3_PIV_to_Xarray_Local.ipynb

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   "source": [
    "# Analyzing Lava Flow Velocity with Python \n",
    "##  OpenPIV CSV files to Xarray, Convert to Real World Units , and correct for Drone Motion\n",
    "#### Jasper Baur"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: fsspec==0.8.4 in /Users/Coding_Stuff/anaconda3/lib/python3.8/site-packages (0.8.4)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import numpy as np\n",
    "import fsspec\n",
    "\n",
    "import urllib\n",
    "import urllib.request\n",
    "from urllib.request import urlopen\n",
    "\n",
    "import IPython ## \n",
    "from IPython import display\n",
    "display.set_matplotlib_formats('retina')\n",
    "from IPython.display import YouTubeVideo\n",
    "import glob\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import ticker, cm\n",
    "%matplotlib inline  \n",
    "\n",
    "!pip install fsspec==0.8.4\n",
    "#!pip install 'git+git://github.com/tjcrone/gdrivefs.git@540a55fae06cbed4f7d9f8d540ac29fcb640c38a'\n",
    "\n",
    "#!pip install 'git+git://github.com/tjcrone/gdrivefs.git@540a55fae06cbed4f7d9f8d540ac29fcb640c38a'\n",
    "#import gdrivefs\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading Multiple files into one xarray and cleaning the data\n",
    "Site 6: Flights 7, 8, 9, 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Flight 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Local Drive Method!\n",
    "files = glob.glob(\"/Users/Jasper/Volc_Research/Workflow_OPENPIV/2_Site_4_PIV/F07/*.csv\") #This is the directory witht the CSV files\n",
    "\n",
    "F07 = []\n",
    "i=0\n",
    "for i in range(len(files)):\n",
    "    dfi = pd.read_csv(files[i], sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F07.append(dfi)\n",
    "    i=i+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jupyter": {
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   "source": [
    "#Using gdrive implementation of fsspec to access data\n",
    "\n",
    "#Google drive link for F07 0-20\n",
    "#https://drive.google.com/drive/u/3/folders/1dRzyQe1T4phq_TKitCZs4m4UdfW2a5Ed\n",
    "gdfid1 = '1dRzyQe1T4phq_TKitCZs4m4UdfW2a5Ed'\n",
    "gdfs1 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid1, token ='browser')\n",
    "files1 = gdfs1.ls('')\n",
    "\n",
    "#Google drive link for F07 21-120\n",
    "#https://drive.google.com/drive/u/3/folders/1pgNI8H-yI5kWkIrmeTF0rvw4g8Fo3zOq\n",
    "gdfid2 = '1pgNI8H-yI5kWkIrmeTF0rvw4g8Fo3zOq'\n",
    "gdfs2 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid2, token ='cache')\n",
    "files2 = gdfs2.ls('')\n",
    "\n",
    "files07 = files1 + files2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "source_hidden": true
    }
   },
   "source": [
    "#Takes multiple CSV files and reads them all into one xarray as a List\n",
    "files1 = glob.glob(\"/Users/Jasper/Volc_Research/Workflow_OPENPIV/2_Site_5_PIV/F07/*.csv\") #This is the directory witht the CSV files\n",
    "\n",
    "F07 = []\n",
    "i=0\n",
    "for i in range(len(files1)):\n",
    "    dfi = pd.read_csv(gdfs1.open(files1[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files1[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F07.append(dfi)\n",
    "    \n",
    "    \n",
    "    \n",
    "\n",
    "    \n",
    "#i=0\n",
    "#for i in range(len(files2)):\n",
    "    dfi = pd.read_csv(gdfs2.open(files2[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file2 = files2[i]\n",
    "    sec = file1[len(file2)-6: len(file2)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F07.append(dfi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "    u        (time, x, y) float64 0.3826 0.4679 0.5215 ... -0.0463 -0.0829\n",
       "    v        (time, x, y) float64 -2.979 -3.021 -3.082 ... -0.9042 -0.8046\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6871a81d-f81c-4585-84ce-47d600275ffe' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6871a81d-f81c-4585-84ce-47d600275ffe' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 120</li><li><span class='xr-has-index'>x</span>: 119</li><li><span class='xr-has-index'>y</span>: 66</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-73822547-7ad2-42da-a7eb-f41a3edc9c71' class='xr-section-summary-in' type='checkbox'  checked><label for='section-73822547-7ad2-42da-a7eb-f41a3edc9c71' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 3.776e+03 3.808e+03</div><input id='attrs-27970a8a-1a35-45ac-b16f-dfca3e85527f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27970a8a-1a35-45ac-b16f-dfca3e85527f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00ef3cad-4173-493d-89c5-e5f1436e0de6' class='xr-var-data-in' type='checkbox'><label for='data-00ef3cad-4173-493d-89c5-e5f1436e0de6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112., 2144., 2176., 2208., 2240.,\n",
       "       2272., 2304., 2336., 2368., 2400., 2432., 2464., 2496., 2528., 2560.,\n",
       "       2592., 2624., 2656., 2688., 2720., 2752., 2784., 2816., 2848., 2880.,\n",
       "       2912., 2944., 2976., 3008., 3040., 3072., 3104., 3136., 3168., 3200.,\n",
       "       3232., 3264., 3296., 3328., 3360., 3392., 3424., 3456., 3488., 3520.,\n",
       "       3552., 3584., 3616., 3648., 3680., 3712., 3744., 3776., 3808.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 2.08e+03 2.112e+03</div><input id='attrs-549b5e1b-e770-424c-82a6-bb44159c6853' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-549b5e1b-e770-424c-82a6-bb44159c6853' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71d28fac-7a55-4578-a500-6556cfd5a06b' class='xr-var-data-in' type='checkbox'><label for='data-71d28fac-7a55-4578-a500-6556cfd5a06b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 115 116 117 118 119</div><input id='attrs-79ab8de8-122e-4df2-b4d0-ad587ef92e52' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79ab8de8-122e-4df2-b4d0-ad587ef92e52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-720101de-a484-41f8-bef9-833a29b53250' class='xr-var-data-in' type='checkbox'><label for='data-720101de-a484-41f8-bef9-833a29b53250' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c920c961-2580-4a0e-b239-d73884765dbd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c920c961-2580-4a0e-b239-d73884765dbd' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3826 0.4679 ... -0.0463 -0.0829</div><input id='attrs-b09a3f5d-dc55-4095-b865-942fd989d52c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b09a3f5d-dc55-4095-b865-942fd989d52c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17514be3-8dff-4942-a21b-492bfb118168' class='xr-var-data-in' type='checkbox'><label for='data-17514be3-8dff-4942-a21b-492bfb118168' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 3.8260e-01,  4.6790e-01,  5.2150e-01, ..., -2.6500e-01,\n",
       "         -2.4420e-01, -2.2030e-01],\n",
       "        [ 3.1740e-01,  4.0660e-01,  4.4750e-01, ..., -2.1510e-01,\n",
       "         -1.6360e-01, -2.4340e-01],\n",
       "        [ 2.3630e-01,  3.3380e-01,  4.0560e-01, ..., -2.5640e-01,\n",
       "         -1.6760e-01, -3.7600e-01],\n",
       "        ...,\n",
       "        [ 2.3250e-01,  3.2140e-01,  3.0940e-01, ..., -1.1330e-01,\n",
       "         -3.0000e-04, -4.5900e-02],\n",
       "        [ 1.3690e-01,  1.2410e-01,  9.6800e-02, ..., -9.5100e-02,\n",
       "         -2.1130e-01, -7.2200e-02],\n",
       "        [-3.7800e-02,  9.8400e-02,  6.9900e-02, ..., -2.5000e-03,\n",
       "         -1.8450e-01, -2.7200e-01]],\n",
       "\n",
       "       [[ 1.2033e+00,  1.1482e+00,  1.1948e+00, ...,  3.1737e+00,\n",
       "          3.2792e+00,  3.3442e+00],\n",
       "        [ 1.1242e+00,  1.3172e+00,  1.3266e+00, ...,  3.1923e+00,\n",
       "          3.2726e+00,  3.3113e+00],\n",
       "        [ 1.0144e+00,  1.1981e+00,  1.3030e+00, ...,  3.2110e+00,\n",
       "          3.2435e+00,  3.2587e+00],\n",
       "...\n",
       "        [ 7.7160e-01,  7.8680e-01,  6.8410e-01, ...,  4.5170e-01,\n",
       "          2.2100e-01,  7.5900e-01],\n",
       "        [ 9.6490e-01,  7.3030e-01,  9.1780e-01, ...,  9.7100e-01,\n",
       "          8.5490e-01,  6.9510e-01],\n",
       "        [ 3.4900e-01,  6.5620e-01,  9.1040e-01, ...,  1.0190e+00,\n",
       "          1.0657e+00,  7.5470e-01]],\n",
       "\n",
       "       [[ 2.5520e-01,  3.2400e-01,  4.2300e-01, ..., -6.1910e-01,\n",
       "         -4.9870e-01, -6.5620e-01],\n",
       "        [ 2.1140e-01,  2.5800e-01,  3.8060e-01, ..., -5.6540e-01,\n",
       "         -5.0910e-01, -6.4700e-01],\n",
       "        [ 1.5370e-01,  2.2840e-01,  3.3340e-01, ..., -5.0940e-01,\n",
       "         -5.3070e-01, -6.0310e-01],\n",
       "        ...,\n",
       "        [-4.9730e-01, -5.9490e-01, -5.8900e-01, ..., -3.1200e-01,\n",
       "         -1.8600e-01, -7.8000e-02],\n",
       "        [-6.7610e-01, -5.1680e-01, -5.4360e-01, ..., -6.9600e-02,\n",
       "         -1.2350e-01, -2.0140e-01],\n",
       "        [-5.4770e-01, -3.7200e-01, -3.1090e-01, ..., -8.8600e-02,\n",
       "         -4.6300e-02, -8.2900e-02]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.979 -3.021 ... -0.9042 -0.8046</div><input id='attrs-ff5f5612-5605-4f73-a188-f8c3a074d265' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff5f5612-5605-4f73-a188-f8c3a074d265' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dce41840-7f95-43f2-9d18-dcacbe69f8de' class='xr-var-data-in' type='checkbox'><label for='data-dce41840-7f95-43f2-9d18-dcacbe69f8de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-2.9791e+00, -3.0213e+00, -3.0816e+00, ...,  3.1800e-01,\n",
       "          3.1090e-01,  3.4770e-01],\n",
       "        [-2.9436e+00, -3.0073e+00, -3.0652e+00, ...,  3.4970e-01,\n",
       "          3.4320e-01,  2.9510e-01],\n",
       "        [-2.9957e+00, -3.0668e+00, -3.1353e+00, ...,  3.5310e-01,\n",
       "          3.4610e-01,  3.0300e-01],\n",
       "        ...,\n",
       "        [ 2.0400e-01,  2.0320e-01,  2.7820e-01, ...,  8.8500e-02,\n",
       "          4.7300e-02, -4.2100e-02],\n",
       "        [-3.7400e-02,  1.1870e-01,  1.9910e-01, ...,  5.3600e-02,\n",
       "          6.7100e-02,  8.1700e-02],\n",
       "        [ 1.5270e-01,  1.7960e-01,  2.2360e-01, ...,  8.3300e-02,\n",
       "          1.0470e-01,  1.6820e-01]],\n",
       "\n",
       "       [[-1.6350e+00, -1.7855e+00, -1.6962e+00, ...,  1.0674e+00,\n",
       "          1.2355e+00,  1.2208e+00],\n",
       "        [-1.6120e+00, -1.6342e+00, -1.5753e+00, ...,  1.1189e+00,\n",
       "          1.2795e+00,  1.2786e+00],\n",
       "        [-1.6709e+00, -1.5999e+00, -1.5060e+00, ...,  1.2129e+00,\n",
       "          1.3241e+00,  1.3065e+00],\n",
       "...\n",
       "        [-4.0290e-01, -4.7540e-01, -4.4520e-01, ..., -2.5220e-01,\n",
       "         -2.9740e-01, -8.5220e-01],\n",
       "        [-5.7580e-01, -5.9570e-01, -5.7330e-01, ..., -7.3380e-01,\n",
       "         -7.1840e-01, -8.4840e-01],\n",
       "        [-1.7310e-01, -4.8640e-01, -5.3330e-01, ..., -7.8280e-01,\n",
       "         -8.2860e-01, -6.6420e-01]],\n",
       "\n",
       "       [[-4.0359e+00, -4.1334e+00, -4.2713e+00, ..., -1.0755e+00,\n",
       "         -8.4030e-01, -1.0667e+00],\n",
       "        [-4.0892e+00, -3.6715e+00, -4.3229e+00, ..., -1.1516e+00,\n",
       "         -1.0974e+00, -1.0448e+00],\n",
       "        [-4.1790e+00, -4.2772e+00, -4.4041e+00, ..., -1.1141e+00,\n",
       "         -9.9090e-01, -1.0212e+00],\n",
       "        ...,\n",
       "        [-9.8210e-01, -9.0380e-01, -8.4630e-01, ..., -9.3540e-01,\n",
       "         -9.9790e-01, -9.7530e-01],\n",
       "        [-1.0431e+00, -9.1230e-01, -8.2650e-01, ..., -9.1890e-01,\n",
       "         -9.2440e-01, -9.5180e-01],\n",
       "        [-1.0991e+00, -9.9060e-01, -8.1580e-01, ..., -9.6710e-01,\n",
       "         -9.0420e-01, -8.0460e-01]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-a5fb77da-0836-4d7f-9fce-de3564bea299' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a5fb77da-0836-4d7f-9fce-de3564bea299' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce4fef02-febe-4231-be67-566b427e3192' class='xr-var-data-in' type='checkbox'><label for='data-ce4fef02-febe-4231-be67-566b427e3192' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-896c7b73-c901-4fed-ba3a-798ef80d02c2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-896c7b73-c901-4fed-ba3a-798ef80d02c2' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 0.3826 0.4679 0.5215 ... -0.0463 -0.0829\n",
       "    v        (time, x, y) float64 -2.979 -3.021 -3.082 ... -0.9042 -0.8046\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert it to dataArray and merge coordiantes along time dimension\n",
    "df07 = xr.concat(F07, dim = 'time')\n",
    "df07 =df07.sortby('time', ascending=True)\n",
    "df07['time'] =np.arange(0,120)\n",
    "df07"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Flight 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"/Users/Jasper/Volc_Research/Workflow_OPENPIV/2_Site_4_PIV/F08/*.csv\") #This is the directory witht the CSV files\n",
    "\n",
    "F08 = []\n",
    "i=0\n",
    "for i in range(len(files)):\n",
    "    dfi = pd.read_csv(files[i], sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F08.append(dfi)\n",
    "    i=i+1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
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   "outputs": [],
   "source": [
    "#Using gdrive implementation of fsspec to access data\n",
    "\n",
    "#Google drive link for F08 0-20\n",
    "#https://drive.google.com/drive/u/3/folders/1TF0KZIQaSnXhf38jxtKGdZSZ9NF-9WIE\n",
    "gdfid1 = '1TF0KZIQaSnXhf38jxtKGdZSZ9NF-9WIE'\n",
    "gdfs1 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid1, token ='cache')\n",
    "files1 = gdfs1.ls('')\n",
    "\n",
    "#Google drive link for F08 21-120\n",
    "#https://drive.google.com/drive/u/3/folders/1q9EgvnGwpZvJFGbBe6yuM1afLoh1n633\n",
    "gdfid2 = '1q9EgvnGwpZvJFGbBe6yuM1afLoh1n633'\n",
    "gdfs2 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid2, token ='cache')\n",
    "files2 = gdfs2.ls('')\n",
    "\n",
    "files08 = files1 + files2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "#Takes multiple CSV files and reads them all into one xarray as a List\n",
    "\n",
    "# files1 + files2 : these are the directory with the CSV files\n",
    "\n",
    "F08 = []\n",
    "i=0\n",
    "for i in range(len(files1)):\n",
    "    dfi = pd.read_csv(gdfs1.open(files1[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files1[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F08.append(dfi)\n",
    "    \n",
    "i=0\n",
    "for i in range(len(files2)):\n",
    "    dfi = pd.read_csv(gdfs2.open(files2[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file2 = files2[i]\n",
    "    sec = file1[len(file2)-6: len(file2)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F08.append(dfi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "\n",
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 -2.119 -2.052 -2.008 ... 0.3661 0.3512 0.1482\n",
       "    v        (time, x, y) float64 -3.996 -3.914 -3.957 ... 0.3498 0.3509 0.2115\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a35a8799-61c3-4351-a361-f743eff13602' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a35a8799-61c3-4351-a361-f743eff13602' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 120</li><li><span class='xr-has-index'>x</span>: 119</li><li><span class='xr-has-index'>y</span>: 66</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b479a0ad-31a5-4590-9a84-bb72c4000210' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b479a0ad-31a5-4590-9a84-bb72c4000210' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 3.776e+03 3.808e+03</div><input id='attrs-52e34d80-5680-4a2b-94c5-faab4f60272e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52e34d80-5680-4a2b-94c5-faab4f60272e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f078db55-0b6d-4572-a2aa-d7a1f6410e86' class='xr-var-data-in' type='checkbox'><label for='data-f078db55-0b6d-4572-a2aa-d7a1f6410e86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112., 2144., 2176., 2208., 2240.,\n",
       "       2272., 2304., 2336., 2368., 2400., 2432., 2464., 2496., 2528., 2560.,\n",
       "       2592., 2624., 2656., 2688., 2720., 2752., 2784., 2816., 2848., 2880.,\n",
       "       2912., 2944., 2976., 3008., 3040., 3072., 3104., 3136., 3168., 3200.,\n",
       "       3232., 3264., 3296., 3328., 3360., 3392., 3424., 3456., 3488., 3520.,\n",
       "       3552., 3584., 3616., 3648., 3680., 3712., 3744., 3776., 3808.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 2.08e+03 2.112e+03</div><input id='attrs-cb6f8dfb-c61d-4070-8dd9-8bb06c827237' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb6f8dfb-c61d-4070-8dd9-8bb06c827237' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-110bc0f9-c3ed-4e87-85da-82d09b86c448' class='xr-var-data-in' type='checkbox'><label for='data-110bc0f9-c3ed-4e87-85da-82d09b86c448' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 115 116 117 118 119</div><input id='attrs-c9a64169-61ff-4a7d-9de6-c2dc451ab16a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9a64169-61ff-4a7d-9de6-c2dc451ab16a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2745cd5-632c-4168-b391-52c0710ef938' class='xr-var-data-in' type='checkbox'><label for='data-e2745cd5-632c-4168-b391-52c0710ef938' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0519a241-b9da-41b6-a770-1567a7bba8dd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0519a241-b9da-41b6-a770-1567a7bba8dd' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.119 -2.052 ... 0.3512 0.1482</div><input id='attrs-1bf56926-575e-49f5-b411-a93780a25ed6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1bf56926-575e-49f5-b411-a93780a25ed6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f54ebef2-d069-44ed-895c-8738d65f9c19' class='xr-var-data-in' type='checkbox'><label for='data-f54ebef2-d069-44ed-895c-8738d65f9c19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-2.1186, -2.0518, -2.0076, ..., -2.1585, -1.9466, -2.1696],\n",
       "        [-1.867 , -2.1019, -1.8804, ..., -2.413 , -2.231 , -2.1892],\n",
       "        [-2.4384, -2.4538, -2.1399, ..., -2.4384, -2.2857, -2.1298],\n",
       "        ...,\n",
       "        [-2.3266, -2.4501, -2.8021, ..., -2.0977, -2.0304, -2.0926],\n",
       "        [-2.4173, -2.1613, -2.4684, ..., -2.7331, -1.9742, -2.1317],\n",
       "        [-2.4348, -1.8311, -2.4392, ..., -2.1206, -2.1259, -2.0696]],\n",
       "\n",
       "       [[ 2.5885,  2.746 ,  2.7881, ...,  1.2616,  1.292 ,  1.3255],\n",
       "        [ 2.5896,  2.9224,  2.8692, ...,  1.3192,  1.3731,  1.2702],\n",
       "        [ 2.4977,  2.6321,  2.6437, ...,  1.2779,  1.2372,  1.2242],\n",
       "        ...,\n",
       "        [ 1.1459,  1.6108,  2.3582, ...,  2.4578,  2.3935,  2.5921],\n",
       "        [ 1.8305,  1.9377,  2.3913, ...,  2.4279,  2.435 ,  2.5415],\n",
       "        [ 1.446 ,  1.9242,  2.2958, ...,  2.636 ,  2.5605,  2.5034]],\n",
       "\n",
       "       [[-1.1576, -1.1055, -1.0641, ..., -1.3888, -1.2079, -1.2024],\n",
       "        [-0.8079, -1.0077, -1.1312, ..., -1.4696, -1.5073, -1.2921],\n",
       "        [-1.4492, -1.4248, -1.2849, ..., -1.4899, -1.4602, -1.3327],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [-3.9728, -4.0782, -3.9089, ..., -2.7352, -1.9774, -2.3574],\n",
       "        [-3.9381, -3.8759, -4.0072, ..., -2.9147, -1.95  , -2.3098],\n",
       "        [-3.933 , -3.8459, -3.8198, ..., -2.5194, -2.4733, -2.5324]],\n",
       "\n",
       "       [[ 1.3923,  1.5211,  1.6614, ...,  0.2361,  0.3251,  0.1336],\n",
       "        [ 1.5954,  1.4386,  1.5923, ...,  0.2046,  0.251 ,  0.1806],\n",
       "        [ 0.9769,  0.9909,  1.5061, ...,  0.2247,  0.1603,  0.1249],\n",
       "        ...,\n",
       "        [-0.9599, -0.6532, -0.627 , ...,  0.784 ,  0.6022,  0.6003],\n",
       "        [-0.9999, -0.5757, -0.2805, ...,  0.506 ,  0.7361,  0.8342],\n",
       "        [-0.6496, -0.4297, -0.5407, ...,  0.699 ,  0.6507,  0.1284]],\n",
       "\n",
       "       [[ 0.9272,  0.9829,  1.1632, ...,  0.623 ,  0.4243,  0.3269],\n",
       "        [ 1.1716,  1.036 ,  1.0001, ...,  0.5874,  0.5091,  0.2767],\n",
       "        [ 0.5804,  0.5959,  0.9344, ...,  0.6096,  0.4376,  0.4041],\n",
       "        ...,\n",
       "        [-0.1289, -0.1465, -0.1983, ...,  0.3375,  0.3197,  0.4238],\n",
       "        [ 0.2339,  0.3125,  0.1514, ...,  0.1681,  0.5357,  0.55  ],\n",
       "        [-0.2686, -0.2145, -0.0546, ...,  0.3661,  0.3512,  0.1482]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.996 -3.914 ... 0.3509 0.2115</div><input id='attrs-7b3a0713-62ca-4cba-a863-d466000e95c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7b3a0713-62ca-4cba-a863-d466000e95c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c699efb5-f0b1-4134-879b-852239d152dc' class='xr-var-data-in' type='checkbox'><label for='data-c699efb5-f0b1-4134-879b-852239d152dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-3.9959, -3.9139, -3.9568, ..., -0.8056, -0.8437, -0.9462],\n",
       "        [-3.7379, -3.9282, -3.8023, ..., -0.791 , -0.8065, -0.8921],\n",
       "        [-4.1215, -4.2002, -4.6196, ..., -0.8382, -0.8679, -0.8858],\n",
       "        ...,\n",
       "        [ 0.0233,  0.322 ,  0.4901, ...,  0.3301,  0.5074,  0.5204],\n",
       "        [ 0.4349,  0.4888,  0.3868, ...,  0.7597,  0.6453,  0.6796],\n",
       "        [ 0.2862,  0.9619,  0.3922, ...,  0.427 ,  0.4973,  0.7629]],\n",
       "\n",
       "       [[-4.2026, -5.2055, -5.1342, ..., -2.122 , -2.0043, -2.0492],\n",
       "        [-5.3397, -4.934 , -5.0926, ..., -2.1021, -2.076 , -2.0806],\n",
       "        [-5.4466, -5.7284, -6.0269, ..., -2.1041, -2.0679, -2.0782],\n",
       "        ...,\n",
       "        [-1.8163, -1.5061, -1.5565, ..., -2.2528, -2.1023, -2.3027],\n",
       "        [-1.6987, -1.5516, -1.611 , ..., -2.3919, -2.0888, -2.2719],\n",
       "        [-1.9393, -1.5498, -1.6128, ..., -2.4232, -2.3398, -2.2706]],\n",
       "\n",
       "       [[-4.801 , -4.6845, -4.6526, ..., -1.8827, -1.8604, -1.791 ],\n",
       "        [-4.5873, -4.7964, -4.751 , ..., -1.7256, -1.7643, -1.7374],\n",
       "        [-4.9258, -4.9963, -5.2568, ..., -1.6473, -1.714 , -1.5817],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [ 0.1286,  0.6472,  0.9603, ...,  1.9063,  1.078 ,  1.6131],\n",
       "        [ 0.6473,  0.9067,  0.6645, ...,  1.8519,  1.3208,  1.5939],\n",
       "        [ 0.6762,  0.7135,  0.7525, ...,  1.7833,  1.7584,  2.1271]],\n",
       "\n",
       "       [[-6.3959, -6.3411, -6.448 , ..., -2.0583, -2.0678, -2.1652],\n",
       "        [-6.3303, -5.902 , -6.7705, ..., -1.9966, -2.0775, -2.2945],\n",
       "        [-6.2228, -6.3873, -6.9731, ..., -2.0087, -2.0594, -2.1536],\n",
       "        ...,\n",
       "        [-0.7873, -0.9126, -0.7836, ..., -0.9371, -1.1515, -1.0925],\n",
       "        [-0.7098, -0.8752, -0.9571, ..., -1.0468, -1.526 , -1.5874],\n",
       "        [-0.6427, -0.6693, -0.8397, ..., -1.146 , -1.1681, -1.2766]],\n",
       "\n",
       "       [[-4.9149, -4.8277, -3.5972, ..., -0.9398, -0.775 , -0.8584],\n",
       "        [-4.8554, -4.9251, -5.3035, ..., -0.8764, -0.8994, -0.8515],\n",
       "        [-5.2917, -5.2586, -5.5626, ..., -0.8455, -0.8469, -0.8807],\n",
       "        ...,\n",
       "        [-0.1464, -0.1671, -0.1077, ...,  0.4995,  0.1812,  0.2311],\n",
       "        [-0.1432, -0.0906, -0.4178, ...,  0.6712,  0.428 ,  0.1646],\n",
       "        [-0.4336, -0.5167, -0.3145, ...,  0.3498,  0.3509,  0.2115]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-92d7182e-9c4f-434e-9645-25249e1cfe45' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-92d7182e-9c4f-434e-9645-25249e1cfe45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb045708-f959-4cc2-a993-b58db3b2858d' class='xr-var-data-in' type='checkbox'><label for='data-bb045708-f959-4cc2-a993-b58db3b2858d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e1d4937-51bd-4edd-a67d-4f670e1c91e1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8e1d4937-51bd-4edd-a67d-4f670e1c91e1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 -2.119 -2.052 -2.008 ... 0.3661 0.3512 0.1482\n",
       "    v        (time, x, y) float64 -3.996 -3.914 -3.957 ... 0.3498 0.3509 0.2115\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert it to dataArray and merge coordiantes along time dimension\n",
    "df08 = xr.concat(F08, dim = 'time')\n",
    "df08 =df08.sortby('time', ascending=True)\n",
    "df08['time'] =np.arange(0,120)\n",
    "df08"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Flight 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"/Users/Jasper/Volc_Research/Workflow_OPENPIV/2_Site_4_PIV/F09/*.csv\") #This is the directory witht the CSV files\n",
    "\n",
    "F09 = []\n",
    "i=0\n",
    "for i in range(len(files)):\n",
    "    dfi = pd.read_csv(files[i], sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F09.append(dfi)\n",
    "    i=i+1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "#Using gdrive implementation of fsspec to access data\n",
    "\n",
    "#Google drive link for F09 0-20\n",
    "#https://drive.google.com/drive/u/3/folders/1B0trTgJ1KlnV24w8PRBixb6GbE7cBI_s\n",
    "gdfid1 = '1B0trTgJ1KlnV24w8PRBixb6GbE7cBI_s'\n",
    "gdfs1 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid1, token ='cache')\n",
    "files1 = gdfs1.ls('')\n",
    "\n",
    "#Google drive link for F09 21-120\n",
    "#https://drive.google.com/drive/u/3/folders/1veNpNBtfcMws9455MkvQyhip4n_Wdn6B\n",
    "gdfid2 = '1veNpNBtfcMws9455MkvQyhip4n_Wdn6B'\n",
    "gdfs2 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid2, token ='cache')\n",
    "files2 = gdfs2.ls('')\n",
    "\n",
    "files08 = files1 + files2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "#Takes multiple CSV files and reads them all into one xarray as a List\n",
    "\n",
    "# files1 + files2 : these are the directory with the CSV files\n",
    "\n",
    "F09 = []\n",
    "i=0\n",
    "for i in range(len(files1)):\n",
    "    dfi = pd.read_csv(gdfs1.open(files1[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files1[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F09.append(dfi)\n",
    "    \n",
    "i=0\n",
    "for i in range(len(files2)):\n",
    "    dfi = pd.read_csv(gdfs2.open(files2[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file2 = files2[i]\n",
    "    sec = file1[len(file2)-6: len(file2)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F09.append(dfi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
       ".xr-var-attrs,\n",
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       "\n",
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       "\n",
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       "\n",
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       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
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       "\n",
       ".xr-attrs,\n",
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       "\n",
       "dl.xr-attrs {\n",
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       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
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       "  display: inline-block;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 1.824 1.701 1.968 ... 0.8069 1.008 0.9958\n",
       "    v        (time, x, y) float64 0.777 0.8736 0.7732 ... -1.282 -1.316 -1.443\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ab621972-9c35-480b-a8b4-15466bf78437' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ab621972-9c35-480b-a8b4-15466bf78437' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 120</li><li><span class='xr-has-index'>x</span>: 119</li><li><span class='xr-has-index'>y</span>: 66</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8bac7c13-d6b2-4630-a274-a547f49cc3bf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8bac7c13-d6b2-4630-a274-a547f49cc3bf' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 3.776e+03 3.808e+03</div><input id='attrs-0f41d624-9e5a-4367-83e5-0bbd223dbb0e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f41d624-9e5a-4367-83e5-0bbd223dbb0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19563501-33c8-4aab-817c-d3bd41941528' class='xr-var-data-in' type='checkbox'><label for='data-19563501-33c8-4aab-817c-d3bd41941528' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112., 2144., 2176., 2208., 2240.,\n",
       "       2272., 2304., 2336., 2368., 2400., 2432., 2464., 2496., 2528., 2560.,\n",
       "       2592., 2624., 2656., 2688., 2720., 2752., 2784., 2816., 2848., 2880.,\n",
       "       2912., 2944., 2976., 3008., 3040., 3072., 3104., 3136., 3168., 3200.,\n",
       "       3232., 3264., 3296., 3328., 3360., 3392., 3424., 3456., 3488., 3520.,\n",
       "       3552., 3584., 3616., 3648., 3680., 3712., 3744., 3776., 3808.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 2.08e+03 2.112e+03</div><input id='attrs-84cede2a-6bb7-4337-a4cb-fa77819c3236' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-84cede2a-6bb7-4337-a4cb-fa77819c3236' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dce96ff0-0bc9-42d1-b451-49e56114e67f' class='xr-var-data-in' type='checkbox'><label for='data-dce96ff0-0bc9-42d1-b451-49e56114e67f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 115 116 117 118 119</div><input id='attrs-dad67802-75cf-4c8f-9f14-2093067ca2fd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dad67802-75cf-4c8f-9f14-2093067ca2fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5010344-1739-4581-9313-1186a442ecdc' class='xr-var-data-in' type='checkbox'><label for='data-f5010344-1739-4581-9313-1186a442ecdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd78f62b-79f3-44dd-9e1b-75235eda2c12' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cd78f62b-79f3-44dd-9e1b-75235eda2c12' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.824 1.701 1.968 ... 1.008 0.9958</div><input id='attrs-5edcbef8-7361-4ff5-be79-7706f82edc71' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5edcbef8-7361-4ff5-be79-7706f82edc71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f13d995-40cd-4698-b516-81b713d03fe1' class='xr-var-data-in' type='checkbox'><label for='data-1f13d995-40cd-4698-b516-81b713d03fe1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 1.8239e+00,  1.7014e+00,  1.9677e+00, ...,  1.9543e+00,\n",
       "          1.8130e+00,  1.8198e+00],\n",
       "        [ 1.8703e+00,  1.8606e+00,  1.9567e+00, ...,  1.8196e+00,\n",
       "          1.8248e+00,  1.7809e+00],\n",
       "        [ 2.0553e+00,  2.0206e+00,  1.9187e+00, ...,  1.7921e+00,\n",
       "          1.7963e+00,  1.7056e+00],\n",
       "        ...,\n",
       "        [ 2.1041e+00,  2.1338e+00,  2.1631e+00, ...,  1.5797e+00,\n",
       "          1.1756e+00,  1.3317e+00],\n",
       "        [ 2.0511e+00,  2.1064e+00,  2.1261e+00, ...,  1.5935e+00,\n",
       "          1.1845e+00,  1.2767e+00],\n",
       "        [ 2.2656e+00,  2.1263e+00,  2.1551e+00, ...,  1.5222e+00,\n",
       "          1.5221e+00,  1.3816e+00]],\n",
       "\n",
       "       [[-8.8590e-01, -6.6820e-01, -8.5820e-01, ..., -4.7450e-01,\n",
       "         -4.7820e-01, -4.7360e-01],\n",
       "        [-7.4510e-01, -8.2920e-01, -8.4480e-01, ..., -5.2070e-01,\n",
       "         -5.9620e-01, -6.3150e-01],\n",
       "        [-1.0250e+00, -8.9880e-01, -8.0770e-01, ..., -6.3330e-01,\n",
       "         -6.1400e-01, -6.2280e-01],\n",
       "...\n",
       "        [-1.2320e-01, -1.6310e-01, -3.1920e-01, ..., -5.4020e-01,\n",
       "         -5.9860e-01, -5.8630e-01],\n",
       "        [-1.9970e-01, -2.0980e-01, -3.8120e-01, ..., -5.8410e-01,\n",
       "         -5.5440e-01, -6.2540e-01],\n",
       "        [-5.7400e-02, -2.4250e-01, -3.7930e-01, ..., -3.0140e-01,\n",
       "         -1.7540e-01, -7.0970e-01]],\n",
       "\n",
       "       [[ 1.5289e+00,  1.4416e+00,  1.3940e+00, ...,  9.8220e-01,\n",
       "          9.0370e-01,  8.4260e-01],\n",
       "        [ 1.3891e+00,  1.5516e+00,  1.4570e+00, ...,  8.6160e-01,\n",
       "          7.7760e-01,  7.8910e-01],\n",
       "        [ 1.4636e+00,  1.5606e+00,  1.4551e+00, ...,  8.2080e-01,\n",
       "          7.9190e-01,  7.7120e-01],\n",
       "        ...,\n",
       "        [ 1.0145e+00,  9.2760e-01,  1.0416e+00, ...,  1.1174e+00,\n",
       "          1.1675e+00,  1.4028e+00],\n",
       "        [ 1.0836e+00,  9.9440e-01,  9.6130e-01, ...,  1.0402e+00,\n",
       "          1.2079e+00,  1.5028e+00],\n",
       "        [ 1.1573e+00,  9.8010e-01,  7.7100e-01, ...,  8.0690e-01,\n",
       "          1.0078e+00,  9.9580e-01]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.777 0.8736 ... -1.316 -1.443</div><input id='attrs-35d242df-528f-4958-8ad7-57b537d18d7d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-35d242df-528f-4958-8ad7-57b537d18d7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be78fd6c-cd52-4813-87b3-4cf4b612ff6a' class='xr-var-data-in' type='checkbox'><label for='data-be78fd6c-cd52-4813-87b3-4cf4b612ff6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 0.777 ,  0.8736,  0.7732, ...,  1.4158,  1.4217,  1.4375],\n",
       "        [ 0.6579,  0.8547,  0.7909, ...,  1.3267,  1.2936,  1.4144],\n",
       "        [ 0.7895,  0.8728,  0.8215, ...,  1.368 ,  1.3803,  1.4484],\n",
       "        ...,\n",
       "        [ 1.125 ,  0.9414,  0.9086, ...,  0.2526,  0.6395,  0.581 ],\n",
       "        [ 1.1556,  0.937 ,  0.9044, ...,  0.2397,  0.5529,  0.5857],\n",
       "        [ 1.0549,  1.0531,  0.8197, ...,  0.2551,  0.292 ,  0.4772]],\n",
       "\n",
       "       [[-0.5719, -0.5033, -0.3925, ..., -0.9563, -1.0667, -1.1326],\n",
       "        [-0.5321, -0.4801, -0.3452, ..., -0.9897, -1.0073, -1.1488],\n",
       "        [-0.4558, -0.3932, -0.3479, ..., -0.9849, -1.0353, -1.0688],\n",
       "        ...,\n",
       "        [ 0.8022,  0.8681,  1.0005, ...,  0.4192,  0.492 ,  0.4067],\n",
       "        [ 0.7107,  0.8219,  0.8556, ...,  0.5724,  0.5487,  0.4197],\n",
       "        [ 0.2709,  0.7601,  0.7234, ...,  0.5999,  0.4554,  0.3811]],\n",
       "\n",
       "       [[ 2.0499,  2.3613,  2.2461, ...,  2.5963,  2.6386,  2.6705],\n",
       "        [ 2.112 ,  2.1115,  2.2668, ...,  2.5516,  2.7175,  2.7065],\n",
       "        [ 1.6453,  2.0319,  2.1896, ...,  2.4719,  2.7501,  2.742 ],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [-0.513 , -0.4742, -0.486 , ..., -0.1967, -0.1777, -0.2002],\n",
       "        [-0.3597, -0.4316, -0.5632, ..., -0.1839, -0.1648, -0.1436],\n",
       "        [-0.3157, -0.4549, -0.6663, ..., -0.115 , -0.1554, -0.2494]],\n",
       "\n",
       "       [[-0.0279, -0.0167,  0.1503, ...,  0.3093,  0.4617,  0.5996],\n",
       "        [-0.0509,  0.1729,  0.2033, ...,  0.2534,  0.4733,  0.5631],\n",
       "        [-0.0347,  0.2044,  0.2484, ...,  0.4312,  0.5124,  0.54  ],\n",
       "        ...,\n",
       "        [ 0.0735,  0.064 ,  0.1207, ...,  0.6827,  0.7842,  0.6453],\n",
       "        [-0.0229,  0.0491,  0.1608, ...,  0.6419,  0.7374,  0.7076],\n",
       "        [-0.2261,  0.0448,  0.1562, ...,  0.3271,  0.4033,  0.6746]],\n",
       "\n",
       "       [[-1.1268, -0.874 , -0.9335, ..., -0.7814, -0.8932, -0.933 ],\n",
       "        [-0.9366, -1.1188, -0.9541, ..., -0.7959, -0.8941, -0.9306],\n",
       "        [-0.8644, -1.1402, -0.9346, ..., -0.8642, -0.8789, -0.9166],\n",
       "        ...,\n",
       "        [-1.0316, -0.9415, -0.9018, ..., -1.4067, -1.4385, -1.537 ],\n",
       "        [-0.9728, -0.9482, -0.8942, ..., -1.3552, -1.4615, -1.6777],\n",
       "        [-0.8301, -0.8356, -0.7664, ..., -1.2821, -1.3162, -1.4431]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-9dee0a58-75bf-41d1-a8b7-560d8dbc7a4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9dee0a58-75bf-41d1-a8b7-560d8dbc7a4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71a69ac7-f404-470f-9650-cd6ae1850c30' class='xr-var-data-in' type='checkbox'><label for='data-71a69ac7-f404-470f-9650-cd6ae1850c30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eec40013-1de4-4664-8aa0-197cb83422b0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eec40013-1de4-4664-8aa0-197cb83422b0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 1.824 1.701 1.968 ... 0.8069 1.008 0.9958\n",
       "    v        (time, x, y) float64 0.777 0.8736 0.7732 ... -1.282 -1.316 -1.443\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert it to dataArray and merge coordiantes along time dimension\n",
    "df09 = xr.concat(F09, dim = 'time')\n",
    "df09 =df09.sortby('time', ascending=True)\n",
    "df09['time'] =np.arange(0,120)\n",
    "df09"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Flight 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"/Users/Jasper/Volc_Research/Workflow_OPENPIV/2_Site_4_PIV/F10/*.csv\") #This is the directory witht the CSV files\n",
    "\n",
    "F10 = []\n",
    "i=0\n",
    "for i in range(len(files)):\n",
    "    dfi = pd.read_csv(files[i], sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F10.append(dfi)\n",
    "    i=i+1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "#Using gdrive implementation of fsspec to access data\n",
    "\n",
    "#Google drive link for F10 0-20\n",
    "#https://drive.google.com/drive/u/3/folders/10AKN5mi2jbbhTd5vgthX3TWjRBDDuBs6\n",
    "gdfid1 = '10AKN5mi2jbbhTd5vgthX3TWjRBDDuBs6'\n",
    "gdfs1 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid1, token ='cache')\n",
    "files1 = gdfs1.ls('')\n",
    "\n",
    "#Google drive link for F07 21-120\n",
    "#https://drive.google.com/drive/u/3/folders/1BB-QnJI0FEdswQT9z6X8tYPjSgzx9Q94\n",
    "gdfid2 = '1BB-QnJI0FEdswQT9z6X8tYPjSgzx9Q94'\n",
    "gdfs2 = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfid2, token ='cache')\n",
    "files2 = gdfs2.ls('')\n",
    "\n",
    "files08 = files1 + files2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "#Takes multiple CSV files and reads them all into one xarray as a List\n",
    "\n",
    "# files1 + files2 : these are the directory with the CSV files\n",
    "\n",
    "F10 = []\n",
    "i=0\n",
    "for i in range(len(files1)):\n",
    "    dfi = pd.read_csv(gdfs1.open(files1[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file1 = files1[i]\n",
    "    sec = file1[len(file1)-6: len(file1)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F10.append(dfi)\n",
    "    \n",
    "i=0\n",
    "for i in range(len(files2)):\n",
    "    dfi = pd.read_csv(gdfs2.open(files2[i]), sep = '\\t', header=None,index_col=(0,1) )\n",
    "    dfi.columns = ('u', 'v', 'mask')\n",
    "    dfi.index.rename(['x','y'], inplace=True)\n",
    "    dfi = dfi[~dfi.index.duplicated()]\n",
    "    dfi =dfi.to_xarray()\n",
    "    file2 = files2[i]\n",
    "    sec = file1[len(file2)-6: len(file2)-4] # may need to be adjusted depending on file name length\n",
    "    dfi['time']=sec\n",
    "    F10.append(dfi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
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       "  display: inline-block;\n",
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       "\n",
       ".xr-dim-list {\n",
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       "\n",
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       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
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       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       ".xr-var-dims,\n",
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       ".xr-preview,\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 -0.2521 -0.287 -0.3775 ... -0.5201 -0.5707\n",
       "    v        (time, x, y) float64 1.043 0.8029 0.7745 ... 0.1839 0.1432 -0.1152\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-521d476d-35d5-4eea-ac5b-10a8f571a9e2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-521d476d-35d5-4eea-ac5b-10a8f571a9e2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 120</li><li><span class='xr-has-index'>x</span>: 119</li><li><span class='xr-has-index'>y</span>: 66</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fa8c85b3-9720-4ba0-a0ee-12dc8812c792' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fa8c85b3-9720-4ba0-a0ee-12dc8812c792' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 3.776e+03 3.808e+03</div><input id='attrs-95684ffb-4eb6-4e98-a299-9084c0d7a8ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95684ffb-4eb6-4e98-a299-9084c0d7a8ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95f5e3e6-9ff3-43a8-a1de-36801a2e84d0' class='xr-var-data-in' type='checkbox'><label for='data-95f5e3e6-9ff3-43a8-a1de-36801a2e84d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112., 2144., 2176., 2208., 2240.,\n",
       "       2272., 2304., 2336., 2368., 2400., 2432., 2464., 2496., 2528., 2560.,\n",
       "       2592., 2624., 2656., 2688., 2720., 2752., 2784., 2816., 2848., 2880.,\n",
       "       2912., 2944., 2976., 3008., 3040., 3072., 3104., 3136., 3168., 3200.,\n",
       "       3232., 3264., 3296., 3328., 3360., 3392., 3424., 3456., 3488., 3520.,\n",
       "       3552., 3584., 3616., 3648., 3680., 3712., 3744., 3776., 3808.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 2.08e+03 2.112e+03</div><input id='attrs-029c6537-5836-418f-b5d1-270413035e99' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-029c6537-5836-418f-b5d1-270413035e99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00235487-419c-4a5e-a332-60323015fc9b' class='xr-var-data-in' type='checkbox'><label for='data-00235487-419c-4a5e-a332-60323015fc9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 115 116 117 118 119</div><input id='attrs-c2925e1e-b844-4845-8466-bf6fd91322f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2925e1e-b844-4845-8466-bf6fd91322f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25b6f60f-3ef0-436a-81e5-50bce9550c91' class='xr-var-data-in' type='checkbox'><label for='data-25b6f60f-3ef0-436a-81e5-50bce9550c91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d08aab16-e823-4b97-82f1-398b69aa7b60' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d08aab16-e823-4b97-82f1-398b69aa7b60' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.2521 -0.287 ... -0.5201 -0.5707</div><input id='attrs-9349080f-ce6a-4982-97e5-be1de9bf6fe3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9349080f-ce6a-4982-97e5-be1de9bf6fe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f087a70-ef9a-428e-86e9-eceac7b59c92' class='xr-var-data-in' type='checkbox'><label for='data-2f087a70-ef9a-428e-86e9-eceac7b59c92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-0.2521, -0.287 , -0.3775, ...,  0.0369,  0.1941,  0.1983],\n",
       "        [-0.3248, -0.3794, -0.4991, ..., -0.1317,  0.0143,  0.1364],\n",
       "        [-0.3608, -0.3852, -0.2851, ..., -0.1119,  0.0082,  0.1016],\n",
       "        ...,\n",
       "        [ 0.0562,  0.0957,  0.1429, ..., -0.1038, -0.2486, -0.3256],\n",
       "        [-0.0295,  0.0968,  0.1403, ..., -0.0682, -0.2886, -0.3529],\n",
       "        [ 0.2158,  0.0347,  0.0593, ..., -0.1551, -0.173 , -0.2161]],\n",
       "\n",
       "       [[-0.1603, -0.3825, -0.4936, ..., -0.9276, -0.8923, -0.6665],\n",
       "        [-0.17  , -0.3278, -0.4308, ..., -0.8707, -0.8245, -0.7905],\n",
       "        [-0.1946, -0.3709, -0.4679, ..., -0.8456, -0.8207, -0.8432],\n",
       "        ...,\n",
       "        [ 0.4689,  0.4253,  0.3801, ..., -0.3503, -0.2751, -0.3546],\n",
       "        [ 0.4793,  0.4347, -0.007 , ..., -0.3072, -0.2152, -0.3432],\n",
       "        [ 0.3784,  0.3772,  0.6202, ..., -0.3385, -0.2202, -0.2592]],\n",
       "\n",
       "       [[-1.5316, -1.4925, -1.3607, ..., -0.8776, -0.6573, -0.6919],\n",
       "        [-1.4169, -1.3472, -1.417 , ..., -0.8902, -0.7026, -0.8401],\n",
       "        [-1.3096, -1.3105, -1.3648, ..., -0.604 , -0.6727, -0.9299],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [ 0.1161,  0.118 ,  0.1615, ...,  0.4329,  0.3875,  0.2161],\n",
       "        [ 0.0992,  0.1575,  0.1591, ...,  0.2504,  0.3285,  0.1851],\n",
       "        [ 0.4072,  0.2433,  0.125 , ...,  0.2749,  0.2921,  0.2978]],\n",
       "\n",
       "       [[ 1.2567,  1.2653,  1.3032, ...,  1.1145,  0.9242,  0.8451],\n",
       "        [ 1.3095,  1.2901,  1.181 , ...,  1.0115,  1.2574,  1.586 ],\n",
       "        [ 1.2307,  1.2993,  1.2883, ...,  1.3527,  1.3549,  1.5889],\n",
       "        ...,\n",
       "        [ 1.6931,  1.7508,  1.2707, ...,  1.5898,  0.9286,  1.2157],\n",
       "        [ 1.295 ,  1.2869,  1.2023, ...,  1.5568,  1.1184,  1.1838],\n",
       "        [ 1.8123,  1.1616,  1.2067, ...,  1.3784,  1.361 ,  1.4765]],\n",
       "\n",
       "       [[-1.1815, -1.0899, -0.9536, ..., -0.6131, -0.3551, -0.3717],\n",
       "        [-1.1596, -1.0157, -0.8296, ..., -0.7076, -0.4967, -0.4341],\n",
       "        [-1.0951, -1.0271, -0.9045, ..., -0.698 , -0.6021, -0.4278],\n",
       "        ...,\n",
       "        [-1.0436, -1.0657, -1.0603, ..., -0.4751, -0.3105, -0.308 ],\n",
       "        [-1.0094, -1.0418, -1.0737, ..., -0.6698, -0.5053, -0.4277],\n",
       "        [-0.9406, -0.9069, -1.0975, ..., -0.5795, -0.5201, -0.5707]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.043 0.8029 ... 0.1432 -0.1152</div><input id='attrs-534e068c-1fb1-41ac-b4f7-b88133521869' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-534e068c-1fb1-41ac-b4f7-b88133521869' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e053cc5-50b3-4b1b-83c4-77903fcd7345' class='xr-var-data-in' type='checkbox'><label for='data-6e053cc5-50b3-4b1b-83c4-77903fcd7345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 1.0427e+00,  8.0290e-01,  7.7450e-01, ...,  6.4840e-01,\n",
       "          6.5990e-01,  7.1480e-01],\n",
       "        [ 8.3690e-01,  7.0480e-01,  7.0940e-01, ...,  5.8610e-01,\n",
       "          6.7790e-01,  7.3620e-01],\n",
       "        [ 7.4410e-01,  7.0630e-01,  7.2260e-01, ...,  5.9020e-01,\n",
       "          6.9280e-01,  7.4130e-01],\n",
       "        ...,\n",
       "        [ 3.3800e-01,  3.8540e-01,  4.0220e-01, ...,  2.4800e-01,\n",
       "          2.5090e-01,  3.0750e-01],\n",
       "        [ 2.7100e-01,  3.5280e-01,  2.4530e-01, ...,  2.6690e-01,\n",
       "          5.5130e-01,  3.3580e-01],\n",
       "        [ 3.5990e-01,  3.6780e-01,  2.1320e-01, ...,  2.5280e-01,\n",
       "          2.8310e-01,  3.1210e-01]],\n",
       "\n",
       "       [[ 1.9010e+00,  1.6748e+00,  1.6670e+00, ...,  1.2560e+00,\n",
       "          1.1980e+00,  1.0852e+00],\n",
       "        [ 1.8120e+00,  1.7687e+00,  1.6701e+00, ...,  1.2153e+00,\n",
       "          1.1579e+00,  1.0643e+00],\n",
       "        [ 1.7351e+00,  1.7164e+00,  1.6905e+00, ...,  1.1964e+00,\n",
       "          1.1158e+00,  1.0152e+00],\n",
       "...\n",
       "        [ 8.2020e-01,  8.1110e-01,  2.6070e-01, ...,  2.3320e-01,\n",
       "          6.2740e-01,  4.8590e-01],\n",
       "        [ 1.4640e-01,  1.6830e-01,  2.4400e-01, ...,  1.4700e-01,\n",
       "          3.9170e-01,  4.7820e-01],\n",
       "        [ 8.5240e-01,  2.3160e-01,  1.2590e-01, ...,  3.2570e-01,\n",
       "          3.5270e-01,  7.2490e-01]],\n",
       "\n",
       "       [[ 1.5890e-01,  1.5550e-01,  2.3740e-01, ..., -2.8400e-01,\n",
       "         -1.9690e-01, -1.3140e-01],\n",
       "        [ 1.5420e-01,  1.7250e-01,  2.8430e-01, ..., -2.7150e-01,\n",
       "         -2.5790e-01, -2.1460e-01],\n",
       "        [ 1.1520e-01,  1.7040e-01,  2.7620e-01, ..., -2.9170e-01,\n",
       "         -3.6650e-01, -2.8020e-01],\n",
       "        ...,\n",
       "        [ 1.8400e-02,  1.4870e-01,  2.8860e-01, ...,  1.8500e-02,\n",
       "         -6.5000e-03,  4.4900e-02],\n",
       "        [ 1.0000e-04,  1.5560e-01,  2.6230e-01, ...,  4.0550e-01,\n",
       "          1.0320e-01, -2.2100e-02],\n",
       "        [ 9.7000e-02,  2.0080e-01,  2.7130e-01, ...,  1.8390e-01,\n",
       "          1.4320e-01, -1.1520e-01]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-56c19a77-2ecb-4883-ae25-4270586091e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56c19a77-2ecb-4883-ae25-4270586091e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96dcb8e8-2921-4474-8e51-21c07aac96aa' class='xr-var-data-in' type='checkbox'><label for='data-96dcb8e8-2921-4474-8e51-21c07aac96aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-48fe5fad-b012-42cc-bdf5-8621fd23d1b6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-48fe5fad-b012-42cc-bdf5-8621fd23d1b6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 -0.2521 -0.287 -0.3775 ... -0.5201 -0.5707\n",
       "    v        (time, x, y) float64 1.043 0.8029 0.7745 ... 0.1839 0.1432 -0.1152\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert it to dataArray and merge coordiantes along time dimension\n",
    "df10 = xr.concat(F10, dim = 'time')\n",
    "df10 =df10.sortby('time', ascending=True)\n",
    "df10['time'] =np.arange(0,120)\n",
    "df10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combine all Flights into one Dataset with new dimension (Flight)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (Flight: 4, time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "  * Flight   (Flight) &lt;U3 &#x27;F07&#x27; &#x27;F08&#x27; &#x27;F09&#x27; &#x27;F10&#x27;\n",
       "Data variables:\n",
       "    u        (Flight, time, x, y) float64 0.3826 0.4679 ... -0.5201 -0.5707\n",
       "    v        (Flight, time, x, y) float64 -2.979 -3.021 ... 0.1432 -0.1152\n",
       "    mask     (Flight, time, x, y) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ec51695e-c649-4dfc-8b59-5f54d62e667b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ec51695e-c649-4dfc-8b59-5f54d62e667b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Flight</span>: 4</li><li><span class='xr-has-index'>time</span>: 120</li><li><span class='xr-has-index'>x</span>: 119</li><li><span class='xr-has-index'>y</span>: 66</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-67c1905d-43d3-46a1-bace-565022a87e23' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67c1905d-43d3-46a1-bace-565022a87e23' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 3.776e+03 3.808e+03</div><input id='attrs-0227042e-8b2a-45b7-b55a-f35e97fc865f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0227042e-8b2a-45b7-b55a-f35e97fc865f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecf31aa9-bc31-4596-8eb1-6b24aea0c1c0' class='xr-var-data-in' type='checkbox'><label for='data-ecf31aa9-bc31-4596-8eb1-6b24aea0c1c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112., 2144., 2176., 2208., 2240.,\n",
       "       2272., 2304., 2336., 2368., 2400., 2432., 2464., 2496., 2528., 2560.,\n",
       "       2592., 2624., 2656., 2688., 2720., 2752., 2784., 2816., 2848., 2880.,\n",
       "       2912., 2944., 2976., 3008., 3040., 3072., 3104., 3136., 3168., 3200.,\n",
       "       3232., 3264., 3296., 3328., 3360., 3392., 3424., 3456., 3488., 3520.,\n",
       "       3552., 3584., 3616., 3648., 3680., 3712., 3744., 3776., 3808.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0 64.0 ... 2.08e+03 2.112e+03</div><input id='attrs-45adc7f7-7445-4766-aa8a-18be2c306d89' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-45adc7f7-7445-4766-aa8a-18be2c306d89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c46cb1e2-c235-414c-b914-01c5b7febfbf' class='xr-var-data-in' type='checkbox'><label for='data-c46cb1e2-c235-414c-b914-01c5b7febfbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  32.,   64.,   96.,  128.,  160.,  192.,  224.,  256.,  288.,  320.,\n",
       "        352.,  384.,  416.,  448.,  480.,  512.,  544.,  576.,  608.,  640.,\n",
       "        672.,  704.,  736.,  768.,  800.,  832.,  864.,  896.,  928.,  960.,\n",
       "        992., 1024., 1056., 1088., 1120., 1152., 1184., 1216., 1248., 1280.,\n",
       "       1312., 1344., 1376., 1408., 1440., 1472., 1504., 1536., 1568., 1600.,\n",
       "       1632., 1664., 1696., 1728., 1760., 1792., 1824., 1856., 1888., 1920.,\n",
       "       1952., 1984., 2016., 2048., 2080., 2112.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 115 116 117 118 119</div><input id='attrs-6e7c4ce7-0a4f-4705-b902-0af18771c256' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e7c4ce7-0a4f-4705-b902-0af18771c256' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06c52694-1e8b-4c0f-ba96-edbbc29f8c3f' class='xr-var-data-in' type='checkbox'><label for='data-06c52694-1e8b-4c0f-ba96-edbbc29f8c3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Flight</span></div><div class='xr-var-dims'>(Flight)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27; &#x27;F08&#x27; &#x27;F09&#x27; &#x27;F10&#x27;</div><input id='attrs-3d74edcc-26ca-4ed2-acdc-ef14098c1e5f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d74edcc-26ca-4ed2-acdc-ef14098c1e5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d36abf90-3f87-45b6-9c11-5d4693111837' class='xr-var-data-in' type='checkbox'><label for='data-d36abf90-3f87-45b6-9c11-5d4693111837' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;F07&#x27;, &#x27;F08&#x27;, &#x27;F09&#x27;, &#x27;F10&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55d21b14-2c58-4890-967b-1c41eb9dce80' class='xr-section-summary-in' type='checkbox'  checked><label for='section-55d21b14-2c58-4890-967b-1c41eb9dce80' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(Flight, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3826 0.4679 ... -0.5201 -0.5707</div><input id='attrs-d2018c37-92b0-423f-a64f-4fd9348b9c76' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d2018c37-92b0-423f-a64f-4fd9348b9c76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-804cb987-b687-48ab-82e2-aecc8f10bba4' class='xr-var-data-in' type='checkbox'><label for='data-804cb987-b687-48ab-82e2-aecc8f10bba4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[ 3.8260e-01,  4.6790e-01,  5.2150e-01, ..., -2.6500e-01,\n",
       "          -2.4420e-01, -2.2030e-01],\n",
       "         [ 3.1740e-01,  4.0660e-01,  4.4750e-01, ..., -2.1510e-01,\n",
       "          -1.6360e-01, -2.4340e-01],\n",
       "         [ 2.3630e-01,  3.3380e-01,  4.0560e-01, ..., -2.5640e-01,\n",
       "          -1.6760e-01, -3.7600e-01],\n",
       "         ...,\n",
       "         [ 2.3250e-01,  3.2140e-01,  3.0940e-01, ..., -1.1330e-01,\n",
       "          -3.0000e-04, -4.5900e-02],\n",
       "         [ 1.3690e-01,  1.2410e-01,  9.6800e-02, ..., -9.5100e-02,\n",
       "          -2.1130e-01, -7.2200e-02],\n",
       "         [-3.7800e-02,  9.8400e-02,  6.9900e-02, ..., -2.5000e-03,\n",
       "          -1.8450e-01, -2.7200e-01]],\n",
       "\n",
       "        [[ 1.2033e+00,  1.1482e+00,  1.1948e+00, ...,  3.1737e+00,\n",
       "           3.2792e+00,  3.3442e+00],\n",
       "         [ 1.1242e+00,  1.3172e+00,  1.3266e+00, ...,  3.1923e+00,\n",
       "           3.2726e+00,  3.3113e+00],\n",
       "         [ 1.0144e+00,  1.1981e+00,  1.3030e+00, ...,  3.2110e+00,\n",
       "           3.2435e+00,  3.2587e+00],\n",
       "...\n",
       "         [ 1.6931e+00,  1.7508e+00,  1.2707e+00, ...,  1.5898e+00,\n",
       "           9.2860e-01,  1.2157e+00],\n",
       "         [ 1.2950e+00,  1.2869e+00,  1.2023e+00, ...,  1.5568e+00,\n",
       "           1.1184e+00,  1.1838e+00],\n",
       "         [ 1.8123e+00,  1.1616e+00,  1.2067e+00, ...,  1.3784e+00,\n",
       "           1.3610e+00,  1.4765e+00]],\n",
       "\n",
       "        [[-1.1815e+00, -1.0899e+00, -9.5360e-01, ..., -6.1310e-01,\n",
       "          -3.5510e-01, -3.7170e-01],\n",
       "         [-1.1596e+00, -1.0157e+00, -8.2960e-01, ..., -7.0760e-01,\n",
       "          -4.9670e-01, -4.3410e-01],\n",
       "         [-1.0951e+00, -1.0271e+00, -9.0450e-01, ..., -6.9800e-01,\n",
       "          -6.0210e-01, -4.2780e-01],\n",
       "         ...,\n",
       "         [-1.0436e+00, -1.0657e+00, -1.0603e+00, ..., -4.7510e-01,\n",
       "          -3.1050e-01, -3.0800e-01],\n",
       "         [-1.0094e+00, -1.0418e+00, -1.0737e+00, ..., -6.6980e-01,\n",
       "          -5.0530e-01, -4.2770e-01],\n",
       "         [-9.4060e-01, -9.0690e-01, -1.0975e+00, ..., -5.7950e-01,\n",
       "          -5.2010e-01, -5.7070e-01]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(Flight, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.979 -3.021 ... 0.1432 -0.1152</div><input id='attrs-4e889941-15b5-457f-a222-0609e8b7b4f6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e889941-15b5-457f-a222-0609e8b7b4f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b462469-22ed-4139-8588-6ac9b2f229d8' class='xr-var-data-in' type='checkbox'><label for='data-0b462469-22ed-4139-8588-6ac9b2f229d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[-2.9791e+00, -3.0213e+00, -3.0816e+00, ...,  3.1800e-01,\n",
       "           3.1090e-01,  3.4770e-01],\n",
       "         [-2.9436e+00, -3.0073e+00, -3.0652e+00, ...,  3.4970e-01,\n",
       "           3.4320e-01,  2.9510e-01],\n",
       "         [-2.9957e+00, -3.0668e+00, -3.1353e+00, ...,  3.5310e-01,\n",
       "           3.4610e-01,  3.0300e-01],\n",
       "         ...,\n",
       "         [ 2.0400e-01,  2.0320e-01,  2.7820e-01, ...,  8.8500e-02,\n",
       "           4.7300e-02, -4.2100e-02],\n",
       "         [-3.7400e-02,  1.1870e-01,  1.9910e-01, ...,  5.3600e-02,\n",
       "           6.7100e-02,  8.1700e-02],\n",
       "         [ 1.5270e-01,  1.7960e-01,  2.2360e-01, ...,  8.3300e-02,\n",
       "           1.0470e-01,  1.6820e-01]],\n",
       "\n",
       "        [[-1.6350e+00, -1.7855e+00, -1.6962e+00, ...,  1.0674e+00,\n",
       "           1.2355e+00,  1.2208e+00],\n",
       "         [-1.6120e+00, -1.6342e+00, -1.5753e+00, ...,  1.1189e+00,\n",
       "           1.2795e+00,  1.2786e+00],\n",
       "         [-1.6709e+00, -1.5999e+00, -1.5060e+00, ...,  1.2129e+00,\n",
       "           1.3241e+00,  1.3065e+00],\n",
       "...\n",
       "         [ 8.2020e-01,  8.1110e-01,  2.6070e-01, ...,  2.3320e-01,\n",
       "           6.2740e-01,  4.8590e-01],\n",
       "         [ 1.4640e-01,  1.6830e-01,  2.4400e-01, ...,  1.4700e-01,\n",
       "           3.9170e-01,  4.7820e-01],\n",
       "         [ 8.5240e-01,  2.3160e-01,  1.2590e-01, ...,  3.2570e-01,\n",
       "           3.5270e-01,  7.2490e-01]],\n",
       "\n",
       "        [[ 1.5890e-01,  1.5550e-01,  2.3740e-01, ..., -2.8400e-01,\n",
       "          -1.9690e-01, -1.3140e-01],\n",
       "         [ 1.5420e-01,  1.7250e-01,  2.8430e-01, ..., -2.7150e-01,\n",
       "          -2.5790e-01, -2.1460e-01],\n",
       "         [ 1.1520e-01,  1.7040e-01,  2.7620e-01, ..., -2.9170e-01,\n",
       "          -3.6650e-01, -2.8020e-01],\n",
       "         ...,\n",
       "         [ 1.8400e-02,  1.4870e-01,  2.8860e-01, ...,  1.8500e-02,\n",
       "          -6.5000e-03,  4.4900e-02],\n",
       "         [ 1.0000e-04,  1.5560e-01,  2.6230e-01, ...,  4.0550e-01,\n",
       "           1.0320e-01, -2.2100e-02],\n",
       "         [ 9.7000e-02,  2.0080e-01,  2.7130e-01, ...,  1.8390e-01,\n",
       "           1.4320e-01, -1.1520e-01]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(Flight, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-9a7c5267-4e3c-475e-b830-56df826ed65e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a7c5267-4e3c-475e-b830-56df826ed65e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6a5aaba-fbd1-4215-9c90-ff2ad9137142' class='xr-var-data-in' type='checkbox'><label for='data-e6a5aaba-fbd1-4215-9c90-ff2ad9137142' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-05b8f55f-b064-4d30-a6b3-4cecb9ffc8a5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-05b8f55f-b064-4d30-a6b3-4cecb9ffc8a5' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (Flight: 4, time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 32.0 64.0 96.0 128.0 ... 3.744e+03 3.776e+03 3.808e+03\n",
       "  * y        (y) float64 32.0 64.0 96.0 128.0 ... 2.048e+03 2.08e+03 2.112e+03\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "  * Flight   (Flight) <U3 'F07' 'F08' 'F09' 'F10'\n",
       "Data variables:\n",
       "    u        (Flight, time, x, y) float64 0.3826 0.4679 ... -0.5201 -0.5707\n",
       "    v        (Flight, time, x, y) float64 -2.979 -3.021 ... 0.1432 -0.1152\n",
       "    mask     (Flight, time, x, y) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Flights = [df07, df08, df09, df10]\n",
    "dfx = xr.concat(Flights, dim = 'Flight')\n",
    "dfx =dfx.sortby('Flight', ascending=True)\n",
    "dfx = dfx.assign_coords(Flight =['F07','F08','F09', 'F10'])\n",
    "dfx['time'] =np.arange(0,120)\n",
    "dfx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make Conversions to real world units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Image Footprint: 436.4249645610448 m x 245.4890425655877 m\n",
      "Ground Sampling Distance: x: 0.11365233452110542 y: 0.11260965255302188\n"
     ]
    }
   ],
   "source": [
    "#Sensor and Drone Measurments ----\n",
    "AGL = 304.8 #meters  \n",
    "FOV = np.deg2rad(78.8) #degrees\n",
    "Aspect =  2160/3840   #aspect ratio 16:9 \n",
    "\n",
    "D =   2 * AGL *np.tan(FOV/2) #diagnol of image\n",
    "\n",
    "A = (D) / np.sqrt(1 + Aspect**2)\n",
    "B = Aspect * D / np.sqrt(1 + Aspect**2)\n",
    "print('Image Footprint:',A, 'm x', B, 'm')\n",
    "\n",
    "PixelX = 3840 #width of image in pixels\n",
    "PixelY = 2180 #height of image in pixels\n",
    "\n",
    "\n",
    "GSDx = A/ PixelX\n",
    "GSDy = B/ PixelY\n",
    "\n",
    "print('Ground Sampling Distance:', 'x:', GSDx, 'y:', GSDy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Velocity Calculation\n",
    "\n",
    "dfx['u'] = dfx.u *GSDx \n",
    "dfx['v'] = dfx.v*-1 * GSDy # the negative is to make the downstream velocity positive\n",
    "\n",
    "#Spatial Calculation\n",
    "dfx['x'] = dfx.x*GSDx \n",
    "dfx['y'] = dfx.y*GSDy "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Subtract out drone motion from velocity fields"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Subtract out v velocity of still region from image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Each flight\n",
    "F07 = dfx.sel(Flight= 'F07')\n",
    "F08 = dfx.sel(Flight= 'F08')\n",
    "F09 = dfx.sel(Flight= 'F09')\n",
    "F10 = dfx.sel(Flight= 'F10')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7f8f15282730>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x432 with 8 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 386,
       "width": 1738
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(30, 6), ncols=4, )\n",
    "\n",
    "F07.v.mean(dim='time').transpose().plot.contourf(ax=axes[0], levels=300, vmin=0, vmax=3.5, cmap=cm.nipy_spectral, yincrease=False)\n",
    "F08.v.mean(dim='time').transpose().plot.contourf(ax=axes[1], levels=300, vmin=0, vmax=3.5, cmap=cm.nipy_spectral, yincrease=False)\n",
    "F09.v.mean(dim='time').transpose().plot.contourf(ax=axes[2], levels=300, vmin=0, vmax=3.5, cmap=cm.nipy_spectral, yincrease=False)\n",
    "F10.v.mean(dim='time').transpose().plot.contourf(ax=axes[3],levels=300, vmin=0, vmax=3.5, cmap=cm.nipy_spectral, yincrease=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 3.637 7.274 10.91 14.55 ... 421.9 425.5 429.2 432.8\n",
       "  * y        (y) float64 3.604 7.207 10.81 14.41 ... 227.0 230.6 234.2 237.8\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "    Flight   &lt;U3 &#x27;F07&#x27;\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 0.04348 0.05318 ... -0.005262 -0.009422\n",
       "    v        (time, x, y) float64 0.3355 0.3402 0.347 ... 0.1089 0.1018 0.09061\n",
       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6bf15e57-e77a-4c09-b570-e578f4824c6a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6bf15e57-e77a-4c09-b570-e578f4824c6a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 120</li><li><span class='xr-has-index'>x</span>: 119</li><li><span class='xr-has-index'>y</span>: 66</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2741b45a-ba2f-4227-b6a5-510f83d2e266' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2741b45a-ba2f-4227-b6a5-510f83d2e266' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.637 7.274 10.91 ... 429.2 432.8</div><input id='attrs-0ac8f324-ae56-496a-9846-e952f1c85ba6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ac8f324-ae56-496a-9846-e952f1c85ba6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90e5d5e1-e6af-41b2-a4e9-86f9f2ce0931' class='xr-var-data-in' type='checkbox'><label for='data-90e5d5e1-e6af-41b2-a4e9-86f9f2ce0931' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  3.636875,   7.273749,  10.910624,  14.547499,  18.184374,  21.821248,\n",
       "        25.458123,  29.094998,  32.731872,  36.368747,  40.005622,  43.642496,\n",
       "        47.279371,  50.916246,  54.553121,  58.189995,  61.82687 ,  65.463745,\n",
       "        69.100619,  72.737494,  76.374369,  80.011244,  83.648118,  87.284993,\n",
       "        90.921868,  94.558742,  98.195617, 101.832492, 105.469366, 109.106241,\n",
       "       112.743116, 116.379991, 120.016865, 123.65374 , 127.290615, 130.927489,\n",
       "       134.564364, 138.201239, 141.838113, 145.474988, 149.111863, 152.748738,\n",
       "       156.385612, 160.022487, 163.659362, 167.296236, 170.933111, 174.569986,\n",
       "       178.206861, 181.843735, 185.48061 , 189.117485, 192.754359, 196.391234,\n",
       "       200.028109, 203.664983, 207.301858, 210.938733, 214.575608, 218.212482,\n",
       "       221.849357, 225.486232, 229.123106, 232.759981, 236.396856, 240.033731,\n",
       "       243.670605, 247.30748 , 250.944355, 254.581229, 258.218104, 261.854979,\n",
       "       265.491853, 269.128728, 272.765603, 276.402478, 280.039352, 283.676227,\n",
       "       287.313102, 290.949976, 294.586851, 298.223726, 301.8606  , 305.497475,\n",
       "       309.13435 , 312.771225, 316.408099, 320.044974, 323.681849, 327.318723,\n",
       "       330.955598, 334.592473, 338.229348, 341.866222, 345.503097, 349.139972,\n",
       "       352.776846, 356.413721, 360.050596, 363.68747 , 367.324345, 370.96122 ,\n",
       "       374.598095, 378.234969, 381.871844, 385.508719, 389.145593, 392.782468,\n",
       "       396.419343, 400.056218, 403.693092, 407.329967, 410.966842, 414.603716,\n",
       "       418.240591, 421.877466, 425.51434 , 429.151215, 432.78809 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.604 7.207 10.81 ... 234.2 237.8</div><input id='attrs-4100c561-201c-4b42-8f8a-3972370de2db' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4100c561-201c-4b42-8f8a-3972370de2db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0cef3e9-42ef-486f-83af-f66461c0edf2' class='xr-var-data-in' type='checkbox'><label for='data-f0cef3e9-42ef-486f-83af-f66461c0edf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  3.603509,   7.207018,  10.810527,  14.414036,  18.017544,  21.621053,\n",
       "        25.224562,  28.828071,  32.43158 ,  36.035089,  39.638598,  43.242107,\n",
       "        46.845615,  50.449124,  54.052633,  57.656142,  61.259651,  64.86316 ,\n",
       "        68.466669,  72.070178,  75.673687,  79.277195,  82.880704,  86.484213,\n",
       "        90.087722,  93.691231,  97.29474 , 100.898249, 104.501758, 108.105266,\n",
       "       111.708775, 115.312284, 118.915793, 122.519302, 126.122811, 129.72632 ,\n",
       "       133.329829, 136.933338, 140.536846, 144.140355, 147.743864, 151.347373,\n",
       "       154.950882, 158.554391, 162.1579  , 165.761409, 169.364917, 172.968426,\n",
       "       176.571935, 180.175444, 183.778953, 187.382462, 190.985971, 194.58948 ,\n",
       "       198.192988, 201.796497, 205.400006, 209.003515, 212.607024, 216.210533,\n",
       "       219.814042, 223.417551, 227.02106 , 230.624568, 234.228077, 237.831586])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 115 116 117 118 119</div><input id='attrs-b6d2e5e9-32d5-43d0-a799-a6584c49d5be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6d2e5e9-32d5-43d0-a799-a6584c49d5be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2669f2a2-953e-4962-8ca1-f600ee40fa65' class='xr-var-data-in' type='checkbox'><label for='data-2669f2a2-953e-4962-8ca1-f600ee40fa65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Flight</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27;</div><input id='attrs-bec739e6-8bf8-4eda-8d11-6eaca9699b1a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bec739e6-8bf8-4eda-8d11-6eaca9699b1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9daa354-74be-4f82-9095-d8fc06081358' class='xr-var-data-in' type='checkbox'><label for='data-e9daa354-74be-4f82-9095-d8fc06081358' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;F07&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-48c1f70f-f978-4cc3-a873-6eea9ed6bddc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-48c1f70f-f978-4cc3-a873-6eea9ed6bddc' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04348 0.05318 ... -0.009422</div><input id='attrs-ac12fbeb-fb25-4c22-afcc-d594ff07c76a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ac12fbeb-fb25-4c22-afcc-d594ff07c76a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba734edf-54a1-4fe5-aa94-35ce5acdbd29' class='xr-var-data-in' type='checkbox'><label for='data-ba734edf-54a1-4fe5-aa94-35ce5acdbd29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 4.34833832e-02,  5.31779273e-02,  5.92696925e-02, ...,\n",
       "         -3.01178686e-02, -2.77539001e-02, -2.50376093e-02],\n",
       "        [ 3.60732510e-02,  4.62110392e-02,  5.08594197e-02, ...,\n",
       "         -2.44466172e-02, -1.85935219e-02, -2.76629782e-02],\n",
       "        [ 2.68560466e-02,  3.79371493e-02,  4.60973869e-02, ...,\n",
       "         -2.91404586e-02, -1.90481313e-02, -4.27332778e-02],\n",
       "        ...,\n",
       "        [ 2.64241678e-02,  3.65278603e-02,  3.51640323e-02, ...,\n",
       "         -1.28768095e-02, -3.40957004e-05, -5.21664215e-03],\n",
       "        [ 1.55590046e-02,  1.41042547e-02,  1.10015460e-02, ...,\n",
       "         -1.08083370e-02, -2.40147383e-02, -8.20569855e-03],\n",
       "        [-4.29605824e-03,  1.11833897e-02,  7.94429818e-03, ...,\n",
       "         -2.84130836e-04, -2.09688557e-02, -3.09134350e-02]],\n",
       "\n",
       "       [[ 1.36757854e-01,  1.30495610e-01,  1.35791809e-01, ...,\n",
       "          3.60698414e-01,  3.72688735e-01,  3.80076137e-01],\n",
       "        [ 1.27767954e-01,  1.49702855e-01,  1.50771187e-01, ...,\n",
       "          3.62812347e-01,  3.71938630e-01,  3.76336975e-01],\n",
       "        [ 1.15288928e-01,  1.36166862e-01,  1.48088992e-01, ...,\n",
       "          3.64937646e-01,  3.68631347e-01,  3.70358863e-01],\n",
       "...\n",
       "        [ 8.76941413e-02,  8.94216568e-02,  7.77495620e-02, ...,\n",
       "          5.13367595e-02,  2.51171659e-02,  8.62621219e-02],\n",
       "        [ 1.09663138e-01,  8.30002999e-02,  1.04310113e-01, ...,\n",
       "          1.10356417e-01,  9.71613808e-02,  7.89997377e-02],\n",
       "        [ 3.96646647e-02,  7.45786619e-02,  1.03469085e-01, ...,\n",
       "          1.15811729e-01,  1.21119293e-01,  8.57734169e-02]],\n",
       "\n",
       "       [[ 2.90040758e-02,  3.68233564e-02,  4.80749375e-02, ...,\n",
       "         -7.03621603e-02, -5.66784192e-02, -7.45786619e-02],\n",
       "        [ 2.40261035e-02,  2.93223023e-02,  4.32560785e-02, ...,\n",
       "         -6.42590299e-02, -5.78604035e-02, -7.35330604e-02],\n",
       "        [ 1.74683638e-02,  2.59581932e-02,  3.78916883e-02, ...,\n",
       "         -5.78944992e-02, -6.03152939e-02, -6.85437229e-02],\n",
       "        ...,\n",
       "        [-5.65193060e-02, -6.76117738e-02, -6.69412250e-02, ...,\n",
       "         -3.54595284e-02, -2.11393342e-02, -8.86488209e-03],\n",
       "        [-7.68403434e-02, -5.87355265e-02, -6.17814090e-02, ...,\n",
       "         -7.91020248e-03, -1.40360633e-02, -2.28895802e-02],\n",
       "        [-6.22473836e-02, -4.22786684e-02, -3.53345108e-02, ...,\n",
       "         -1.00695968e-02, -5.26210309e-03, -9.42177853e-03]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3355 0.3402 ... 0.1018 0.09061</div><input id='attrs-a1066ed7-9a3a-46a1-8ff4-26b934ef4975' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a1066ed7-9a3a-46a1-8ff4-26b934ef4975' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f673590-1b70-4eb9-9661-9040b9b4350b' class='xr-var-data-in' type='checkbox'><label for='data-4f673590-1b70-4eb9-9661-9040b9b4350b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 3.35475416e-01,  3.40227543e-01,  3.47017905e-01, ...,\n",
       "         -3.58098695e-02, -3.50103410e-02, -3.91543762e-02],\n",
       "        [ 3.31477773e-01,  3.38651008e-01,  3.45171107e-01, ...,\n",
       "         -3.93795955e-02, -3.86476328e-02, -3.32311085e-02],\n",
       "        [ 3.37344736e-01,  3.45351282e-01,  3.53065044e-01, ...,\n",
       "         -3.97624683e-02, -3.89742007e-02, -3.41207247e-02],\n",
       "        ...,\n",
       "        [-2.29723691e-02, -2.28822814e-02, -3.13280053e-02, ...,\n",
       "         -9.96595425e-03, -5.32643657e-03,  4.74086637e-03],\n",
       "        [ 4.21160101e-03, -1.33667658e-02, -2.24205818e-02, ...,\n",
       "         -6.03587738e-03, -7.55610769e-03, -9.20020861e-03],\n",
       "        [-1.71954939e-02, -2.02246936e-02, -2.51795183e-02, ...,\n",
       "         -9.38038406e-03, -1.17902306e-02, -1.89409436e-02]],\n",
       "\n",
       "       [[ 1.84116782e-01,  2.01064535e-01,  1.91008493e-01, ...,\n",
       "         -1.20199543e-01, -1.39129226e-01, -1.37473864e-01],\n",
       "        [ 1.81526760e-01,  1.84026694e-01,  1.77393986e-01, ...,\n",
       "         -1.25998940e-01, -1.44084050e-01, -1.43982702e-01],\n",
       "        [ 1.88159468e-01,  1.80164183e-01,  1.69590137e-01, ...,\n",
       "         -1.36584248e-01, -1.49106441e-01, -1.47124511e-01],\n",
       "...\n",
       "        [ 4.53704290e-02,  5.35346288e-02,  5.01338173e-02, ...,\n",
       "          2.84001544e-02,  3.34901107e-02,  9.59659459e-02],\n",
       "        [ 6.48406379e-02,  6.70815700e-02,  6.45591138e-02, ...,\n",
       "          8.26329630e-02,  8.08987744e-02,  9.55380292e-02],\n",
       "        [ 1.94927309e-02,  5.47733350e-02,  6.00547277e-02, ...,\n",
       "          8.81508360e-02,  9.33083581e-02,  7.47953312e-02]],\n",
       "\n",
       "       [[ 4.54481297e-01,  4.65460738e-01,  4.80989609e-01, ...,\n",
       "          1.21111681e-01,  9.46258910e-02,  1.20120716e-01],\n",
       "        [ 4.60483391e-01,  4.13446339e-01,  4.86800267e-01, ...,\n",
       "          1.29681276e-01,  1.23577833e-01,  1.17654565e-01],\n",
       "        [ 4.70595738e-01,  4.81654006e-01,  4.95944171e-01, ...,\n",
       "          1.25458414e-01,  1.11584905e-01,  1.14996977e-01],\n",
       "        ...,\n",
       "        [ 1.10593940e-01,  1.01776604e-01,  9.53015490e-02, ...,\n",
       "          1.05335069e-01,  1.12373172e-01,  1.09828194e-01],\n",
       "        [ 1.17463129e-01,  1.02733786e-01,  9.30718778e-02, ...,\n",
       "          1.03477010e-01,  1.04096363e-01,  1.07181867e-01],\n",
       "        [ 1.23769269e-01,  1.11551122e-01,  9.18669546e-02, ...,\n",
       "          1.08904795e-01,  1.01821648e-01,  9.06057264e-02]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ce5b5046-d06e-4f86-83c1-9b9ea00e53ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce5b5046-d06e-4f86-83c1-9b9ea00e53ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92266227-f46c-46e6-b460-ebcd2bbd11ff' class='xr-var-data-in' type='checkbox'><label for='data-92266227-f46c-46e6-b460-ebcd2bbd11ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cf8c7dd7-6156-4b7a-9d51-e0b57b5eaa5f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cf8c7dd7-6156-4b7a-9d51-e0b57b5eaa5f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:  (time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 3.637 7.274 10.91 14.55 ... 421.9 425.5 429.2 432.8\n",
       "  * y        (y) float64 3.604 7.207 10.81 14.41 ... 227.0 230.6 234.2 237.8\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "    Flight   <U3 'F07'\n",
       "Data variables:\n",
       "    u        (time, x, y) float64 0.04348 0.05318 ... -0.005262 -0.009422\n",
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       "    mask     (time, x, y) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
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   ],
   "source": [
    "F07"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
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       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
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       "\n",
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       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
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       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
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       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;v&#x27; ()&gt;\n",
       "array(2.08280025)\n",
       "Coordinates:\n",
       "    Flight   &lt;U3 &#x27;F07&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'v'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d2f6f4a1-1b0c-426b-8914-a490c84f8b7e' class='xr-array-in' type='checkbox' checked><label for='section-d2f6f4a1-1b0c-426b-8914-a490c84f8b7e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.083</span></div><div class='xr-array-data'><pre>array(2.08280025)</pre></div></div></li><li class='xr-section-item'><input id='section-331d01c2-3851-4568-bab9-6dcc44bdc378' class='xr-section-summary-in' type='checkbox'  checked><label for='section-331d01c2-3851-4568-bab9-6dcc44bdc378' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Flight</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27;</div><input id='attrs-330b159c-9402-4482-a71e-1df165c3f7f6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-330b159c-9402-4482-a71e-1df165c3f7f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a2f7a64-dd00-45b0-b450-bd654832d0b4' class='xr-var-data-in' type='checkbox'><label for='data-5a2f7a64-dd00-45b0-b450-bd654832d0b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;F07&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-debf0cf9-a1fa-4207-8ec7-94a46162c6b1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-debf0cf9-a1fa-4207-8ec7-94a46162c6b1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'v' ()>\n",
       "array(2.08280025)\n",
       "Coordinates:\n",
       "    Flight   <U3 'F07'"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dfx.sel(Flight= 'F07', x=slice(100,200), y=slice(100, 237)).v.mean(dim= ('x', 'y', 'time'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;v&#x27; ()&gt;\n",
       "array(37243.45071385)\n",
       "Coordinates:\n",
       "    Flight   &lt;U3 &#x27;F07&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'v'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5a6769d3-a199-4a5d-b746-72d75af453c4' class='xr-array-in' type='checkbox' checked><label for='section-5a6769d3-a199-4a5d-b746-72d75af453c4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>3.724e+04</span></div><div class='xr-array-data'><pre>array(37243.45071385)</pre></div></div></li><li class='xr-section-item'><input id='section-5936660a-2598-4dda-bf77-029853558f50' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5936660a-2598-4dda-bf77-029853558f50' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Flight</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27;</div><input id='attrs-72c86482-6a3b-4fdb-8064-0991f1484518' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-72c86482-6a3b-4fdb-8064-0991f1484518' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5029d22f-09e7-44b5-998a-52fa7c5686a2' class='xr-var-data-in' type='checkbox'><label for='data-5029d22f-09e7-44b5-998a-52fa7c5686a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;F07&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1917a3f-948b-4b28-9d87-75f2cab79b5b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f1917a3f-948b-4b28-9d87-75f2cab79b5b' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'v' ()>\n",
       "array(37243.45071385)\n",
       "Coordinates:\n",
       "    Flight   <U3 'F07'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#total error of still region v before correction\n",
    "np.sum(np.sqrt(F07.sel(x=slice(0,70), y=slice(0, 237)).v**2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;u&#x27; ()&gt;\n",
       "array(8201.3531236)\n",
       "Coordinates:\n",
       "    Flight   &lt;U3 &#x27;F07&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8c4e8a63-dd26-4154-9b9a-ee3d75ddc0bb' class='xr-array-in' type='checkbox' checked><label for='section-8c4e8a63-dd26-4154-9b9a-ee3d75ddc0bb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>8.201e+03</span></div><div class='xr-array-data'><pre>array(8201.3531236)</pre></div></div></li><li class='xr-section-item'><input id='section-246a28ff-abce-47d4-b30e-964552169a6a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-246a28ff-abce-47d4-b30e-964552169a6a' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Flight</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27;</div><input id='attrs-9daacea4-c044-44b2-89b9-98ea4a79ee32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9daacea4-c044-44b2-89b9-98ea4a79ee32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-617c3dd9-3f1a-442c-9784-55089a85caad' class='xr-var-data-in' type='checkbox'><label for='data-617c3dd9-3f1a-442c-9784-55089a85caad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;F07&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a27e7090-af1f-4800-aab0-2f2ccc40184f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a27e7090-af1f-4800-aab0-2f2ccc40184f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'u' ()>\n",
       "array(8201.3531236)\n",
       "Coordinates:\n",
       "    Flight   <U3 'F07'"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#total error of still region u before correction\n",
    "np.sum(np.sqrt(F07.sel(x=slice(0,70), y=slice(100, 237)).u**2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### F07"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "###########################################################################################\n",
    "for i in range(120):\n",
    "    Av = dfx.sel(Flight= 'F07',time= i, x=slice(350,432), y=slice(0, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Bv = dfx.sel(Flight= 'F07', time= i, x=slice(0,25), y=slice(100, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Cv = (Av+Bv)/ 2\n",
    "    dfx.sel(Flight='F07').v[i] = dfx.sel(Flight='F07').v[i] - Cv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;v&#x27; ()&gt;\n",
       "array(2337.85398114)\n",
       "Coordinates:\n",
       "    Flight   &lt;U3 &#x27;F07&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'v'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-73ac6f9d-b0c5-4b09-b70a-ef8bb1d412a2' class='xr-array-in' type='checkbox' checked><label for='section-73ac6f9d-b0c5-4b09-b70a-ef8bb1d412a2' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.338e+03</span></div><div class='xr-array-data'><pre>array(2337.85398114)</pre></div></div></li><li class='xr-section-item'><input id='section-3836197c-6db8-497a-bbb2-0d0b5b2b4862' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3836197c-6db8-497a-bbb2-0d0b5b2b4862' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Flight</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27;</div><input id='attrs-b8091900-31de-47be-acd6-1c90b6804d2a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8091900-31de-47be-acd6-1c90b6804d2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3039413f-4d84-46fc-ac1e-ae1f5d2a7f13' class='xr-var-data-in' type='checkbox'><label for='data-3039413f-4d84-46fc-ac1e-ae1f5d2a7f13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;F07&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ce4019d3-a26f-4418-b95e-279e3afbeb26' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ce4019d3-a26f-4418-b95e-279e3afbeb26' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'v' ()>\n",
       "array(2337.85398114)\n",
       "Coordinates:\n",
       "    Flight   <U3 'F07'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#total error of still region v after correction\n",
    "np.sum(np.sqrt(dfx.sel(Flight='F07',x=slice(380,420), y=slice(50, 237)).v**2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "for i in range(120):\n",
    "    Au = dfx.sel(Flight= 'F07',time= i, x=slice(350,432), y=slice(0, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Bu = dfx.sel(Flight= 'F07', time= i, x=slice(0,25), y=slice(100, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Cu = (Au+Bu)/ 2\n",
    "    dfx.sel(Flight='F07').u[i] = dfx.sel(Flight='F07').u[i] - Cu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;u&#x27; ()&gt;\n",
       "array(1559.35751314)\n",
       "Coordinates:\n",
       "    Flight   &lt;U3 &#x27;F07&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2f5f6f07-7963-4ab7-979f-f5723a61fd4c' class='xr-array-in' type='checkbox' checked><label for='section-2f5f6f07-7963-4ab7-979f-f5723a61fd4c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.559e+03</span></div><div class='xr-array-data'><pre>array(1559.35751314)</pre></div></div></li><li class='xr-section-item'><input id='section-17b31c2f-2420-402f-88ed-6ca7a3a04113' class='xr-section-summary-in' type='checkbox'  checked><label for='section-17b31c2f-2420-402f-88ed-6ca7a3a04113' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Flight</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27;</div><input id='attrs-903d5fee-71f7-4025-84c9-3f641f554147' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-903d5fee-71f7-4025-84c9-3f641f554147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27482cc6-5adf-4583-89f6-73149bce47eb' class='xr-var-data-in' type='checkbox'><label for='data-27482cc6-5adf-4583-89f6-73149bce47eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;F07&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dff56277-10ee-4aa9-8b6f-1186b5cd6e40' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dff56277-10ee-4aa9-8b6f-1186b5cd6e40' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'u' ()>\n",
       "array(1559.35751314)\n",
       "Coordinates:\n",
       "    Flight   <U3 'F07'"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#total error of still region u after correction\n",
    "np.sum(np.sqrt(F07.sel(x=slice(380,420), y=slice(50, 237)).u**2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### F08"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(120):\n",
    "    Av = dfx.sel(Flight= 'F08',time= i, x=slice(350,432), y=slice(0, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Bv = dfx.sel(Flight= 'F08', time= i, x=slice(0,25), y=slice(100, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Cv = (Av+Bv)/ 2\n",
    "    dfx.sel(Flight='F08').v[i] = dfx.sel(Flight='F08').v[i] - Cv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(120):\n",
    "    Au = dfx.sel(Flight= 'F08',time= i, x=slice(350,432), y=slice(0, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Bu = dfx.sel(Flight= 'F08', time= i, x=slice(0,25), y=slice(100, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Cu = (Au+Bu)/ 2\n",
    "    dfx.sel(Flight='F08').u[i] = dfx.sel(Flight='F08').u[i] - Cu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### F09"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(120):\n",
    "    Av = dfx.sel(Flight= 'F09',time= i, x=slice(350,432), y=slice(0, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Bv = dfx.sel(Flight= 'F09', time= i, x=slice(0,25), y=slice(100, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Cv = (Av+Bv)/ 2\n",
    "    dfx.sel(Flight='F09').v[i] = dfx.sel(Flight='F09').v[i] - Cv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(120):\n",
    "    Au = dfx.sel(Flight= 'F09',time= i, x=slice(350,432), y=slice(0, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Bu = dfx.sel(Flight= 'F09', time= i, x=slice(0,25), y=slice(100, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Cu = (Au+Bu)/ 2\n",
    "    dfx.sel(Flight='F09').u[i] = dfx.sel(Flight='F09').u[i] - Cu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### F10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(120):\n",
    "    Av = dfx.sel(Flight= 'F10',time= i, x=slice(350,432), y=slice(0, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Bv = dfx.sel(Flight= 'F10', time= i, x=slice(0,25), y=slice(100, 237)).v.mean(dim= ('x', 'y'))\n",
    "    Cv = (Av+Bv)/ 2\n",
    "    dfx.sel(Flight='F10').v[i] = dfx.sel(Flight='F10').v[i] - Cv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(120):\n",
    "    Au = dfx.sel(Flight= 'F10',time= i, x=slice(350,432), y=slice(0, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Bu = dfx.sel(Flight= 'F10', time= i, x=slice(0,25), y=slice(100, 237)).u.mean(dim= ('x', 'y'))\n",
    "    Cu = (Au+Bu)/ 2\n",
    "    dfx.sel(Flight='F10').u[i] = dfx.sel(Flight='F10').u[i] - Cu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Additional Data Processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add Total Velocity (s) to dataArray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
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       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (Flight: 4, time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 3.637 7.274 10.91 14.55 ... 421.9 425.5 429.2 432.8\n",
       "  * y        (y) float64 3.604 7.207 10.81 14.41 ... 227.0 230.6 234.2 237.8\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "  * Flight   (Flight) &lt;U3 &#x27;F07&#x27; &#x27;F08&#x27; &#x27;F09&#x27; &#x27;F10&#x27;\n",
       "Data variables:\n",
       "    u        (Flight, time, x, y) float64 0.05169 0.06138 ... 0.03728 0.03153\n",
       "    v        (Flight, time, x, y) float64 0.3545 0.3593 ... -0.01625 0.01285\n",
       "    mask     (Flight, time, x, y) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    s        (Flight, time, x, y) float64 0.3583 0.3645 ... 0.04067 0.03405</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-09fad3d2-d802-4c3e-b3c2-77b3045655c7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-09fad3d2-d802-4c3e-b3c2-77b3045655c7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Flight</span>: 4</li><li><span class='xr-has-index'>time</span>: 120</li><li><span class='xr-has-index'>x</span>: 119</li><li><span class='xr-has-index'>y</span>: 66</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0456aaf2-6db1-4c1e-a505-fa7868c37265' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0456aaf2-6db1-4c1e-a505-fa7868c37265' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.637 7.274 10.91 ... 429.2 432.8</div><input id='attrs-b02cec85-ecf6-41cd-846b-2821cf9d31f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b02cec85-ecf6-41cd-846b-2821cf9d31f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f406484a-970a-4a5e-8934-eaa82f846cc1' class='xr-var-data-in' type='checkbox'><label for='data-f406484a-970a-4a5e-8934-eaa82f846cc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  3.636875,   7.273749,  10.910624,  14.547499,  18.184374,  21.821248,\n",
       "        25.458123,  29.094998,  32.731872,  36.368747,  40.005622,  43.642496,\n",
       "        47.279371,  50.916246,  54.553121,  58.189995,  61.82687 ,  65.463745,\n",
       "        69.100619,  72.737494,  76.374369,  80.011244,  83.648118,  87.284993,\n",
       "        90.921868,  94.558742,  98.195617, 101.832492, 105.469366, 109.106241,\n",
       "       112.743116, 116.379991, 120.016865, 123.65374 , 127.290615, 130.927489,\n",
       "       134.564364, 138.201239, 141.838113, 145.474988, 149.111863, 152.748738,\n",
       "       156.385612, 160.022487, 163.659362, 167.296236, 170.933111, 174.569986,\n",
       "       178.206861, 181.843735, 185.48061 , 189.117485, 192.754359, 196.391234,\n",
       "       200.028109, 203.664983, 207.301858, 210.938733, 214.575608, 218.212482,\n",
       "       221.849357, 225.486232, 229.123106, 232.759981, 236.396856, 240.033731,\n",
       "       243.670605, 247.30748 , 250.944355, 254.581229, 258.218104, 261.854979,\n",
       "       265.491853, 269.128728, 272.765603, 276.402478, 280.039352, 283.676227,\n",
       "       287.313102, 290.949976, 294.586851, 298.223726, 301.8606  , 305.497475,\n",
       "       309.13435 , 312.771225, 316.408099, 320.044974, 323.681849, 327.318723,\n",
       "       330.955598, 334.592473, 338.229348, 341.866222, 345.503097, 349.139972,\n",
       "       352.776846, 356.413721, 360.050596, 363.68747 , 367.324345, 370.96122 ,\n",
       "       374.598095, 378.234969, 381.871844, 385.508719, 389.145593, 392.782468,\n",
       "       396.419343, 400.056218, 403.693092, 407.329967, 410.966842, 414.603716,\n",
       "       418.240591, 421.877466, 425.51434 , 429.151215, 432.78809 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.604 7.207 10.81 ... 234.2 237.8</div><input id='attrs-f7c4a634-9b0a-4f1c-8b0a-88257c8ca24e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7c4a634-9b0a-4f1c-8b0a-88257c8ca24e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-875427b9-2385-4c4d-9fa8-d72280fa43d1' class='xr-var-data-in' type='checkbox'><label for='data-875427b9-2385-4c4d-9fa8-d72280fa43d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  3.603509,   7.207018,  10.810527,  14.414036,  18.017544,  21.621053,\n",
       "        25.224562,  28.828071,  32.43158 ,  36.035089,  39.638598,  43.242107,\n",
       "        46.845615,  50.449124,  54.052633,  57.656142,  61.259651,  64.86316 ,\n",
       "        68.466669,  72.070178,  75.673687,  79.277195,  82.880704,  86.484213,\n",
       "        90.087722,  93.691231,  97.29474 , 100.898249, 104.501758, 108.105266,\n",
       "       111.708775, 115.312284, 118.915793, 122.519302, 126.122811, 129.72632 ,\n",
       "       133.329829, 136.933338, 140.536846, 144.140355, 147.743864, 151.347373,\n",
       "       154.950882, 158.554391, 162.1579  , 165.761409, 169.364917, 172.968426,\n",
       "       176.571935, 180.175444, 183.778953, 187.382462, 190.985971, 194.58948 ,\n",
       "       198.192988, 201.796497, 205.400006, 209.003515, 212.607024, 216.210533,\n",
       "       219.814042, 223.417551, 227.02106 , 230.624568, 234.228077, 237.831586])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 115 116 117 118 119</div><input id='attrs-fe9d4680-28fa-4e99-9be4-7934142c1c29' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe9d4680-28fa-4e99-9be4-7934142c1c29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65594329-2089-4570-a680-4f56f6716116' class='xr-var-data-in' type='checkbox'><label for='data-65594329-2089-4570-a680-4f56f6716116' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Flight</span></div><div class='xr-var-dims'>(Flight)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;F07&#x27; &#x27;F08&#x27; &#x27;F09&#x27; &#x27;F10&#x27;</div><input id='attrs-af3b9606-71c0-4022-80d3-0e1dded14f78' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af3b9606-71c0-4022-80d3-0e1dded14f78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7fd8364-3bdc-488b-b049-7b3028c7ef8a' class='xr-var-data-in' type='checkbox'><label for='data-e7fd8364-3bdc-488b-b049-7b3028c7ef8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;F07&#x27;, &#x27;F08&#x27;, &#x27;F09&#x27;, &#x27;F10&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3ee3838a-21fb-4d29-afc0-bfa8d151c8ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3ee3838a-21fb-4d29-afc0-bfa8d151c8ef' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(Flight, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.05169 0.06138 ... 0.03728 0.03153</div><input id='attrs-304a37dd-348e-4f63-b69a-67e890a01dcc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-304a37dd-348e-4f63-b69a-67e890a01dcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc7749c9-074c-44f2-90c9-a856361dee5f' class='xr-var-data-in' type='checkbox'><label for='data-fc7749c9-074c-44f2-90c9-a856361dee5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[ 5.16852733e-02,  6.13798174e-02,  6.74715825e-02, ...,\n",
       "          -2.19159786e-02, -1.95520100e-02, -1.68357192e-02],\n",
       "         [ 4.42751410e-02,  5.44129293e-02,  5.90613098e-02, ...,\n",
       "          -1.62447271e-02, -1.03916319e-02, -1.94610882e-02],\n",
       "         [ 3.50579367e-02,  4.61390393e-02,  5.42992769e-02, ...,\n",
       "          -2.09385685e-02, -1.08462412e-02, -3.45313877e-02],\n",
       "         ...,\n",
       "         [ 3.46260578e-02,  4.47297504e-02,  4.33659224e-02, ...,\n",
       "          -4.67491944e-03,  8.16779436e-03,  2.98524791e-03],\n",
       "         [ 2.37608947e-02,  2.23061448e-02,  1.92034360e-02, ...,\n",
       "          -2.60644695e-03, -1.58128482e-02, -3.80848959e-06],\n",
       "         [ 3.90583182e-03,  1.93852798e-02,  1.61461882e-02, ...,\n",
       "           7.91775923e-03, -1.27669657e-02, -2.27115449e-02]],\n",
       "\n",
       "        [[-1.74761384e-01, -1.81023627e-01, -1.75727428e-01, ...,\n",
       "           4.91791764e-02,  6.11694977e-02,  6.85568995e-02],\n",
       "         [-1.83751283e-01, -1.61816383e-01, -1.60748051e-01, ...,\n",
       "           5.12931098e-02,  6.04193923e-02,  6.48177377e-02],\n",
       "         [-1.96230310e-01, -1.75352376e-01, -1.63430246e-01, ...,\n",
       "           5.34184085e-02,  5.71121094e-02,  5.88396249e-02],\n",
       "...\n",
       "         [ 6.26549222e-02,  6.92126619e-02,  1.46481761e-02, ...,\n",
       "           5.09146360e-02, -2.42322876e-02,  8.39729769e-03],\n",
       "         [ 1.74099278e-02,  1.64893439e-02,  6.87435641e-03, ...,\n",
       "           4.71641090e-02, -2.66107446e-03,  4.77178822e-03],\n",
       "         [ 7.62022805e-02,  2.24870639e-03,  7.37442668e-03, ...,\n",
       "           2.68885325e-02,  2.49109819e-02,  3.80378265e-02]],\n",
       "\n",
       "        [[-3.78891039e-02, -2.74785501e-02, -1.19877369e-02, ...,\n",
       "           2.67108830e-02,  5.60331854e-02,  5.41465566e-02],\n",
       "         [-3.54001178e-02, -1.90455468e-02,  2.10515263e-03, ...,\n",
       "           1.59707374e-02,  3.99400148e-02,  4.70546509e-02],\n",
       "         [-2.80695422e-02, -2.03411834e-02, -6.40740723e-03, ...,\n",
       "           1.70617998e-02,  2.79610587e-02,  4.77706606e-02],\n",
       "         ...,\n",
       "         [-2.22164470e-02, -2.47281636e-02, -2.41144409e-02, ...,\n",
       "           4.23949052e-02,  6.11020795e-02,  6.13862103e-02],\n",
       "         [-1.83295371e-02, -2.20118728e-02, -2.56373822e-02, ...,\n",
       "           2.02667957e-02,  3.89626047e-02,  4.77820259e-02],\n",
       "         [-1.05102565e-02, -6.68017283e-03, -2.83423078e-02, ...,\n",
       "           3.05296015e-02,  3.72805502e-02,  3.15297420e-02]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(Flight, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3545 0.3593 ... -0.01625 0.01285</div><input id='attrs-5a20dd4d-2e19-40a2-9d0c-d24d50070682' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5a20dd4d-2e19-40a2-9d0c-d24d50070682' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a46baef-94f9-4f8d-9fb4-f7317c9f3e38' class='xr-var-data-in' type='checkbox'><label for='data-3a46baef-94f9-4f8d-9fb4-f7317c9f3e38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[ 3.54511084e-01,  3.59263211e-01,  3.66053573e-01, ...,\n",
       "          -1.67742017e-02, -1.59746732e-02, -2.01187084e-02],\n",
       "         [ 3.50513441e-01,  3.57686676e-01,  3.64206775e-01, ...,\n",
       "          -2.03439277e-02, -1.96119649e-02, -1.41954407e-02],\n",
       "         [ 3.56380404e-01,  3.64386950e-01,  3.72100711e-01, ...,\n",
       "          -2.07268005e-02, -1.99385329e-02, -1.50850569e-02],\n",
       "         ...,\n",
       "         [-3.93670131e-03, -3.84661359e-03, -1.22923375e-02, ...,\n",
       "           9.06971356e-03,  1.37092312e-02,  2.37765342e-02],\n",
       "         [ 2.32472688e-02,  5.66890205e-03, -3.38491401e-03, ...,\n",
       "           1.29997904e-02,  1.14795601e-02,  9.83545920e-03],\n",
       "         [ 1.84017387e-03, -1.18902579e-03, -6.14385050e-03, ...,\n",
       "           9.65528375e-03,  7.24543719e-03,  9.47242528e-05]],\n",
       "\n",
       "        [[ 4.87982639e-01,  5.04930392e-01,  4.94874350e-01, ...,\n",
       "           1.83666314e-01,  1.64736631e-01,  1.66391993e-01],\n",
       "         [ 4.85392617e-01,  4.87892551e-01,  4.81259843e-01, ...,\n",
       "           1.77866917e-01,  1.59781807e-01,  1.59883155e-01],\n",
       "         [ 4.92025325e-01,  4.84030040e-01,  4.73455994e-01, ...,\n",
       "           1.67281609e-01,  1.54759416e-01,  1.56741346e-01],\n",
       "...\n",
       "         [-4.78207631e-02, -4.67960153e-02,  1.51843375e-02, ...,\n",
       "           1.82811029e-02, -2.61096221e-02, -1.01753563e-02],\n",
       "         [ 2.80556207e-02,  2.55894694e-02,  1.70649187e-02, ...,\n",
       "           2.79880550e-02,  4.32472977e-04, -9.30826197e-03],\n",
       "         [-5.14467940e-02,  1.84612784e-02,  3.03641186e-02, ...,\n",
       "           7.86471005e-03,  4.82424943e-03, -3.70890633e-02]],\n",
       "\n",
       "        [[-1.80155406e-02, -1.76326678e-02, -2.68553983e-02, ...,\n",
       "           3.18592745e-02,  2.20509738e-02,  1.46750415e-02],\n",
       "         [-1.74862753e-02, -1.95470319e-02, -3.21367910e-02, ...,\n",
       "           3.04516538e-02,  2.89201626e-02,  2.40441646e-02],\n",
       "         [-1.30944988e-02, -1.93105516e-02, -3.12246529e-02, ...,\n",
       "           3.27263688e-02,  4.11495708e-02,  3.14313578e-02],\n",
       "         ...,\n",
       "         [-2.19388443e-03, -1.68669222e-02, -3.26210126e-02, ...,\n",
       "          -2.20514540e-03,  6.10095915e-04, -5.17804023e-03],\n",
       "         [-1.33127792e-04, -1.76439288e-02, -2.96593787e-02, ...,\n",
       "          -4.57850809e-02, -1.17431830e-02,  2.36680650e-03],\n",
       "         [-1.10450031e-02, -2.27338851e-02, -3.06728656e-02, ...,\n",
       "          -2.08307819e-02, -1.62475691e-02,  1.28507651e-02]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(Flight, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-855a12f1-0be3-472f-a809-c4b959fdf37c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-855a12f1-0be3-472f-a809-c4b959fdf37c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e747ea1a-b092-495e-8503-f300950e3a4e' class='xr-var-data-in' type='checkbox'><label for='data-e747ea1a-b092-495e-8503-f300950e3a4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         ...,\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.],\n",
       "         [0., 0., 0., ..., 0., 0., 0.]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>s</span></div><div class='xr-var-dims'>(Flight, time, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3583 0.3645 ... 0.04067 0.03405</div><input id='attrs-4b9f518f-6168-4403-aced-07d2739a7b0b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b9f518f-6168-4403-aced-07d2739a7b0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-080b8c61-5d25-4fee-a1bb-45d35818019e' class='xr-var-data-in' type='checkbox'><label for='data-080b8c61-5d25-4fee-a1bb-45d35818019e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[0.35825895, 0.36446884, 0.37221987, ..., 0.02759862,\n",
       "          0.02524819, 0.02623364],\n",
       "         [0.35329868, 0.36180178, 0.36896451, ..., 0.02603395,\n",
       "          0.02219494, 0.02408826],\n",
       "         [0.35810062, 0.36729642, 0.37604169, ..., 0.02946225,\n",
       "          0.02269771, 0.03768256],\n",
       "         ...,\n",
       "         [0.03484912, 0.04489484, 0.04507444, ..., 0.01020366,\n",
       "          0.01595794, 0.02396321],\n",
       "         [0.03324178, 0.02301522, 0.01949948, ..., 0.01325851,\n",
       "          0.01954038, 0.00983546],\n",
       "         [0.00431761, 0.01942171, 0.0172756 , ..., 0.01248661,\n",
       "          0.01467964, 0.02271174]],\n",
       "\n",
       "        [[0.51833252, 0.53639934, 0.52514831, ..., 0.19013655,\n",
       "          0.17572668, 0.17996206],\n",
       "         [0.51900918, 0.51402693, 0.50739627, ..., 0.18511516,\n",
       "          0.17082368, 0.17252235],\n",
       "         [0.52971243, 0.51481408, 0.50086927, ..., 0.17560371,\n",
       "          0.16496142, 0.16742148],\n",
       "...\n",
       "         [0.07881919, 0.08354795, 0.02109818, ..., 0.05409712,\n",
       "          0.03562185, 0.0131929 ],\n",
       "         [0.03301853, 0.03044207, 0.01839751, ..., 0.05484327,\n",
       "          0.00269599, 0.0104601 ],\n",
       "         [0.09194324, 0.01859773, 0.03124679, ..., 0.02801512,\n",
       "          0.02537381, 0.05312697]],\n",
       "\n",
       "        [[0.04195407, 0.03264937, 0.02940949, ..., 0.04157505,\n",
       "          0.06021597, 0.05609997],\n",
       "         [0.03948339, 0.02729138, 0.03220567, ..., 0.03438557,\n",
       "          0.04931106, 0.05284186],\n",
       "         [0.03097362, 0.02804748, 0.03187529, ..., 0.03690691,\n",
       "          0.04975046, 0.05718362],\n",
       "         ...,\n",
       "         [0.02232451, 0.02993284, 0.04056645, ..., 0.04245222,\n",
       "          0.06110513, 0.06160421],\n",
       "         [0.01833002, 0.02821047, 0.03920401, ..., 0.05007012,\n",
       "          0.04069382, 0.04784061],\n",
       "         [0.01524656, 0.02369503, 0.04176256, ..., 0.03695914,\n",
       "          0.04066722, 0.03404801]]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7285e194-21b1-45ff-9250-bbb38e7fafe4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7285e194-21b1-45ff-9250-bbb38e7fafe4' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (Flight: 4, time: 120, x: 119, y: 66)\n",
       "Coordinates:\n",
       "  * x        (x) float64 3.637 7.274 10.91 14.55 ... 421.9 425.5 429.2 432.8\n",
       "  * y        (y) float64 3.604 7.207 10.81 14.41 ... 227.0 230.6 234.2 237.8\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 ... 112 113 114 115 116 117 118 119\n",
       "  * Flight   (Flight) <U3 'F07' 'F08' 'F09' 'F10'\n",
       "Data variables:\n",
       "    u        (Flight, time, x, y) float64 0.05169 0.06138 ... 0.03728 0.03153\n",
       "    v        (Flight, time, x, y) float64 0.3545 0.3593 ... -0.01625 0.01285\n",
       "    mask     (Flight, time, x, y) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    s        (Flight, time, x, y) float64 0.3583 0.3645 ... 0.04067 0.03405"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = np.sqrt(dfx.u**2+dfx.v**2)\n",
    "dfx['s']= s\n",
    "dfx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;u&#x27; (quantile: 2)&gt;\n",
       "array([0.4484614 , 0.77807099])\n",
       "Coordinates:\n",
       "  * quantile  (quantile) float64 0.99 1.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>quantile</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-80dbe2e0-9b0e-408c-a100-35f9fdbcad36' class='xr-array-in' type='checkbox' checked><label for='section-80dbe2e0-9b0e-408c-a100-35f9fdbcad36' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.4485 0.7781</span></div><div class='xr-array-data'><pre>array([0.4484614 , 0.77807099])</pre></div></div></li><li class='xr-section-item'><input id='section-a2de8910-333f-4427-9037-96478e945bcc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a2de8910-333f-4427-9037-96478e945bcc' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>quantile</span></div><div class='xr-var-dims'>(quantile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.99 1.0</div><input id='attrs-6065651c-83dc-457a-b541-fe1abd2e6759' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6065651c-83dc-457a-b541-fe1abd2e6759' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32139223-3df9-49ec-b3b5-4427caa87ffb' class='xr-var-data-in' type='checkbox'><label for='data-32139223-3df9-49ec-b3b5-4427caa87ffb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.99, 1.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3d7913d1-a5e9-43f6-abb0-0a159674f256' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3d7913d1-a5e9-43f6-abb0-0a159674f256' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'u' (quantile: 2)>\n",
       "array([0.4484614 , 0.77807099])\n",
       "Coordinates:\n",
       "  * quantile  (quantile) float64 0.99 1.0"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfx.u.quantile([.99,1.00])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Correct for Spikes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfx = dfx.where(dfx.v<5 )\n",
    "dfx = dfx.where(dfx.u<3 , dfx.u > -3)\n",
    "dfx = dfx.where(dfx.s<5 )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drop Mask (no information)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfx = dfx.drop('mask')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save the Xarray with all the velocity fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfx.to_netcdf('0726_Site4_Velocity_Fields.nc') # Saves on your local disk "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load in the Xarray you Created"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Pull from Google Drive folder (example below) by adding your own unique ID or just load Xarray from you local drive\n",
    "\n",
    "gdfidXR = '1Hly2lA3gg9HvbmMxH7wt4aTDTY-BzFg0' \n",
    "gdfsXR = gdrivefs.GoogleDriveFileSystem(root_file_id=gdfidXR, token ='cache')\n",
    "filesXr = gdfsXR.ls('')\n",
    "\n",
    "dfx = xr.open_dataset(gdfsXR.open(filesXr[0]))  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Select By Flights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "F07 = dfx.sel(Flight= 'F07')\n",
    "F08 = dfx.sel(Flight= 'F08')\n",
    "F09 = dfx.sel(Flight= 'F09')\n",
    "F10 = dfx.sel(Flight= 'F10')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Metadata \n",
    "#### Site 6 Location\n",
    "Latitude: 19.476251  \n",
    "Longitude: -154.899143\n",
    "\n",
    "\n",
    "#### Date 07/26/2018 \n",
    "Start and end times HST\n",
    "\n",
    "Flight 07: 12:53\t13:08\n",
    "\n",
    "Flight 08: 13:19\t13:35\n",
    "\n",
    "Flight 09: 13:48\t14:05\n",
    "\n",
    "Flight 10: 14:25\t14:40\n",
    "\n",
    "- Flights trimed to 2:00 min in pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "from matplotlib import ticker, cm\n",
    "\n",
    "F08.v.mean(dim='time').transpose().plot.contourf(levels=300, vmin=0, vmax=3, cmap=cm.nipy_spectral, yincrease=False)"
   ]
  }
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