{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "45286d4d-0f1d-4bad-93d5-101bb64e2eef",
   "metadata": {},
   "source": [
    "## CDPP3DVIEW Provider examples"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcfa9c96-bfd8-4b5c-b95e-72da4ac21e47",
   "metadata": {},
   "source": [
    "## Only for Google Colab Users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d7b5ae5-9ae9-4194-9a27-69bb53f32af3",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install --upgrade ipympl speasy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "629d9793-cddb-4900-a93e-4a55493d6c3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    from google.colab import output\n",
    "    output.enable_custom_widget_manager()\n",
    "except:\n",
    "    print(\"Not running inside Google Collab\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f62ae7c-74bd-408a-b658-a6ff0b668cd3",
   "metadata": {},
   "source": [
    "## For all users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ea744d85-70c8-408e-a94b-83e2af4d8cd0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Can't get data from proxy server http://sciqlop.lpp.polytechnique.fr/cache\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Can't get inventory for provider cdpp3dview from proxy server http://sciqlop.lpp.polytechnique.fr/cache, status code 400\n"
     ]
    }
   ],
   "source": [
    "import speasy as spz\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1e40ebb-4bbf-467f-93a7-3178a047d866",
   "metadata": {},
   "source": [
    "### Show inventories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d6b25ac2-ada5-4d37-aaae-3f75b906115d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['GEOTAIL', 'WIND', 'SOHO', 'Pioneer10', 'Pioneer11', 'Voyager_1', 'Voyager_2', 'Mariner 10', 'MEX', 'Mars Odyssey', 'ULYSSES', 'Phobos2', 'Galileo', 'Cassini', 'ACE', 'Chandra (CXO)', 'CLUSTER1', 'CLUSTER2', 'CLUSTER3', 'CLUSTER4', 'Rosetta', 'HelioSwarm0', 'HelioSwarm1', 'HelioSwarm2', 'HelioSwarm3', 'HelioSwarm4', 'HelioSwarm5', 'HelioSwarm6', 'HelioSwarm7', 'HelioSwarm8', 'Stereo-A', 'Stereo-B', 'MESSENGER', 'THEMISA', 'THEMISB', 'THEMISC', 'THEMISD', 'THEMISE', 'VEX', 'COROT', 'Planck', 'SVOM', 'Jason 2', 'INTERBALL-Auroral', 'INTERBALL-Tail', 'Giotto', 'PICARD', 'MRO', 'MSL', 'Juno', 'JUICE', 'MAVEN', 'MMO', 'MPO', 'BepiColombo', 'Solar Orbiter', 'MGS', 'Parker Solar Probe', 'Europa Clipper', 'Proba2', 'ISEE1', 'ISEE2', 'ISEE3', 'Doublestar1', 'Doublestar2', 'IMP-8', 'POLAR', 'CHAMP', 'DEMETER', 'FAST', 'Freja', 'IMAGE', 'AMPTE-IRM', 'Oersted', 'Reimei', 'SDO', 'Swarm-A', 'Swarm-B', 'Swarm-C', 'Timed', 'TRACE', 'Helios1', 'Helios2', 'MMS1', 'MMS2', 'MMS3', 'MMS4', 'RBSPA', 'RBSPB', 'XMM', 'Herschel', 'Gaia', 'TGO', 'DSCOVR', 'EMM', 'ARASE', 'Akebono', 'Alouette1', 'Alouette2', 'AMPTE-CCE', 'AMPTE-UKS', 'New Horizons', 'Smile', 'Henri', 'Marguerite', 'Cassiope', 'CRRES', 'CSSWE', 'DE1', 'DE2', 'DMSPF06', 'DMSPF07', 'DMSPF08', 'DMSPF09', 'DMSPF10', 'DMSPF11', 'DMSPF12', 'DMSPF13', 'DMSPF14', 'DMSPF15', 'DMSPF16', 'DMSPF17', 'DMSPF18', 'DMSPF19', 'Equator-S', 'GOES06', 'GOES07', 'GOES08', 'GOES09', 'GOES10', 'GOES11', 'GOES12', 'GOES13', 'GOES14', 'GOES15', 'GOES16', 'Grace1', 'Grace2', 'Hawkeye', 'IMP-7', 'ISIS1', 'ISIS2', 'ISS', 'METOP1B', 'METOP2A', 'NOAA5', 'NOAA6', 'NOAA7', 'NOAA8', 'NOAA10', 'NOAA12', 'NOAA14', 'NOAA15', 'NOAA16', 'NOAA17', 'NOAA18', 'NOAA19', 'Ohzora', 'Rhessi', 'Rocsat1', 'Sampex', 'Scatha', 'SNOE', 'ST5a', 'ST5b', 'ST5c', 'TWINS1', 'TWINS2', 'UARS', 'Aureol-3', 'CNOFS', 'ICON', 'Chandrayaan-1', 'Kaguya', 'HERA', 'EscaPADE-B', 'EscaPADE-G', 'Sun', 'Mercury', 'Venus', 'Earth', 'Moon', 'Mars', 'Phobos', 'Deimos', 'Jupiter', 'Io', 'Europa', 'Ganymede', 'Callisto', 'Amalthea', 'Thebe', 'Saturn_barycenter', 'Saturn', 'Mimas', 'Enceladus', 'Tethys', 'Dione', 'Rhea', 'Titan', 'Hyperion', 'Iapetus', 'Phoebe', 'Helene', 'Telesto', 'Methone', 'Pallene', 'Anthe', 'Uranus', 'Ariel', 'Umbriel', 'Titania', 'Oberon', 'Miranda', 'Neptune', 'Triton', 'Neired', 'Pluto', 'Charon', 'Churyumov-Gerasimenko', 'Halley', 'Grigg-Skjellerup', 'Lutetia', 'Steins', 'Didymos', 'Dimorphos']\n"
     ]
    }
   ],
   "source": [
    "print(list(spz.inventories.flat_inventories.cdpp3dview.parameters.keys()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ea77b6f-80f2-4dc6-9855-dd63d0b4f07d",
   "metadata": {},
   "source": [
    "#### Completion works well\n",
    "cdpp3dview tree is like\n",
    "\n",
    "```\n",
    "Trajectory\n",
    "└── <BodyType>\n",
    "    └── <Body>\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ca8e25b6-1be1-43da-9b4a-5b768a3ddb37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ParameterIndex: Didymos>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spz.inventories.tree.cdpp3dview.Trajectories.ASTEROID.Didymos"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8548a706-39f8-474d-98d9-6283952f2b1a",
   "metadata": {},
   "source": [
    "### get_data() with string or ParameterIndex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d2263811-e6eb-4100-b08c-a82f69145ce7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SpeasyVariable(\n",
       "    Name: 'pos', \n",
       "    Time Range: 2008-01-01T00:00:00.000000000 - 2008-01-01T23:50:00.000000000\n",
       "    Shape: (144, 3), \n",
       "    Unit: 'km', \n",
       "    Columns: ['x', 'y', 'z'], \n",
       "    Meta: {\n",
       "        CATDESC: 'position in J2000 frame', \n",
       "        DISPLAY_TYPE: 'time_series', \n",
       "        FIELDNAM: 'Position', \n",
       "        UNITS: 'km', \n",
       "        VAR_TYPE: 'data', \n",
       "        DEPEND_0: 'Epoch', \n",
       "        LABL_PTR_1: ['x', 'y', 'z'], \n",
       "        }, \n",
       "    Size: '3.5 kB', \n",
       "    )"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# with ParameterIndex as product\n",
    "dimorphos_ParamIdx = spz.inventories.tree.cdpp3dview.Trajectories.ASTEROID.Dimorphos\n",
    "dimorphos_SpzVar = spz.get_data(dimorphos_ParamIdx, '2008-1-1', '2008-1-2')\n",
    "dimorphos_SpzVar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4cc13fe7-a2d0-4c95-b035-f473bde5863f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-01-01 00:00:00</th>\n",
       "      <td>148738016.0</td>\n",
       "      <td>38082860.0</td>\n",
       "      <td>7979088.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 00:10:00</th>\n",
       "      <td>148731184.0</td>\n",
       "      <td>38100460.0</td>\n",
       "      <td>7987508.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 00:20:00</th>\n",
       "      <td>148724368.0</td>\n",
       "      <td>38118064.0</td>\n",
       "      <td>7995928.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 00:30:00</th>\n",
       "      <td>148717536.0</td>\n",
       "      <td>38135664.0</td>\n",
       "      <td>8004348.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 00:40:00</th>\n",
       "      <td>148710704.0</td>\n",
       "      <td>38153264.0</td>\n",
       "      <td>8012768.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 23:10:00</th>\n",
       "      <td>147770688.0</td>\n",
       "      <td>40524640.0</td>\n",
       "      <td>9148443.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 23:20:00</th>\n",
       "      <td>147763600.0</td>\n",
       "      <td>40542172.0</td>\n",
       "      <td>9156847.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 23:30:00</th>\n",
       "      <td>147756496.0</td>\n",
       "      <td>40559700.0</td>\n",
       "      <td>9165252.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 23:40:00</th>\n",
       "      <td>147749408.0</td>\n",
       "      <td>40577232.0</td>\n",
       "      <td>9173656.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 23:50:00</th>\n",
       "      <td>147742304.0</td>\n",
       "      <td>40594760.0</td>\n",
       "      <td>9182060.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>144 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               x           y          z\n",
       "2008-01-01 00:00:00  148738016.0  38082860.0  7979088.0\n",
       "2008-01-01 00:10:00  148731184.0  38100460.0  7987508.5\n",
       "2008-01-01 00:20:00  148724368.0  38118064.0  7995928.5\n",
       "2008-01-01 00:30:00  148717536.0  38135664.0  8004348.5\n",
       "2008-01-01 00:40:00  148710704.0  38153264.0  8012768.5\n",
       "...                          ...         ...        ...\n",
       "2008-01-01 23:10:00  147770688.0  40524640.0  9148443.0\n",
       "2008-01-01 23:20:00  147763600.0  40542172.0  9156847.0\n",
       "2008-01-01 23:30:00  147756496.0  40559700.0  9165252.0\n",
       "2008-01-01 23:40:00  147749408.0  40577232.0  9173656.0\n",
       "2008-01-01 23:50:00  147742304.0  40594760.0  9182060.0\n",
       "\n",
       "[144 rows x 3 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dimorphos_SpzVar.to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "97bd82c4-3644-4053-bdae-55d059c7e97c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SpeasyVariable(\n",
       "    Name: 'pos', \n",
       "    Time Range: 2008-01-01T00:00:00.000000000 - 2008-01-01T23:50:00.000000000\n",
       "    Shape: (144, 3), \n",
       "    Unit: 'km', \n",
       "    Columns: ['x', 'y', 'z'], \n",
       "    Meta: {\n",
       "        CATDESC: 'position in J2000 frame', \n",
       "        DISPLAY_TYPE: 'time_series', \n",
       "        FIELDNAM: 'Position', \n",
       "        UNITS: 'km', \n",
       "        VAR_TYPE: 'data', \n",
       "        DEPEND_0: 'Epoch', \n",
       "        LABL_PTR_1: ['x', 'y', 'z'], \n",
       "        }, \n",
       "    Size: '3.5 kB', \n",
       "    )"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With String as product\n",
    "ace_product_str = 'cdpp3dview/ACE'\n",
    "spz.get_data(ace_product_str, '2008-1-1', '2008-1-2')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76fde0e6-b027-4deb-b9af-da0b27f2f0f7",
   "metadata": {},
   "source": [
    "### get_data() with coordinate_frame as additionnal parameter\n",
    "raise Exception if frame not available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "22fa5033-df16-4764-a245-8c58518e4d66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SpeasyVariable(\n",
       "    Name: 'pos', \n",
       "    Time Range: 2008-01-01T00:00:00.000000000 - 2008-01-01T23:50:00.000000000\n",
       "    Shape: (144, 3), \n",
       "    Unit: 'km', \n",
       "    Columns: ['x', 'y', 'z'], \n",
       "    Meta: {\n",
       "        CATDESC: 'position in HEEQ frame', \n",
       "        DISPLAY_TYPE: 'time_series', \n",
       "        FIELDNAM: 'Position', \n",
       "        UNITS: 'km', \n",
       "        VAR_TYPE: 'data', \n",
       "        DEPEND_0: 'Epoch', \n",
       "        LABL_PTR_1: ['x', 'y', 'z'], \n",
       "        }, \n",
       "    Size: '3.5 kB', \n",
       "    )"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spz.get_data(ace_product_str, '2008-1-1', '2008-1-2', coordinate_frame=\"HEEQ\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1417db72-8135-4fc6-b94a-37fba5a6074b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR IN ARGUMENTS\n",
      "Coordinate frame 'HEEY' is not available.\n",
      "Available frames are: ['J2000', 'ECLIPJ2000', 'HEE', 'HEEQ', 'HCI', 'IAU_SUN', 'MESO', 'MEME', 'MECLIP', 'MESE', 'MESEQ', 'IAU_MERCURY', 'VSO', 'VME', 'IAU_VENUS', 'GSE', 'EME', 'GSEQ', 'ECLIPDATE', 'MAG', 'GSM', 'SM', 'IAU_EARTH', 'LSE', 'LME', 'IAU_MOON', 'MSO', 'MME', 'IAU_MARS', 'PSE', 'PME', 'DSE', 'DME', 'JSO', 'JEME', 'JECLIP', 'JSM', 'SYSTEM_3', 'IAU_JUPITER', 'IPHIO', 'EPHIO', 'GPHIO', 'CPHIO', 'KSO', 'KEME', 'KECLIP', 'KSM', 'IAU_SATURN', 'MIIS', 'ENIS', 'TEIS', 'DIIS', 'RHIS', 'TIIS', 'UEME', 'UECLIP', 'USO', 'IAU_URANUS', 'NEME', 'NECLIP', 'NSO', 'IAU_NEPTUNE', 'PEME', 'PECLIP', 'PSO', 'IAU_PLUTO', '67PCG_EME', '67PCG_CSO', 'LUTETIA_EME', 'LUTETIA_CSO', 'STEINS_EME', 'STEINS_CSO', 'HALLEY_EME', 'HALLEY_CSO', 'GRIGGSKELL_EME', 'GRIGGSKELL_CSO', 'IAU_DIDYMOS', 'DIDYMOS_EME', 'DIDYMOS_CSO']\n"
     ]
    }
   ],
   "source": [
    "from speasy.data_providers.cdpp3dview import Cdpp3dViewWebException\n",
    "from sys import stderr\n",
    "# with no such frame raises exception , show available frames\n",
    "try:\n",
    "    spz.get_data(ace_product_str, '2008-1-1', '2008-1-2', coordinate_frame=\"HEEY\")\n",
    "except Cdpp3dViewWebException as e:\n",
    "    print(\"ERROR IN ARGUMENTS\", file=stderr)\n",
    "    print(str(e), file=stderr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b356829c-4754-4578-806c-b94bc57e9eb5",
   "metadata": {},
   "source": [
    "#### What if wrong date_range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "13a2a3cd-bc0b-4610-8c20-38c80a911630",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are requesting ACE outside of its definition range <DateTimeRange: 1997-08-26T17:48:00+00:00 -> 2026-03-22T17:49:00+00:00>\n"
     ]
    }
   ],
   "source": [
    "spz.get_data(ace_product_str, '1900-1-1', '1900-1-2')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42811e3e-5615-4408-aa63-b312c86cf692",
   "metadata": {},
   "source": [
    "#### Request other sampling than default '600'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1ab3afc0-6948-472b-8788-c4e684d7de4d",
   "metadata": {},
   "outputs": [
    {
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       "      <th>2008-01-01 12:30:00</th>\n",
       "      <td>-26254528.0</td>\n",
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       "    <tr>\n",
       "      <th>2008-01-01 12:40:00</th>\n",
       "      <td>-26272170.0</td>\n",
       "      <td>131438520.0</td>\n",
       "      <td>57139468.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              x            y           z\n",
       "2008-01-01 12:00:00 -26201596.0  131450416.0  57144592.0\n",
       "2008-01-01 12:10:00 -26219240.0  131447448.0  57143312.0\n",
       "2008-01-01 12:20:00 -26236884.0  131444472.0  57142032.0\n",
       "2008-01-01 12:30:00 -26254528.0  131441496.0  57140748.0\n",
       "2008-01-01 12:40:00 -26272170.0  131438520.0  57139468.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# with default 600\n",
    "spz.get_data(ace_product_str, '2008-01-01T12:00:00', '2008-01-01T13:00:00').to_dataframe().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "938252cc-c153-4bd3-befd-5ad7902d38c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-01-01 12:00:00</th>\n",
       "      <td>-26201596.0</td>\n",
       "      <td>131450416.0</td>\n",
       "      <td>57144592.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 12:01:00</th>\n",
       "      <td>-26203360.0</td>\n",
       "      <td>131450120.0</td>\n",
       "      <td>57144464.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 12:02:00</th>\n",
       "      <td>-26205124.0</td>\n",
       "      <td>131449824.0</td>\n",
       "      <td>57144336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 12:03:00</th>\n",
       "      <td>-26206890.0</td>\n",
       "      <td>131449528.0</td>\n",
       "      <td>57144208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01 12:04:00</th>\n",
       "      <td>-26208654.0</td>\n",
       "      <td>131449232.0</td>\n",
       "      <td>57144080.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              x            y           z\n",
       "2008-01-01 12:00:00 -26201596.0  131450416.0  57144592.0\n",
       "2008-01-01 12:01:00 -26203360.0  131450120.0  57144464.0\n",
       "2008-01-01 12:02:00 -26205124.0  131449824.0  57144336.0\n",
       "2008-01-01 12:03:00 -26206890.0  131449528.0  57144208.0\n",
       "2008-01-01 12:04:00 -26208654.0  131449232.0  57144080.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# with sampling = one minute\n",
    "spz.get_data(ace_product_str, '2008-01-01T12:00:00', '2008-01-01T13:00:00', sampling='60').to_dataframe().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4281b2a0-eb59-4be5-afa6-5a1b341574d6",
   "metadata": {},
   "source": [
    "#### Other utilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8bbe558a-7f4e-4f3c-a521-72aa05b82222",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<DateTimeRange: 1972-03-05T12:00:00+00:00 -> 2049-12-31T00:00:00+00:00>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spz.cdpp3dview.parameter_range(\"Pioneer10\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acda180c-5335-4aab-9823-01bc9ac358dd",
   "metadata": {},
   "source": [
    "### A Simple Example with MEX trajectory in frame MSO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "613d3c36-7d2a-4241-a3af-63ec87be945a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "mex_parameter = spz.inventories.tree.cdpp3dview.Trajectories.SPACECRAFT.MEX\n",
    "mex_traj = spz.get_data(mex_parameter, '20200102', '20200103', coordinate_frame=\"MSO\", sampling=60)\n",
    "mex_traj.plot()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.13.11"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}