components                \n",
    "        [x_heeq,y_heeq,z_heeq]=np.dot(  np.dot(   np.dot(S2_1,S2_2),S2_3), w_hae) \n",
    "        \n",
    "        sc.x[i]=x_heeq\n",
    "        sc.y[i]=y_heeq\n",
    "        sc.z[i]=z_heeq\n",
    "\n",
    "    \n",
    "    print('HEE to HEEQ done')  \n",
    "    \n",
    "    return sc"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
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   "source": [
    "\n",
    "def get_positions(dt):\n",
    "    frame = HeliographicStonyhurst()\n",
    "    \n",
    "    ### PSP ###\n",
    "    kernels_psp = astrospice.registry.get_kernels('psp', 'predict')\n",
    "    psp_kernel = kernels_psp[0]\n",
    "    # generate coordinates for whole time coverage in a pre-defined interval\n",
    "    coverage_psp = psp_kernel.coverage('Solar probe plus')\n",
    "    times_psp = Time(np.arange(coverage_psp[0], coverage_psp[1], dt))\n",
    "    coords_psp = astrospice.generate_coords('Solar probe plus', times_psp)\n",
    "    coords_psp = coords_psp.transform_to(frame)\n",
    "    \n",
    "    psp = np.zeros(np.size(times_psp),dtype=[('sc', object),('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    psp = psp.view(np.recarray)\n",
    "    psp.sc = 'PSP'\n",
    "    psp.time = times_psp.to_datetime(leap_second_strict='silent')\n",
    "    psp.r = coords_psp.radius.to(u.au).value\n",
    "    psp.lon = coords_psp.lon.value #degrees\n",
    "    psp.lat = coords_psp.lat.value #degrees\n",
    "    [psp.x, psp.y, psp.z] = hd.sphere2cart(psp.r, np.deg2rad(-psp.lat+90), np.deg2rad(psp.lon))\n",
    "    \n",
    "    \n",
    "    ### SolO ###\n",
    "    kernels_solo = astrospice.registry.get_kernels('solar orbiter', 'predict')\n",
    "    solo_kernel = kernels_solo[0]\n",
    "    coverage_solo = solo_kernel.coverage('Solar orbiter')\n",
    "    times_solo = Time(np.arange(coverage_solo[0], coverage_solo[1], dt))\n",
    "    coords_solo = astrospice.generate_coords('Solar orbiter', times_solo)\n",
    "    coords_solo = coords_solo.transform_to(frame)\n",
    "    \n",
    "    solo = np.zeros(np.size(times_solo),dtype=[('sc', object),('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    solo = solo.view(np.recarray)\n",
    "    solo.sc = 'SolO'\n",
    "    solo.time = times_solo.to_datetime(leap_second_strict='silent')\n",
    "    solo.r = coords_solo.radius.to(u.au).value\n",
    "    solo.lon = coords_solo.lon.value #degrees\n",
    "    solo.lat = coords_solo.lat.value\n",
    "    [solo.x, solo.y, solo.z] = hd.sphere2cart(solo.r, np.deg2rad(-solo.lat+90), np.deg2rad(solo.lon))\n",
    "    \n",
    "    \n",
    "    ### Stereo-A ###\n",
    "    kernels_stereo_recon = astrospice.registry.get_kernels('stereo-a', 'recon')\n",
    "    times_stereo_recon = Time(np.arange(Time('2006-10-27'), Time('2023-8-1'), dt))\n",
    "    coords_stereo_recon = astrospice.generate_coords('Stereo ahead', times_stereo_recon)\n",
    "    coords_stereo_recon = coords_stereo_recon.transform_to(frame)\n",
    "\n",
    "    stereo_recon = np.zeros(np.size(times_stereo_recon),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    stereo_recon = stereo_recon.view(np.recarray)\n",
    "    stereo_recon.time = times_stereo_recon.to_datetime(leap_second_strict='silent')\n",
    "    stereo_recon.r = coords_stereo_recon.radius.to(u.au).value\n",
    "    stereo_recon.lon = coords_stereo_recon.lon.value #degrees\n",
    "    stereo_recon.lat = coords_stereo_recon.lat.value\n",
    "    [stereo_recon.x, stereo_recon.y, stereo_recon.z] = hd.sphere2cart(stereo_recon.r, np.deg2rad(-stereo_recon.lat+90), np.deg2rad(stereo_recon.lon))\n",
    "    \n",
    "    kernels_stereo_pred = astrospice.registry.get_kernels('stereo-a', 'predict')\n",
    "    stereo_kernel_pred = kernels_stereo_pred[0]\n",
    "    coverage_stereo_pred = stereo_kernel_pred.coverage('Stereo ahead')\n",
    "    times_stereo_pred = Time(np.arange(times_stereo_recon[-1]+dt, coverage_stereo_pred[1], dt))\n",
    "    coords_stereo_pred = astrospice.generate_coords('Stereo ahead', times_stereo_pred)\n",
    "    coords_stereo_pred = coords_stereo_pred.transform_to(frame)\n",
    "\n",
    "    stereo_pred = np.zeros(np.size(times_stereo_pred),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    stereo_pred = stereo_pred.view(np.recarray)\n",
    "    stereo_pred.time = times_stereo_pred.to_datetime(leap_second_strict='silent')\n",
    "    stereo_pred.r = coords_stereo_pred.radius.to(u.au).value\n",
    "    stereo_pred.lon = coords_stereo_pred.lon.value #degrees\n",
    "    stereo_pred.lat = coords_stereo_pred.lat.value\n",
    "    [stereo_pred.x, stereo_pred.y, stereo_pred.z] = hd.sphere2cart(stereo_pred.r, np.deg2rad(-stereo_pred.lat+90), np.deg2rad(stereo_pred.lon))\n",
    "\n",
    "    stereo = np.zeros(np.size(times_stereo_recon)+np.size(times_stereo_pred),dtype=[('sc', object),('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    stereo = stereo.view(np.recarray)\n",
    "    \n",
    "    stereo.sc='STA'\n",
    "    stereo.time=np.hstack((stereo_recon.time,stereo_pred.time))\n",
    "    stereo.x=np.hstack((stereo_recon.x,stereo_pred.x))\n",
    "    stereo.y=np.hstack((stereo_recon.y,stereo_pred.y))\n",
    "    stereo.z=np.hstack((stereo_recon.z,stereo_pred.z))\n",
    "    stereo.r=np.hstack((stereo_recon.r,stereo_pred.r))\n",
    "    stereo.lon=np.hstack((stereo_recon.lon,stereo_pred.lon))\n",
    "    stereo.lat=np.hstack((stereo_recon.lat,stereo_pred.lat))\n",
    "    \n",
    "    \n",
    "    ### Stereo-B ###\n",
    "    kernels_stereob_recon = astrospice.registry.get_kernels('stereo-b', 'recon')\n",
    "    times_stereob_recon = Time(np.arange(Time('2006-10-27'), Time('2014-9-28'), dt))\n",
    "    coords_stereob_recon = astrospice.generate_coords('Stereo behind', times_stereob_recon)\n",
    "    coords_stereob_recon = coords_stereob_recon.transform_to(frame)\n",
    "\n",
    "    stereob_recon = np.zeros(np.size(times_stereob_recon),dtype=[('sc', object),('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    stereob_recon = stereob_recon.view(np.recarray)\n",
    "    stereob_recon.sc='STB'\n",
    "    stereob_recon.time = times_stereob_recon.to_datetime(leap_second_strict='silent')\n",
    "    stereob_recon.r = coords_stereob_recon.radius.to(u.au).value\n",
    "    stereob_recon.lon = coords_stereob_recon.lon.value #degrees\n",
    "    stereob_recon.lat = coords_stereob_recon.lat.value\n",
    "    [stereob_recon.x, stereob_recon.y, stereob_recon.z] = hd.sphere2cart(stereob_recon.r, np.deg2rad(-stereob_recon.lat+90), np.deg2rad(stereob_recon.lon))\n",
    "\n",
    "    \n",
    "    ### Bepi ###\n",
    "    kernels_bepi = astrospice.registry.get_kernels('mpo', 'predict')\n",
    "    bepi_kernel = kernels_bepi[0]\n",
    "    coverage_bepi = bepi_kernel.coverage('Bepicolombo mpo')\n",
    "    times_bepi = Time(np.arange(coverage_bepi[0], coverage_bepi[1], dt))\n",
    "    coords_bepi = astrospice.generate_coords('Bepicolombo mpo', times_bepi)\n",
    "    coords_bepi = coords_bepi.transform_to(frame)\n",
    "    \n",
    "    bepi_ = np.zeros(np.size(times_bepi),dtype=[('sc', object),('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    bepi_ = bepi_.view(np.recarray)\n",
    "    bepi_.sc = 'Bepi'\n",
    "    bepi_.time = times_bepi.to_datetime(leap_second_strict='silent')\n",
    "    bepi_.r = coords_bepi.radius.to(u.au).value\n",
    "    bepi_.lon = coords_bepi.lon.value #degrees\n",
    "    bepi_.lat = coords_bepi.lat.value\n",
    "    [bepi_.x, bepi_.y, bepi_.z] = hd.sphere2cart(bepi_.r, np.deg2rad(-bepi_.lat+90), np.deg2rad(bepi_.lon))\n",
    "    \n",
    "    \n",
    "    ### Earth ###\n",
    "    times_earth = Time(np.arange(Time('1995-1-1'), Time('2035-1-1'), dt))\n",
    "    coords_earth = astrospice.generate_coords('Earth', times_earth)\n",
    "    coords_earth = coords_earth.transform_to(frame)\n",
    "    \n",
    "    earth = np.zeros(np.size(times_earth),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    earth = earth.view(np.recarray)\n",
    "    earth.time = times_earth.to_datetime(leap_second_strict='silent')\n",
    "    earth.r = coords_earth.radius.to(u.au).value\n",
    "    earth.lon = coords_earth.lon.value #degrees\n",
    "    earth.lat = coords_earth.lat.value\n",
    "    [earth.x, earth.y, earth.z] = hd.sphere2cart(earth.r, np.deg2rad(-earth.lat+90), np.deg2rad(earth.lon))\n",
    "    \n",
    "    \n",
    "    ### Wind ###\n",
    "    wind = np.zeros(np.size(times_earth),dtype=[('sc', object), ('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    wind = wind.view(np.recarray)\n",
    "    wind.sc = 'Wind'\n",
    "    wind.time = earth.time\n",
    "    wind.x = earth.x - 0.01\n",
    "    wind.y = earth.y\n",
    "    wind.z = earth.z\n",
    "    [wind.r, wind_lat, wind_lon] = hd.cart2sphere(wind.x, wind.y, wind.z)\n",
    "    wind.lat = np.rad2deg(wind_lat)\n",
    "    wind.lon = np.rad2deg(wind_lon)\n",
    "\n",
    "    \n",
    "    ### Mercury ###\n",
    "    coords_mercury = astrospice.generate_coords(1, earth.time)\n",
    "    coords_mercury = coords_mercury.transform_to(frame)\n",
    "    \n",
    "    mercury = np.zeros(np.size(earth.time),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    mercury = mercury.view(np.recarray)\n",
    "    mercury.time = earth.time\n",
    "    mercury.r = coords_mercury.radius.to(u.au).value\n",
    "    mercury.lon = coords_mercury.lon.value #degrees\n",
    "    mercury.lat = coords_mercury.lat.value\n",
    "    [mercury.x, mercury.y, mercury.z] = hd.sphere2cart(mercury.r, np.deg2rad(-mercury.lat+90), np.deg2rad(mercury.lon))\n",
    "    \n",
    "    \n",
    "    ### Venus ###\n",
    "    coords_venus = astrospice.generate_coords(2, earth.time)\n",
    "    coords_venus = coords_venus.transform_to(frame)\n",
    "    \n",
    "    venus = np.zeros(np.size(earth.time),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    venus = venus.view(np.recarray)\n",
    "    venus.time = earth.time\n",
    "    venus.r = coords_venus.radius.to(u.au).value\n",
    "    venus.lon = coords_venus.lon.value #degrees\n",
    "    venus.lat = coords_venus.lat.value\n",
    "    [venus.x, venus.y, venus.z] = hd.sphere2cart(venus.r, np.deg2rad(-venus.lat+90), np.deg2rad(venus.lon))\n",
    "    \n",
    "    \n",
    "    ### Mars ###\n",
    "    coords_mars = astrospice.generate_coords(4, earth.time)\n",
    "    coords_mars = coords_mars.transform_to(frame)\n",
    "\n",
    "    mars = np.zeros(np.size(earth.time),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    mars = mars.view(np.recarray)\n",
    "    mars.time = earth.time\n",
    "    mars.r = coords_mars.radius.to(u.au).value\n",
    "    mars.lon = coords_mars.lon.value #degrees\n",
    "    mars.lat = coords_mars.lat.value\n",
    "    [mars.x, mars.y, mars.z] = hd.sphere2cart(mars.r, np.deg2rad(-mars.lat+90), np.deg2rad(mars.lon))\n",
    "    \n",
    "    \n",
    "    ### Jupiter ###\n",
    "    coords_jupiter = astrospice.generate_coords(5, earth.time)\n",
    "    coords_jupiter = coords_jupiter.transform_to(frame)\n",
    "    \n",
    "    jupiter = np.zeros(np.size(earth.time),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    jupiter = jupiter.view(np.recarray)\n",
    "    jupiter.time = earth.time\n",
    "    jupiter.r = coords_jupiter.radius.to(u.au).value\n",
    "    jupiter.lon = coords_jupiter.lon.value #degrees\n",
    "    jupiter.lat = coords_jupiter.lat.value\n",
    "    [jupiter.x, jupiter.y, jupiter.z] = hd.sphere2cart(jupiter.r, np.deg2rad(-jupiter.lat+90), np.deg2rad(jupiter.lon))\n",
    "    \n",
    "    \n",
    "    ### Saturn ###\n",
    "    coords_saturn = astrospice.generate_coords(6, earth.time)\n",
    "    coords_saturn = coords_saturn.transform_to(frame)\n",
    "    \n",
    "    saturn = np.zeros(np.size(earth.time),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    saturn = saturn.view(np.recarray)\n",
    "    saturn.time = earth.time\n",
    "    saturn.r = coords_saturn.radius.to(u.au).value\n",
    "    saturn.lon = coords_saturn.lon.value #degrees\n",
    "    saturn.lat = coords_saturn.lat.value\n",
    "    [saturn.x, saturn.y, saturn.z] = hd.sphere2cart(saturn.r, np.deg2rad(-saturn.lat+90), np.deg2rad(saturn.lon))\n",
    "    \n",
    "    \n",
    "    ### Uranus ###\n",
    "    coords_uranus = astrospice.generate_coords(7, earth.time)\n",
    "    coords_uranus = coords_uranus.transform_to(frame)\n",
    "    \n",
    "    uranus = np.zeros(np.size(earth.time),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    uranus = uranus.view(np.recarray)\n",
    "    uranus.time = earth.time\n",
    "    uranus.r = coords_uranus.radius.to(u.au).value\n",
    "    uranus.lon = coords_uranus.lon.value #degrees\n",
    "    uranus.lat = coords_uranus.lat.value\n",
    "    [uranus.x, uranus.y, uranus.z] = hd.sphere2cart(uranus.r, np.deg2rad(-uranus.lat+90), np.deg2rad(uranus.lon))\n",
    "    \n",
    "    \n",
    "    ### Neptune ###\n",
    "    coords_neptune = astrospice.generate_coords(8, earth.time)\n",
    "    coords_neptune = coords_neptune.transform_to(frame)\n",
    "    \n",
    "    neptune = np.zeros(np.size(earth.time),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "    neptune = neptune.view(np.recarray)\n",
    "    neptune.time = earth.time\n",
    "    neptune.r = coords_neptune.radius.to(u.au).value\n",
    "    neptune.lon = coords_neptune.lon.value #degrees\n",
    "    neptune.lat = coords_neptune.lat.value\n",
    "    [neptune.x, neptune.y, neptune.z] = hd.sphere2cart(neptune.r, np.deg2rad(-neptune.lat+90), np.deg2rad(neptune.lon))  \n",
    "    \n",
    "    return [psp, solo, stereo, stereob_recon, bepi_, wind, earth, mercury, venus, mars, jupiter, saturn, uranus, neptune]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "da1bef44-9205-4df5-9a93-c5bd46d22890",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "ename": "HTTPError",
     "evalue": "HTTP Error 404: Not Found",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[6], line 4\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m### SAVE SPACECRAFT POSITIONS ###\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m# get data in 1 min resolution\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m data_1min \u001b[38;5;241m=\u001b[39m \u001b[43mget_positions\u001b[49m\u001b[43m(\u001b[49m\u001b[43mTimeDelta\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mu\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mminute\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[38;5;66;03m# get data in rad/mdates\u001b[39;00m\n\u001b[1;32m      7\u001b[0m data_new_1min \u001b[38;5;241m=\u001b[39m copy\u001b[38;5;241m.\u001b[39mdeepcopy(data_1min)\n",
      "Cell \u001b[0;32mIn[5], line 5\u001b[0m, in \u001b[0;36mget_positions\u001b[0;34m(dt)\u001b[0m\n\u001b[1;32m      2\u001b[0m frame \u001b[38;5;241m=\u001b[39m HeliographicStonyhurst()\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m### PSP ###\u001b[39;00m\n\u001b[0;32m----> 5\u001b[0m kernels_psp \u001b[38;5;241m=\u001b[39m \u001b[43mastrospice\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mregistry\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_kernels\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mpsp\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mpredict\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      6\u001b[0m psp_kernel \u001b[38;5;241m=\u001b[39m kernels_psp[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# generate coordinates for whole time coverage in a pre-defined interval\u001b[39;00m\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/site-packages/astrospice/net/reg.py:117\u001b[0m, in \u001b[0;36mKernelRegistry.get_kernels\u001b[0;34m(self, body, type, version)\u001b[0m\n\u001b[1;32m    114\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m types:\n\u001b[1;32m    115\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m is not one of the known kernel types \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m    116\u001b[0m                      \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfor \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mbody\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtypes\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 117\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_kernels\u001b[49m\u001b[43m[\u001b[49m\u001b[43mbody\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mtype\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_kernels\u001b[49m\u001b[43m(\u001b[49m\u001b[43mversion\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mversion\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/site-packages/astrospice/net/reg.py:207\u001b[0m, in \u001b[0;36mRemoteKernelsBase.get_kernels\u001b[0;34m(self, version)\u001b[0m\n\u001b[1;32m    184\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_kernels\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m, version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m    185\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    186\u001b[0m \u001b[38;5;124;03m    Get a set of kernels. Any kernels not present locally will be\u001b[39;00m\n\u001b[1;32m    187\u001b[0m \u001b[38;5;124;03m    downloaded.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    205\u001b[0m \u001b[38;5;124;03m        timerange.\u001b[39;00m\n\u001b[1;32m    206\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 207\u001b[0m     kernels \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_remote_kernels\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    208\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m version \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    209\u001b[0m         kernels \u001b[38;5;241m=\u001b[39m [k \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m kernels \u001b[38;5;28;01mif\u001b[39;00m k\u001b[38;5;241m.\u001b[39mversion \u001b[38;5;241m==\u001b[39m version]\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/site-packages/astrospice/net/sources/psp.py:21\u001b[0m, in \u001b[0;36mPSPPredict.get_remote_kernels\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_remote_kernels\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m     16\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m     17\u001b[0m \u001b[38;5;124;03m    Returns\u001b[39;00m\n\u001b[1;32m     18\u001b[0m \u001b[38;5;124;03m    -------\u001b[39;00m\n\u001b[1;32m     19\u001b[0m \u001b[38;5;124;03m    list[RemoteKernel]\u001b[39;00m\n\u001b[1;32m     20\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m---> 21\u001b[0m     page \u001b[38;5;241m=\u001b[39m \u001b[43murlopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mhttps://spdf.gsfc.nasa.gov/pub/data/psp/ephemeris/spice/Long_Term_Predicted_Ephemeris/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     22\u001b[0m     soup \u001b[38;5;241m=\u001b[39m BeautifulSoup(page, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhtml.parser\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m     24\u001b[0m     kernel_urls \u001b[38;5;241m=\u001b[39m []\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/urllib/request.py:216\u001b[0m, in \u001b[0;36murlopen\u001b[0;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[1;32m    214\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    215\u001b[0m     opener \u001b[38;5;241m=\u001b[39m _opener\n\u001b[0;32m--> 216\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mopener\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/urllib/request.py:525\u001b[0m, in \u001b[0;36mOpenerDirector.open\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m    523\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m processor \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprocess_response\u001b[38;5;241m.\u001b[39mget(protocol, []):\n\u001b[1;32m    524\u001b[0m     meth \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(processor, meth_name)\n\u001b[0;32m--> 525\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[43mmeth\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreq\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mresponse\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m response\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/urllib/request.py:634\u001b[0m, in \u001b[0;36mHTTPErrorProcessor.http_response\u001b[0;34m(self, request, response)\u001b[0m\n\u001b[1;32m    631\u001b[0m \u001b[38;5;66;03m# According to RFC 2616, \"2xx\" code indicates that the client's\u001b[39;00m\n\u001b[1;32m    632\u001b[0m \u001b[38;5;66;03m# request was successfully received, understood, and accepted.\u001b[39;00m\n\u001b[1;32m    633\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;241m200\u001b[39m \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m code \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m300\u001b[39m):\n\u001b[0;32m--> 634\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43merror\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    635\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mhttp\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mresponse\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmsg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhdrs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    637\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m response\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/urllib/request.py:563\u001b[0m, in \u001b[0;36mOpenerDirector.error\u001b[0;34m(self, proto, *args)\u001b[0m\n\u001b[1;32m    561\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m http_err:\n\u001b[1;32m    562\u001b[0m     args \u001b[38;5;241m=\u001b[39m (\u001b[38;5;28mdict\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdefault\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhttp_error_default\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;241m+\u001b[39m orig_args\n\u001b[0;32m--> 563\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_chain\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/urllib/request.py:496\u001b[0m, in \u001b[0;36mOpenerDirector._call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m    494\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m handler \u001b[38;5;129;01min\u001b[39;00m handlers:\n\u001b[1;32m    495\u001b[0m     func \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(handler, meth_name)\n\u001b[0;32m--> 496\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    497\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m result \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    498\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/urllib/request.py:643\u001b[0m, in \u001b[0;36mHTTPDefaultErrorHandler.http_error_default\u001b[0;34m(self, req, fp, code, msg, hdrs)\u001b[0m\n\u001b[1;32m    642\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhttp_error_default\u001b[39m(\u001b[38;5;28mself\u001b[39m, req, fp, code, msg, hdrs):\n\u001b[0;32m--> 643\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m HTTPError(req\u001b[38;5;241m.\u001b[39mfull_url, code, msg, hdrs, fp)\n",
      "\u001b[0;31mHTTPError\u001b[0m: HTTP Error 404: Not Found"
     ]
    }
   ],
   "source": [
    "### SAVE SPACECRAFT POSITIONS ###\n",
    "\n",
    "# get data in 1 min resolution\n",
    "data_1min = get_positions(TimeDelta(1*u.minute))\n",
    "\n",
    "# get data in rad/mdates\n",
    "data_new_1min = copy.deepcopy(data_1min)\n",
    "\n",
    "for i in range(len(data_1min)):\n",
    "    data_new_1min[i].lat = np.deg2rad(data_1min[i].lat)\n",
    "    data_new_1min[i].lon = np.deg2rad(data_1min[i].lon)\n",
    "    data_new_1min[i].time = mdates.date2num(data_1min[i].time)\n",
    "\n",
    "# get data in 1 hour resolution\n",
    "data_1h = get_positions(TimeDelta(1*u.hour))\n",
    "\n",
    "#get data in rad/mdates\n",
    "data_new_1h = copy.deepcopy(data_1h)\n",
    "\n",
    "for i in range(len(data_1h)):\n",
    "    data_new_1h[i].lat = np.deg2rad(data_1h[i].lat)\n",
    "    data_new_1h[i].lon = np.deg2rad(data_1h[i].lon)\n",
    "    data_new_1h[i].time = mdates.date2num(data_1h[i].time)\n",
    "\n",
    "pickle.dump(data_1min, open( 'data/newdata/positions_psp_solo_sta_bepi_wind_planets_HEEQ_1min_degrees.p', \"wb\" ) ) \n",
    "pickle.dump(data_new_1min, open( 'data/newdata/positions_psp_solo_sta_bepi_wind_planets_HEEQ_1min_rad.p', \"wb\" ) ) \n",
    "pickle.dump(data_1h, open( 'data/newdata/positions_psp_solo_sta_bepi_wind_planets_HEEQ_1hour_degrees.p', \"wb\" ) )\n",
    "pickle.dump(data_new_1h, open( 'data/newdata/positions_psp_solo_sta_bepi_wind_planets_HEEQ_1hour_rad.p', \"wb\" ) )\n",
    "\n",
    "#[psp, solo, stereo, stereob_recon, bepi_, wind, earth, mercury, venus, mars, jupiter, saturn, uranus, neptune] = pickle.load( open( 'data/newdata/positions_psp_solo_sta_bepi_wind_planets_HEEQ_1min_degrees.p', \"rb\" ) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29ae4762-0c19-4f34-83dd-9fb70f55183a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#### PLOT SPACECRAFT POSITIONS ####\n",
    "\n",
    "fig = plt.figure(1, figsize=(15,15), dpi=100)\n",
    "ax = fig.add_subplot(projection='polar')\n",
    "ax.scatter(np.deg2rad(psp.lon), psp.r, s=2)\n",
    "plt.show()\n",
    "\n",
    "fig = plt.figure(2, figsize=(15,15), dpi=100)\n",
    "ax = fig.add_subplot(projection='polar')\n",
    "ax.scatter(np.deg2rad(solo.lon), solo.r, s=2)\n",
    "plt.show()\n",
    "\n",
    "fig = plt.figure(3, figsize=(15,15), dpi=100)\n",
    "ax = fig.add_subplot(projection='polar')\n",
    "ax.scatter(np.deg2rad(stereo.lon), stereo.r, s=2)\n",
    "plt.show()\n",
    "\n",
    "fig = plt.figure(4, figsize=(15,15), dpi=100)\n",
    "ax = fig.add_subplot(projection='polar')\n",
    "ax.scatter(np.deg2rad(wind.lon), wind.r, s=2)\n",
    "plt.show()\n",
    "\n",
    "fig = plt.figure(5, figsize=(15,15), dpi=100)\n",
    "ax = fig.add_subplot(projection='polar')\n",
    "ax.scatter(np.deg2rad(earth.lon), earth.r, s=2)\n",
    "ax.scatter(np.deg2rad(mercury.lon), mercury.r, s=2)\n",
    "ax.scatter(np.deg2rad(venus.lon), venus.r, s=2)\n",
    "ax.scatter(np.deg2rad(mars.lon), mars.r, s=2)\n",
    "ax.scatter(np.deg2rad(jupiter.lon), jupiter.r, s=2)\n",
    "ax.scatter(np.deg2rad(saturn.lon), saturn.r, s=2)\n",
    "ax.scatter(np.deg2rad(uranus.lon), uranus.r, s=2)\n",
    "ax.scatter(np.deg2rad(neptune.lon), neptune.r, s=2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "29d9b855-15b5-4224-ac94-9b87b06b60be",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: TimeDeltaMissingUnitWarning: Numerical value without unit or explicit format passed to TimeDelta, assuming days [astropy.time.core]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "frame=HeliographicStonyhurst()\n",
    "### Earth ###\n",
    "dt = TimeDelta(60 * u.minute)\n",
    "times_earth = Time(np.arange(Time('2018-1-1'), Time('2019-1-1'), dt))\n",
    "coords_earth = astrospice.generate_coords('Earth', times_earth)\n",
    "coords_earth = coords_earth.transform_to(frame)\n",
    "\n",
    "earth = np.zeros(np.size(times_earth),dtype=[('time',object),('r','f8'),('lon','f8'),('lat','f8'),('x','f8'),('y','f8'),('z','f8')])\n",
    "earth = earth.view(np.recarray)\n",
    "earth.time = times_earth.to_datetime(leap_second_strict='silent')\n",
    "earth.r = coords_earth.radius.to(u.au).value\n",
    "earth.lon = coords_earth.lon.value #degrees\n",
    "earth.lat = coords_earth.lat.value\n",
    "[earth.x, earth.y, earth.z] = hd.sphere2cart(earth.r, np.deg2rad(-earth.lat+90), np.deg2rad(earth.lon))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "01adf0e0-ffb6-4654-b100-7cb5f161704c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x309e9d7e0>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(earth.r)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8d66cbf0-0829-4958-b4fc-4247000a6e02",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/chris/python/heliocats'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dbdb239-eaf5-4416-84b6-4582b57f105b",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### USE spicepy for Earth in ECLIPJ2000 for Bepi\n",
    "\n",
    "https://gist.github.com/kerel-fs/40dc8e80c3652f276ea580ab87f32ccd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fdeb9234-edbd-467c-9f2a-581d43df4367",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "ename": "SpiceNOLEAPSECONDS",
     "evalue": "\n================================================================================\n\nToolkit version: CSPICE_N0067\n\nSPICE(NOLEAPSECONDS) --\n\nThe variable that points to the leapseconds (DELTET/DELTA_AT) could not be located in the kernel pool.  It is likely that the leapseconds kernel has not been loaded.\n\nstr2et_c --> STR2ET --> TTRANS\n\n================================================================================",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mSpiceNOLEAPSECONDS\u001b[0m                        Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[10], line 11\u001b[0m\n\u001b[1;32m      7\u001b[0m     t \u001b[38;5;241m=\u001b[39m t\u001b[38;5;241m+\u001b[39m datetime\u001b[38;5;241m.\u001b[39mtimedelta(hours\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m24\u001b[39m)\n\u001b[1;32m      8\u001b[0m     times\u001b[38;5;241m.\u001b[39mappend(t)\n\u001b[0;32m---> 11\u001b[0m time_spice \u001b[38;5;241m=\u001b[39m [spiceypy\u001b[38;5;241m.\u001b[39mstr2et(t\u001b[38;5;241m.\u001b[39mstrftime(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mY-\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mm-\u001b[39m\u001b[38;5;132;01m%d\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mH:\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mM\u001b[39m\u001b[38;5;124m'\u001b[39m)) \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m times]\n\u001b[1;32m     13\u001b[0m spice_files \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/generic/naif0012.tls\u001b[39m\u001b[38;5;124m'\u001b[39m, \n\u001b[1;32m     14\u001b[0m                \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/generic/de430.bsp\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     15\u001b[0m                \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/generic/pck00010.tpc\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     16\u001b[0m                \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/solo/solo_ANC_soc-orbit-stp_20200210-20301120_312_V1_00350_V01.bsp\u001b[39m\u001b[38;5;124m'\u001b[39m]    \n\u001b[1;32m     17\u001b[0m spiceypy\u001b[38;5;241m.\u001b[39mfurnsh(spice_files)\n",
      "Cell \u001b[0;32mIn[10], line 11\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m      7\u001b[0m     t \u001b[38;5;241m=\u001b[39m t\u001b[38;5;241m+\u001b[39m datetime\u001b[38;5;241m.\u001b[39mtimedelta(hours\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m24\u001b[39m)\n\u001b[1;32m      8\u001b[0m     times\u001b[38;5;241m.\u001b[39mappend(t)\n\u001b[0;32m---> 11\u001b[0m time_spice \u001b[38;5;241m=\u001b[39m [\u001b[43mspiceypy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstr2et\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstrftime\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m%\u001b[39;49m\u001b[38;5;124;43mY-\u001b[39;49m\u001b[38;5;124;43m%\u001b[39;49m\u001b[38;5;124;43mm-\u001b[39;49m\u001b[38;5;132;43;01m%d\u001b[39;49;00m\u001b[38;5;124;43m \u001b[39;49m\u001b[38;5;124;43m%\u001b[39;49m\u001b[38;5;124;43mH:\u001b[39;49m\u001b[38;5;124;43m%\u001b[39;49m\u001b[38;5;124;43mM\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m times]\n\u001b[1;32m     13\u001b[0m spice_files \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/generic/naif0012.tls\u001b[39m\u001b[38;5;124m'\u001b[39m, \n\u001b[1;32m     14\u001b[0m                \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/generic/de430.bsp\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     15\u001b[0m                \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/generic/pck00010.tpc\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     16\u001b[0m                \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/kernels/solo/solo_ANC_soc-orbit-stp_20200210-20301120_312_V1_00350_V01.bsp\u001b[39m\u001b[38;5;124m'\u001b[39m]    \n\u001b[1;32m     17\u001b[0m spiceypy\u001b[38;5;241m.\u001b[39mfurnsh(spice_files)\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/site-packages/spiceypy/spiceypy.py:139\u001b[0m, in \u001b[0;36mspice_error_check.<locals>.with_errcheck\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    138\u001b[0m     res \u001b[38;5;241m=\u001b[39m f(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 139\u001b[0m     \u001b[43mcheck_for_spice_error\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    140\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m res\n\u001b[1;32m    141\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m:\n",
      "File \u001b[0;32m~/python/miniconda3/envs/helio4/lib/python3.10/site-packages/spiceypy/spiceypy.py:122\u001b[0m, in \u001b[0;36mcheck_for_spice_error\u001b[0;34m(f)\u001b[0m\n\u001b[1;32m    120\u001b[0m traceback \u001b[38;5;241m=\u001b[39m qcktrc(\u001b[38;5;241m200\u001b[39m)\n\u001b[1;32m    121\u001b[0m reset()\n\u001b[0;32m--> 122\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m dynamically_instantiate_spiceyerror(\n\u001b[1;32m    123\u001b[0m     short\u001b[38;5;241m=\u001b[39mshort, explain\u001b[38;5;241m=\u001b[39mexplain, long\u001b[38;5;241m=\u001b[39mlong, traceback\u001b[38;5;241m=\u001b[39mtraceback\n\u001b[1;32m    124\u001b[0m )\n",
      "\u001b[0;31mSpiceNOLEAPSECONDS\u001b[0m: \n================================================================================\n\nToolkit version: CSPICE_N0067\n\nSPICE(NOLEAPSECONDS) --\n\nThe variable that points to the leapseconds (DELTET/DELTA_AT) could not be located in the kernel pool.  It is likely that the leapseconds kernel has not been loaded.\n\nstr2et_c --> STR2ET --> TTRANS\n\n================================================================================"
     ]
    }
   ],
   "source": [
    "\n",
    "import spiceypy\n",
    "from sunpy.time import TimeRange\n",
    "timerange = TimeRange('2020-02-10', 1*u.year)\n",
    "times = [timerange.start.datetime]\n",
    "t = times[0]\n",
    "while t < timerange.end:\n",
    "    t = t+ datetime.timedelta(hours=24)\n",
    "    times.append(t)\n",
    "\n",
    "    \n",
    "time_spice = [spiceypy.str2et(t.strftime('%Y-%m-%d %H:%M')) for t in times]\n",
    "    \n",
    "spice_files = ['../data/kernels/generic/naif0012.tls', \n",
    "               '../data/kernels/generic/de430.bsp',\n",
    "               '../data/kernels/generic/pck00010.tpc',\n",
    "               '../data/kernels/solo/solo_ANC_soc-orbit-stp_20200210-20301120_312_V1_00350_V01.bsp']    \n",
    "spiceypy.furnsh(spice_files)\n",
    "\n",
    "positions_earth, lightTimes_earth = spiceypy.spkezr('Earth', time_spice, 'ECLIPJ2000', 'NONE', 'Sun')\n",
    "\n",
    "pos_earth = np.array(positions_earth)[:, :3] * u.km\n",
    "\n",
    "earth_x_ej2 = pos_earth[:, 0].to(u.au).value\n",
    "earth_y_ej2 = pos_earth[:, 1].to(u.au).value\n",
    "earth_z_ej2 = pos_earth[:, 2].to(u.au).value\n",
    "\n",
    "\n",
    "earth_x_ej2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9efd0742-2b8f-477f-86c0-852ffb2d333e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "plt.plot(earth_y_ej2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3dc37d0b-faa9-4903-9761-1a52112c8281",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "time_spice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f33496cf-83d9-4258-8cf8-a85db0a6592b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d49df05-846c-45d4-aeb6-775edb2e6f64",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "113cbc74-7b15-417e-b31d-ce698cd7dc03",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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