{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f741bd0b-0743-4f7f-9bc5-9c4d54109fdc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "from matplotlib.animation import FuncAnimation\n",
    "import cartopy\n",
    "import xarray as xr\n",
    "import cmocean.cm as cmo\n",
    "import cartopy.crs as ccrs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8155155-7c40-4192-982d-f381e408ab72",
   "metadata": {},
   "source": [
    "### Load the ERA5 data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6c0e600a-175e-419b-95f3-1556f0f0c5f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = '/Volumes/GoogleDrive/My Drive/Projects/duplessis-2021-turbulent-heatflux/data/'\n",
    "files = ['era5_airT_012019',\n",
    "         'era5_airT_022019'\n",
    "        ]\n",
    "\n",
    "ds = xr.open_mfdataset(path+'era5_airT*.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "57d73473-7309-4361-89b5-1a9df16e9aa9",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (latitude: 361, longitude: 1440, time: 1416)\n",
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       "  * longitude  (longitude) float32 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n",
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       "Data variables:\n",
       "    t2m        (time, latitude, longitude) float32 dask.array&lt;chunksize=(744, 361, 1440), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2021-10-20 19:09:56 GMT by grib_to_netcdf-2.23.0: /opt/ecmw...</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-c521e02b-248d-4b25-bbf6-7d733be2f1d1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c521e02b-248d-4b25-bbf6-7d733be2f1d1' 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'>latitude</span>: 361</li><li><span class='xr-has-index'>longitude</span>: 1440</li><li><span class='xr-has-index'>time</span>: 1416</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a2c1e160-713c-42ae-bd0f-97da44c456f9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a2c1e160-713c-42ae-bd0f-97da44c456f9' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 359.2 359.5 359.8</div><input id='attrs-b2945177-7550-4f00-8b29-ea46891be870' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2945177-7550-4f00-8b29-ea46891be870' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-494402a6-859c-441a-8510-dcf0f1eed64e' class='xr-var-data-in' type='checkbox'><label for='data-494402a6-859c-441a-8510-dcf0f1eed64e' 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'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-01, 5.0000e-01, ..., 3.5925e+02, 3.5950e+02,\n",
       "       3.5975e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -0.25 -0.5 ... -89.75 -90.0</div><input id='attrs-d7851dd4-ee81-49b7-9566-69013914fd1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7851dd4-ee81-49b7-9566-69013914fd1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3d787be-10dc-498d-a6da-14d09a6cb3b7' class='xr-var-data-in' type='checkbox'><label for='data-c3d787be-10dc-498d-a6da-14d09a6cb3b7' 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'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,  -0.25,  -0.5 , ..., -89.5 , -89.75, -90.  ], dtype=float32)</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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-01-01 ... 2019-02-28T23:00:00</div><input id='attrs-3f3effcd-7a76-43b1-a105-cb1d6d18f315' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f3effcd-7a76-43b1-a105-cb1d6d18f315' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57544121-c7b8-427e-b9ca-b00d50521447' class='xr-var-data-in' type='checkbox'><label for='data-57544121-c7b8-427e-b9ca-b00d50521447' 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'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2019-01-01T02:00:00.000000000&#x27;, ..., &#x27;2019-02-28T21:00:00.000000000&#x27;,\n",
       "       &#x27;2019-02-28T22:00:00.000000000&#x27;, &#x27;2019-02-28T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9984ad7c-fdcf-4862-8f8c-0da7941d20df' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9984ad7c-fdcf-4862-8f8c-0da7941d20df' class='xr-section-summary' >Data variables: <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>t2m</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(744, 361, 1440), meta=np.ndarray&gt;</div><input id='attrs-fbfb45b9-9aa7-4437-84ae-79c3fbdad9aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fbfb45b9-9aa7-4437-84ae-79c3fbdad9aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6517b4b5-0d8d-4c66-ac63-44bcc58aff9c' class='xr-var-data-in' type='checkbox'><label for='data-6517b4b5-0d8d-4c66-ac63-44bcc58aff9c' 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'><dt><span>units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd></dl></div><div class='xr-var-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 2.74 GiB </td> <td> 1.44 GiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (1416, 361, 1440) </td> <td> (744, 361, 1440) </td></tr>\n",
       "    <tr><th> Count </th><td> 6 Tasks </td><td> 2 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"249\" height=\"162\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"79\" y2=\"69\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
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       "  <line x1=\"79\" y1=\"69\" x2=\"79\" y2=\"112\" style=\"stroke-width:2\" />\n",
       "\n",
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       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"139.411765\" y=\"132.320928\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"219.411765\" y=\"90.866346\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,219.411765,90.866346)\">361</text>\n",
       "  <text x=\"34.705882\" y=\"97.615045\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,34.705882,97.615045)\">1416</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a8ee5480-63ad-41b5-b3a4-7abe9c00f75e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a8ee5480-63ad-41b5-b3a4-7abe9c00f75e' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2021-10-20 19:09:56 GMT by grib_to_netcdf-2.23.0: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data9/adaptor.mars.internal-1634756989.6694415-22604-7-38696145-3e4c-415c-9e78-62776da5dc00.nc /cache/tmp/38696145-3e4c-415c-9e78-62776da5dc00-adaptor.mars.internal-1634756934.7028122-22604-1-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (latitude: 361, longitude: 1440, time: 1416)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 0.0 -0.25 -0.5 -0.75 ... -89.5 -89.75 -90.0\n",
       "  * time       (time) datetime64[ns] 2019-01-01 ... 2019-02-28T23:00:00\n",
       "Data variables:\n",
       "    t2m        (time, latitude, longitude) float32 dask.array<chunksize=(744, 361, 1440), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2021-10-20 19:09:56 GMT by grib_to_netcdf-2.23.0: /opt/ecmw..."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cb2e0c5-3cee-46e2-aab1-cb63921f2e35",
   "metadata": {},
   "source": [
    "### Test the intial plot\n",
    "\n",
    "This is what the plot is going to look like so good to refine this here and then run the loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a508ca3e-687e-47f1-b9d6-b5b2551555e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "variable = (ds.t2m-273.15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2664c024-c211-474b-add7-6139e3c5f357",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.feature_artist.FeatureArtist at 0x7feed476c2b0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup the initial plot\n",
    "fig = figure(figsize=(8, 8))\n",
    "ax  = fig.add_subplot(projection=ccrs.NearsidePerspective(satellite_height=2000000.0, \n",
    "                                                          central_longitude=0, \n",
    "                                                          central_latitude=-50\n",
    "                                                         )\n",
    "                     )\n",
    "\n",
    "variable.sel(time=variable.time[0].values).plot(ax=ax, \n",
    "                                                vmin=0, vmax=20, \n",
    "                                                transform=ccrs.PlateCarree(),\n",
    "                                                cmap=cmo.thermal,\n",
    "                                                cbar_kwargs={'orientation': 'horizontal',\n",
    "                                                             'aspect': 30,\n",
    "                                                             'shrink': 0.7,\n",
    "                                                             'pad': 0.05,\n",
    "                                                             'label': 'Air temperature ($^{\\circ}$C)'\n",
    "                                                            },\n",
    "                                               )\n",
    "\n",
    "ax.coastlines(resolution='110m')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b570c15d-7aa8-401a-b0d0-b5c6ab8d2ae6",
   "metadata": {},
   "source": [
    "### Run full animation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9965a9e5-63a7-40a7-a7a6-a8039e602976",
   "metadata": {},
   "outputs": [],
   "source": [
    "save_animation=True\n",
    "\n",
    "# Setup the initial plot\n",
    "fig = figure(figsize=(8, 8))\n",
    "ax  = fig.add_subplot(projection=ccrs.NearsidePerspective(satellite_height=2000000.0, \n",
    "                                                          central_longitude=0, \n",
    "                                                          central_latitude=-55\n",
    "                                                         )\n",
    "                     )\n",
    "\n",
    "ax.coastlines(resolution='110m')\n",
    "\n",
    "# Select the variable & region of interest\n",
    "# variable = (ds.t2m-273.15).isel(time=np.arange(150))\n",
    "variable = (ds.t2m-273.15)\n",
    "\n",
    "# Set up levels etc in this call\n",
    "image = variable.sel(time=variable.time[0].values).plot(ax=ax, \n",
    "                                                vmin=-5, vmax=20, \n",
    "                                                transform=ccrs.PlateCarree(),\n",
    "                                                cmap=cmo.thermal,\n",
    "                                                cbar_kwargs={'orientation': 'horizontal',\n",
    "                                                             'aspect': 30,\n",
    "                                                             'shrink': 0.7,\n",
    "                                                             'pad': 0.05,\n",
    "                                                             'label': 'Air temperature ($^{\\circ}$C)'\n",
    "                                                            },\n",
    "                                               )\n",
    "\n",
    "ax.scatter(0, -54, s=100, marker='*', c='k', transform=ccrs.PlateCarree())\n",
    "\n",
    "def update(t):\n",
    "    # Update the plot for a specific time\n",
    "    print(t)\n",
    "    ax.set_title(\"time = %s\"%t)\n",
    "    image.set_array(variable.sel(time=t))\n",
    "    return image,\n",
    "\n",
    "# Run the animation, applying `update()` for each of the times in the variable\n",
    "anim = FuncAnimation(fig, update, frames=variable.time.values, repeat=True)\n",
    "\n",
    "# Save to file or display on screen\n",
    "if save_animation:\n",
    "    anim.save('t2m.mp4', fps=25, \n",
    "              extra_args=['-vcodec', 'libx264'],\n",
    "              dpi=200,\n",
    "             ) "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}