{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Spacecraft data downloading\n",
    "\n",
    "## Introduction\n",
    "\n",
    "Here we demonstrate how to download spacecraft data using the *load_data* function of **AIDApy**. Three missions are currently implemented: Omniweb, Cluster and MMS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "#AIDApy Modules\n",
    "from aidapy import load_data\n",
    "import aidapy.aidaxr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Omniweb data\n",
    "\n",
    "First, we set up the parameters of the data: time interval and name of the mission. For this example, we will download from Omniweb all available data between May 15, 2008 and May 16, 2008, thus all other parameters are let to default values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_time_omni = datetime(2008, 5, 15, 0, 0, 0)\n",
    "end_time_omni = datetime(2008, 5, 16, 0, 0, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once all the parameters have been set up, the *load_data* function can be called. The data are given in a **xarray.DataSet** format, which is an implementation of labeled and multi-dimensional arrays. A specific extension has been developed (aidapy.aidaxr) to provide specific pre and postprocessing of the data (see the statistical example). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray 'all1' (time1: 25, products: 52)>\n",
      "array([[2385. ,   51. ,   52. , ...,  -15. ,   10. ,    6. ],\n",
      "       [2385. ,   51. ,   52. , ...,  -12. ,   10. ,    6.1],\n",
      "       [2385. ,   51. ,   52. , ...,  -12. ,   11. ,    5.9],\n",
      "       ...,\n",
      "       [2385. ,   51. ,   52. , ...,  -17. ,   19. ,    5.7],\n",
      "       [2385. ,   51. ,   52. , ...,  -16. ,   27. ,    5.9],\n",
      "       [2385. ,   51. ,   52. , ...,  -13. ,   25. ,    6.2]])\n",
      "Coordinates:\n",
      "  * products  (products) <U33 'Bartels Rotation Number' ... 'Magnetosonic Mach No.'\n",
      "  * time1     (time1) datetime64[ns] 2008-05-15 ... 2008-05-16\n",
      "Attributes:\n",
      "    Units:    {'Bartels Rotation Number': Unit(dimensionless), 'ID IMF Spacec...\n"
     ]
    }
   ],
   "source": [
    "xr_omni = load_data(mission='omni', start_time=start_time_omni, end_time=end_time_omni)\n",
    "xr_omni_all = xr_omni['all1']\n",
    "print(xr_omni_all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rdupuis/miniconda3/envs/aidapy/lib/python3.7/site-packages/pandas/plotting/_matplotlib/converter.py:103: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n",
      "\n",
      "To register the converters:\n",
      "\t>>> from pandas.plotting import register_matplotlib_converters\n",
      "\t>>> register_matplotlib_converters()\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff6c028a750>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6c0246050>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6c0246310>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xr_omni_mag = xr_omni_all.sel(products=['Bx GSE, GSM', 'By GSM', 'Bz GSM'])\n",
    "xr_omni_mag.plot.line(x='time1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cluster data\n",
    "\n",
    "Then, data can be downloaded from cluster mission. As this mission has several spacecraft, the index of the spacecraft called probe must also be provided.\n",
    "For this example, we will download the magnetic field during 5 minutes on August 5, 2013 for the probe 1 and 2 in GSE coordinate system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_time_cluster = datetime(2013, 8, 5, 0, 0, 0)\n",
    "end_time_cluster = datetime(2013, 8, 5, 0, 5, 0)\n",
    "\n",
    "settings_cluster = {'prod': ['dc_mag'], 'probes': ['1', '2'], 'coords': 'gse'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:                        (B_vec_xyz_gse__C1_CP_FGM_SPIN: 3, B_vec_xyz_gse__C2_CP_FGM_SPIN: 3, time1: 71, time2: 72)\n",
      "Coordinates:\n",
      "  * B_vec_xyz_gse__C1_CP_FGM_SPIN  (B_vec_xyz_gse__C1_CP_FGM_SPIN) <U1 'x' ... 'z'\n",
      "  * time1                          (time1) datetime64[ns] 2013-08-05T00:00:02.000119 ... 2013-08-05T00:04:58.000458\n",
      "  * B_vec_xyz_gse__C2_CP_FGM_SPIN  (B_vec_xyz_gse__C2_CP_FGM_SPIN) <U1 'x' ... 'z'\n",
      "  * time2                          (time2) datetime64[ns] 2013-08-05T00:00:02.000182 ... 2013-08-05T00:04:56.000512\n",
      "Data variables:\n",
      "    dc_mag1                        (time1, B_vec_xyz_gse__C1_CP_FGM_SPIN) float32 144.983 ... 4.068\n",
      "    dc_mag2                        (time2, B_vec_xyz_gse__C2_CP_FGM_SPIN) float32 86.769 ... 29.271\n",
      "Attributes:\n",
      "    mission:        cluster\n",
      "    load_settings:  {'prod': ['dc_mag'], 'probes': ['1', '2'], 'coords': 'gse'}\n"
     ]
    }
   ],
   "source": [
    "xr_cluster = load_data('cluster', start_time_cluster, end_time_cluster, **settings_cluster)\n",
    "print(xr_cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff6c02b2f50>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6c01291d0>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6c012f190>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xr_cluster['dc_mag1'].plot.line(x='time1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff6bf759810>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6bf7be9d0>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6bf7becd0>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEbCAYAAAA1T5h7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdd3gVZdrA4d+kd0IqkAChhJIQCBB6kSJVAUFELKAIIjZQV1dsy67rt2th14pdmqIUFUUWEOkC0gk99AQC6b2d5JT3+2PCkZKEnJBwIDz3deUKZ857Zp4JyTzz1tGUUgghhBAADvYOQAghxI1DkoIQQggrSQpCCCGsJCkIIYSwkqQghBDCSpKCEEIIKyd7B3CtAgICVFhYmL3DEEKIm8ru3bvTlVKBl2+/6ZNCWFgYu3btsncYQghxU9E0LaGs7dJ8JIQQwkqSghBCCCtJCkIIIawkKQghhLCSpCCEEMJKkoIQQggrSQpCiGqjlCI+vQBZkv/mJUlBCFEtLBbFjGWH6DNzA08s2ENOkdHeIYkqkKQghLhmJrOFvyzZx/w/EritRSC/HU7hjg9+J/Zstr1DEzaSpCCEKJfZoig2mSssYzCaeXzBHpbuPcfzA1swd0InFk/phlIw+pOtfL7pJBaLNCfdLCQpCFFJJrPllmorP5qcx5D3N9Fv5kbiknPLLJNnMDJx3k5+O5zC6yMieapfOJqm0aFRXVZM7cXtrYP514o45m6Nv77BiyrTbvZf8piYGCVrH4ma8M22BLacSOd8joHknCJS84ppEuDJG3e1oXuzgErtIy2vmFUHk4gK9aVtSB0cHLQajvraKaVYuPMsf192CG83Zxw0KCwx8/EDHejd4s/107aeTOeFJftJzjXwzui2jOoQWua+xn21g8NJuWx8oQ/ebs7X81REBTRN262UirliuyQFIa40b2s8M5YdorG/B438PKjn40awjxu/7D9PQkYho9qH8PIdrQnwci13H78dTmH6D/vJKCgBINjHlQERwQyOrE+P5v5o2o2XIHINRl7+8QDL9yfRKzyA/46JxmSxMGHOTo6n5vPGXW24KzqEt1bpd/9h/h78Z0w7Ojb2K3ef+xOzGf7RFqb1D+fZAS2u49mIikhSEKKS1selMnHeTvq3DubTBzvieNHdvcFo5qN1J/hs00k8XJx4aUgrxsQ0vKQGUFBs4p/LD7Nw51ki6vvwz7vakJBRwOpDKWw8lkaR0cyMYRFM6NHEHqdXrv2J2Tz17V7OZRfxl4EtmNK7mfW88gxGnvp2LxuPpRHg5Up6fjEPdw/jr4Nb4uFy9cWWn1iwm41H09j4174VJlJx/UhSEKIS4pJzGf3JHzT292DJlG7lXvBOpObx8tKD7DidSUM/d4K83fB2c8LbzZl9Z7M5m1XIY72b8dyAFrg4/dl1ZzCaeXT+LmLPZLP+hT43zAXySFIuoz/Ziq+HCx/cF13mnb/JbOH15YfZfCKdN0a0oXvzyjWhAZxMy2fgu5sY360xM4ZFVmfooookKQhxFal5BkbO2orJYuHnJ3tSr45bheWVUvyw5xy/HU4mz2Aiv9hEnsGEh4sjf7szgi5N/cv83InUfAa/t4nRHUN58+62NXEqNknNNXDXrC2YlarUeVfV9B/28+Oec6x7/jZC63rUyDFE5ZWXFGr0ITuaps0G7gRSlVJtSrf5AYuAMCAeGKOUytL0Btb3gaFAIfCwUmpPTcYnxAUWi+Kxr3eTWVDCkindKnVh1DSN0R1DGd3xyg7WijQP8mJCjzC+3HyaB7o0Jiq0TlXDvmaFJSYmzd9FVqGx0uddVdNuD+fHved4b81xZt7TrsaOI65NTQ9JnQsMvmzbdGCtUiocWFv6GmAIEF76NRn4pIZjE8JqZ3wme89kM2NYBG1Cav4i/XT/cPw9XZix7KDdhrlaLIpnF8Vy4FwOH9zXvsbPu34ddx7q1pgf9yRyLCWvRo8lqq5Gk4JSahOQednmEcC80n/PA+66aPt8pdsG+GqaVr8m4xPigmX7zuPu7Mjw6AbX5Xg+bs78dXAr9pzJ5qfYc9flmBcopTidXsBrPx/k10MpvHpHBAMigq/LsZ/o0xwvVyce/2Y3aXnF1+WYwjb2eEZzsFIqCUAplaRpWlDp9hDg7EXlEku3JV2+A03TJqPXJmjUqFHNRitqPaPZwsqDyfRvHVSpkTTVZXSHUBZsS+DfK+IYEFEPL9fqP3axycz5bAOJWYXEZxSyKz6TbacySMnVL8gPdWvMIz3Cqv245anr6cKXD3Xiodk7ePDL7Xw3uSt+ni7X7fji6uyRFMpT1qDtMuvVSqnPgc9B72iuyaBE7bf1ZAaZBSUMa3d9agkXODhozBgeyaiPtzLk/U080KUxY2IaVvkiqZQiIaOQLSfT2Xoyg93xWSTnGi4pE+jtStem/nRt6keXJv40C/S87vMlOjfx48uHYpgwdyfjvtrOt5O6UsdDJrXdKOyRFFI0TatfWkuoD6SWbk8EGl5ULhQ4f92jE7ecX/adx9vNiT4tA69euJp1aFSXrx6K4fNNp3hzZRz//e0Yd0TVp3szf/y9XKjr4YKfpwt1PV1wcXTAYDRTZDRTVGImo6CEU2n5nEor4GRaAUeScjmXXQToE+W6NvWnaYAXoXXdCanrrn/3db8hJs31aB7AZ+M68tj83Yyfs4PXh0dyNquQ02kFnE4v4FR6AT7uzjx+WzO6NSt7FJeoGTU+JFXTtDBg+UWjj94BMpRSb2qaNh3wU0r9VdO0O4Cn0EcfdQE+UEp1vtr+ZUiquBbFJjMx/1zDoDb17D4i5lhKHgu2JfDDnnPkF5sq/TkXRwfCAjwID/Kma1M/ujcPoGnA9a8BVMXqQ8k8sWAPposWzKtfx40wf09OpuWTmldMlyZ+TLs9nG5Nb8xZ4Dcru8xT0DTtO6APEACkADOAn4DFQCPgDHCPUiqzdEjqR+ijlQqBCUqpq17tJSmIa7H6UDKTv97NvEc6c1uL619TKIvBaCY1t5jMwhKyCkrILP0qMVvwcHHEzdkRd2dH6rg70zTQk9C6HpfMur7ZHEjMISGzgKYBXoQFeFj7dQxGM9/tOMMnG06SmldMj+b+vHtvNEHeNTds9lYik9eEKMNT3+5h68kMtr/cH2dHWTT4RnQhOby96ii+Hs58MT7mugwbru3KSwryVyBuWYUlJtYeSWVIm3qSEG5gbs6OTOjRhO8f74YGjP50KysOXDEoUVQT+UsQt6w1R1IpMpqv+6gjUTWRDerw81M9iajvwxML9vDOr3Ek5RTZO6xa50YakirEdfXLvvME+7jSKaz8ZZ/FjSXQ25XvJnfl5R8PMmv9SWatP0nTAE+6N/enR7MAOobVLbPPwWJRJGYVEeTjipuzY43Edi67iO2nMjh4LpfbWgbeMH1UtpKkIG5JOYVGNh5NY1y3xjd1J+2tyNXJkZn3tGVSryZsOZHOlhPpLN1zjm+2nQGgoZ87HRvVpU1IHVJyDRw4l8PBc7nkF5sI8nbl8T7NuK9zo2pJDqfS8vls4ym2nEwnMUuvtTg6aMzecpreLQJ5ZWhrWtbzvup+zBZFbpERD1dHXBwd7DrKSjqaxS1p1voTvPPrUf43tSeRDaTT8mZnNFvYn5jDnoQs9pzJYldCFml5xbg4OdC6vg9tQ+rQItiL/x1IYtupTIJ9XHmiT3Pu7dSwSskhz2Dko3UnmL3lNC6ODvQKD6RL6YTApoGefLMtgQ/WHie/2MS9nRrxQJdGNA/yuuRYuQb9xmRdXCrrj6aSXWgEwMlBw9PViUBvV/q0CGRARDAdG9fFqZr7vWT0kRClikrM9HhrHW1D6zB3wlWnwoibkFKKtLxifD1cLnmeBeiPEX3vt+PsiNefhfG3OyO5vXVQpe7OTWYLS/ee461VR0nPL2ZMTCgvDGpFoPeVz8XIKijhg3XH+fqPBEwWhaODRrNAT1rV8yEtr5id8ZmYLIq6Hs70bRVEZIM6GIxmCopNFBSbOJ1RyLaTGZSYLdT1cKZfq2AGRATRKzwQz2pYEkWSghClZm8+zevLD/P9lG7ESH/CLUkpxeYT6bz+y2GOp+ZzW4tAZgyLoGmgV5ll9yXm8NPecyzfn0R6fjHtG/ny92GRtGvoe9VjJeUUsSchmyNJuRxJyiUuOQ8vVyf6tQ7i9tZBRDesW24TZp7ByKZj6fx2OJl1cankGky4ODrQrZk/t0cEMziyXpkJqTIkKQgBlJgs9H57PY38PVj8WDd7hyPszGi2MP+PBN777RgGk5mJPZsytlNDEjILOZ6Sx4nUfLafzuR0egEujg70axXEyA4hDGgdfMkjWK9XrDvjM1l7JJU1R1JIyCjks3EdGRRZr0r7k6QgBLBwxxmm/3jghprBLOwvNc/AWyuP8sOexEu2+3u6ENHAhzvb1mdwm/rUcb8xFu5TSnEyLZ8QXw/cXarWYW6XJ6+JG0dBsYnsIiMhvu72DsVuTGYLn2w8SVRIHXqHV/75wqL2C/J24z9j2jGuW2MOn8+lWaAnzYO88L9BnqF9OU3TaB509VFNVSFJoZY7mpzHN9sSWLpXX2RtSJt6PDegBeHBl/5CnUrL58C5HG5vHVwtnVg3ov8dSCIho5BPH+wgC6uJMkU39CW6Ev0EtVnt/Ou/xSmlWBeXyqcbT7IzPgsXJwfujKpPfV835m1N4NdDydzVPoT7Ojdi+6kMlu9PIi5ZfzxiRH0fvno4hvp1aleNwmJRfLz+JM2DvBgYUbU2WCFuBdKnUMucTi/gH78cYsPRNBr5eTCua2NGdwylbumDWzILSvh040nmbY2n2GQBoGPjutwRVZ8Ab1de/vEAnq6OfDm+k10fKF9dzmQUsupQEisOJBN7Npv/jmnHqA6h9g5LCLuTjuZarrDExEfrTvDl76dxcXLgmdvDeah7WLkLvSXnGNh2KoMuTf0uqRUcTc7jkbk7ySwo4b2x0VUe2WBPZzMLWbbvPMv3J3EkKReANiE+jGgXwiM9m8gMZiGQpFCrrTqYzD9+OURSjoFRHUKYPqTVNa05n5pnYPL83exLzCaygQ8tgr1Lv7wID/ImxNf9ug/Hu8BiUZzLLiKzoASzUlgsCrNFYVFwNDmXn/edZ++ZbAA6NPJlaFR9BkXWo6Gfh13iFeJGJUmhFio2mfnX/44w748EIur78PqIyGqbjGUwmvl4w0liz2ZzLDnvkmf9erg4Eh7kRXiwN4Mi6zEgIrhajlmetUdSWBuXSlxSLkeT8ygoMZdbtlU9b0ZEhzCsXX1C60oiEKI8khRqmbOZhTz57R72J+bwaK8m/HVwqxp9JkBOkZHjKXkcS8nnWEoex1PziEvKI6OghDvb1uf1EW2q/MD5ivx+PI3xs3fg7epEq/o+tK7nTav6PgR5u+LgoOGoaTg6aGgaBPu40ayMGalCiCvJPIVaZM3hFJ5bHIuCa5rRaIs67s7EhPldUhMxmi18uuEkH6w7zh8nM3jjrjYMiapfbcdMzTXw7KJYwoO8+PnJnlWepCOEqDx5yM5NZs+ZLB77ZjeN/D3439O97NoR7OzowNP9w1n2VE/q+7rx+II9PPXtHjILSq5532aL4plFseQXm5h1fwdJCEJcJ1JTqKJik5kNR9NIzTVgMFooNpkpNlmo4+5MsyAvmgd62dwhm19sYv4f8fx6MJnX7oy4on8g12Bk2sK91PNxY8GkrjfMlPvW9X1Y+kQPa61hw9E0RnUIYXy3xpfMulRKcSI1nzOZhXRr5m99QHtZZq0/wdaTGbw9uu0VE+2EEDVH+hRsdCI1n4U7zvDDnkSyStc/v0DT4OIfp7uzI00DPWkW6EVYgCdNAzwJC/AktK47Pm7O1iV9c4qMzN0Sz+wtp8kpMuLt5oRS8M2kLtbZlUrpd87L9yex+LGudGx8Y67ueSwlj083nGT5/iRKzBa6NfWnZ3gA+xOz2RmfZa1FeLs6MaJ9A+7r3OiK5xlsO5XB/V9sY0R0CP8d005mHwtRA6Sj2UbFJjMJGYXEpxcQn1FAfEYhR5Jy2XsmGycHjYGRwYzt1IiIBj64OTvi6uSAk4NGVqGRE6n5f36l5XMqLZ9z2UVc/qN2dXLA282ZwhIThSVmbm8dzNP9mhPk48qYz/4gp9DIt492pU1IHX7YnchfluzjuQEtmNo/vNrPt7pl5BezaNdZFmw7w7nsIhr6udM5zJ8uTf0I9nHj573nWH4giRKThdb1ffB2c6KoxEyR0cz57CLq+bix7OmeeNXSJTeEsDdJCpcxGM2k5RWTmmcgNbeYtPxizmcbOJGaz8m0fBIyCrBc9KOp6+FMWIAngyLrcXeHUJvXMC82mTmbWciptAKScgzkGYzkGUzkGow4Omjc37kxEQ18rOXPZhYy9vNtFJaY+PeotvxlcSyRIXX47tGuN9XkK7NFkV1YUubCYtmFJSzde45VB5MBfairu4sj3q7OTL6tqYwkEqIGSVK4zIyfDzLvj4RLtjk7ajQJ0Jt7mgd50SzQiyYBnoT5e1LH4/q338enF3Dv53+QkltMHXdnVk7rRYNbeJVTIUT1kSGplxnWrgGRDeoQ6ONKkLcrQd5u+Hm63FB34WEBniyY1JW/fr+Pp/o1l4QghKhxt2xNQQghbmXl1RRknoIQQggrSQpCCCGsJCkIIYSwkqQghBDCSpKCEEIIK0kKQgghrCQpCCGEsJKkIIQQwkqSghBCCCu7JQVN057VNO2QpmkHNU37TtM0N03Tmmiatl3TtOOapi3SNK36n+8ohBCiXHZJCpqmhQBTgRilVBvAERgLvAW8q5QKB7KAifaITwghblX2bD5yAtw1TXMCPIAkoB/wfen784C77BSbEELckuySFJRS54CZwBn0ZJAD7AaylVKm0mKJQIg94hNCiFuVvZqP6gIjgCZAA8ATGFJG0TKXcNU0bbKmabs0TduVlpZWc4EKIcQtxl7NR7cDp5VSaUopI/Aj0B3wLW1OAggFzpf1YaXU50qpGKVUTGBg4PWJWAghbgH2SgpngK6apnlo+lPZ+wOHgfXA6NIyDwE/2yk+IYS4JdmrT2E7eofyHuBAaRyfAy8Cz2madgLwB76yR3xCCHGrstvjOJVSM4AZl20+BXS2QzhCCCGQGc1CCCEuIklBCCGElSQFIYQQVpIUhBBCWElSEEIIYWW30UdC3AyMRiOJiYkYDAZ7hyJElbi5uREaGoqzs3OlyktSEKICiYmJeHt7ExYWhj7PUoibh1KKjIwMEhMTadKkSaU+I81HQlTAYDDg7+8vCUHclDRNw9/f36aariQFIa5CEoK4mdn6+ytJQQghhJUkBSGEEFaSFISwkaOjI9HR0bRr144OHTqwdetWe4d0U0tOTmbs2LE0a9aMiIgIhg4dyrFjx4iNjaVbt25ERkbStm1bFi1aVOF+jEYj06dPJzw8nDZt2tC5c2dWrlwJQFhYGFFRUbRr146BAweSnJxc7n4ulI2OjiY6Otr6/3v8+HHuvPNOmjVrRseOHenbty+bNm0CYO7cuWiaxtq1a637Wbp0KZqm8f3335d5HIDly5fTvn172rVrR0REBJ999hkAf//73wkJCSE6Opo2bdqwbNky6/aZM2cC8PDDDxMSEkJxcTEA6enphIWFVfgzqgwZfSSEjdzd3YmNjQXg119/5aWXXmLjxo12jurmpJRi5MiRPPTQQyxcuBCA2NhYUlJSCA4OZv78+YSHh3P+/Hk6duzIoEGD8PX1LXNfr732GklJSRw8eBBXV1dSUlIu+X9Zv349AQEBvPzyy/zrX//igw8+KDeuC2UvMBgM3HHHHcycOZPhw4cDcPDgQXbt2kXv3r0BiIqK4rvvvqN///4ALFy4kHbt2pV7DKPRyOTJk9mxYwehoaEUFxcTHx9vff/ZZ5/l+eef58iRI/Tq1YvU1NQr9uHo6Mjs2bN5/PHHyz2OraSmIMQ1yM3NpW7duuW+f++997JixQrr64cffpgffvgBs9nMCy+8QKdOnWjbtq31DhHg7bfftt7VTp8+vcz9mkwmOnXqxIYNGwB46aWXeOWVV1i7di0jR460lvvtt98YNWoUy5Yts975tmzZssLhiStWrKBVq1b07NmTqVOncueddwKwceNG6z7at29PXl4eAO+88471PGbMuHzh44qtX78eZ2dnpkyZYt0WHR1Nr169aNGiBeHh4QA0aNCAoKAgynvSYmFhIV988QUffvghrq6uAAQHBzNmzJgryvbu3ZsTJ07YFOeCBQvo1q2bNSEAtGnThocfftj6ulevXuzYsQOj0Uh+fj4nTpwgOjq63H3m5eVhMpnw9/cHwNXVlZYtW15RrnXr1jg5OZGenn7Fe8888wzvvvsuJpPpiveqSmoKQtioqKiI6OhoDAYDSUlJrFu3rtyyY8eOZdGiRQwdOpSSkhLWrl3LJ598wldffUWdOnXYuXMnxcXF9OjRg4EDBxIXF8dPP/3E9u3b8fDwIDMzs8z9Ojk5MXfuXEaPHs0HH3zAqlWr2L59O87Ozjz55JOkpaURGBjInDlzmDBhAsOGDbNe0MaMGcNtt91W5n4NBgOPPfYYmzZtokmTJtx3333W92bOnMmsWbPo0aMH+fn5uLm5sXr1ao4fP86OHTtQSjF8+HA2bdpkvXu+moMHD9KxY8erltuxYwclJSU0a9aszPdPnDhBo0aN8PHxueq+li9fTlRUVIVl+vbti6OjI66urmzfvp1Dhw7RoUOHCj+jaRq33347v/76Kzk5OQwfPpzTp0+XW97Pz4/hw4fTuHFj+vfvz5133sl9992Hg8Ol9+rbt2/HwcGBsp4y2ahRI3r27MnXX3/NsGHDKoyvsqSmIISNLjQfxcXFsWrVKsaPH49SZT5OnCFDhrBu3TqKi4tZuXIlvXv3xt3dndWrVzN//nyio6Pp0qULGRkZHD9+nDVr1jBhwgQ8PDwA/cJRnsjISMaNG8ewYcOYPXs2Li4uaJrGuHHj+Oabb8jOzuaPP/5gyJA/H3/+9ttv4+7uzpNPPlnmPuPi4mjatKm1JnFxUujRowfPPfccH3zwAdnZ2Tg5ObF69WpWr15N+/bt6dChA3FxcRw/ftzmn2lFkpKSGDduHHPmzLnigmmLvn37Eh0dTW5uLi+99FKFZdevX09sbCzbt28v8/2RI0fSpk0bRo0adcn2sWPHsnDhQhYuXHjJz648X375JWvXrqVz587MnDmTRx55xPreu+++S3R0NM8//zyLFi0qd2jpyy+/zDvvvIPFYrnq8SpDagpCXINu3bqRnp5OWloaQUFBV7zv5uZGnz59+PXXX1m0aJH1QqGU4sMPP2TQoEGXlF+1apVN48oPHDiAr68vKSkp1m0XagZubm7cc889ODnpf+Zr165lyZIl1s7RspSX3ACmT5/OHXfcwYoVK+jatStr1qxBKcVLL73EY489VumYLxYZGVlhR2xubi533HEHb7zxBl27di23XPPmzTlz5gx5eXl4e3uXWebyfgJb47z457Z06VJ27drF888/f0m5zp07c/DgQdzd3WnRokWl9h0VFUVUVBTjxo2jSZMmzJ07F/izT+FqmjdvTnR0NIsXL678CVVAagpCXIO4uDjMZrO1XbgsY8eOZc6cOfz+++/WJDBo0CA++eQTjEYjAMeOHaOgoICBAwcye/ZsCgsLAcptPgL48ccfycjIYNOmTUydOpXs7GxAb39v0KABb7zxhrXNOyEhgSeeeILFixfj7u5e7j5btWrFqVOnrB2eF4/4OXnyJFFRUbz44ovExMQQFxfHoEGDmD17Nvn5+QCcO3euzA7R8vTr14/i4mK++OIL67adO3eyceNGSkpKGDlyJOPHj+eee+6pcD8eHh5MnDiRqVOnUlJSAug1jG+++abSsVTk/vvvZ8uWLdZRQID1/+hy//73v/nXv/511X3m5+db+4RA72Bv3LhxleJ75ZVXrKOSrlWlagqaprUCQoDtSqn8i7YPVkqtqpZIhLhJXOhTAP3Oet68eTg6OpZbfuDAgYwfP57hw4fj4uICwKRJk4iPj6dDhw4opQgMDOSnn35i8ODBxMbGEhMTg4uLC0OHDi3zApOens706dNZu3YtDRs25KmnnmLatGnMmzcPgAceeIC0tDQiIiIAfchkRkaGtRO6QYMGl3SAX+Du7s7HH3/M4MGDCQgIoHPnP5+O+95777F+/XocHR2JiIhgyJAhuLq6cuTIEbp16waAl5cX33zzTZm1prJomsbSpUt55plnePPNN3FzcyMsLIz33nuPxYsXs2nTJjIyMqx3z3Pnzi238/aNN97g1VdfJSIiAjc3Nzw9PXn99dcrFcfVuLu7s3z5cp577jmeeeYZgoOD8fb25tVXX72i7MXNdRVRSvH222/z2GOP4e7ujqenp/U8bRUZGUmHDh3Ys2dPlT5/Ma2i6iKApmlTgSeBI0A0ME0p9XPpe3uUUhX3vtSwmJgYtWvXLnuGIGqxI0eO0Lp1a3uHYbOnnnqK9u3bM3HiRJs/m5+fj5eXF0opnnzyScLDw3n22WdrIEpxvZT1e6xp2m6lVMzlZStTU3gU6KiUytc0LQz4XtO0MKXU+4AsCiPEDaZjx454enryn//8p0qf/+KLL5g3bx4lJSW0b9++yv0F4uZUmaTgeKHJSCkVr2laH/TE0BhJCkIAeofvuHHjLtl2YTjjtXryySfZsmXLJdumTZvGhAkTyiy/e/fuSu135MiRVwyZfOutt3j22WevqWaQkZFhncB1gdlsBriimW3t2rUV9seUpby4L++0v5ouXbpYZwNf8PXXX191uGpVVFfM10Nlmo/WAc8ppWIv2uYEzAYeUEqV35h6HUjzkahJN2vzkRAXs6X5qDKjj8YDlywUopQyKaXGA5WboSKEEOKmcNXmI6VUIoCmaWXNotlR7REJIYSwG1vmKewB0oBjwPHSf5/WNG2PpmlXn6cuhBDihmdLUlgFDFVKBSil/IEhwGLgCeDjmghOCCHE9WVLUohRSv164YVSajXQWym1DXCt9siEEEJcd7YkhUxN017UNK1x6ddfgSxN0xyB6lmJSQghKrBz507atm2LwWCgoKCAyMhIDh48aO+wahVbFsS7H5gB/IQ+P2Fz6TZH4Dl3PB0AACAASURBVMpFy4UQtdo/fjnE4fO51brPiAY+zBgWWe77nTp1Yvjw4bz66qsUFRXx4IMP0qZNm2qN4VZX6aSglEoHni7nbdueWCGEEFX0t7/9jU6dOuHm5lbh09NE1VQ6KWiaFgj8FYgE3C5sV0r1q4G4hBA3uIru6GtSZmYm+fn5GI1GDAYDnp6edomjtrKlT2EBEAc0Af4BxAM7ayAmIYQo1+TJk/nnP//JAw88wIsvvmjvcGodW/oU/JVSX2maNk0ptRHYqGmaPK1cCHHdzJ8/HycnJ+6//37MZjPdu3dn3bp19OsnDRbVxZakYCz9nqRp2h3AeSC0+kMSQoiyjR8/nvHjxwP64nrVseCguJQtSeENTdPqAH8BPgR8gCovpahpmi/wJdAGUMAjwFFgERCG3jw1RimVVdVjCCGEsE2l+xSUUsuVUjlKqYNKqb5KqY5KqWVX/2S53gdWKaVaAe3QH+IzHVirlAoH1pa+FkIIcZ3YMvqoCfqQ1LCLP6eUGm7rQTVN80FfYfXh0n2UACWapo0A+pQWmwdsAKQnSQghrhNbmo9+Ar4CfuHaZzA3RV9Qb46mae2A3cA0IFgplQSglErSNK1yD3oVQghRLWxJCgalVHXNFHECOgBPK6W2a5r2PjY0FWmaNhmYDNCoUaNqCkkIIYQt8xTe1zRthqZp3TRN63Dhq4rHTQQSlVIXhg58j54kUjRNqw9Q+j21rA8rpT5XSsUopWICAwOrGIIQQojL2VJTiALGAf34s/lIlb62iVIqWdO0s5qmtVRKHQX6A4dLvx4C3iz9/rOt+xZCCFF1tiSFkUDT0k7h6vA0sEDTNBfgFDABveayWNO0icAZ4J5qOpYQQohKsCUp7AN8KadJx1ZKqVjgiodGo9cahBDiCq+99hoBAQFMmzYNgFdeeYXg4GCmTp1q58hqD1uSQjAQp2naTqD4wsaqDEkVQtQCK6dD8oHq3We9KBjyZrlvT5w4kVGjRjFt2jQsFgsLFy5kxw55VHx1siUpzKixKIQQohLCwsLw9/dn7969pKSk0L59e/z9/e0dVq1iy/MUKlz8TtO0P5RS3a49JCHETaGCO/qaNGnSJObOnUtycjKPPPKIXWKozWwZkno1blcvIoQQ12bkyJGsWrWKnTt3MmjQIHuHU+vY0nx0Naoa9yWEEGVycXGhb9+++Pr64ujoaO9wap3qTApCCFHjLBYL27ZtY8mSJfYOpVaqzuYjrRr3JYQQVzh8+DDNmzenf//+hIeH2zucWsnWVVKTlFKG0tfu6AvYxZcWGVf94QkhxJ8iIiI4deqUvcOo1WypKSzh0tVRzaXbAFBKHayuoIQQQtiHLUnB6eIlLkr/7VL9IQkhhLAXW5JCmqZp1tnLpQ/ESa/+kIQQQtiLLaOPpqAvYPdR6etEpB9BCCFqlasmBU3Tnrvo5WLAA32kUQEwAvhvzYQmhBDieqtMTcG79HtLoBP6Mw409FrCphqKSwghhB1cNSkopf4BoGnaaqCDUiqv9PXfuWj0kRBC1LRPP/2UTz/9FICcnBzCwsJYv369naOqXWzpU2gEXPyAnRIgrFqjEULcNN7a8RZxmXHVus9Wfq14sfOL5b4/ZcoUpkyZgtFopF+/fjz33HPllhVVY0tS+BrYoWnaUvR1jkYC82okKiGEqMC0adPo168fw4YNs3cotY4tS2f/n6ZpK4FepZsmKKX21kxYQogbXUV39DVp7ty5JCQk8NFHH129sLCZTQviKaX2AHtqKBYhhKjQ7t27mTlzJr///jsODtW5dJu4QH6qQoibxkcffURmZiZ9+/YlOjqaSZMm2TukWkeWzhZC3DTmzJlj7xBqPakpCCGEsJKkIIQQwkqSghBXoZQ8aVbcvGz9/ZWkIEQF3NzcyMjIkMQgbkpKKTIyMnBzc6v0Z6SjWYgKhIaGkpiYSFpamr1DEaJK3NzcCA0NrXR5SQpCVMDZ2ZkmTZrYOwwhrhtpPhJCCGElSUEIIYSVJAUhhBBWkhSEEEJYSVIQQghhJUlBCCGElSQFIYQQVpIUhBBCWElSEEIIYWXXpKBpmqOmaXs1TVte+rqJpmnbNU07rmnaIk3TXOwZnxBC3GrsXVOYBhy56PVbwLtKqXAgC5hol6iEEOIWZbekoGlaKHAH8GXpaw3oB3xfWmQecJd9ohNCiFuTPWsK7wF/BSylr/2BbKWUqfR1IhBS1gc1TZusadouTdN2yeqVQghRfeySFDRNuxNIVUrtvnhzGUXLXMReKfW5UipGKRUTGBhYIzEKIcStyF5LZ/cAhmuaNhRwA3zQaw6+mqY5ldYWQoHzdopPCCFuSXapKSilXlJKhSqlwoCxwDql1APAemB0abGHgJ/tEZ8QQtyq7D366HIvAs9pmnYCvY/hKzvHI4QQtxS7P3lNKbUB2FD671NAZ3vGI4QQt7IbraYghBDCjuxeUxDilmcqAZMBzEawGPXv3vXBUf48xfUnv3VCXE+552H1q5AVD4UZUJABJXlXlgtoASNmQUNpTRXXlyQFIa6X9BPw9Ug9GTTqAn7NwMNf/3J2B0cXvXZgNsHWD+CrgdBlCvR/DVw8bT9eQTqkHobUOEg7AjmJ0H4cRAyv/nMTtYYkBXFr2rcI1v0TxsyDkI41f7zze+Gb0tHWE/4HDdpXXD76Pljzd9j+CRxdAcM/gKZ9Kv5MXgrE/w7xm/XvGSf+fM+tDrj6wOJxEDUGhr4N7nWv4YREbSVJQdxazEa9+Wb7p/rrgz/WfFI4vQm+u1+/CI9bCgHNr/4ZV2+44z8QOQqWPQXzR0DUPdDlcQjpANpFCwCc2QabZsKJ30o/6wONu0OH8VAvCgJbg3c9sJjg9//Cprf1pDH8QwgfUDPnLG5amlJlriRx04iJiVG7du2ydxjiZpCfCksehoQt0PUJSNoHRdnwxNaaO+aR5fD9BPBrqicEnwa278NYBBvfgh1fQEk+1I+GTpP0zujN70LCZr0JqvNkCB8I9dpW3El9PhaWTtGblPq8BH2mV/38aruiLEg7Co262juSaqdp2m6lVMwV2yUpiFtC+nGYN0xPAsM/hLb36HfNa/8BfzkG3sHVf8zYb+HnJ6FBB3hgCXj4Xdv+DLmwfxHs/Eq/oIOeGLpPhY4P2dbvYCqGX56Bfd/CwDeg+9PXFlttlHIIvhsL2Weg9XC95uYVZO+oqk15SUGaj0TtZyyCxQ+BuQQm/aY3qQA066snhdMboe2Y6j3mtk9g1XS9H+DeBeDqde37dPOBzo/qtYSErZCfDK3uBCdX2/fl5AojPgJjod6c5uoNHR++9hhriyO/wI+P6T/zHtP0/8/4zTD0HWhz96XNd7WMTF4Ttd+vL0PqIRj52Z8JAaBeO3D3g5Prq+9YSsH6f+sJofUwuH9x9SSEi2kahPXQL05VSQgXODjCqC+g+QC91nDg+6t/prZTCja+DYsehKBW8Oh6GPA6TNmsNwH+MFF/z2iwd6Q1RpKCqN0O/QS7ZuvNI5d3qjo4QNPb4NR6/WJwrQy5sPQx2PgmRD8Ao+de20X7enBygTHz9Y7ppY/BhrfgxBp9JNOtpjgPFo+H9f8HbcfCwyvAp77+XmBLmLgabv8HxC3XR67VUtJ8JGqvrHhYNlUfXdTvb2WXadoXDi3VOxODWlX9WIm74YdH9PbnPi9D7xf0pHMzcPGA+xbCwvthw7/+3O4ZqNesGnaFqNHg36z6j52fql9gA1rYt18j46R+/unHYMA/9VgubyJycISez0DOWfhjFrQYDE162SfeGiRJQdROZiN8PxFQMHq2fkdclqZ99O+n1lctKVgssOU9/e7Su75+d9m4WxWDtiM3H3h4ORRm6h2sKQch+QAk74cN/9aTRYP2+hyHVkOhTkP9IllVSsHer/X+DEOOvs1shF7PVc/52OLYr/DDo/r5PPij3tdUkQGv602OPz0Oj2/Vf3a1iIw+ErVPYab+B3tsFdwzFyJHVlz+g/bgHw4PLK7c/pWCc7vh8E9w+Ge9dhBxFwx7r3ZOCMs9Dwd/gANL9GG8AA5O+vDaOo3At6GeJHwbQp1QqNsE6oaV3xmbdgyWP6sPpW3cA+74L/w+U9//4Deh6+PX57wsFvj9P3pCr9dGHxBQt3HlPnt2J8weCO3ug7s+rtk4a4iMPhK3hjPb9BpCQSoMnXn1hAB6E9K+hfrCdOXVKEC/mO2eA4eXQW4iODjrd5W3/0M/Tm0dkeLTQG9O6f603swWv1lfMiPnLGSf1Sfn5SWBsvz5mYAW+s8kcpReA8tP1ft3Dv4AZ7fpM6yHfwjRD+rNbHd9qi8KuGo6OLlBzISaPaeSAvhxst4/EDUGhr2vN6NVVsNO0PM5PZm1HAqt77x032aj/m9NAzR9dNdN8vshNQVxY1FKXxLCv5l+4SiLsQgK0krXCnLR71odnfVZymv/qd+x3jP36ktJXHDkF31EyYSVeodrWTJOwhf99CGczfpDxAhoOQTcfat0mrWO2Qi55/RkkXpEr0HFbwYU+DbStysLBEVAm1HQ4aErx/ybSmDRA3D8N7jrE32pj/IU50HyQQjtZPtqsjnn9PkHKQf1ORpdn6jaBdtUAl/215NjSEd9v7nnoTjnyrIhMXotqGEn249THrMR0Kq8mq5MXhM3vpPrYe3rcH4PeARAv1eg/fg/f+lLCmHnF/os3qKssvcROVK/6ysvoZSlKBvebgK9ntePecX7WfDl7Xqz1KNr9aGJ4uryUvTkcHKt3mEdOQqCIyr+jNEA347Rl+G48z19FNfFFz2l9H2uegnyzus1kr6v6Em6Mhf2c3vgu/v0u/nRs6HFQJtOqdBYyK6UXfQM6YmD5qAvNrh0MqDpTWc+DfS+JSc3oPTaWlIIO7/U55W0GQ23/12/cbkaowHS4vS+nZSDeid4YYb++1iYRZExH8cx3+BycS3FBpIUhO2K8/VZsjVd7T23G9aUTiKr0xC6PanfvSdsgaBIGPg6ZCXo48fzk6H57foMU2XW75bMJfp3v6aVvzhc7svb9e+T1ly63WyCBXdD/BYY/7M+P0DUrJICWHCP/v/vFay327d/UO8IXvGCPmQ2OEqfxb3jC0g/qi/90f9v0Lx/+fs99JO+vIdnINy/EIIjbQorvSidJ9Y8wZHMI9zf6n6md56OVtnfteJ8fUDC1g/1163uBL8m4NtY78fwbaz/Pp/dCYk74OwO8lMPk+2gyHFwJMfFnfQ6DTjp6sopB8UJVcw5SyGzYl6hV+RYm87jAkkKonKKsvU7sf2L9T/KgBYQ8wi0G1v9TSVKweb/6rUDD399GGfMI/rYfqXgyDJ9dEr2Gb18w676H35NXJjX/Z/ePvzX05ee54oXYMfnMPwj6DCu+o8rymY26s1Ie7/WRwcps95M6OSu1+Y6ParXICxmfemP9f+GnNLlKIbOvHTZkuJ8fQLjnnl6c9PYb21eriI+J54pa6aQacikZ0hPfkv4jUlRk5jWYZpt55V9Vu/Yjt+i90td3A8DZDo4sKJOXZb51uUIJVd83MnBiTCfMJr5NqOZbzMGhw2mSZ0mtsVQSpKCqFhhpj4i5OgK/c7bv7negZawRb+Td3KHqLv1zrXqGK9uKoHlz0DsAr1KPew9vTPuckaD/kfvE6LfBdZUrSVhK8wZol9U/Jvrs5Dz0/Slq7s/rbc9C/vIS4F930F+iv5/UdaigqZi+OMjffKds7veft9uLCTu1DuUs+Khx1S9qcnGCYX70/bz1Nqn0DSNWf1nEekfyT+3/ZMlx5Ywtf1UHm37aKX3pZRiZ/JOjmcfx2wuwVSYgbkwA1NRJkeKUvg9Px6TMtParzUDGg8g0COQOi518HXzpa5rXUK8Q3B2cLYp/vJIUhDlMxv1h7+c3QGdJupLNDdo/+cF+HysPupm/xJAwaD/g44Tqn6BLsyEReP0IYm3TddX6bT3yAyzEebeobfbFufpy0yDXs0fM//axuSL6yftmL7U+Nnt+u9w0j69rf+uT6tUw1x3Zh0vbnqRAPcAPhvwGY18GgFgURZe2fwKy08tZ3rn6TzQ+oGr7mt70nZmxc5ib+reMt8Pcg/ijqZ3MKzZMMLrhtscq60kKYiyKaXXEHbP0dfBqWhhuNwkffz/qfX6bM7hH9pWDc85p39287t6k9CIWdW/EF11UEofHllSoDdr2TthCdtYzHpfw/r/02t+g/9t8wQzpRRfHviSD/d+SKR/JB/2/5AA94BLypgsJp7f+Dxrz6ylR4Me3NPyHm4LvQ0nhz87xguNhexO2c2cQ3PYmbyTII8gJkdNZkDYAJwdnHFycMJJc8LRwVHvuL6OJCmIsu34AlY8Dz2egQH/uHp5i0VvY//tb3pzT79X9GYm73pllz27TX+mwMm1+kgKAJ9QuPvLm3PmbzVTSvHNkW/wdPakV0gvAj0C7R1S7WGxVGmpEYPJwN+2/o2Vp1cytMlQ/tH9H7g5uZVZtsRcwuyDs1lybAmphakEeQQxvNlwCowFxKbGcizrGGZlJsA9gElRkxjdYjSujjfGeliSFMSVTm2Ar0fpC8WN/da2JpLUI/oCahdmuNaPhhaD9C8nN3126oHv9THcjq76+P/m/aFZP32sutx9A7D1/FYe++0x6+sI/wh6h/ZmeNPhNPSpxLBFUa1SClKYtn4ahzMOM7XDVCa2mVipEUYmi4lNiZtYfGwxW89txc3JjbaBbYkOjKZdYDs61etUbmKxF0kKtzpDjj6KozATDNn669hv9Tv8ib9Vbf0WpfQHwx9bBcdW60PpLoym0Bz1BNB2jF6TqO7lo2sBpRTjV44nqSCJ9/u9zx/n/2BT4ib2pe3DUXPk4ciHmRQ1CQ9nG2baiirbmbyT5zc+j8Fk4M1eb9K30VXWQCpHTnEOns6elzQj3YgkKdzKivP0TtQLd/UALt76+jT3zq++yViFmfoY8pJ8aDUMvKQppCJ/nP+Dyb9N5tUur3Jvq3ut21MLU3lv93v8cuoX6nnW44WYFxjQeEDlx8SXyivJI70onYyiDDINmRQYC+jXqB91XG2Y2FcDlhxbgq+rL30a9qn0SJozuWfYlbILJwcnXBxccHF0wc/Nj3aB7Wz+uVxOKcXcQ3N5f8/7NPRuyHt936OZbw2sCHuDkaRwqzKVwLf3wOnfYfRXENZbn+1bxanxonoopXho1UOczz/PilErcHG8cs2lPSl7+Nf2f3E06yhd6nfhqeiniAyILPNCalEW4nPjiU2NZU/KHvam7uVM3pkryjXwbMDM22YSFRh1xXvXw4pTK3jx9xcBCHQP5O4Wd3N3+N3U8yyjTwo4mX2Sz/d/zqr4VVguG9MP0KV+F17u/DJNfat2Y5NXksdrW15j7Zm1DGg8gNe7v46Xy61Rq5WkcCuyWPQp+AeWwIiPof3Vh82J62Nb0jYeXf0or3R5hbGtyp+RaraYWXJsCR/s/YC8kjzcndxpE9CGdoHtCHAP4ET2CY5lHeN41nGKTEUA+Lr60j6oPW0D21Lfsz5+bn74ufmRW5LLK5tfIa0ojedjnuf+Vvdf8122LZILkhm1bBTN6jRjYtREFh9dzOZzm9E0jea+zQlwDyDAPQB/d3/83fzZl7aPNQlrcHNy496W93J3+N04ao6UWEooNhezN3Uvs2JnUWQs4sGIB5nSbgqezpV/TvXxrOM8u+FZEvMSebbjs4yPGH9dfx72JknhBqSU4kT2CRLzEuke0r36RyX8+oo+oaf/DPusUy/KpJTi4VUPk5ifyMpRK8usJVwupziHP5L+YF/qPmJTY4nLjMOkTHi7eNOybkta1G1BS7+WRAdF08SnSbkXt5ziHF7e/DKbEjcxsPFAXu/xuk0X0qqyKAuTf5vM/rT9/DDsB2snemJeIj8e/5HjWcf1pi5DBulF6RgtRrycvbiv1X2MixhHXbeylyTPNGTy/p73+fH4jwS4BzAobBA9GvQgpl4M7k7u5cazKXETL2x8AQ9nD2beNpOOwR1r5LxvZJIUbhBFpiI2n9vMlnNb2HxuMymF+mMPA9wDGB8xnnta3HPt1VeLRX8k5Ma3oPNjMOQtGe1zA9metJ1JqyfxcpeXua9VBSuBVqDIVEReSR6B7oE2391alIU5B+fw4d4PGdB4AO/c9k6VYrg4loouwAALjizgzR1v8rduf+OeFvdUWFYpRZ4xD2cH56vu94L9afv5bP9n7EjagcFswMXBhY7BHRkZPpIBjQdYO32VUiw4soB3dr1Dy7ot+bDfhwR7Bl9l77WTJAU7yy3JZWHcQhYcWUCmIRMvZy+6NehGjwY9CPQI5OvDX7MtaRvezt6MbTWWR9o8UrXkUJCuT+s/uRba3a9PELtZHgt5C7DWEvISWXH3CruOWf9k3yd8HPsxn9z+CT1DelZpH7NiZ/H5/s/pHdKbe1vdS/cG3a+YhHUq+xRjlo+hS/0ufNTvoxptoik2F7M7ZTdbz21l/dn1nMk7Q4hXCOMixjG82XDe3/M+i44uol/Dfvy7179v6ZFdkhTsJLkgmW/jvmXx0cUUGAvoFdKLcRHjiKkXc0WH4aH0Q3x18CvWJKwhyCOI17q+xm0hvWDPXH1mbaPuFY/oSfgDvn9EX153yJuXLEWRU5xDckEyYXXCbpjJM7capRTv7n6XOYfm8FLnl7i/9f12jafEXMLdy+7GaDGydMTSSt+VX/DTiZ94bctrdAjqQHxuPJmGTEK9QhnRfATuTu4UmYooNBWy8exGMg2ZLB2x9IpZwTXJoixsPLuROYfmsDd1L06aEyZlYkKbCTzT4ZnrPoP4RiNJ4TpKyk9idcJqViesZn/afhw0BwY1HsTEqIm09Gt51c/vT9vPjK0zOJF9gsF12/Bi7CoCLKUjLwJaQKNu0CAaAlpCYEtw94Ot7+sPmKnbGO6Zi6VeFIczDlubqvan78eiLDhqjjSp04QWdVvQyq8VbQLaEOEfcc3tykopTuec5vdzv5NlyCLCP4KogCjqedarkTvDQmMhWcVZZBmyyDRkkmXIIqxOGO0C21X7saqDyWLi71v/zs8nf2Zsy7FM7zwdxxtgPaWdyTt55NdHmNhmIs90fMamz03+bTIdgzvyye2fgII1Z9aw6OgidqfstpZzdXSljksdZnSfQe/Q3jVxCpUSmxrLd3Hf0a1BN+5qfpfd4riRSFKwkVKKQlMhLo4uVx1LbbaYOZJ5hG1J21h/Zj370/cD0MqvFQMbD2Rwk8E09LZtdqrRbGT2ga/4LHYWbkDHwGjqlRRTPz+D+unxNC3KoWmJEWcAFy8oyaew9TC2xdzHhuTtbEzU7840NCL9I+kR0oMmdZpwMvskR7OOcjTzqLU/Q0OjmW8zogKi6NOwDz1CelSqNnHhgSObEjex+dxmzuWfA7DekQH4ufnRrUE3Xur8UpXGx1uUhSVHl7A/fT8phSmkFqaSUpBCoanwirKOmiNzB88lOija5uPUJIPJwAsbX2BD4gaeaPcEU9pNuaFGuby25TWWn1zOomGLaFG3xVXLn8o5xYMrHiTQPZCvh36Nj8ulEx9zinNw1Bxxc3K74Sdw3cokKVxm3qF5rDi9Ak9nT+uXo+ZISmEKKQUpJBckYzAbAHBzdMPT2RMvFy/qutbFz80Pf3d/fF19OZ59nN3Ju8kz5gHQ2q81A8MGMrDxQOuKilW2fzGnfnmcj6MGcopikguSySvJs77t6uBMC5e6tFbOpLi4sa0wkWJzMd7O3vQM7cltobfRvUH3CkduHEo/xMH0gxzMOEhsaiy5Jbl4OnvSt2FfBjQegJ+bHwazgRJzCUWmIs7knrEmlYTcBBQKdyd3utbvSs+QnvQK6YW/uz/Hso5xIP0AB9MPsvL0Shp4NeCjfh8RVies0qefX5LPy5tfZv3Z9QS5B1HPqx7BHsEEeQQR4B6An5uf/v/h7oenkydPrXtKTyLDlth9gtYFBcYCnljzBHtT9/Jyl5crHH5qL9mGbIb/NJxGPo2YP2R+hc0qaYVpjF85nkJTIQuGLiDUO/Q6Riqq0w2VFDRNawjMB+oBFuBzpdT7mqb5AYuAMCAeGKOUKue5i7qqJoWlx5ey5swa8kvyKTQVkl+Sj0mZ9IuPZz3qedbD392fEnMJBcYC8o355Jfkk2XIIsOQQUZRBtnF2YR6h9K5Xme61O9Cp3qdqq/N1GyCWZ31teEf+93aWZxfkk9SQRLHso5xJOMIhzMPE5cRh4+rD30a9qFvw750CO5QpTXXjRYjO5N2sip+FWvPrCW3JLfMciFeIbTya0XLui1pF9SOmOCYCodV7k3dy7R10zArM+/2eZfO9TtfNZb4nHimrZ9GQm4CL3R6oVJj6g+kHWD8yvHc1vA23u3zboXlT+ecZsbWGbg4utDEpwlN6uhfod6h1POoh7Nj9axZP2PrDH468RNv9X6LwWGDq2WfNWHZyWW8svkVRjQbQd+GfYkKjCLI488VcI9kHOHbuG9ZeXolSim+GvTVDVcjE7a50ZJCfaC+UmqPpmnewG7gLuBhIFMp9aamadOBukqpFyvalz37FCzKUnOdVXu/gZ+fhHsXQBWfwXotjGYjsWmxGM1GXBxdcHV0xcXRhfpe9a9oLqiMs3lneXrt0yTkJjC983RGNB9R5gJhJouJjYkbeW3zazg6OPKf2/5TqSRywbxD85i5a2aFwz1zinO4/3/3k1uSS0PvhpzOOU2+Md/6voZGoEcgDTwbEB0UzZAmQ2jt19rmJp/N5zbz+JrHeaTNIzzb8VmbPnu9KaV4bctr/O/0/zCVPkuinmc92ga0JbUwldi0WNyd3Lmz6Z082PrBKs8gFjeOGyopXBGEpv0MfFT61UcplVSaODYopSrsmb0RO5qvmakEPuqodyBP3lBr5hjkleTx/Mbn2Xp+K06aEy39WtIusB3hdcNJyE1gf9p+DmccxmA20MqvFe/1fY8QrxCbjmFRFp5c+yTbk7bz7R3f0sqv1SXvGy1GG7GUIgAADp1JREFUHv/tcfak7mH2oNlEB0WjlCK9KJ3TOac5l3+OpIIkzuefJzE/kX1p+zBZTIT5hDG4yWCGhA2p1AUxrySPkT+PxMvZi0XDFt00I76KzcXEZcZxIO0A+9P2sz99P84OzoxpOYYRzUdU6YZA3Jhu2KSgaVoYsAloA5xRSvle9F6WUuqKBnFN0yYDkwEaNWrUMSHh/9u78yCryjOP498f0NAEGgFpRxahAWWJLUqijoMSwZggZEaDhpggLgmTGBgnFSVJRUiwysCMCZqJGSXGqTiTaGKCoxM1xaIyLoACQUQEg6DT7Bh2bG22pp/54z19vZJm6e5z77nL86nqqnPP3d7fXfq571ned0N2Gpstyx4KE9+MfQz6fTbp1sSqtq6WRVsW8dr211i5cyWrdq5if+1+SlqUMPDUgQzqMohB5YMYfsbwJg81vPvAbsY8NYaSliVMOn8Sl51xGS1btMTMmLZ4GrPWzmL6JdO5su+VJ3ysfQf38dyG55hTNYel7y7FMPp36s/I3iO5ovcVxyxaUxdN5cl3nuSRkY8kNs6Qc8eTk0VBUnvgRWC6mT0hae/JFIV0BddTqD0IPxsc5qEd/2zB9BKOpbaulq3vb6Vru66xbceHcAji5IWT2VS9iZ5lPbnx7BvZX7ufu5fd3eTNOTtqdvDMhmeYXTWblTvCEWbnlp/LiIoRXNrj0tSBBQs2L2Di/ImNPszTuWzKuaIgqQT4IzDPzH4SrXuLXN58dKgGti4P879uWgpblkPHnmFqyn4j4PRzmv9PfME9MP9OuOFJ6DMsjlYXrSN1R5i/cT4PrXqI1btWAzDsjGHcO/zeZu8L2ly9mbnr5zKnag5r96wFoKJDBUN7DGXe+nmUlZQx6x9mndS4Rs4lIaeKgsIeu18Rdip/K239DGBX2o7mzmb23eM9VpOLwq534N03wlzBezfAng1h8pmOPeHUM6FzXyj7G9jxVpi4ftuKsGxHwv279IfunwgTvW+JTtbp0B0qr4G/vTlMFt5YezfCfReGGcq+9JvG3981yMxY9pdlvLL1FcafMz72AeA2VW/ipc0vsWDzgrCJyYyHRz1MZZfKWJ/HuTjlWlG4BFgAvEE4JBVgMrAEmAX0BDYCY8xs9/Eeq8lFYe7tsHhmWC7tGIpB246hOOzdCKS9Lu3Kw3ST3c6DHheEv491/vD697fDumdgzewwC5kEZ4+Gv7sl3Odk/e46eHs+3PIn6OhTMeajmsM17D24l27tuyXdFOeOK6eKQpyaXBR2V4UZyeqLQbrag7BnPVRvg1PPCtv3T3az0N6NsPgBWP5rOFQNFUPhwq/DWZ+FkuPsOF33LPzmC/DpqTB0UuPzOOdcI3hRyLYD++DVX8GSB+C9LdCmAwz4XNi81GcYpO9UPXwAZl4ELVrBhJehlW+Hds5l1rGKgg9Mkimlp8DF34SLJkLVi7DqCfjz0/D6o9C2E3z8Kqj8AvQaAovuhT1VYeeyFwTnXIK8p5BNtQfDPoNVj8Nbs+FwDZR1DRPeD/gcjPnPpFvonCsS3lPIBa3awIBR4e/QB2Gn9BuPw651MGJ60q1zzjkvColp3S7sX6i8JumWOOdcSnFPPeScc+4jvCg455xL8aLgnHMuxYuCc865FC8KzjnnUrwoOOecS/Gi4JxzLsWLgnPOuZS8H+ZC0g6gsfNxdgF2ZqA5uc5zF5dizQ3Fm70xuXuZWfnRK/O+KDSFpGUNjflR6Dx3cSnW3FC82ePI7ZuPnHPOpXhRcM45l1KsReHBpBuQEM9dXIo1NxRv9mbnLsp9Cs455xpWrD0F55xzDfCi4JxzLsWLQgGSpKTb4FwmSWqTdBuSIKlTpp+j4IqCpDJJd0u6QVKvpNuTLZLaSxotqdTMrFgKQ5T7h5K+LKkiWldwn+ujRbl/JOlmSf2idQWfG0DS/cA0SZ2jywX/WZfUTtI9wE8llWXyuQrqQySpO/AHoB3QH3hU0pnJtirzJI0CNgO3A18EsCI4gkDSWGAx0Bk4H5gDYGZ1SbYr0yRdT8jdBugGPA9Fkbv+/9XHgdOAy6DwP+uSxgFrgA+Ab5pZdSafr9DmaC4HSs1sAoCknwLjJP2Xma1PtGWZ9R7wXWA3cJmkF8xsoyQV6hdGUgfCKf3fMLOF0brhkq42syeSbV3mSCoFDgHXmdnr0boLJHUxs52F/J6bWZ2k9kAtsAkYJGmlma0t5NxAB+ADM5sKIKkc2Fm/RSDu3HndU5DUT9IUSQMltSL8Wq6SNDi6yQPAGcB5hdS1Pjq3mS00sweBN4H3gTFQeL+g0nIPIOR8DHhZUkl0k4XAjsQamCHp7zdw2Mx+b2avS+ouaSnhx9Dtkk4ppPe8ge83QAmhZzQXKCMUhk5Ay6TaGbcGvt8zgTXRZvFfAjOB30sqz8T7nbf/KCVdCzwF9ASmANOAPYRfzf0klZjZGkK3a1j0KyNv89Y7Kvdk4MdpV/8ZWAoMkHRRdPuC2N56VO7vAz82s21mVmdmh6ObDQEOJtXGTGjg/Z4RrW8J9AJ+DVwMlAJ3KpJQc2NzrNyErRtXRL3DN4E7gEeA8gLMPYUPv98/B75OyPxV4ADhexD/d9zM8vIPmARMipZPA7YB50Uv2E+AC9Ku2wB0SLrNGchdDmwFhqZd3xv4AfC96HK3pNucwdyfii63APoBy9Juf2rSbc5C7pbpeYF3C/z9HkboHdwJ3Aq8DawEvp90ezOYe1va+90j7Xado9eka9xtyMtfztEv/jJgr6TWZradUFHvAGYRfi1+LTr6qDdhs0JtUu2NSwO5dwB3Ef1iADCzKuBpYLikfcB3ol+Vees4uadAagdrJ2CepCGSlgATEmtwTE4i95G0mw8E/pewWS2vHSP3j4DbCD2Fq4GRwOejdT3qe8b57Bi5/5UP3+/NaTc/h7AZLf73O+nKeBKVs1XastKW/5FwpFH6r6U1wKho+XZgHrAOuDbpHBnO/SYwJlpuDbwU5R6bdI4s5P5itDwFqANeKLL3exDwW8LRSNcknSPDud8CPg20S1tXBlQmnSOL7/dZwO+AJZl6vxN/cU7wwv0L8O/1/+ijdS2BPtHyy8B1QIvo8jeAmWm37ZV0hizlvhn4edptJyadIdu5gX8i6nbn218TP+f3R8tXAbcmnSFLuScc9Tlvla22Jpz75vr/a8BngG9lsn05e0iqpBlAH0JV/HZ0vsF/AKMJXcj/I7y4twDVhJ0zvYFX6x/DzBo7I1vimpi7D7Cs/jEsHK2QV5qRe3n0EL8ws7zbRNiMz/mK6CGetjw8P6GJuSv46Oe8WN7vPsBr0UM8Z2bPZrSNUfXJKZLaEU5E+pKZbZV0OfD3wBIze/So295IOPri3GjVV81sdVYbHBPP7bnx3J6bhHMn3ZWKilIX4N+AcUD3aN0vgcnRcikwlnBYVkUD928LXJJ0Ds/tuT2358733IkffSSpN2HHCsAngIcl9YnWnSmpt5kdAFYBNcDp0f0+I+l6Se3MbL9FZ7XmC88NeG7P7blzLnfiRYHwYtSa2a1mdhvhCIOrCS/UeuArAGa2knAewinR/XYDc83sg6y3OB6e23N7bs+dc7lzoShsB9ZLOju6/CBhMLtSYD4wRNJXJJ0OHCE6Y9XMXrVwHG++8tyB5/bcnjuHcmetKEhqK6lnA1e1JIz+119SCzN7jTCG0cVmtohw8sanCCfmPGdmL2SrzXHw3H/Fc3tuz53LubOx44JwnO1a4MvHuH4S4UzNwdHlvkAV0Da6XAK0zkZbPbfn9tyeu5hzZ7SnIKmLpP8GbgJGW9phVwrqn79+/QRJpxEG+noRMAAzO2xmhzLZ1jh5bs+ddp3n9tx5lTsjRUEfDnO7j9CFesDMVks6TdIno+6UWTRyqZltJRy6tRl4mDDk9eMW9s7nDc/tuT2358733LGevBa9aHcRukWzzWyepKGEblYpcCZhxNK/AL81sxcktbS0gb0kVVieTYjjuT235/bcFEju2HoKkgT8jHAo1lLC6JwTzGwBYaC6rcAFhBdyBWHgJ+yjIz2SLy9cPc/tuT2356aAcsc59lEZ4XjbEWZWLWkncKWk0WY2TWHSm8PAu5K2ALsUhnSuszi7K9nnuT235/bcBZM7tp6Cmb1HOCnjpmjVIuBPwOWSTo9eOCR9jDAC4HtmdiRfX7h6nttz47k9dwHljntH8/8Q5kPuambvE2ZFOgh0jfbK30EYB3yNmf0g5udOkuf23J7bcxdE7riLwkJgF1FVNbPlwIWESTGMsE1upJlNjfl5k+a58dx4bs9dAGKdT8HMtkn6A3CXpLcJ3awDRFNhmtmcOJ8vV3huz43n9twFIiPzKUgaCYwBhgD3mdl9sT9JDvLcnjvhJmWF5y7s3BmbZEdSCWCWh7MjNYfn9tzFwHMXbu6cnHnNOedcMnJh6GznnHM5wouCc865FC8KzjnnUrwoOOecS/Gi4NwJSOooaWK03E1hLP04Hvc2SW9KWilpvqRecTyuc83hRx85dwKSKoA/mlllzI87HFhiZjWSJgDDzOzaOJ/DucaK9Yxm5wrUXUBfSSuAdcBAM6uUdBPwecJ8vJXAPUBr4HrC2DijzGy3pL7A/UA5UAN8zczWmNnzac+xGBiXrUDOHYtvPnLuxL4HvGNm5wHfOeq6SmAsYSyc6UCNmQ0GXgFuiG7zIPDPZvZJ4NvAzAaeYzxQUMMluPzkPQXnmud5M6sGqiXtA56O1r8BDJLUnjAswmNhvhYA2qQ/gKRxwPnApdlpsnPH5kXBueY5mLZcl3a5jvD9agHsjXoZf0XS5cAU4FIzO9jQbZzLJt985NyJVRNm4Gq0aJKWKkljIEzvKOncaHkw8AvgSjPbHldjnWsOLwrOnYCZ7QIWSVoFzGjCQ1wHjJf0OrAauCpaPwNoT9i0tELSU7E02Llm8ENSnXPOpXhPwTnnXIoXBeeccyleFJxzzqV4UXDOOZfiRcE551yKFwXnnHMpXhScc86leFFwzjmX8v+Mov9+ECIX9gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xr_cluster['dc_mag2'].plot.line(x='time2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MMS data\n",
    "\n",
    "Finally, data can be downloaded from Magnetospheric Multiscale Mission (MMS) mission. This mission has also several spacecrafts. For this example, we will download the magnetic field during 1 minute on April 8, 2018 for the probe 1 and 2 in GSE coordinate system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_time_mms = datetime(2018, 4, 8, 0, 0, 0)\n",
    "end_time_mms = datetime(2018, 4, 8, 0, 1, 0)\n",
    "\n",
    "settings_mms = {'prod': ['dc_mag'], 'probes': ['1', '2'], 'coords': 'gse'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rdupuis/miniconda3/envs/aidapy/lib/python3.7/site-packages/HelioPy-0+unknown-py3.7.egg/heliopy/data/util.py:601: UserWarning: The CDF provided units ('hours') for key 'mms1_mec_mlt' are unknown\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating new directory /home/rdupuis/heliopy/data/mms/2/fgm/srvy\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d596f812871a4d4b97a6e353605ab8cf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rdupuis/miniconda3/envs/aidapy/lib/python3.7/site-packages/HelioPy-0+unknown-py3.7.egg/heliopy/data/util.py:601: UserWarning: The CDF provided units ('hours') for key 'mms2_mec_mlt' are unknown\n",
      "  warnings.warn(message)\n"
     ]
    }
   ],
   "source": [
    "xr_mms = load_data(mission='mms', start_time=start_time_mms, end_time=end_time_mms, **settings_mms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray 'dc_mag1' (time1: 849, mms1_fgm_b_gse_srvy_l2: 4)>\n",
      "array([[ 1.712529,  2.073415, -1.225534,  2.95529 ],\n",
      "       [ 1.714843,  2.064923, -1.207659,  2.943303],\n",
      "       [ 1.710802,  2.077349, -1.215393,  2.952863],\n",
      "       ...,\n",
      "       [ 2.291496,  1.610505, -1.082593,  3.00278 ],\n",
      "       [ 2.281956,  1.615301, -1.089721,  3.000669],\n",
      "       [ 2.277435,  1.605456, -1.105932,  2.99788 ]], dtype=float32)\n",
      "Coordinates:\n",
      "  * mms1_fgm_b_gse_srvy_l2  (mms1_fgm_b_gse_srvy_l2) <U3 'x' 'y' 'z' 'tot'\n",
      "  * time1                   (time1) datetime64[ns] 2018-04-08T00:00:06.987911 ... 2018-04-08T00:00:59.988633\n",
      "Attributes:\n",
      "    Units:    {'mms1_fgm_b_gse_srvy_l2': Unit(\"nT\")}\n",
      "    pos_gse:  <xarray.DataArray 'mms1_mec_r_gse' (time: 3, mms1_mec_r_gse: 3)...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff6bf78ff10>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6b65c3a90>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6b65c3790>,\n",
       " <matplotlib.lines.Line2D at 0x7ff6b65c3610>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYEAAAEbCAYAAAA8pDgBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdd3QU1dvA8e9ssumVNEhC6D0JAUKXLgiIKCiKCIKKgj9UbKivXbGiYgNBBUEFpAiIIEUBaVITWuiQUBJI733bff8YsmFJIYGQBPZ+zuGQnb135m6bZ24dRQiBJEmSZJ00NV0ASZIkqebIICBJkmTFZBCQJEmyYjIISJIkWTEZBCRJkqyYDAKSJElWzLamC1BZ3t7eomHDhjVdDEmSpFtKZGRkihDC5+rtt1wQaNiwIRERETVdDEmSpFuKoijnS9sum4MkSZKsmAwCkiRJVkwGAUmSJCsmg4AkSZIVk0FAkiTJiskgIEmSZMVkEJCkm0CYTJjy8q47v+7CBUyFhVVYIkkqnQwCVkqYTORHHSH5m28wZmXVdHFqLUN6+nWdjOPfeJMzffqiO3eO5BkzEXr9NfMIgwEhBCmzZhE94C7O3nsfWevXI4zG6ym6JFXILTdZTKoaab/8QtInnwJgysvH77VXy0xrzMwERUEUFpL199+4DR6MIT4eY1YWzl26qPvIz6fw9GkcQ0OrtJy6uDjy9kVg36gh+sQknMI7YOPujmJ7Y1/d/KgjZP75Jy497sC5W7dS9ydMJk537YZTeDh1xj+Bjbs7jiEhoCikL1iA+733YuPhYU6bvnAR2Rs3YsrNpeDIEQCiBw4CIGfrVvw//RT7xo0QOh0C0NjZIYQgcepUsrdswZCcgsbODlNurvraz53j4vMv4DHyIdyHDiX/0GGcu3fDkJiIxsUFY1oaLn37oijKDb0XlZEfFYV98+Zo7O3LTGNITkbodGgDAiy2CyEsyiqMRhQbm5tTzkOH0Li6ovX3J3PlSuybNSNl1my8J07AvmVLCk+fwZiWSmF0DKacbOqMG0fcpGcw5efjPeEp3AYPLrFPk06HISkZbYB/tb7nN5tSk3cWUxTFAdgG2KMGpN+FEO+Ulyc8PFzIGcOVI4Qg599/cQwLw7ZOHQDOjXyY/IMHsW/eHH18PHXffQe3AQNQtFr0SUkYEhKwa9CAzDVrSJz6AWi1aH180F+6hOLggCgoAMCuSRP1hGBjQ0FUFAFfTsdt0CCETodiZ2cugyk/n8Rp06gzejT2TZqgT0wCYUJbty4AuXv2Ev/mmzh37YowGMiPjER3vtQJjji2b4/PM5Nw7tZNfX0GA9l//41Lr15onJ3LfS8KTp4k4Z13yT940LxN6+9P4HczcWjZ0iJt+uLFJLz7nsU2n+efx7FdOy6MHQuA2+DBOHXtQsJbb1uks/H0xKV3bzJXrrTY7jlqFOmLFmHj4UHgjG/JXLOGjMVL0Li4YMrJMaer+957KDYa4t98q9zXA6BxcsK5e3fsW7XEc+RI82dcWcacHDROTigaywaC1PnzSZkxE9+XXiThvfdxHTSQwC+/VPNkZ6OPjcWucWM0Dg5krl7NpSmvAGDr64vXE49j61eXi88/D0DTrVvR+vmSvngJiR99RMBXX+Lat2+JsugTk7BxcS7389TFxnJh3GOg0dDwt0Vo3NzIXLECU14+SdOmlfleaVxcMCQllblfjasrzXftRLG1Reh0JHz0EfoLsdh4epL111+43z8c/w8/tAhqhvR0hE5PQdRhtEFBODRvXs47XTMURYkUQoSX2F7DQUABnIUQOYqiaIEdwGQhxO6y8sggUHn5R45y7oEHsGvahCZr1pAXGcn5R0bjNWECjm3bEve//wHqCd174kTSfv2VgsOHS92Xc/fuaIPqU3DkqNpunZlZIo3W3x/9pUv4f/oJju3akfD+VHJ37DA/79ihA/mRkaAoNFi4AFNODrFPTSj1eHYNGqA7fx5tQAD6ixctnnMdOJCAL6eT+sOPJH/5JVp/f4J+no9d/fplvhdxzz5H9j//gEaD32uvIvR60ub/jI2nJ0HzfiIvMhKXHj0oPHmScyMfLn0nWi2U0rzj1KkTQT/NJWvdOhyCg7Fv1AhTXh6GlBRi7r0PkZ9fZrma7diOPiGRwlOncOnVE1svL0AN4PFvvIkoKECfkEDB8ePm/Th3707uf/+V2FejFctxaN1azW8wWNRyhE5H9pYtGFNTyT94EH18Anl79+Lz0oskfzEd3ykv4/XEE+b0htRUTne/o8Qx7Bo3xpiRgTEtDQD71q3wHj+eiy++VOZrNOdt2BDduXPmxy59++Ix4gHyDx/Ge/x4kr/5hrSff8ExvAMNfv2V+LfeIm/vPuzq10d34QKu/fvjft+9XBg7DmN6eqnHsPHxxn3w3aT98gtcPsfZeHlhTE0FwOPBB8lYutQij0NoKF7jn+Dic5PxenI8BceOl/r+Amjc3ND6+eL/xRcYEpOIffJJi+eb/PM3io0NqXPm4jHiARxatSrz/bi6hnSz1MogcCVFUZxQg8DTQog9ZaWrbUEg6auvwCRwbBuKY/v22Hp6mp8z5eeTsXwFupgYvJ+eiK1PibWbbip9UhJJ0z4jf/9+9JcuAWDr44MhORmARqv+wL5xY86PHkP+oUMld6DRUOexcdR5dCzZ69eR+PEnBP0013wFDmpzTfqChRScOIFz505krl6DLiamxK5s69XDEB+PxtkZxcHB/GNU7OwQOh0AjdeupeDoURxatcSQlITuwgU8R47EVFCAYm+PyM/nTL87LX74DqGhJQJWg19/wb5VaxStLYqtLekLFmAqKCR7wwYKjh3DKTycgG++Nl8xZ2/aRNykZ0p9D+tOfR+tv7/6Grx9uPDYY2hcXfAYNhynTp04P2oUAEE/zcWpS5cSV9FXOt5SPRF4TZxA9t//oIuJwa5BA3xeeAG3gXeVme9KwmjEmJGBPiEBxzZtMKSnY+PiQu7OneTu3Uva3J9Q7Oxwu2cImctXAODzwgsoWi0ZK5ajOxNd7v4VrRbPUQ+Tf+Qovi++QNa69WrNxc0NY0YGnmPGkP7rr2raK2qEReyaNCFwxrcUnjiBQ5s25O3fjyE5mdztO8iPirIIhG6DB5O1dm2FXnepZbWzI3DGt1x69bUSwaDZju3YentjKiw0N10ZMzNJ+/kXXHr3wjE0lPyjR8FkQuPsQuafq/AcMQLbevU4e/8DFB4/bnkwrRbnzp3x+7/XSP7qa/VC4hqu/K3ZN2+Orbc3zj17UGfsWBRFIXvLFuL/73WM6em4DR6MY1hbHEJCcGrXzrwPYTKRu2sX6b/9Rr1338XW2/v636/aGgQURbEBIoGmwEwhRNmN09x4EBAmU7k/VHM6nQ40GgpPnyZ5xkxyNm3C1r8e/h99hH3TplwY/ySG5GTzyQzApU8fAr76EkWrpeD4ceLffMv8ZXK7+24CvvgcIQR5e/bi1KE9psJCFBsb0n9bjDE9jTqPP46tpydFn8mNXB0Y0tOJfWI8BceOAeqVWuExtSyKVkv9H38wt+cDGDMySP/tN3J37Ubr70/d999DURQUrVZ9P4RAFx2NfdOm1zx2xoqV5O7eRdafq9Uvd9tQ6lxuPinalyk7m0uvv07Oxk0A+L76Kl6PjbvmvnUXLlBw7BiFp8+QMnOmebtr/zvJ/ncLGAzmbRo3N0yldHo3/msN9k2aWGy79Opr5Pz3H659+5qvEH2en4z3xIkW6YROB1qt+bMpPHMG27r1sHEpvxkKIHP1atIWLKDhokXmPhaNo+M181WUEIK8Xbu48PgTZSdSFLwmPIVL9+7kRUbiEByCYqMh7dcF5GzeXGoW9/vuo+5772JISsKufn2M2dlkrVmD+7BhGBITMeXmkrV+AxkrVxA0Zy4OLcpuCtEnJGBISEBxcsK+aVPSFy8mbc5cPMeMIW/vXnL+/ReAwFnfkfzlVxSeOgVaLS0jIxBCYMzM5EzPXgB4PjqGuq+/jv7iRbI2/E36woX4fzYNbb16aOvVu+73Me/AAeKeeRah0+E1fjxeTz1Z4rcohCBrzRpSf/iRwtOn8XvjDeqMGY0hNZXUOXNJmzcPANdBA9GdOUPh6TPmvG5D78G2jhdp8+eXevzA777DtW8fAFLnziXps8/VJ2xsaLhoIY5t217X66q1QaCIoigewErgWSHEkaueewp4CiAoKKjD+TLaistjKiwk888/Sf5iOnUef5w6Y0aT8N772HjVIW3uTwDUffcdNM7OON9xB2eHDceQkAAaDZhMFvvyHD2a9AULcAwLw5CSguuAAeqHfq330tYW586dy6xiOrRpQ8DXXxP33LMUHjuO8x13EDhzBvmRkdg1aYrWz7fCr/fc6NHkR0Ti/cwzOLRsgXOPHhhTUxE6HXbVsBS3EAKRl1dum27ByZPE/9/reD8zqdR24WvRx8cT98yzIAQNFi5A4+hI8rczSJk50yLoAdjUqYNTx464DRqI28CBpZYXkwnFxoaU2d+j2Nnh9fhjlS5TbZD8zbfoExLwnfIy2Rs2kDD1A+q99y7u996LKTfX3Jl9NUNqKjlbtqLY2uDQpg3nx47DmJpKk3/+LreJrSqZCgspPHECx7ZtEUKQvW4d9q1aYd+okTlN9ubN5P63E98XX7hmH1B10MfHY1u3rjlQCJ2OvIMHydu3D6/x49HY25Py/Q/o42LJO3DAojYW+N13uPTuRe6uXcQ+MR4AW/96eD/5JEmff2EeJODSqxfaBkH4vvDCdV841PogAKAoyjtArhDi87LSXG9N4MLjT5C7c2el8zl17ozf66+TvWE92oBA4t94Q90eHk6DBb+a0+liYzn3wAh1JM0VAmd8i8bNjYR33yu1mQTAvlUrtL6+5GzdWuI55549yN22HQCPESMQRiOZK1bQcPnvOLRsiSgowJSXR8GJkzh360rO1q3Yenlx7qGRuA8bhv/HH1X6Nd8uCo4fp/DUKVzvvLNWnCxqitDrzTW6SuetpvZqa1Jw6hSFp0/j0rMnNq6u5u2mwkKy1vxlPscUafDrLzh17HjDx62VQUBRFB9AL4TIUBTFEfgb+FQIsaasPNcbBHJ37yHxo4+o99FHJH7wAcb0dFz734liZ4/G1ZX0RYvQx8aa0zuFh+P9zDM4tg01R15hMhE7/knyIiNpsGABjiHBFscQJhMoSqk/GlNeHsIk0J05jUNICBnLfsemjieu/fub0+dFRpL4yafYBQVh36wZyV99VbkXaWtrbg7RuLrS5O8NFn0UkiTVfvlRRzBmpGPfuDGKk1OV/YZraxAIBX4GbFAnri0VQrxfXp6q6BgWej3Y2pZs5zMYyNu3j4LjJ/B8ZFS5Y6GrQ1FHYqM/VlJ4+gxpC37Fe8JEkqZ/cc0OPt9XXrllmzMkSap6tTIIXI/aNjroZso/fBjF3qHUjjZhMFAYE0Pm8uU4d+uGS69eGLOzuTj5eXJ37qTp5k3mUS2SJEkyCFgJQ3o6+gsXrnsEgSRJt6eygoBcNuI2Y+vpKfsBJEmqMLmAnCRJkhWTQUCSJMmKySAgSZJkxWQQkCRJsmIyCEiSJFkxGQQkSZKsmAwCkiRJVkwGAUmSJCsmg4AkSZIVk0FAkiTJiskgIEmSZMVkEJAkSbJiMghIkiRZMRkEJEmSrJgMApIkSVZMBgFJkiQrJoOAJEmSFZNBQJIkyYrJICDVGgV6Iyk5hTVdDEmyKvIew1KNE0Lw56FLvLj0EE52Nqx4uhtNfFyIS88nu1DPodhMujXxIim7kK2nknikcwP8PRyrpWyzt0bTyNuZpr4uNPRyxkaj3PRj5uuM/L4/jraB7oQEuKMoN/+YkvWSQUCqMSaTQKNR+PPQJSYvPghAdoGB/l9uKzff8fhsZo1uj72tTaWPqTOYiLqYSfsgj2ueXBMyC/hk3Qnz4+HtAvhsRNsKBYINRxNYsPs8L/ZvTmJWIYGejgR5OeFqb4sQoLlqH0v3xTJ3x1m+fjiMJ+ZHcDEj3/zcmmfvIDjAvZKvVLoe6bk6PJy0Ft+N9FwdOqMJB1sbLmbk09rfrcz8QohbLmgrQoiaLkOlhIeHi4iIiJouhnSdjCaBzmDirVVHWHP4Eh8NC+GzDSeJzyzgj0nd2RWdyqfrT1DP3YGErAJ6NPNh26lkfF3tScoubiqq42zH+ud74OvqwKnEbBbsPo+rgy2T+jTFya7sa5v/W3GY3/bG0tTXhax8PS3qujK2a0P6tfIlObuQt1YdYWzXhnRt4sUdn/5rcTIGuDukHtMeCOWTdSdYdySeEeH1GdUpiEd/2osQgnOpeUx/sC0vLj1U4ti+rvb4uTkQk5zDC/2b83j3RlzKzOeHbTH8suu8RVoHrYYCvQmARt7OrHqmO24O2ht562+K2nDSK7qYKJJbaOBQbAYxKbkMCa2Hh5MdM/89w/LIOL55uB02GoVTidlk5uvp0MCTOs52OGlteW/1Uf48dIkR4fX5eHgIAJtPJPL4fMvzzX1h/kx/MAxFgcSsQtwcbbmUUcDzSw5w5GIWG1/sSVNf12p9DypCUZRIIUR4ie0yCEjV4WRCNmPm7rE4kV/p24fbcU9b/1KfM5kEigLxmQV8uv4Eqw5eAqBfS1/eHdqGrzed5vfIOHP6rVN642Rni4+rPdkFevL1Rryc7bmQlkffL7Zw5Vfex9We5OxCnu7dhL1n04g8nw7AqM5BLNpzgTb+bjzVszEXUvP492QS+y9kVPg1Dw6pi6PWlv0X0jmbkltu2pAAd7xc7NhyMplAT0e2vNybrAIDfx68yLurjwHwSOcgXujfnKiLmfRo6o2NRqmWE/DumFTmbD/L/e0DeHrhfoID3Aj2d2fxvlhzmmkPhDKiQyA6o4lZW6LxcrZjePtAHLQ2ZBfo2XEmhSGhpX++12v9kXgmLtgPwBcj2nJ/h0CSsgoY/0sEh+MyK7WvtvU9OBRb/Nm+eXcrPvjreIXy2tlo0BlNFtu2vNybmJQcXlsexYxR7enUqI7F80nZBfx7Iol959KJTcujaxMvJvVpitam9G7aqgi2MghIFvRGE+m5OtwctThoK9+sUhn5OiOt3l4PgLOdDQ29nZncrxkXM/J5b/UxWtZ1Zd3kHhX6khcajKTn6vl282kW7rlg3l7H2Y60XJ1F2reHtGbujrMWV/NOdjasn9yTs6m5hAa44+Jgy5O/RLDlZDIAE3o15vutMQD4uzuwZUof7GzVH6bJJFiw5zy/7Y2lZV1XdkankJilBrWXBzRnWPtAsvL1jP85AjtbDesm98BBa0Ohwcg/xxJ5ZtEBAJr6unAmKcf8911t/HixfwtsNApFv8ei90IIQa/PtnAhLQ8AW42CwaSmaebrwr1h/rjY23IoLpPUXB3fjAzDw8muwp9NESEEC3afp09LXwI9nczbL6TmMejrbeTqjCXyuNjbYhKCvMvP3Rvmz4W0PA5cESgf796ILSeTiEnJZcaoduZAcDYllx+2RROdlMuFtDxmj+lAWH0PQK0tTttwgvZBntzVpi4Amfl6dp5J4ffIOHRGEyEB7ny3Jdp8nDrOdkzq05Spa9SA2djbma5NvCy+I1+PDOOlpYcwmAT9Wvqy6USSxetp5uvCrNHtGfz1DouT+qjOQfRs5kP7Bh44am14bN4+NIrC3nNpFvnvauNHcz9Xvt18psz3OTTQnVcHtmTqmmOcSMgG1N9Ers6IosBPYzvSp6WvRZ71R+KZuuY4c8aG06pe2U1R1yKDgJU7kZBFc19Xc7X5uy1nmLb+JDYahRVPd6Pt5R/gleLS87iUUUDk+XTu7xCAvY0NF9LyCAmsePt0Wq6OoTN2EJeez52t/Pjx0Q4WJ7jj8dn4uNrj42pfqdejM5gYMXsnhy5f8X32QChDw/z5eO0J5u88V2qeZr4uTOrTlPvaBVhsLzQYWbw3Fo1GYUyXBuw4ncKKA3E83asJzfzKrtbnFBoIfmcDDbyc2Dqlj3m70SQwmoQ5eBRZfySe3/bG8v2YDhTqTfz031km9mqCo135QbhAbyQrX8/8nef448BFLmUWlJl2dJcgPrgvhMw8Pc72NtiWcWVZJE9n4K0/jqIzmlh96BLtgtQTXV03Bz65P5SxP+1l/4V0Cg3qSXFs1wZsPJ5EUB0nvh3VDlcHW45czOL+WTsBsNEovNi/OSsPXDQHuqu18HPlZGJ2ie1aG4XIt/rT49N/yczXA9CzuQ/3tw8w9xldqVsTL94a0hqjSTDk2x3m7RN6NubVgS3RaBRyCg28sTIKJzsbPh4eatF0dDguA6NJkJhVwNqoBO7vEEiv5j78dyaFl5cdIi1Xx5yx4fRo5lPq6zAYTZxIyGbItzuYPbo9A4PrAbBwz3neWHkEgIfC67N8f5w5cF/t94ldCW9Yh4/WHueHberFx/v3tqF9kCcTfo20uIBxc7Dllyc6m4NlZckgYIWEEExefJDsAj3/nkxmUp8mTLmrJQAP/7CbXTGpgHrF29DbmS8ebIufqwMHYjMYMXsnV35vPZ20NPZxIfJ8Okue6oKXiz15OgNOdrYcis0gPU/H9tMpvDe0DQ29nc35pq0/wXdbormrjR/fjynx/bthSdkFHL2YRa/mPmiuuJLOKTTw3upj2CgKU+8LLnFCriqR59Np7ueCazW11wshSMgqIDYtH4PJxHf/RnN3aD383Oz5fmsMe86mYW+rodBgYkBrP6Y9EFpqzSC30MD9s3aar0bL81y/ZozsWJ+Tidn0aeFbapq0XB3/HEsgvGEdmvi4IIQgNi2f11dG0djHGT83Bz7bcNIiz+guQXRo4El2gYG3Vx29Zjnubx/ISwOa89fheGJScnh7SBtzAH152SH+PHiJmY+0p39rv2vuqyoZTaLEYIG0XB2bjifyQIdAFEUhT2cgMauQnAIDX248RXJ2Id8+3M78WzGZBBuPJ7JgzwX+O5OC8Yofn4NWw4+PhrM8Mo6Ph4de86KhLDIIWBmD0cQjc/aw52xxlbWeuwO7/q8fBqOJrp9splOjOgR6OPL95SuQivJw0pKRpy/z+T8mdWfCrxH0benHb3sv0LelL3PHhtd4B+Ltbmd0CqN+3FNi+4v9mxPo6Uh4gzp8s/k0K/bHWQR4F3tbejb3pkODOszZHsNz/Zqx72waKw5cBKiyjs61UfHmzvGI82ncE+pvrqkU6I18uv4EG48nYqvR8PvErpxOyuHJnyNoVc+Nt4a0JjjArczvUNFJszqG8N5MWQV67vl2B+dT87irjR9P925KU18XXOxvfCCnDAJWZvWhSzz72wGGtw/A2c6WX3ero0+8nNWrwtRcHT8+Gk63Jl60eWdDifwfDgumXX1PWvu7oTeamLb+BD9uP8uzfZuy8sBF4tLzURTwcrY3T/Aqatu82qInO9OtifdNfLVSEaNJMP7nfQCE1ffky42nSqTp2NCT1BwddwXXZVSnIOrXcSqRRghBrs5Ieq6u1OerS6HBiJ2NxqouIDLz9Gw4msCw9gFldhRfDxkErIgQgn7Tt2KjKPz1XA/sbDVsOJrAhF8jzWm6NK7Db092QVEUjlzMxM/NgTydgQtpeegMJvq1KlmlTsouwNfVAVCbE5wvX52si4pnz9k0JvdrxpZTSSyPvEiQlxMHL2QwoI0fz9/ZvHpeuFTCxYx8lkXE4ulkx9mUXLILDEx7IPSWv2KWKk8GASvy35kUHpmzh4+Hh/BwpyDz9ohzaWTk6YlJyaFncx9a1r3+kQaSJN1aygoCcsbw9RICEqLAtR7Y2IKjZ+XyZpyHmK3g4gu7Z4FrXej1Kng1ueGifbPpNP7uDgxvbzkKJrxh0Vjl6u04kySp9pJBoKLyMyD1DHgEQfp5+HkIGK4YqnffbAh7WP07Jwmifoem/SD5BOz4EgyF0PEJ8G0D8waWfoyYrTD2T1Bs1OAA4FC5q/UDF9KJOJ/OhJ6Nr2tZBUmSrIv1BIGiK/d5g6H7c9DjZdBco9NFCEiNhn/ehpN/FW938rIMAAB/TAQbLTh4wML71W1X97f+9VLx3y51wasppEVDk77QqCf8/RbM7GSZ55Wz4GQ527AsRZ3BAJ0be1UojyRJ1s16gsCaFyBynvr3vx+q/wAeWQ7N7rRMe2YjHF0Jh5eC0XIWKgB5qfDQQvXkHX8Isi7Cpvdh+RNlH//Z/erx4yKh/3tQLwxsrxq/XTcEfh4K+WkgLs9Y3DdHrXkIEwz6BBzKnqg1d8dZ898dGlSieUqSJKtVo0FAUZT6wC9AXcAE/CCE+PqmHKxeKDh5Q+/X1Db4tMtTzhfeDz4tYcAHcOBXOLbqqnxt4f65kHQcWgyGlJPgXr+4maZB18vpwtQaQ+IRGDEf/NrAqQ1qMKkXqrb1D/ig/DL6tYGXT6s1lIv74cc+xcEKQNGo+7mwW92XT/Gom7MpuRyMzeCJOxoxOKRulYwrliTp9lejo4MURakH1BNC7FcUxRWIBO4TQhwrK88NjQ4SAhQFjHrQ2MLx1bB0TMl0dq7Q5Wk1Tfhjxe3z1W3e3XB+B/iFQGJUyecHTYPOEwB4fWUUyyJi2TqlT+XW2jcUgm3llmyQJOnWUytHBwkh4oH4y39nK4pyHAgAygwCN6RowonN5Sn+rYfCG4kw5071JDt8DgR1AY/6N+XwlTZmhRqw7F3Ujua/XoS7PoacBLX5ad0r5MWfYHZeH7YeTuP+ju0rFgCSTqg1mb/fhCPLocdL0O/tm/96JEmqdWrNPAFFURoC24BgIUTWVc89BTwFEBQU1OH8+fMl8ludvDQMS8Zie774BiyZDyzBPbiMkUe6PLgYAfU7wwdX1Gzs3aEwE9qOUpuYnK/RoXwxEjJi1VpSYTaEjFCHyEqSVKvVyppAEUVRXIDlwPNXBwAAIcQPwA+gNgdVc/FqJ6c6TNG8zF3GfBrZptJCxOAeORPKCgJrp8DBBeropSLdn4fQh2BWVzi0SP03dAb8/QaEjoRBnxbXngAu7IH5g8FkKN52ab9aOynIVDu67WvfzTQkSSpbjdcEFEXRAmuADUKI6ddKL2cMF2v73t9k5uuZN64jfVIXwz9vqZ3H98+FOo1Bn692bCcdhzl9izP6hcCwWepoJIC8NNj4Duz/xfIAAR2gaX84tU4dBQXgHift/FwAACAASURBVAShI9QRS+d2qE1TpXH1h3Fr1El0FRziKknSzVMrl41Q1FWhfgbShBDPVySPNQcBg9HE3B1n2XA0gXOpeaTl6nhjcCue7NkY9AXwQy91ctrVgrpC8kl4crM6v8G7RelzJGK2wD/vQLP+kHgUTq4tfs61HmTHw9g10KiHuk0ItU/h+J+QdhYSDpdSagWe2QfezariLZAk6TrV1iBwB7AdiEIdIgrwuhBibVl5rDEIxGfmcyg2k6lrjlncZGJirya8PKB58Y1DDIWw5kW12edqXSbBwI8qd2CDTh0yGxgOdRpBYY7aSV1e+uxLkJMMu2bAsT+Kn+v1Gjh7q30Ijtd3U4xaxWQETTkzsg26kvNAqlphduWa3/LSwM4F9Hlq851HkGVzn3Rbq5VB4HpYYxDo8tEmErLUGcou9rbk643seb0f3i6lDO0syISEI9CgmzpDOuk47P8Z7p2pnsirS2G22on8xyTIKr7/L4Gd4NFVYFdzyxMDYDJde8Z4WTJi4atgeOAnCL48O9yoh4wL4B4I/36kBsHwJ+COF+DQb9DtueIOdJNRbbZTFLU2teIp9XMb/oMaIIWA/HQ1zZUB89wOtUZWp7H6ma6erPbr9H4NtOWMCjMa4Nw2+HWY5faBn0KXidf3Hki3HBkEblFFK4IC/PJ4J3o2L/1Wd7VWajTkJELKaVj9nLrN1hH+7/IIo6uvRA06OLVebWJqeqfakd38LnXGdGFW5RbqK4suD2Z1g/Sz0PZhtZmr/aPFJ/TSFGTBnu/VprCFI9SyADj7qJMIcxLVcpelYQ8Yu1o91vRWat9Kw+5qs9uVzWhN+8OZf9S/64bAU9vUYLXnB1g3pez9t74XHryiT8dkhC0fq4Hjwq6y89VprA4O6P1a2Wmk24IMAreol5Ye4u9jCex7486bfkP4my79PHwdWvzYxQ/G/AF+rSH9nLq2koO72s9QlpZDIOWUumSHd3MIf7w4kBR9l6/VxLHrO9jwfyW3T4lRh8gaCiEuArIuwc5v1CashMMQtaz8/do6qBPv7N3gkWWwZLS66GCRBt3V2llhiQFwUL8L5KWonflZFy2fqxcG8VfcY9elrjrXZeJ2tZwLH1C327upgaPrJLUmtnJCcR4Hd3gmQp3Rfm6HOmBg6aPFzUP/22MxA/2G5aWp+3UPVB8XZKk1w8a9ZRNUDZFB4Ba0LiqepxfuZ2TH+nxyf+i1M9wK8tLgmzC1+aPIwE8g4if15F5ZT2xUr5SXj1ebY5x91ADhXl9t/mo7Es7vUk+alw5AQHuY019tLhu3Rg0+e39Um29a3A33fAWfl9OJ7eipzqcICFevohUFTq6DpGPqUuDCVNxXUJijrgOl2MC2aRA5X90+5EvQ5aprVPkFq7WEFlcM7U06ob4XF3apJ2yEWmPpOF49mTp7q81PRX0OBVlqU8/FUn4XTfqqK+CO/bNk/4E+Xy3HV6Hq+9HtGQjsCHbOao0s/ZwaGGL3wq6Z0PdN8GxYeg3uSrmpam3HWKjmCb5fXbsrZosa0MasVFfaFUZ1qRSpWsggUI7YtDwy8/UEB5S9OFtNmLLsEMsi44h6d0C13ci8WuRnqFfVMVvgxJqSz0/8D87/B7F71JOIvbt6hZ6fDtMaFy+udyMm7bO88t3yidp8cqWm/dUmKUOBekU/+DOwsb++vgQh1CXFL+2HEb9cf39EeQqy1H6E1c+pgWnkImjS59r5rmxq0mhh6LfqqrigBqx1r1oupNh8EDz8W8lAcHy12k+Rl1rxMvd+HXq9UnJfQhSv1Pt9L7WGM2R6uQsoXrOz3srJIFCGq2+7+OrAlozr1hBHu+IvU3aBvtpPwtHJOfT7Yiu9W/gw/7FO185QzfR6PXFxcRQUFFw7cVmESW22KMhUO0C1TurJRluBTmNDIRRkqP+DOhfBZFKbY4pOQiYjUNREpCkOHlon9Wr6avnpan+Bg5va0aqpFXMpq0dRraUsdi6gyyl+7Oxd/Dnpci93Zl+RX1FwcHQi0NmIdt/36oKNd74LO79VA7x7fbXWdmm/Oov9kWWw9wf182wzDHbOgKMr1Ca/oj4T/3ZqUPJtXXK9q63T1MUWrw7uoHaMXzmrPeGI2lnv3UytgRZkweMb1JpVVfQ51VIyCABnknJ4YclBnurZGC8XO15YcpDErMIS6Rp7OxNW34O/ouJpH+TJrphUXB1sebRrA0Z2LP3G3KUxmQQHYtNpG+hRPIyzgvnun72TAxcyePPuVozv0bjCeavL2bNncXV1xcvLq2ZvAm4oVK/+rj5hCwEmvdo0Yeesntiz4tV2d+/mctG80uSlqR3Xtg7g0UC9Es+MU5uR3PzVAF2QofaVgJrOUIg50II6esnRE2FjR2pqKtnZ2TRqdMWoNINODdJu9dQg/X4FJhK2fViduLj2ZfVx/S7w+HrITVEnOR5eqn7WRZ6PguRTUL+T2okfu1udIGnIh56vwJ7ZavApjVdTdaZ80ztLf/4WZvVBYNr6E3y3JbrU5+aN60h6no5Fey4QcT693P20rOvKX8/1IPJ8OuENPFEUMAnYcSaFVnVd8XUrvhH7W38cYcWBi3i72PP7xK409HauUFnf/fMo83eew0ajcPS9u2plh/Dx48dp2bJlzQYAqWbkpqiBQBiLt2m04NnAot9BCMGJEydo1apV2fuK3Qtz+6ujpVoPVftm3IPUGz/F7VObfwZ/pqZNiIJVz6id5N4t1GXdS6VgEZhK0/dNtWZh1KtB5OiKK7Jr1JpB/atq4EXzYNzr35LNTlYfBL7eeJptp5MZElqP86l5uDlqeahjfdwcbC2aepKyCpi4IJK29T14vHsjfFztsbPRsOdsGq+tOMz51Dzq13EkNi2fNv5uHL1UPNLDz82eyf2a0y7Ig/dXH2NXTHHb6JS7WlC/jhOu9rasjYrnztZ++Lk50LKuKwaT4K/Dl9AbBW/+ccScZ8vLvSscOKrb8ePHy/9xS7c/o0Ht/FU0Zc5TqPLvib4Avmxd3OTXcwpsuxwkXj4Dnze1TO8XrM7VOLhIHTiQeloNIBO2Wpa5aN5IYTbM7KLObWk1VK0xxkWoAwrc/NXmrJZD1GG1+WnQfuzl5ekNtX4hRasPAlUhNaeQDh9sND8O8HC0mMF7tf6t/fh+dAcGfb2dk4nZFT5OWH0PFozvXKtvDCODgFQRN+V7EhcBc/rB4M+h05PqYyGgfkd1JNiyserkyGb9LfMJoY66qtOk/BP26Y3Ft4i9lkeWqwFjzQsw7Ac1kBxdqQ4H7jxRnXG/90foNUXt+xCi7ImSQqjBrbT+qiogg0AVOXopk+l/n+LzEW3xcNKyOyaNVQcvcm9YAA//uBsArY1CuyBPfn6sE452NuyKTjU/9+GwYNYfSWD76RTzPrs29sLWRuFwXCZT7wtmaFv/GnltlVETQWDbtm08//zzHD58mMWLF/PAAw+Um37KlCmsXbuWwYMH89lnn1V5ecaNG8eQIUOuWY7bxfz584mIiGDGjBlMnz6dOXPmYGtri4+PDz/99BMNGjQokeeWvVgougFV1O9wdpvaLJUarU4q/O0hdYLg+f8shzpXRNECj8HD1eG/26erTV+7ZxVPNhzylXozK1BHeW37HO7+AvzDbugl1eqlpG8lbfzdmTuuo/lx1yZedG2irsH/8oDmBAe406lRHRy1Nub28q5NvJj3WEdMJkG/Vn7cGxbAo3P30LWJFyM7BhHg4YhGI9vWryUoKIj58+fz+eefVyj9999/T3JyMvb21t0JbDAYsLWt2p96u3btiIiIwMnJiVmzZvHKK6+wZMmSKj1GjSrq6wp5QP13pXcvn/iProRl49S/h86A9f+n1gT6Ty2eHQ/q/ciXPKL+LUzw+2PqhMGN76lNStGbLPe/5nnYPFU98f/7sdr38UMvuOdr6DCuql8pN2GwsvV6pm8zerfwxcnOtkSHaZ8WvvRr5Qeo6/+s+F93ptzVkvp1nG6bAHDu3DlatmzJ+PHjCQ4O5pFHHmHjxo10796dZs2asXfvXt59913Gjh3LgAEDaNiwIStWrOCVV14hJCSEgQMHoterozxee+01WrduTWhoKC+/rI4KadiwIaGhoWgqMMZ+6NCh5Obm0rlzZ5YsWUJ0dDRdunShY8eOvP3227i4qAvhbdmyhV69evHggw/SvHlzXnvtNRYuXEinTp0ICQkhOrr0wQRFNm7cSI8ePWjevDlr1pQy5+GyvLw8HnzwQUJDQ3nooYfo3LkzERERGI1Gxo0bR3BwMCEhIXz55ZcAREdHM3DgQDp06ECPHj04caKU1WEvW7ZsGcHBwbRt25aePXsC6lX7iBEjuOeeexgwYAAPPfQQa9cWr8s4btw4li9fTo8ePTh4sHg2cvfu3Tl8uLTVYC316dMHJye1WaNLly7ExcVdI8dtqM0weOkUvHgc2o+BF6LgpZPQYSy8laLWGkYtg1ZD1HWmHl0FT+9U866eXDyk1t4dJu5QawDdnlW35aWqAebKzu/VkyEukionhLil/nXo0EFINe/YsWMltp09e1bY2NiIw4cPC6PRKNq3by8ee+wxYTKZxB9//CHuvfde8c4774ju3bsLnU4nDh48KBwdHcXatWuFEELcd999YuXKlSI1NVU0b95cmEwmIYQQ6enpFscZO3asWLZs2TXL6OzsbP777rvvFosWLRJCCDFr1izzc//++69wd3cXly5dEgUFBcLf31+8/fbbQgghvvrqKzF58uQy9z927Fhx1113CaPRKE6dOiUCAgJEfn5+qWk/++wz8dRTTwkhhIiKihI2NjZi3759IiIiQtx5553mdEWvtW/fvuLUqVNCCCF2794t+vTpU2Y5goODRVxcnEX+efPmiYCAAJGamiqEEGLFihXi0UcfFUIIUVhYKAIDA0VeXp6YP3+++TWePHlSlPf7mjdvnpg0aVKJ7ZMmTRJTp04tNU9p3xOrd/GAEJ81E+L38ULE7hPCaCx+Li9diIj5QhxbLcQ7buq/xONCxEYIsfp5IQpzr/uwQIQo5ZwqawJSlWrUqBEhISFoNBratGlDv379UBSFkJAQzp07B8CgQYPQarWEhIRgNBoZOFBdMqEojZubGw4ODowfP54VK1aYrzhvxK5duxgxYgQAo0aNsniuY8eO1KtXD3t7e5o0acKAAQMsylOeBx98EI1GQ7NmzWjcuHGZV+w7duxg5MiRAAQHBxMaqi4D0rhxY2JiYnj22WdZv349bm5u5OTksHPnTkaMGEFYWBgTJkwgPj6+zDJ0796dcePG8eOPP2I0Fg/b7N+/P3XqqOPwBw0axObNmyksLGTdunX07NkTR0dHRowYwZo1a9Dr9fz000+MGzeu3Nd7tQULFhAREcGUKeUsbidZ8g+Dl0/B/T+qy7RfWbN19FBrEq2GqKOdHlsPvi0hsIM6Ue4mrL4r+wSkKnVl+7tGozE/1mg0GAwGizQajQatVmtuOitKY2try969e9m0aROLFy9mxowZbN68uUbLXJarm/3KmjchyhiA4enpyaFDh9iwYQMzZ85k6dKlfPXVV3h4eFg005Rn9uzZ7Nmzh7/++ouwsDBzPmfn4uHFDg4O9O7dmw0bNrBkyRIefvhhAJycnOjfvz+rVq1i6dKlVGbQxcaNG/nwww/ZunWr1fe73BQuPuq/m0zWBKRaJycnh8zMTAYPHsxXX31V4ZNhebp06cLy5erqpIsXL77h/RVZtmwZJpOJ6OhoYmJiaNGiRanp7rjjDpYuXQrAsWPHiIqKAiAlJQWTycT999/P1KlT2b9/P25ubjRq1Ihly9RVS4UQHDp0qMwyREdH07lzZ95//328vb2JjY0tNd3IkSOZN28e27dv56677jJvHz9+PM899xwdO3Y01xyu5cCBA0yYMIE///wTX1/fCuWRaicZBKRaJzs7myFDhhAaGkqvXr3MnaX79u0jMDCQZcuWMWHCBNq0qfgKlF999RXTp0+nU6dOxMfH4+5eNYsFtmjRgl69ejFo0CBmz56Ng4NDqen+97//kZycTGhoKJ9++imhoaG4u7tz8eJFevfuTVhYGOPGjePjj9VF7BYuXMjcuXNp27Ytbdq0YdWqVWWWYcqUKYSEhBAcHEzPnj1p27ZtqekGDBjAtm3buPPOO7GzK77rWYcOHXBzc+Oxxx6r8OueMmUKOTk55iaroUOHVjivVLvIeQLSdbnVxn/n5eXh6OiIoigsXryY3377rdwTa1UzGo3o9XocHByIjo6mX79+nDp1yuJkXFMuXbpE7969OXHiRIVGXlXGrfY9uZ3JeQKSVYuMjOSZZ55BCIGHhwc//fRTtR4/Ly+PPn36oNfrEUIwa9asWhEAfvnlF9544w2mT59e5QFAujXImoB0XWrLFV5UVBRjxoyx2GZvb8+ePXuq7BgffvihuX2+yIgRI3jjjTdKpN2wYQOvvvqqxbZGjRqxcuXKai3HjZg3bx5ff/21xbbu3bszc+bMSu+rtnxPJLlshFTF5I9bqgj5Pak9ygoCsv4nSZJkxWQQkCRJsmIyCEiSJFmxGwoCiqJUfGCxJEmSVOvcaE3gvSophSRJklQjrhkEFEU5XMa/KMCvGsooSbeFffv2ERoaSkFBAbm5ubRp04YjR45cO6Mk3UQVmSzmB9wFXH0HdgXYWeUlkqSb7L3VRzl2xb2hq0Jrfzfeuaf8ZSw6duzI0KFDefPNN8nPz2f06NEEBwdXaTkkqbIqEgTWAC5CiBKreCmKsqXKSyRJt7G3336bjh074uDgwDfffFPTxZGkawcBIcQT5Tw3qqznJKm2utYV+82UlpZGTk4Oer2egoICi+WeJakmVLhjWFGUOqX8097MwknS7eapp55i6tSpPPLIIyWWl5CkmlCZBeT2A/VR+wYUwAOIVxQlCXhSCHETbn4pSbePX375BVtbW0aNGoXRaKRbt25s3ryZvn371nTRJCtWmSCwHlgphNgAoCjKAGAgsBT4Duhc9cWTpNvHo48+yqOPPgqAjY1NlS5yJ0nXqzLzBMKLAgCAEOJvoKcQYjcg7y0nSZJ0C6pMTSBNUZRXgaJ78z0EpCuKYgOYqrxkkiRJ0k1XmZrAKCAQ+ANYBQRd3mYDPHi9BVAU5SdFUZIURZGzZiRJkqpZhWsCQogU4Nkynj5zA2WYD8wAfrmBfUiSJEnXocJBQFEUH+AVoA1gvpu2EOKGhjYIIbYpitLwRvYhSZIkXZ/KNActBE4AjVAXjjsH7LsJZZIkSZKqSWWCgJcQYi6gF0JsFUI8DnS5SeWyoCjKU4qiRCiKEpGcnFwdh5QkSbIKlQkC+sv/xyuKcreiKO1QO4pvOiHED0KIcCFEuI+PT3UcUpIkySpUJgh8oCiKO/AS8DIwB3jhppRKkm5Db731Fl9//bX58RtvvCEXkZNqXGVGB625/Gcm0KeqCqAoym9Ab8BbUZQ44J3LzU6SdHOsew0Soqp2n3VDYNAn5SZ54oknGD58OJMnT8ZkMrF48WL27t1bteWQpEqqzOigRqhDRBtemU8IMfRGCiCEePhG8kvSraJhw4Z4eXlx4MABEhMTadeuHV5eXjVdLMnKVWbG8B/AXGA1coawdCu7xhX7zTR+/Hjmz59PQkICjz/+eI2VQ5KKVCYIFAghZAOmJN2AYcOG8fbbb6PX61m0aFFNF0eSKhUEvlYU5R3gb6CwaKMQYn+Vl0qSblN2dnb06dMHDw8PbGxsaro4klSpIBACjAH6UtwcJC4/liSpAkwmE7t372bZsmU1XRRJAioXBIYBjYUQuptVGEm6nR07dowhQ4YwbNgwmjVrVtPFkSSgckHgEOrdxJJuUlkk6bbWunVrYmJiaroYkmShMkHADzihKMo+LPsEbmiIqCRJklRzKhME3rlppZAkSZJqRGVmDG8t73lFUXYJIbreeJEkSZKk6lKZtYOuxeHaSSRJkqTapCqDgKjCfUmSJEnVoCqDgCRJknSLqcogoFThviTptjN79mzCwsIICwujUaNG9OlTZYvxStJ1q+wqovFCiILLjx0BPyHEuctJxlR98SSp6n2691NOpJ2o0n22rNOSVzu9Wm6aiRMnMnHiRPR6PX379uXFF1+s0jJI0vWoTE1gGZarhxovbwNACHGkqgolSbezyZMn07dvX+65556aLookVWqegO2VS0YIIXSKotjdhDJJ0k11rSv2m2n+/PmcP3+eGTNm1FgZJOlKlQkCyYqiDBVC/AmgKMq9QMrNKZYk3X4iIyP5/PPP2b59OxqNHJMh1Q6VCQITgYWKohRdwsQh+wEkqcJmzJhBWlqauUM4PDycOXPm1HCpJGt3zSCgKMqVvVdLASfUkUC5wL3A9JtTNEm6vcybN6+miyBJJVSkJuB6+f8WQEdgFWoQGANsu0nlkiRJkqrBNYOAEOI9AEVR/gbaCyGyLz9+lytGB0mSJEm3nsr0TgUBV95QRgc0rNLSSJIkSdWqMh3DvwJ7FUVZibpO0DDg55tSKkmSJKlaVGYp6Q8VRVkH9Li86TEhxIGbUyxJkiSpOlSmJoAQYj+w/yaVRZIkSapmcsaKJFWTjIwMvvvuu3LTnDt3jkWLFlVTiSRJBgFJqjYyCEi1kQwCklRNXnvtNaKjowkLC2PKlClMmTKF4OBgQkJCWLJkiTnN9u3bCQsL48svv6zhEkvWoFJ9ApJ0O0j46CMKj1ftUtL2rVpS9/XXy03zySefcOTIEQ4ePMjy5cuZPXs2hw4dIiUlhY4dO9KzZ08++eQTPv/8c9asWVOl5ZOkssiagCTVgB07dvDwww9jY2ODn58fvXr1Yt++fTVdLMkKyZqAZHWudcVeHYSQt+SWagdZE5CkauLq6kp2djYAPXv2ZMmSJRiNRpKTk9m2bRudOnWySCNJ1UEGAUmqJl5eXnTv3p3g4GB27dpFaGgobdu2pW/fvkybNo26desSGhqKra0tbdu2lR3DUrWQzUGSVI2uHv752WefWTzWarVs2rSpOoskWTlZE5AkSbJiMghIkiRZsRoPAoqiDFQU5aSiKGcURXmtpssjSZJkTWo0CCiKYgPMBAYBrYGHFUVpXZNlkipODnOUyiO/H7eGmq4JdALOCCFihBA6YDHqfYulWs7BwYHU1FT5Q5dKJYQgNTUVBweHmi6KdA01PTooAIi94nEc0PnqRIqiPAU8BRAUFFQ9JZPKFRgYSFxcHMnJyTVdFKmWcnBwIDAwsKaLIV1DTQcBpZRtJS4thRA/AD8AhIeHy0vPWkCr1dKoUaOaLoYkSTeoppuD4oD6VzwOBC7VUFkkSZKsTk0HgX1AM0VRGimKYgeMBP6s4TJJkiRZjRptDhJCGBRFeQbYANgAPwkhjtZkmSRJkqxJTfcJIIRYC6yt6XJIkiRZo5puDpIkSZJqkAwCkiRJVkwGAUmSJCsmg4AkSZIVk0FAkiTJiskgIEmSZMVkEJAkSbJiMghIkiRZMRkEJEmSrJgMApIkSVZMBgFJkiQrJoOAJEmSFZNBQJIkyYrJICBJkmTFZBCQJEmyYjIISJIkWTEZBCRJkqyYDAKSJElWTAaB21RKfgpJeUk1XQxJkmo5GQRuQ+cyz9FvWT/6LevHqjOraro4kiTVYjII3GaEEEzZNgWTMAHwRcQX6I16hBCsjVlLekE6AEdTjjInag5Td01la+xWjqYeBcAkTMRkxJjzV5ekvCSyddlEZ0QTnRFdrceWJGtmW9MFkKrWgaQDnEg7wfvd3sfTwZNnNz/LR3s/olPdTry6/VUAGro15FzWOXOepaeWAuCsdaZP/T6siVnDSx1eYlzwuCorl0mYSMxN5GT6SXoG9kSjFF9/5BvyuW/VfWTrss3bBjQYwOPBj9PaqzWKolRZOSRJsiSDwG1m3tF5aDVa7mxwJy5aF+5pfA+/n/qd30/9bk5TFAC6+3fHx8mHP878gb+zP+mF6ayJWQPAF5FfcCj5EC+Gv0h91/o3XK5vD3zLnKg5ALzT9R3aeLXhf5v+x/Bmw/Fz8rMIAAB/n/+bv8//zR0Bd9DGqw2jW43Gw8HjhsshSZIlRQhR02WolPDwcBEREVHTxaiV4nPiGbB8AONDxjO5/WQAtsRu4dnNzwIQ4BJAA7cGfNbrM4QQuNu7W+Q/nX6a4X8Op61PWw4lHwKgc93OzLlrzg2VK9+QT+8lvdGb9OhNekJ9QqnnXI8N5zaY07T3bc/zHZ7H3d6dRm6N+ObANyw+sZgcfY45zaSwSdwRcAf1XeuXKHtV+u3EbzjZOnFv03sttgshmPzvZMJ8w3iszWOyhiLdUhRFiRRChJfYLoPA7WPqrqmsPLOSVfetMl+9G01G/oz+kx6BPfB29L7mPrJ12bhoXYhKieLxDY8DsH3kdhxtHdGb9NgqtpU6+RUaC3l5y8tsidvCnAFz2J+0n+8OfgfA4EaDSc5PJl+fz4x+M/By9CqR/5lNz7A1bqvFNk97TzaN2ITWRlsifWJuIsn5yTT3bI6djV2Fy1nkr5i/eG37awBEjY0C4GDSQZp7NicqJYrxf48HwFXryvf9v6dFnRbY2dghhKjw+2IwGVh/bj05uhy6B3SvkpqWJF1LWUFANgfdJnRGHevOrWNgw4EWJxUbjQ3Dmg2r8H5c7VwBCPUJ5Zu+3zDhnwk8vfFpPuj+gfkE+EbnN+jq35WIxAgauDagnks9i30UGguJTIjEzd6N2YdmszVuK96O3oT7hdOpbify9HmcTDvJlI5TrhmYpvWcRmx2LLYaWy5kXeDziM+5kH2Bv87+xcCGA3GwdTC//g3nNvD6jtfNed/q8hZhvmGsjl6Nu70740PGW7xfRUEiITeBNTFr6O7fnV+P/WpO8+neT8kozGBNzBo0igaTMOHn5Ee/oH6sPLOSUWtHARDsFUyhqZDOdTvzaqdXy3093x74lh8O/2Cx7em2TzO82XBOp5+mg18HnLRO5e5DkqqSrAncJjZf2MzkEWqXWwAAGVpJREFUfycz685Z3BFwR5Xs02gy8nnE5yw4vqDcdDP7zaSRWyPqu9Wn0FjIi1teZFvcNvPzod6hfNnnS3ydfG+4THqTnvEbxrM/aT8aRcNfw/4i0DWQHw//yDcHvik378vhLzO61WgmbZ7Efxf/A6CdbzsOJB2wSPe/tv/jjzN/cCn3ksV2rUbL4iGLae7ZnIs5F5l3ZB5LTi6xSPP7Pb/Tok4L8+MCQwFajRYbjQ1CCDov6ky+Ib/MMjprnVk2ZBn13WTtQKpasjnoNvfqtlfZdWkXmx7chFZTspnkegkheOqfp9gdvxtnrTOf9fyM6ZHTOZNxpkTaYK9gjqQeMT/u5t+N4c2G079Bf4vRQDcqszCT0WtHmzu4fx30K2PWjcFV68qPA37Ew8GD/Yn7+XDPh+Tqc3GwcaDAWID7/7d35uFVldf+/6wQiJAQhhAGwyAGsMwQEJVR0KsUWxCBlkvVn6hovfWKekuLc1sLt5ZWxCpqC2KpenEsomiRWlEpgzigARkMCRBFMCGEMCRkOOv3x7uJSQiQkJOck7PX53ny5OzxrO/Zw3e/09oxzRjRfgTLdiw7YZ9dmncp1bRy4kqWpy/nkU8e4eL2F3NV16toF9eOxMaJJ1RZpeem89jGx+iR0IOnNz1N/9b9efySxwHYlrONKcunUBgoLLfNXYPuYlK3Sewv2E9xoJgbVtxAfEw8PRJ68OqXr9K1RVfmXTyPdnHtiI6ywroRHMwEIpjjVQyjzxnNnBFzauU7Nu/fTFzDODrFdwLg7Z1vk1OQQ1Z+1gnVGwDrpjjTqC2KSopIeTal3LzbU27nht43lE6nH0xnadpSftbvZ6TlpjH5jcmA6xXVJ7EPS7YuIToqmk7xnVh4+UK27N/ClpwtTOw2kYAG2LJ/Cz1b9axyTAtTF/LIJ48ArhH+68Nfn7BOSusUnrj0iZNW+SzZuoRZ62eVTs8cNJOfdP9JlWMwjJNhJhChrPtmHdPengbAvRfcy4+/9+M6/X5VpShQRF5hHsWBYjIOZrAtZ1tQxxicigWpC5j3yTyGnD2EeaPmEdMg5qTrfvjNh+QX5zM0aWhpySSgAaIkKig9fQqKCzj/ufMBaCAN6NWqF7OHzkYQigJFPPzxw9x34X20iW1zyv08vvFxnvzsydLpscljuanPTTRt1JSYBjGl5pqdn00DaUCLs1qccn/fHP6Gw0WH6dqiK8dKjnGs5BiZhzLpmVB1gzPqP2YCEUh+cT5XvHoFWflZ/ODcH/DARQ+UNpT6hYAGSM1OpU+rPmHRZXPz/s0UFBcwoM2AGu3neO6nmR/MJONgRrllSXFJZB3NKq1mmjloJlO+N6Wc/vSD6TRr1IzDRYe5fsX1fHv0W1qe1ZKcgpzSdV764UvszNvJRe0uqtUut0Z4YCYQgTz04UM8u+VZFl62kEHtBoU6HKMWOHjsIM9veZ4vc78kvlE8+cX5rP56NXmFeSes++jIRxnZcSSZeZmM+fuYcssEQan8Wh+WNIz5l86vlfiN8MG6iEYYmXmZvLT9JcYmjzUDiGCaxTTjln63nDD/aNFR9hzeQ2KTRBZtWsTCTQv5zbrfkNA4oXScwwXtLqBZo2b0btWba3tey/tfvc+WnC20i21HYUkhf0n9C4cLD/PB1x+QdTSLxCaJALyz6x3e2vkWP+r2I86KPoutOVv5POtzxpw7hsFnD65T/UbtYyWBekjZJ703r3rTBhsZbN6/meveuo6CkgIARnUYxbxR8067XXpuOuOXjSegAbq16EbusdxTpiC/ssuVZOdn84cRfyC2YWzpILkt+7ew7+g+BrYZSFyjOFSVgAZoENXgpPvKK8zjle2vcHX3qysd+GcEFysJRAhb9m/h3n/fC8DsobPNAAwAeib0ZN6oeczZMIcxnceU6yV1Ks5tfi6/uuhX3L/mfrYf2A5A85jmzBo6i9TsVARhW842/pX5LwCWpi0FYMKyCaW9n7q16Fa6bfeW3Zk7ci4P/PsBco7lsPCyhWQczGD3od2M6TyG/OJ8mjZqSpREsWTrEv706Z8oLCnk5r43B/snMapIyEoCIjIJ+BXQHRikqlV6vPdzSeCFrS/w2/W/BWDeyHmM6jgqxBEZkUJ6bjqLv1hM+sF0/jr6ryc0sheWFDLt7Wl88u0nlW4/+bzJdG3RlQfXPXjS7yjbLpEUl0SHph1Y9806AJ669CkGJ31X1aSq/HP3P1m7Zy0BDXBbym0cLjxMh6YdwqIDQH0k7BqGRaQ7EACeAn5uJnBqXt7+Mr9e+2sAnrz0SYYkDQlxRIYfUVUKA4VEEUWURLEgdQHjuoyjbWxbwHVWWLJtCben3E6b2DbMeG8GAMnNkmkb25b2TduzLWcbG7M2AtApvhOqiqK8Mf4N0nPT2XNkD7vzdvPQhocqjSGldQrdE7pz54A7ySnIITs/m03Zm3gr4y1mD5tNUlzSKTXkF+fzxMYn2HFwB+OSx3HZOZcF8RcKX8LOBEoDEFmFmcAp+cfOf/CL935Br1a9eGjYQ5ZSwAhrCooLSrsqH7+/VHx6f2bTM/zx4z9yY+8b6di0I/evuZ/WTVqXa4+IkiiWXLGE9IPpvJnxZrlUJACtGrciOz+73Lyrul7Frwf/+oSYikqK2F+wn2e/eJYXt79YLnVHs5hmHCk8woRuE4iOiiaxcSKrv16NiFBYUsiQpCFs2LuB+y68j87NOtfsxwkhZgL1lKNFRxnxwgi6J3Tnqf94isbRjUMdkmHUmJJACau+WsX5bc+nJFDCuKXjOHDsACmtU0qrnCrmYTpO1tEs7l59d2lVEsDIDiPJzs8mNTuVGQNncMW5V7D9wHZW7FzBzX1u5pcf/LJcjqhHRj5CUUkRv1n7Gw4VHTrhO05G4+jGjD5nNOe1PI/hScNZnrGc7i27M6LDiHLrnSyrbHpuOgmNE8qNy0g7kMbStKUMThpcq72vQmICIvJPoG0li+5R1de8dVZxGhMQkZuAmwA6duw4YNeuXbUQbXgyZ8McFn+xmMcveZzh7YeHOhzDqBVyC3LJL86nbWxbcgpyyCnIoWuLrqfcZnn6cgAGtBlA29i27D2yl3tW38OHez+sdP0OTTuQeSiT1658jXObnQs4M9qVt4t3dr/DrrxdDGw7kK4tuhIbHcu/Mv9F2yZtSctNI65RHDtyd1Sadwpc7qkFly0g81AmijLjvRlcds5l3NrvVmatn8WaPWvIPZZLcaCYhlENmZ4ynTV71hAlUaz+enXpfpLikhiWNIwbe99Idn52tdKWnA4rCdRDNu/fzJTlUwhogDX/uaY0zbNhGJVTWFLIwk0Lmb9xPomNE7m4w8VER0XTtFFTbu13a40blVfuWsm9q+9lUrdJxETHUBQoYtGmRQBESzTFWnxG+x3ZYSTvZr57wvzExon0bNWTAa0H1DgVi5lAPeTBtQ/y4vYXWTlxZWnDm2EYp6ckUHLKMQrBpKC4gJtX3lxajTU2eSzTU6Zzx7t38Hn250zqNompPaey69AuLmx3IdsPbOfOVXcyPWU6mYcy6ZfYj0HtBpFTkMORoiPcsOIGcgpySG6ezBf7vyj9npNVj1WVsDMBERkP/AlIBHKBjap6+em285MJTFg2gYSzEvjzZSdm6TQMI3woChSRmpVK/9b9S0sbR4uOUhQoqlFepoyDGby+43UWf7GYbi268dyY5864NHMyEwhekvdqoqp/V9X2qhqjqm2qYgB+4nDhYdJy0+jXul+oQzEM4zQ0jGpISpuUcjfoJg2b1DgxX+dmnbkt5TbuvuBuUrNT+Whf8B+AbcRwmJKanUpAA/RN7BvqUAzDCDFjk8fSuVln+rfuH/R9h6wkYJyaz7I+QxB6J/YOdSiGYYSY6KjoWjEA8KEJFBQXlCa3Cmc2Zm0kuXky8Y3iQx2KYRgRjG+qg3bn7eamlTeVe+Vfxfw7G7/dyOz1s4mPieeRix8pfYNTbeQqqTiYJOtoFhkHM7jrg7tIaJzAjtwdjO86PujfaxiGURbfmMD8z+af8M7X6e9OZ/DZgxnUdhA783aWZkgEeOKzJ3gj/Q1iG8ZybY9r6Z3Ym/TcdD7e9zEb9m5gVMdR3DngzmobxL4j+9h2YBvPbH6GDXs38NO+P2XI2UO45q1rStf5Nt8NnZ/aa2oNFBuGYZyekI8TqC5n2kX0nd3v8Om+T7n8nMvp1rIbhwoP8fBHD/N6+uul63Ru1plb+t7Cmxlvsipz1Wn32SuhF49d8hgJjRPKzQ9ogPkb59OqcSvGdx1PTIMYMg9lsjB1Ia98+cop9zn6nNEUlhQyvP1wJnSbUG2dhmEYlRF24wTOlGCOE1BV0nLTCGiAvUf2Mrz9cESE9Nx0pq6YSvu49lzf63oy8jJ4Le01Lmh3Aee1PI8eCT2Y/MZkAHok9OC5Mc8RHeUKVUeKjvDql6/y+w2/L/2eEe1HsGbPGooCRXRv2Z0uzbtwScdLaBfXjs+zPqeguIDk5skMaz8sKLoMwzAqYiYQZJ7e9DRzP54LuKf3mYNmsvabtcz9aG5pdc5t/W/j0U8fBSC+UTyLv7+Y5ObJIYvZMAz/YiZQCwQ0wIRlE0jLTSs3v2dCT6b1nsYlnS7hQMEBvj36LQmNE2jVuFWIIjUMw+/Y6yVrgSiJ4sUfvsj6b9bzf1v/j/e/ep/J503mngvvKV2nxVktaHFWixBGaRiGcXLMBGpIw6iGDE0aytCkoaEOxTAMo9r4brCYYRiG8R1mAoZhGD7GTMAwDMPHmAkYhmH4GDMBwzAMH2MmYBiG4WPMBAzDMHyMmYBhGIaPqXdpI0QkC9gVwhBaAdkh/P66wg86/aAR/KHTDxqhZjo7qWpixZn1zgRCjYh8VFn+jUjDDzr9oBH8odMPGqF2dFp1kGEYho8xEzAMw/AxZgLV58+hDqCO8INOP2gEf+j0g0aoBZ3WJmAYhuFjrCRgGIbhY8wEDMMwfIyZgGEYho8xE6iAiMSKSBcRidi3rvlBI4CINBGRViIioY6ltvCJRr+cryHRaSZQBhG5DtgJ/BFYICLNQhpQLeAHjQAiciNO5+PeX8ThE43X4Y/z9TpCpNNMwMP70UcDQ1R1HCDAf4tIcmgjCx4i0pwI1wggIknAVcAg4FrgeyJys4i0DG1kwcMnGlvgj/M1pNelr02gbLFLVQ8C3XG5OQDmAc2AS0IQWtDwLiQAVDUX6EGEaQQQkVZlJg8ALYHGqnoMmIW7WdbrtAIi0lFE4r3Jg0ALIlPjYABVPUAEXpMAItJaRBpA6K9LX5qAiDQUkUdxbtvUmxcDvAScD6CqnwBbgc4ick6IQj1jPI2zgRUiMltEfugtepUI0QilOmcBK0XkYRGZqKpHgXVAVwBVfQfYA1wgIk1CGO4ZIyLtgQzgJhFpBDQB1hAhGsscx+V4N0NPZ8RckwAiEiUic4D1wBMicoO36GWcide5Tt+ZgIjEAQ8BVwL9gT4A3tPUTqCDiFzorf4BcBGQX/eRnjki0hF4BfekOBV38/i5V/L5AuhY3zVCqc4XgNa4qpHPgWne4mwgpUyR+hVgIlBc13EGiQTga6AfcK6qfgvkEAEaRSQR+Dvuybe/qi4DUNVC3DUZEeerx38AvYBuwPPADBHphbtGzxaRi7z16kyn70wAKASewRW/9gAjRORsb9kHwCFgnIg0UtXtuIPQJRSB1oAjwPOqeouqbgb+AWTibpbrgDzqv0Zw1T53q+o0Vc0AmuOejgEWA0nAKABV3Yi7iXYNRaBBIB/4X+//8afHl4C21H+NBcA7wApVLRaRviIy0qv6eg13Ptfr87VM760SYD9QoqqrcA8xU4EtwGFgbF3r9JUJiIh4TxfbVfUwrgjWHegnIg1UdRfuaaotsEREXgKaAttDFnQ1EZEoVd2PK1YfJxpnegdUdTfu5tGOeqoRSo/lIVXdKiIxIvI/wM+BTiKyHHduPwmMFJFFIvICEENo30VRLSp0++yHuyHcAfQVkYm44/Y6MKwea4xS1UPAe0CiiGzHHbcpwPu4a/ExoAP16Hw9RZfdxrhSagdveg6uNiIe+CvQnrrWqaoR+wdcCDQ/zTr3eAeia5l5jXDF6v8OtYYgaRwIvFxhXr3RWBWdwIAynx8A3vM+twRuBf4n1BpqohFXhXC99/k9IABMjxSNONOeAtxV4Ti+631uBEyoR+drw+O6KsyPBZZ6Ws7y5k0H3g6VzpD/WLV0AC7GVfW8gasKGejN742rM27Od8nzOuGePMYBPwWGhTr+YGkss+5/Ar/3Pk8se8MM978q6GxZyTZ9gEVAk1DHHwSNN3k3hp8AO4CPcSXYd4HvHz+Pw/3vNBpvxjV0N6mwTX9gAa4HVMg1VFHnZFzV61xvOsr73w2YATQErsFVVw72lrUB/gbEhSLmiKsOEpEoXAPTdFX9AbAKuEZEhuGKYR+oaq56v766KqAjuKLYz6gHDU5V1Vhmk+FAvIg8j7vgwl4jVFlnToVtegBzcVV+R+s45GpTBY2r1VVhvoLrUTJDVScCC4FLcdU/YU0VNL6vqkfLHi8R6YkbOPWlqtaX87UT8CPgD7gquj6qGvAWFwCvqmqRqv4N10HjDhH5Ja5ksEddFXXdE2rnDJL7xgMJZabfAu4o47K3An8C4ivZdgjwFTAt1DpqQyPQAFe3uhn4f6HWUYs6m+F6fW0EpoZaRzA1UqFKoT781eA4xgL3A5+F+3Esq5PvahZ6eP/vBZaeYrsYXJfQucCNodRQ70sCIjId+BKYLyLzvNl/AfqLSKyq7gM+BI7hnoiPb9dTRBoCn+BewPyXOg69ytRAYy9VLcE9UfVV1b/WcejVooY6D+K6GQ5U1UV1HHqVORONqhrwztdGZfYTtrmCanJNquoR4E1clWXYHkcorxN3jaGqX3iL5+Mauq/y1m1QZruLgEaq+qGq3qGqC+o28vLUaxMQkc64etFeuGqOviJyDa6IuRdXFw5u4EU8nl4RGY/rgyuqmu/dKMOSGmocLCLRqvqaqoZ13/Eg6GyoquvCWWcQztdS1HucDDdqqHGIdxw/CufjCJXqTBGRqeJSQKCumnI+8AtvusQbKDYQ11MvUPme6576npUvD9fI20RVd4nIw7gcHNnABuBHIrJWVTeLSAHQ0dtuWTjf+CvgB43gD52mMTI0wok6/4DrXJIBrPK6MD8nIqNFZD7upv83VV0PfBS6sE+kXpYEvIYmgDjc4KAeAOpGGh4BvocbfPI5LiPfIuByYK23XtifbH7QCP7QaRojQyOcUucbuMGLg0QkRlVV3Aj9Vriur5meAYQd9cIERGSCiPST7xIuBbz/u3CJtFK8lnlwIwyvUdUcVX0QN7hmPXC+qn4cgvCrhB80gj90msbI0AhnpHOyuhQ04BqHM4D2qvpQHYdeZcL2RfNew1dHXJ/oPNxQ6224BpjDwF24ZGjRuP79G1T1aW/bFbjBFvVhVGFEawR/6DSNkaERgqLzNlXdJi79Q2EIJFSLsDQBrzGz2GtFv1pVfyYi5wH/hWsTu11Euqhqmrf+D3ADMA7g0iFEAZNUtSBUGk6HHzSCP3SaxsjQCP7RWZawMgGvDu13uBGSL+Ba3oep6tXesrNxuVJuVNUNxw+Yt20b4Mc4TfMq/4bQ4weN4A+dpjEyNIJ/dFZG2JiAVwR7HNdtbAUuvcG/gZm4N+5s8da7A9fn/TpvehhutN2OUMRdHfygEfyh0zRGhkbwj86TEU5dRJviMiVerqqHROT4W4W2AvcBU7zGmY+AruJeBxmLy6yYHqKYq4sfNII/dJrGyNAI/tFZKWHTO0hV83AvkLjOm/UesA/XhWy0iFytrhvZ8URTB1V1j6ouUtWvQxFzdfGDRvCHTtMYGRrBPzpPRtiYgMffcbn926nLMb4NdzB+C0wQkRdxo/DWQ3gPnT8FftAI/tBpGiNDI/hH5wmETZsAgIi0w/UhPqCq/+vNW4Nrmd+CG1zyqapmhi7KmuEHjeAPnaYxMjSCf3RWRji1CaCq34jIUuB3IpKGG2ZeAMSoG4CxLKQBBgE/aAR/6DSNkaER/KOzMsKqJHAcEfk+MAkYDDymqo+FOKSg4weN4A+dpjFy8IvOsoSlCQCIS/OsGubZBGuCHzSCP3SaxsjBLzqPE7YmYBiGYdQ+4dY7yDAMw6hDzAQMwzB8jJmAYRiGjzETMAzD8DFmAoZRARFpLiL/5X0+W0ReDtJ+h4vIJyJSLCITg7FPw6gpZgKGcSLNcSNF8XLEBOuGvRuXn+b5IO3PMGpMWI0YNoww4XdAsohsBL4EuqtqLxG5DrgSaIDLN/9HXP75a4BjwBhVzRGRZFxq4kTgKDBNVbeq6k4AEQnUsR7DOClWEjCME5kJ7FDVfsCMCst64V4cPgiYBRxV1f64jJPXeuv8GfcqxQHAz3GJxwwjLLGSgGFUj3e9LJOHROQg7m1TAKlAHxGJw6UceKlMosmYug/TMKqGmYBhVI9jZT4HykwHcNdTFJDrlSIMI+yx6iDDOJFDuLdNVRvvBSUZIjIJXN55EekbzOAMI5iYCRhGBVR1P/BvEdkEzDmDXfwEuEFEPgM2A+MAROR8EfkKl6XyKRHZHKyYDeNMsQRyhmEYPsZKAoZhGD7GTMAwDMPHmAkYhmH4GDMBwzAMH2MmYBiG4WPMBAzDMHyMmYBhGIaPMRMwDMPwMf8fBYWuNh3kdKEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(xr_mms['dc_mag1'])\n",
    "xr_mms['dc_mag1'].plot.line(x='time1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rdupuis/miniconda3/envs/aidapy/lib/python3.7/site-packages/HelioPy-0+unknown-py3.7.egg/heliopy/data/util.py:601: UserWarning: The CDF provided units ('hours') for key 'mms1_mec_mlt' are unknown\n",
      "  warnings.warn(message)\n"
     ]
    }
   ],
   "source": [
    "settings_mms_dist = {'prod': ['i_dist'], 'probes': ['1'], 'coords': 'gse'}\n",
    "xr_mms_dist = load_data(mission='mms', start_time=start_time_mms, end_time=end_time_mms, **settings_mms_dist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray 'i_dist1' (time1: 14, mms1_dis_energy_fast: 32, mms1_dis_theta_fast: 16, mms1_dis_phi_fast: 32)>\n",
      "array([[[[0.000000e+00, ..., 0.000000e+00],\n",
      "         ...,\n",
      "         [0.000000e+00, ..., 0.000000e+00]],\n",
      "\n",
      "        ...,\n",
      "\n",
      "        [[0.000000e+00, ..., 0.000000e+00],\n",
      "         ...,\n",
      "         [1.977800e-20, ..., 0.000000e+00]]],\n",
      "\n",
      "\n",
      "       ...,\n",
      "\n",
      "\n",
      "       [[[8.998902e-21, ..., 0.000000e+00],\n",
      "         ...,\n",
      "         [0.000000e+00, ..., 0.000000e+00]],\n",
      "\n",
      "        ...,\n",
      "\n",
      "        [[9.016211e-21, ..., 0.000000e+00],\n",
      "         ...,\n",
      "         [0.000000e+00, ..., 0.000000e+00]]]], dtype=float32)\n",
      "Coordinates:\n",
      "  * mms1_dis_energy_fast  (mms1_dis_energy_fast) float32 2.16 3.91 ... 17800.0\n",
      "  * mms1_dis_theta_fast   (mms1_dis_theta_fast) float32 5.625 16.875 ... 174.375\n",
      "  * mms1_dis_phi_fast     (mms1_dis_phi_fast) float32 2.75 14.0 ... 340.25 351.5\n",
      "  * time1                 (time1) datetime64[ns] 2018-04-08T00:00:00.120976 ... 2018-04-08T00:00:58.621428\n",
      "Attributes:\n",
      "    mms1_dis_dist_fast:  s^3/cm^6\n",
      "    Units:               {'mms1_dis_dist_fast': Unit(\"s3 / cm6\"), 'mms1_dis_e...\n",
      "    pos_gse:             <xarray.DataArray 'mms1_mec_r_gse' (time: 3, mms1_me...\n"
     ]
    }
   ],
   "source": [
    "print(xr_mms_dist['i_dist1'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
