diff --git a/notebooks/SWOT-EA-2021/Colocate_satellite_insitu_ocean.ipynb b/notebooks/SWOT-EA-2021/Colocate_satellite_insitu_ocean.ipynb index 0995418e..9282fd85 100644 --- a/notebooks/SWOT-EA-2021/Colocate_satellite_insitu_ocean.ipynb +++ b/notebooks/SWOT-EA-2021/Colocate_satellite_insitu_ocean.ipynb @@ -2,6 +2,7 @@ "cells": [ { "cell_type": "markdown", + "id": "43e51b9e", "metadata": {}, "source": [ "## Use Case: Co-locate satellite and in-situ data for cross-validation\n", @@ -33,12 +34,12 @@ "\n", "*Note: in order to currently access PO.DAAC Cloud Pathfinder datasets such as MODIS SST L2 from the Earthdata Cloud, your Earthdata login username needs to be added to an restrcited early access list (during the transition period of migrating PO.DAAC data to the Earthdata Cloud). Please contact podaac@podaac.jpl.nasa.gov to make that request.*\n", "\n", - "\n", "" ] }, { "cell_type": "markdown", + "id": "d31e5680", "metadata": {}, "source": [ "---------------\n", @@ -53,6 +54,7 @@ { "cell_type": "code", "execution_count": 1, + "id": "aafd14ed", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:17.732378Z", @@ -61,42 +63,39 @@ }, "outputs": [], "source": [ - "from netrc import netrc\n", - "from urllib import request\n", - "from platform import system\n", - "from getpass import getpass\n", + "from tqdm import tqdm\n", "from datetime import datetime\n", - "from http.cookiejar import CookieJar\n", - "from os.path import join, isfile, basename, abspath, expanduser\n", "from folium.plugins import MarkerCluster\n", - "import folium\n", - "import matplotlib\n", - "import matplotlib.pyplot as plt\n", "import matplotlib.patches as mpatches\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib\n", "import cartopy.crs as ccrs\n", "import xarray as xr\n", "import pandas as pd\n", "import numpy as np\n", "import requests\n", + "import warnings\n", + "import os.path\n", + "import folium\n", "import json\n", "import time\n", + "tqdm.pandas()\n", "\n", - "matplotlib.rc('font', **{'family' : 'sans-serif', 'weight': 'normal', 'size': 16})\n", + "matplotlib.rc('font', family=\"sans-serif\", weight=\"normal\", size=16)\n", "\n", "!mkdir -p resources/" ] }, { "cell_type": "markdown", + "id": "96f96e82", "metadata": {}, "source": [ "### Earthdata Login\n", "\n", "An Earthdata Login account is required to access data, as well as discover restricted data, from the NASA Earthdata system. Please visit https://urs.earthdata.nasa.gov to register and manage your Earthdata Login account. This account is free to create and only takes a moment to set up.\n", "\n", - "The `setup_earthdata_login_auth` function will allow Python scripts to log into any Earthdata Login application programmatically. To avoid being prompted for\n", - "credentials every time you run and also allow clients such as curl to log in, you can add the following\n", - "to a `.netrc` (`_netrc` on Windows) file in your home directory:\n", + "**User note:** You must set up a local netrc file to run the notebook to completion. Write a file like this into your home directory:\n", "\n", "```\n", "machine urs.earthdata.nasa.gov\n", @@ -110,61 +109,9 @@ "`$ chmod 0600 ~/.netrc` " ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2021-03-15T21:08:26.075640Z", - "start_time": "2021-03-15T21:08:17.734562Z" - } - }, - "outputs": [], - "source": [ - "TOKEN_DATA = (\"\"\n", - " \"%s\"\n", - " \"%s\"\n", - " \"PODAAC CMR Client\"\n", - " \"%s\"\n", - " \"\")\n", - "\n", - "\n", - "def setup_cmr_token_auth(endpoint: str='cmr.earthdata.nasa.gov'):\n", - " ip = requests.get(\"https://ipinfo.io/ip\").text.strip()\n", - " return requests.post(\n", - " url=\"https://%s/legacy-services/rest/tokens\" % endpoint,\n", - " data=TOKEN_DATA % (input(\"Username: \"), getpass(\"Password: \"), ip),\n", - " headers={'Content-Type': 'application/xml', 'Accept': 'application/json'}\n", - " ).json()['token']['id']\n", - "\n", - "\n", - "def setup_earthdata_login_auth(endpoint: str='urs.earthdata.nasa.gov'):\n", - " netrc_name = \"_netrc\" if system()==\"Windows\" else \".netrc\"\n", - " try:\n", - " username, _, password = netrc(file=join(expanduser('~'), netrc_name)).authenticators(endpoint)\n", - " except (FileNotFoundError, TypeError):\n", - " print('Please provide your Earthdata Login credentials for access.')\n", - " print('Your info will only be passed to %s and will not be exposed in Jupyter.' % (endpoint))\n", - " username = input('Username: ')\n", - " password = getpass('Password: ')\n", - " manager = request.HTTPPasswordMgrWithDefaultRealm()\n", - " manager.add_password(None, endpoint, username, password)\n", - " auth = request.HTTPBasicAuthHandler(manager)\n", - " jar = CookieJar()\n", - " processor = request.HTTPCookieProcessor(jar)\n", - " opener = request.build_opener(auth, processor)\n", - " request.install_opener(opener)\n", - "\n", - "\n", - "# Get your authentication token for searching restricted records in the CMR:\n", - "_token = setup_cmr_token_auth(endpoint=\"cmr.earthdata.nasa.gov\")\n", - "\n", - "# Start authenticated session with URS to allow restricted data downloads:\n", - "setup_earthdata_login_auth(endpoint=\"urs.earthdata.nasa.gov\")" - ] - }, { "cell_type": "markdown", + "id": "035b8bcf", "metadata": {}, "source": [ "### Study region and period\n", @@ -174,7 +121,8 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, + "id": "434bbc73", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:28.015518Z", @@ -183,27 +131,26 @@ }, "outputs": [], "source": [ - "# The timeframe of interest (Argovis API limit == 3 months):\n", - "start_date = \"2019-01-01\"\n", - "end_date = \"2019-01-31\"\n", - "\n", - "# The area/region of interest by latitude/longitude:\n", - "aoi_minlon = -26.0\n", - "aoi_minlat = 30.0\n", - "aoi_maxlon = -12.0\n", - "aoi_maxlat = 40.0" + "start_date = \"2019-01-01\"\n", + "end_date = \"2019-01-31\"\n", + "aoi_lon_min = -26.0\n", + "aoi_lat_min = 30.0\n", + "aoi_lon_max = -12.0\n", + "aoi_lat_max = 40.0" ] }, { "cell_type": "markdown", + "id": "e367f584", "metadata": {}, "source": [ - "Plot the spatial extent of our study area with a blue polygon:" + "Plot the spatial extent of our study area with a white rectangle bounding box:" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, + "id": "d0a17a6c", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:28.917055Z", @@ -213,7 +160,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -226,21 +173,18 @@ ], "source": [ "ax = plt.subplot(projection=ccrs.PlateCarree())\n", - "\n", "ax.figure.set_figheight(9)\n", "ax.figure.set_figwidth(9)\n", - "\n", - "ax.add_patch(mpatches.Rectangle(xy=[aoi_minlon, aoi_minlat], \n", - " width=aoi_maxlon-aoi_minlon, \n", - " height=aoi_maxlat-aoi_minlat,\n", + "ax.add_patch(mpatches.Rectangle(xy=[aoi_lon_min, aoi_lat_min], \n", + " width=aoi_lon_max-aoi_lon_min, \n", + " height=aoi_lat_max-aoi_lat_min,\n", " facecolor='white',\n", " alpha=0.5,\n", - " transform=ccrs.Geodetic())\n", - " )\n", - "ax.set_extent((aoi_minlon-20., \n", - " aoi_maxlon+20.,\n", - " aoi_minlat-20.,\n", - " aoi_maxlat+20.), crs=ccrs.PlateCarree())\n", + " transform=ccrs.Geodetic()))\n", + "ax.set_extent((aoi_lon_min-20., \n", + " aoi_lon_max+20.,\n", + " aoi_lat_min-20.,\n", + " aoi_lat_max+20.), crs=ccrs.PlateCarree())\n", "ax.stock_img()\n", "ax.coastlines()\n", "ax.gridlines(color=\"white\", alpha=0.5)\n", @@ -249,6 +193,7 @@ }, { "cell_type": "markdown", + "id": "026e8df3", "metadata": {}, "source": [ "## Access temperature profiles from ArgoVis API\n", @@ -258,7 +203,8 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, + "id": "a735df49", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:29.660346Z", @@ -275,13 +221,14 @@ } ], "source": [ - "argo_api_endpoint = 'https://argovis.colorado.edu/selection/profiles/?'\n", + "argo_api = 'https://argovis.colorado.edu/selection/profiles/?'\n", "\n", - "print(argo_api_endpoint)" + "print(argo_api)" ] }, { "cell_type": "markdown", + "id": "66e493ec", "metadata": {}, "source": [ "Create the AOI polygon in required XY format, make it a string, and collect the dictionary of API parameters:" @@ -289,7 +236,8 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, + "id": "24c4ada0", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:30.322357Z", @@ -305,30 +253,28 @@ " 'shape': '[[[-26.0,30.0],[-26.0,40.0],[-12.0,40.0],[-12.0,30.0],[-26.0,30.0]]]'}" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "argo_api_aoi = [[[aoi_minlon, aoi_minlat], \n", - " [aoi_minlon, aoi_maxlat], \n", - " [aoi_maxlon, aoi_maxlat],\n", - " [aoi_maxlon, aoi_minlat],\n", - " [aoi_minlon, aoi_minlat]]]\n", - "\n", - "argo_api_params = {\n", - " 'startDate': start_date.replace(\"-0\",\"-\"), # 1.\n", - " 'endDate': end_date.replace(\"-0\",\"-\"), # 1. No leading zeros in start/end dates\n", - " 'shape': str(argo_api_aoi).replace(\" \",\"\"), # 2. Array of XY vertices for AOI polygon\n", - " #'presRange': \"[0,30]\" # 3. We wont limit by pressure range\n", - "}\n", + "argo_aoi = [[[aoi_lon_min, aoi_lat_min], \n", + " [aoi_lon_min, aoi_lat_max], \n", + " [aoi_lon_max, aoi_lat_max],\n", + " [aoi_lon_max, aoi_lat_min],\n", + " [aoi_lon_min, aoi_lat_min]]]\n", + "\n", + "argo_par = {'startDate': start_date.replace(\"-0\",\"-\"),\n", + " 'endDate': end_date.replace(\"-0\",\"-\"),\n", + " 'shape': str(argo_aoi).replace(\" \",\"\")}\n", "\n", - "argo_api_params" + "argo_par" ] }, { "cell_type": "markdown", + "id": "0dcf9d43", "metadata": {}, "source": [ "Submit the request parameters to the Argovis API. You should receive a JSON response back. Print the number of profiles inside our AOI:" @@ -336,7 +282,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, + "id": "d1a70b43", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:31.366649Z", @@ -353,19 +300,18 @@ } ], "source": [ - "argo_api_response = requests.get(url=argo_api_endpoint, params=argo_api_params)\n", + "argo_response = requests.get(url=argo_api, params=argo_par)\n", "\n", - "# Load the response from JSON if the response status is 200:\n", - "if argo_api_response.status_code == 200:\n", - " argo_profiles = argo_api_response.json()\n", + "if argo_response.status_code == 200:\n", + " argo_profiles = argo_response.json()\n", " print(len(argo_profiles))\n", "else:\n", - " # Otherwise dump the text for more clues:\n", - " print(argo_api_response.text)" + " print(argo_response.text)" ] }, { "cell_type": "markdown", + "id": "e50539e0", "metadata": {}, "source": [ "### Prepare profile data for further analysis\n", @@ -375,7 +321,8 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, + "id": "928cbe91", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:32.498596Z", @@ -404,8 +351,8 @@ " 9 station_parameters 41 non-null object \n", " 10 pres_max_for_TEMP 41 non-null float64 \n", " 11 pres_min_for_TEMP 41 non-null float64 \n", - " 12 pres_max_for_PSAL 41 non-null float64 \n", - " 13 pres_min_for_PSAL 41 non-null float64 \n", + " 12 pres_max_for_PSAL 38 non-null float64 \n", + " 13 pres_min_for_PSAL 38 non-null float64 \n", " 14 max_pres 41 non-null float64 \n", " 15 date 41 non-null object \n", " 16 date_added 41 non-null object \n", @@ -435,21 +382,17 @@ ], "source": [ "argo_df = pd.DataFrame(argo_profiles).sort_values(\"date\")\n", - "\n", - "# Add a column with pandas datetime objects for easier indexing\n", - "argo_df['datetime'] = pd.to_datetime(argo_df['date'])\n", - "# And then replace the original date column with Python dates\n", + "argo_df['datetime'] = pd.to_datetime(argo_df.date)\n", "argo_df['date'] = argo_df.datetime.apply(lambda x: x.date).tolist()\n", - "\n", - "# Add two columns of sanitized lats/lons to the data frame\n", - "argo_df['lat'] = argo_df['roundLat'].astype(float).tolist()\n", - "argo_df['lon'] = argo_df['roundLon'].astype(float).tolist()\n", + "argo_df['lat'] = argo_df.roundLat.astype(float)\n", + "argo_df['lon'] = argo_df.roundLon.astype(float)\n", "\n", "argo_df.info()" ] }, { "cell_type": "markdown", + "id": "a01bf7b9", "metadata": {}, "source": [ "You can download profiles in netCDF format from the FTP link stored in the *nc_url* fields of the response. Here's the URL for the first of the profiles:" @@ -457,7 +400,8 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, + "id": "8843b6d5", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:33.524480Z", @@ -479,6 +423,7 @@ }, { "cell_type": "markdown", + "id": "bdc9f01c", "metadata": {}, "source": [ "Display a table summarizing the space/time characteristics of eaach profile:" @@ -486,7 +431,8 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, + "id": "9175f884", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:33.919883Z", @@ -943,17 +889,21 @@ "0 32.602 " ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "argo_df[['platform_number', 'cycle_number', 'datetime', 'lon', 'lat']] #, 'measurements']]" + "argo_df['date'] = argo_df.datetime.apply(lambda x: x.date)\n", + "argo_df['time'] = argo_df.datetime.apply(lambda x: x.time)\n", + "\n", + "argo_df[['platform_number', 'cycle_number', 'datetime', 'lon', 'lat']]" ] }, { "cell_type": "markdown", + "id": "f670a877", "metadata": {}, "source": [ "*Now plot argo profile locations on an interactive map.*\n", @@ -963,7 +913,8 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, + "id": "3a9d2611", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:34.320181Z", @@ -974,10 +925,10 @@ { "data": { "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -997,22 +948,27 @@ " tiles=\"Stamen Terrain\",\n", " zoom_start=5, )\n", "\n", - "# Loop over list of unique platform_numbers (floats)\n", "unique_argo_platform_numbers = argo_df.platform_number.unique().tolist()\n", "\n", "for i, platform in enumerate(unique_argo_platform_numbers):\n", + "\n", " # Get row(s) for the current platform\n", " p = argo_df[argo_df['platform_number']==platform]\n", + " \n", " # Make an empty marker cluster to add to the map widget\n", " cluster = MarkerCluster(name=p['platform_number'])\n", + " \n", " # Make markers in a loop and add to the cluster:\n", " for c in p['cycle_number'].tolist():\n", + " \n", " # Select the row for the current profile ('cycle')\n", " profile = p[p['cycle_number']==c].iloc[0]\n", + " \n", " # Create a new marker and add it to the cluster\n", " cluster.add_child(folium.Marker(\n", " location=[profile['lat'], profile['lon']],\n", " tooltip=_get_tooltip(profile.to_dict())))\n", + " \n", " m.add_child(cluster)\n", "\n", "display(m)" @@ -1020,6 +976,7 @@ }, { "cell_type": "markdown", + "id": "397021bf", "metadata": {}, "source": [ "#### Reformat profile data into data frames\n", @@ -1031,7 +988,8 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, + "id": "4aa16480", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:34.642588Z", @@ -1130,7 +1088,7 @@ "max 18.418000 2010.000000 36.504000" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -1138,12 +1096,12 @@ "source": [ "argo_df['measurements'] = argo_df['measurements'].apply(pd.DataFrame).tolist()\n", "\n", - "# Print statistical summary of the table content:\n", "argo_df.iloc[0].measurements.describe()" ] }, { "cell_type": "markdown", + "id": "5f8fd6f6", "metadata": {}, "source": [ "**Plot temperature at the minimum pressure for each profile**\n", @@ -1153,7 +1111,8 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, + "id": "df33e6eb", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:35.174348Z", @@ -1163,7 +1122,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1175,23 +1134,22 @@ } ], "source": [ - "def _get_prof_temp_at_pres_min(x):\n", - " return x[x['pres']==x['pres'].min()]['temp'].item()\n", + "def get_prof_temp_at_min_pres(x):\n", + " return x[x.pres==x.pres.min()].temp.item()\n", "\n", - "# Apply the fuunction over the column of measurements tables\n", - "argo_df['temp_at_pres_min'] = argo_df['measurements'].apply(_get_prof_temp_at_pres_min).tolist()\n", + "argo_df['temp_at_pres_min'] = argo_df.measurements.apply(get_prof_temp_at_min_pres)\n", "\n", - "# Plot temperature measured nearest to the sea surface for each profile \n", "argo_df.plot.scatter(x=\"datetime\", y=\"temp_at_pres_min\", figsize=(16, 4))\n", - "plt.title(\"~Daily temperature at minimum pressure across ~40 argo profiles\")\n", + "plt.title(\"Daily temperature at minimum pressure across ~40 argo profiles\")\n", + "plt.ylabel(\"Temperature (deg C)\")\n", "plt.xlabel(None)\n", - "plt.ylabel(\"Temperature (degrees C)\")\n", - "plt.ylim(15.5, 20.5)\n", + "plt.ylim(15.5,20.5)\n", "plt.grid(alpha=0.25)" ] }, { "cell_type": "markdown", + "id": "fde8c532", "metadata": {}, "source": [ "#### Select an *Argo of Interest* and its *platform_number*\n", @@ -1201,7 +1159,8 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, + "id": "05fd6c6b", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:35.489461Z", @@ -1228,25 +1187,27 @@ "Name: cycle_number, dtype: int64" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "argo_df.groupby(\"platform_number\").count()['cycle_number']" + "argo_df.groupby(\"platform_number\").count().cycle_number" ] }, { "cell_type": "markdown", + "id": "6791f954", "metadata": {}, "source": [ - "Choose a float with six profiles to study further during the remainder of the notebook." + "Choose a float with six profiles to study further during the remainder of the notebook. Take a peek at the relevant data from the target Argo float platform across six profiles:" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, + "id": "9224d2c7", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:35.960685Z", @@ -1275,560 +1236,375 @@ " \n", " \n", " \n", - " pres_max_for_TEMP\n", - " pres_min_for_TEMP\n", - " pres_max_for_PSAL\n", - " pres_min_for_PSAL\n", - " max_pres\n", - " date_qc\n", + " _id\n", + " date\n", + " time\n", " lat\n", " lon\n", - " position_qc\n", - " cycle_number\n", - " platform_number\n", - " BASIN\n", " temp_at_pres_min\n", " \n", " \n", " \n", " \n", - " count\n", - " 6.000000\n", - " 6.0\n", - " 6.000000\n", - " 6.0\n", - " 6.000000\n", - " 6.0\n", - " 6.000000\n", - " 6.000000\n", - " 6.0\n", - " 6.000000\n", - " 6.0\n", - " 6.0\n", - " 6.000000\n", - " \n", - " \n", - " mean\n", - " 1992.666667\n", - " 6.0\n", - " 1992.666667\n", - " 6.0\n", - " 1992.666667\n", - " 1.0\n", - " 38.131167\n", - " -13.030667\n", - " 1.0\n", - " 51.500000\n", - " 6901260.0\n", - " 1.0\n", - " 16.921000\n", - " \n", - " \n", - " std\n", - " 21.500388\n", - " 0.0\n", - " 21.500388\n", - " 0.0\n", - " 21.500388\n", - " 0.0\n", - " 0.297238\n", - " 0.168997\n", - " 0.0\n", - " 1.870829\n", - " 0.0\n", - " 0.0\n", - " 0.495337\n", + " 39\n", + " 6901260_49\n", + " 2019-01-02\n", + " 05:43:00\n", + " 37.707\n", + " -12.812\n", + " 17.479\n", " \n", " \n", - " min\n", - " 1961.000000\n", - " 6.0\n", - " 1961.000000\n", - " 6.0\n", - " 1961.000000\n", - " 1.0\n", - " 37.707000\n", - " -13.265000\n", - " 1.0\n", - " 49.000000\n", - " 6901260.0\n", - " 1.0\n", - " 16.153000\n", + " 31\n", + " 6901260_50\n", + " 2019-01-07\n", + " 05:26:00\n", + " 37.905\n", + " -12.887\n", + " 17.300\n", " \n", " \n", - " 25%\n", - " 1980.500000\n", - " 6.0\n", - " 1980.500000\n", - " 6.0\n", - " 1980.500000\n", - " 1.0\n", - " 37.940500\n", - " -13.132500\n", - " 1.0\n", - " 50.250000\n", - " 6901260.0\n", - " 1.0\n", - " 16.643250\n", + " 24\n", + " 6901260_51\n", + " 2019-01-12\n", + " 05:18:00\n", + " 38.047\n", + " -12.982\n", + " 17.153\n", " \n", " \n", - " 50%\n", - " 1994.500000\n", - " 6.0\n", - " 1994.500000\n", - " 6.0\n", - " 1994.500000\n", - " 1.0\n", - " 38.156500\n", - " -13.037000\n", - " 1.0\n", - " 51.500000\n", - " 6901260.0\n", - " 1.0\n", - " 17.014000\n", + " 16\n", + " 6901260_52\n", + " 2019-01-17\n", + " 05:28:00\n", + " 38.266\n", + " -13.092\n", + " 16.875\n", " \n", " \n", - " 75%\n", - " 2010.750000\n", - " 6.0\n", - " 2010.750000\n", - " 6.0\n", - " 2010.750000\n", - " 1.0\n", - " 38.350000\n", - " -12.910750\n", - " 1.0\n", - " 52.750000\n", - " 6901260.0\n", - " 1.0\n", - " 17.263250\n", + " 11\n", + " 6901260_53\n", + " 2019-01-22\n", + " 05:33:00\n", + " 38.378\n", + " -13.146\n", + " 16.566\n", " \n", " \n", - " max\n", - " 2014.000000\n", - " 6.0\n", - " 2014.000000\n", - " 6.0\n", - " 2014.000000\n", - " 1.0\n", - " 38.484000\n", - " -12.812000\n", - " 1.0\n", - " 54.000000\n", - " 6901260.0\n", - " 1.0\n", - " 17.479000\n", + " 3\n", + " 6901260_54\n", + " 2019-01-27\n", + " 05:38:00\n", + " 38.484\n", + " -13.265\n", + " 16.153\n", " \n", " \n", "\n", "" ], "text/plain": [ - " pres_max_for_TEMP pres_min_for_TEMP pres_max_for_PSAL \\\n", - "count 6.000000 6.0 6.000000 \n", - "mean 1992.666667 6.0 1992.666667 \n", - "std 21.500388 0.0 21.500388 \n", - "min 1961.000000 6.0 1961.000000 \n", - "25% 1980.500000 6.0 1980.500000 \n", - "50% 1994.500000 6.0 1994.500000 \n", - "75% 2010.750000 6.0 2010.750000 \n", - "max 2014.000000 6.0 2014.000000 \n", - "\n", - " pres_min_for_PSAL max_pres date_qc lat lon \\\n", - "count 6.0 6.000000 6.0 6.000000 6.000000 \n", - "mean 6.0 1992.666667 1.0 38.131167 -13.030667 \n", - "std 0.0 21.500388 0.0 0.297238 0.168997 \n", - "min 6.0 1961.000000 1.0 37.707000 -13.265000 \n", - "25% 6.0 1980.500000 1.0 37.940500 -13.132500 \n", - "50% 6.0 1994.500000 1.0 38.156500 -13.037000 \n", - "75% 6.0 2010.750000 1.0 38.350000 -12.910750 \n", - "max 6.0 2014.000000 1.0 38.484000 -12.812000 \n", - "\n", - " position_qc cycle_number platform_number BASIN temp_at_pres_min \n", - "count 6.0 6.000000 6.0 6.0 6.000000 \n", - "mean 1.0 51.500000 6901260.0 1.0 16.921000 \n", - "std 0.0 1.870829 0.0 0.0 0.495337 \n", - "min 1.0 49.000000 6901260.0 1.0 16.153000 \n", - "25% 1.0 50.250000 6901260.0 1.0 16.643250 \n", - "50% 1.0 51.500000 6901260.0 1.0 17.014000 \n", - "75% 1.0 52.750000 6901260.0 1.0 17.263250 \n", - "max 1.0 54.000000 6901260.0 1.0 17.479000 " + " _id date time lat lon temp_at_pres_min\n", + "39 6901260_49 2019-01-02 05:43:00 37.707 -12.812 17.479\n", + "31 6901260_50 2019-01-07 05:26:00 37.905 -12.887 17.300\n", + "24 6901260_51 2019-01-12 05:18:00 38.047 -12.982 17.153\n", + "16 6901260_52 2019-01-17 05:28:00 38.266 -13.092 16.875\n", + "11 6901260_53 2019-01-22 05:33:00 38.378 -13.146 16.566\n", + "3 6901260_54 2019-01-27 05:38:00 38.484 -13.265 16.153" ] }, - "execution_count": 15, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "target_argo = 6901260\n", - "\n", - "# Select rows (profiles) for the desired platform:\n", - "argo_skinny = argo_df[argo_df.platform_number==target_argo].copy()\n", + "argo_skinny = argo_df[argo_df.platform_number==6901260].copy()\n", "\n", - "argo_skinny.describe()" + "argo_skinny[['_id', 'date', 'time', 'lat', 'lon', 'temp_at_pres_min']]" ] }, { "cell_type": "markdown", + "id": "f7457da3", "metadata": {}, "source": [ "## Access *sea surface temperature* from MODIS\n", "\n", - "The user guide for MODIS Level 2 Sea Surface Temperature (SST) from GHRSST is available on the PO.DAAC Drive: https://podaac-tools.jpl.nasa.gov/drive/files/OceanTemperature/ghrsst/docs/GDS20r5.pdf\n", - "\n", - "We will access L2 SST data for our AOI and time period of interest by submitting two subset requests to the [Harmony API](https://harmony.earthdata.nasa.gov/).\n", - "\n", - "**Redefine the AOI to the minimum XY bounds of selected profiles**\n", - "\n", - "Simply replace the *`aoi_*`* Python variables with min/max of the *lat* and *lon* columns in the new *argo_skinny* data frame:" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "ExecuteTime": { - "end_time": "2021-03-15T21:08:36.313559Z", - "start_time": "2021-03-15T21:08:36.308456Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(-13.265, 37.707, -12.812, 38.484)" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "aoi_minlon = argo_skinny.lon.min()\n", - "aoi_maxlon = argo_skinny.lon.max()\n", - "aoi_minlat = argo_skinny.lat.min()\n", - "aoi_maxlat = argo_skinny.lat.max()\n", - "\n", - "aoi_minlon, aoi_minlat, aoi_maxlon, aoi_maxlat" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Search the Common Metadata Repository (CMR) for its unique *concept-id***\n", + "The user guide for MODIS Level 2 Sea Surface Temperature (SST) from GHRSST is available on the PO.DAAC Drive: \n", + "https://podaac-tools.jpl.nasa.gov/drive/files/OceanTemperature/ghrsst/docs/GDS20r5.pdf\n", "\n", "The API requires a dataset identifier that we must obtain from CMR. In the next cell, submit a request to the CMR API to grab the metadata for to the dataset/collection." ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, + "id": "6228671a", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:08:37.076361Z", "start_time": "2021-03-15T21:08:36.696876Z" - } + }, + "scrolled": false }, "outputs": [ { "data": { "text/plain": [ - "'C1940473819-POCLOUD'" + "(dict, ['meta', 'umm'])" ] }, - "execution_count": 17, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "modis_results = requests.get(\n", - " url='https://cmr.earthdata.nasa.gov/search/collections.umm_json', \n", - " params={'provider': \"POCLOUD\",\n", - " 'ShortName': \"MODIS_A-JPL-L2P-v2019.0\",\n", - " 'token': _token}\n", - ").json()\n", + "url = \"https://cmr.earthdata.nasa.gov/search/collections.umm_json\"\n", "\n", - "# Select the first/only record in the JSON response:\n", - "modis_coll = modis_results['items'][0]\n", + "params = dict(provider=\"POCLOUD\", ShortName=\"MODIS_A-JPL-L2P-v2019.0\")\n", "\n", - "# Select the 'concept-id' from the 'meta' dictionary:\n", - "modis_ccid = modis_coll['meta']['concept-id']\n", + "modis = requests.get(url, params).json().get('items')[0]\n", "\n", - "modis_ccid" + "type(modis), list(modis)" ] }, { "cell_type": "markdown", + "id": "09b8ea1d", "metadata": {}, "source": [ - "#### Request subsets from the Harmony API\n", - "\n", - "We will submit two requests to the [Harmony API](https://harmony.earthdata.nasa.gov/). The API is under active development, and it's therefore recommended that you test your input parameters in the [Swagger API interface](https://harmony.earthdata.nasa.gov/docs/api/#).\n", - "\n", - "The next cell joins the base url for the API to the concept-id obtained above. Run the cell and print the complete url to confirm:" + "Select the collection's unique *concept-id* from the *meta* object:" ] }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "ExecuteTime": { - "end_time": "2021-03-15T21:08:37.123308Z", - "start_time": "2021-03-15T21:08:37.120604Z" - } - }, + "execution_count": 16, + "id": "9c909004", + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "https://harmony.earthdata.nasa.gov/C1940473819-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?\n" + "C1940473819-POCLOUD\n" ] } ], "source": [ - "harmony_url = \"https://harmony.earthdata.nasa.gov\"\n", - "harmony_url_modis = f\"{harmony_url}/{modis_ccid}/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?\"\n", + "ccid = modis.get('meta').get('concept-id')\n", "\n", - "print(harmony_url_modis)" + "print(ccid)" ] }, { "cell_type": "markdown", + "id": "ccdbfc17", "metadata": {}, "source": [ - "Make a dictionary of subset parameters and format the values to meet requirements of the Harmony API. (See the Swagger UI linked above for more information about those requirements.)\n", - "\n", - "*Note how I've commented out the `time` parameter for the second half of January.* I requested the first 15 days and then the second 15 days in two requests to get the whole month. \n", + "**Redefine the AOI to the minimum XY bounds of selected profiles**\n", "\n", - "Here we print the parameters for the first request:" + "Simply replace the *`aoi_*`* Python variables with min/max of the *lat* and *lon* columns in the new *argo_skinny* data frame:" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, + "id": "fded0258", "metadata": { "ExecuteTime": { - "end_time": "2021-03-15T21:08:37.941220Z", - "start_time": "2021-03-15T21:08:37.937601Z" + "end_time": "2021-03-15T21:08:36.313559Z", + "start_time": "2021-03-15T21:08:36.308456Z" } }, "outputs": [ { "data": { "text/plain": [ - "{'time': '(\"2019-01-01T00:00:00.000Z\":\"2019-01-15T23:59:59.999Z\")',\n", - " 'lat': '(37.707:38.484)',\n", - " 'lon': '(-13.265:-12.812)'}" + "(-13.265, -12.812, 37.707, 38.484)" ] }, - "execution_count": 19, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "harmony_params_modis1 = {\n", - " 'time': f'(\"{start_date}T00:00:00.000Z\":\"2019-01-15T23:59:59.999Z\")',\n", - " 'lat': f'({aoi_minlat}:{aoi_maxlat})',\n", - " 'lon': f'({aoi_minlon}:{aoi_maxlon})',\n", - "}\n", - "\n", - "harmony_params_modis2 = {\n", - " 'time': f'(\"2019-01-16T00:00:00.000Z\":\"{end_date}T23:59:59.999Z\")',\n", - " 'lat': f'({aoi_minlat}:{aoi_maxlat})',\n", - " 'lon': f'({aoi_minlon}:{aoi_maxlon})',\n", - "}\n", + "aoi_lon_min = argo_skinny.lon.min()\n", + "aoi_lon_max = argo_skinny.lon.max()\n", + "aoi_lat_min = argo_skinny.lat.min()\n", + "aoi_lat_max = argo_skinny.lat.max()\n", "\n", - "harmony_params_modis1" + "aoi_lon_min, aoi_lon_max, aoi_lat_min, aoi_lat_max" ] }, { "cell_type": "markdown", + "id": "88b9e911", "metadata": {}, "source": [ - "Complete the url by formatting the query portion using the parameters dictionary:" + "#### Request subsets from the Harmony API\n", + "\n", + "We will submit two requests to the [Harmony API](https://harmony.earthdata.nasa.gov/). Please note that the API is under active development, we recommend testing input parameters using the [Swagger API interface](https://harmony.earthdata.nasa.gov/docs/api/#)." ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, + "id": "7162541c", "metadata": { "ExecuteTime": { - "end_time": "2021-03-15T21:08:38.639105Z", - "start_time": "2021-03-15T21:08:38.636070Z" + "end_time": "2021-03-15T21:08:37.941220Z", + "start_time": "2021-03-15T21:08:37.937601Z" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "https://harmony.earthdata.nasa.gov/C1940473819-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?subset=time(\"2019-01-01T00:00:00.000Z\":\"2019-01-15T23:59:59.999Z\")&subset=lat(37.707:38.484)&subset=lon(-13.265:-12.812)\n" - ] - } - ], + "outputs": [], "source": [ - "request_url_modis1 = harmony_url_modis+\"subset=time{time}&subset=lat{lat}&subset=lon{lon}\".format(**harmony_params_modis1)\n", - "request_url_modis2 = harmony_url_modis+\"subset=time{time}&subset=lat{lat}&subset=lon{lon}\".format(**harmony_params_modis2)\n", - "\n", - "print(request_url_modis1)" + "harmony_url = \"https://harmony.earthdata.nasa.gov\"" ] }, { "cell_type": "markdown", + "id": "bfbf04d3", "metadata": {}, "source": [ - "#### Submit the request parameters to the Harmony API endpoint\n", - "\n", - "I've already submitted the two requests required to obtain full coverage for our region and timeframe of interest (the two urls in the *job_status* list below). To submit a new request, or to submit these two MODIS requests again, comment out the two items in the list like this:\n", - "\n", - "```python\n", - "job_status = [\n", - " #'https://...'\n", - " #'https://...\n", - "]\n", - "```\n", - "\n", - "It should trigger new requests in the subsequent cells." + "Make two dictionaries of subset parameters. *Note that we need to submit two requests to get the whole month.*" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, + "id": "c1ff6110", "metadata": { "ExecuteTime": { - "end_time": "2021-03-15T21:08:39.787125Z", - "start_time": "2021-03-15T21:08:39.784692Z" + "end_time": "2021-03-15T21:08:37.123308Z", + "start_time": "2021-03-15T21:08:37.120604Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"lat\": \"(37.707:38.484)\",\n", + " \"lon\": \"(-13.265:-12.812)\",\n", + " \"time\": \"(\\\"2019-01-01T00:00:00.000Z\\\":\\\"2019-01-31T23:59:59.999Z\\\")\"\n", + "}\n" + ] + } + ], "source": [ - "job_status = [ \n", - "# \"https://harmony.earthdata.nasa.gov/jobs/512ca343-3bfe-48c5-a480-9281b7348761\", # First time slice\n", - "# \"https://harmony.earthdata.nasa.gov/jobs/5b29414d-3856-4e94-9568-01b32b02a951\", # Second time slice\n", - "]" + "params = {\n", + " 'lat': f'({aoi_lat_min}:{aoi_lat_max})', \n", + " 'lon': f'({aoi_lon_min}:{aoi_lon_max})', \n", + " 'time': f'(\"{start_date}T00:00:00.000Z\":\"{end_date}T23:59:59.999Z\")',\n", + "}\n", + "\n", + "print(json.dumps(params, indent=2))" ] }, { "cell_type": "markdown", + "id": "5d40cfac", "metadata": {}, "source": [ - "The next cell should download a JSON for your new request or from the first request that I submitted while I developed this notebook.\n", + "#### Submit the request parameters to the Harmony API endpoint\n", "\n", - "Print the message field of the JSON response:" + "Format the parameters dictionary as a string to make a query string and append it to the Harmony API endpoint. Then, submit the request and store the response to a variable `job`." ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, + "id": "66f0837b", "metadata": { "ExecuteTime": { - "end_time": "2021-03-15T21:08:46.407504Z", - "start_time": "2021-03-15T21:08:40.543604Z" + "end_time": "2021-03-15T21:08:38.639105Z", + "start_time": "2021-03-15T21:08:38.636070Z" } }, "outputs": [ { - "data": { - "text/plain": [ - "'The job is being processed'" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"username\": \"jmcnelis\",\n", + " \"status\": \"running\",\n", + " \"message\": \"The job is being processed\",\n", + " \"progress\": 0,\n", + " \"createdAt\": \"2021-12-07T06:06:13.930Z\",\n", + " \"updatedAt\": \"2021-12-07T06:06:13.930Z\",\n", + " \"links\": [\n", + " {\n", + " \"href\": \"https://harmony.earthdata.nasa.gov/jobs/f95ae632-9155-41c2-a6f9-5d0cf92a6f6a?page=1&limit=2000\",\n", + " \"title\": \"The current page\",\n", + " \"type\": \"application/json\",\n", + " \"rel\": \"self\"\n", + " }\n", + " ],\n", + " \"request\": \"https://harmony.earthdata.nasa.gov/C1940473819-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?subset=time(%222019-01-01T00%3A00%3A00.000Z%22%3A%222019-01-31T23%3A59%3A59.999Z%22)&subset=lat(37.707%3A38.484)&subset=lon(-13.265%3A-12.812)\",\n", + " \"numInputGranules\": 106,\n", + " \"jobID\": \"f95ae632-9155-41c2-a6f9-5d0cf92a6f6a\"\n", + "}\n" + ] } ], "source": [ - "request_urls_for_modis = [request_url_modis1, request_url_modis2]\n", - "\n", - "if len(job_status)==0:\n", - " # Loop over the list of request urls:\n", - " for r in request_urls_for_modis:\n", - " # Submit the request and decode the response from json string to dict:\n", - " response_modis = requests.get(r)\n", - " # If the response came back with something other than '2xx', raise an error:\n", - " if not response_modis.status_code // 100 == 2: \n", - " raise Exception(response_modis.text)\n", - " else:\n", - " response_data = response_modis.json()\n", - " # Append the status endpoint to the list of 'job_status' urls:\n", - " job_status.append(response_data['links'][0]['href'])\n", - "else:\n", - " response_data = requests.get(job_status[0]).json()\n", + "endpoint = f\"{harmony_url}/{ccid}/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset\"\n", + "\n", + "query = \"subset=time{time}&subset=lat{lat}&subset=lon{lon}\".format(**params)\n", "\n", - "response_data['message']" + "with requests.get(f\"{endpoint}?{query}\") as response:\n", + " job = response.json()\n", + "\n", + "print(json.dumps(job, indent=2))" ] }, { "cell_type": "markdown", + "id": "bc42891c", "metadata": {}, "source": [ - "Successful requests to the API will respond with a JSON that starts like this:\n", - "\n", - "```json\n", - "{\n", - " \"username\": \"jmcnelis\",\n", - " \"status\": \"running\",\n", - " \"message\": \"The job is being processed\",\n", - " \"progress\": 0,\n", - " \"createdAt\": \"2021-02-25T02:09:35.972Z\",\n", - " \"updatedAt\": \"2021-02-25T02:09:35.972Z\",\n", - " ...\n", - "```\n", - "\n", - "The example above is truncated to the first several lines for the sake of space.\n", - "\n", - "**Monitor the status of an in-progress job**\n", - "\n", - "Select the `status` URL(s) from the list(s) of `links`:" + "The first link in the list of *links* in the response will respond with the json shown above. Set it to a python variable called `job_url`:" ] }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "ExecuteTime": { - "end_time": "2021-03-15T21:08:49.362801Z", - "start_time": "2021-03-15T21:08:49.359356Z" - } - }, + "execution_count": 21, + "id": "bd828cc8", + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "['https://harmony.earthdata.nasa.gov/jobs/558426d1-3df4-4cc2-80dc-943d03ac5810', 'https://harmony.earthdata.nasa.gov/jobs/dafd8c06-89b5-4dd6-af1d-cacb12512101']\n" + "https://harmony.earthdata.nasa.gov/jobs/f95ae632-9155-41c2-a6f9-5d0cf92a6f6a?page=1&limit=2000\n" ] } ], "source": [ - "if len(job_status)==0:\n", - " try:\n", - " job_status = [l['href'] for l in response_data['links'] if l['title']==\"Job Status\"]\n", - " except (KeyError, IndexError) as e:\n", - " raise e\n", + "job_url = job.get(\"links\")[0].get(\"href\")\n", "\n", - "print(job_status)" + "print(job_url)" ] }, { "cell_type": "markdown", + "id": "d436e4dc", "metadata": {}, "source": [ - "Run the next cell to monitor the status of as many requests as you need.\n", + "**Monitor status of the in-progress job**\n", "\n", - "It will loop over the `job_status` list and wait for all the requests to finish processing. (It terminates when the `status` field of the JSON response _does not_ contain the string `\"running\"`.)" + "Run the next cell to monitor the status of the request." ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 22, + "id": "19b801d4", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:02.192779Z", @@ -1840,56 +1616,62 @@ "name": "stdout", "output_type": "stream", "text": [ - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (1/2)\n", - "# Job(s) in progress (2/2)\n", - "\n", - "&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&\n", - "%\t\tDONE!\n", - "&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&\n", - "\n" + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "- Job processing (0%)\n", + "# Job finished!\n" ] } ], "source": [ - "wait = 10 # The number of seconds to wait between each status check\n", - "completed = {} # A dict of JSON responses for completed jobs\n", + "def check_job_status(url: str, wait: int=10):\n", + " response = requests.get(url).json()\n", + " if response.get(\"status\") != \"running\":\n", + " print(\"# Job finished!\")\n", + " return response \n", + " progress = response.get(\"progress\")\n", + " print(f\"- Job processing ({progress}%)\")\n", + " time.sleep(wait)\n", + " return\n", "\n", - "# Loop repeatedly to check job status. Wait before retrying.\n", "while True:\n", - " for j in job_status: # Iterate over list of job urls\n", - " if j in completed: # Skip if completed.\n", - " continue\n", - " # Get the current job's status as a JSON object.\n", - " job_data = requests.get(j).json()\n", - " if job_data['status']!='running':\n", - " completed[j] = job_data # Add to 'completed' if finished\n", - " # Break loop if 'completed' dictionary contains all jobs.\n", - " if len(completed)==2:\n", - " break\n", - " # If still processing, print a status update and wait ten seconds.\n", - " print(f\"# Job(s) in progress ({len(completed)+1}/{len(job_status)})\")\n", - " time.sleep(wait)\n", - " \n", - "print(f\"\\n{'&'*40}\\n%\\t\\tDONE!\\n{'&'*40}\\n\")" + " job = check_job_status(job_url)\n", + " if type(job) is dict:\n", + " break" ] }, { "cell_type": "markdown", + "id": "d7624f3e", "metadata": {}, "source": [ - "The final response(s) are *massive* whenever your subset results in a large number of output granules. Print everything but the `links` here:" + "The final response(s) are *massive* whenever your subset results in a large number of output granules. Check out the *third* item from the list of `links` for the last request to complete." ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 23, + "id": "f4c9062c", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:18.825910Z", @@ -1902,77 +1684,40 @@ "output_type": "stream", "text": [ "{\n", - " \"username\": \"jmcnelis\",\n", - " \"status\": \"successful\",\n", - " \"message\": \"The job has completed successfully\",\n", - " \"progress\": 100,\n", - " \"createdAt\": \"2021-03-15T21:08:45.844Z\",\n", - " \"updatedAt\": \"2021-03-15T21:10:51.310Z\",\n", - " \"request\": \"https://harmony.earthdata.nasa.gov/C1940473819-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?subset=time(%222019-01-16T00%3A00%3A00.000Z%22%3A%222019-01-31T23%3A59%3A59.999Z%22)&subset=lat(37.707%3A38.484)&subset=lon(-13.265%3A-12.812)\",\n", - " \"numInputGranules\": 55,\n", - " \"jobID\": \"dafd8c06-89b5-4dd6-af1d-cacb12512101\"\n", - "}\n" - ] - } - ], - "source": [ - "print(json.dumps({k:v for k, v in job_data.items() if k!=\"links\"}, indent=2))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now look at the first url that points to a subset file (skip the first two because they point to other stuff about the order):" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": { - "ExecuteTime": { - "end_time": "2021-03-15T21:11:23.520484Z", - "start_time": "2021-03-15T21:11:23.518083Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{\n", - " \"href\": \"https://harmony.earthdata.nasa.gov/service-results/harmony-prod-staging/public/podaac/l2-subsetter/80c8503e-c958-4825-b072-ccdee3f7863b/20190116023001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\",\n", - " \"title\": \"20190116023001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\",\n", + " \"href\": \"https://harmony.earthdata.nasa.gov/service-results/harmony-prod-staging/public/podaac/l2-subsetter/8e317289-fdce-4622-89f5-e4bf79f07e61/20190101031501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0.nc4\",\n", + " \"title\": \"20190101031501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0.nc4\",\n", " \"type\": \"application/x-netcdf4\",\n", " \"rel\": \"data\",\n", " \"bbox\": [\n", - " -13.3,\n", - " 37.7,\n", - " -12.8,\n", - " 38.5\n", + " -34.223,\n", + " 17.572,\n", + " -5.948,\n", + " 38.763\n", " ],\n", " \"temporal\": {\n", - " \"start\": \"2019-01-16T02:30:01.000Z\",\n", - " \"end\": \"2019-01-16T02:34:59.000Z\"\n", + " \"start\": \"2019-01-01T03:15:01.000Z\",\n", + " \"end\": \"2019-01-01T03:20:00.000Z\"\n", " }\n", "}\n" ] } ], "source": [ - "print(json.dumps(job_data['links'][2], indent=2))" + "print(json.dumps(job.get('links')[2], indent=2))" ] }, { "cell_type": "markdown", + "id": "380b5a66", "metadata": {}, "source": [ - "This cell collects all the output links (Python dicts) from our requests in a list and prints the total number of outputs:" + "Loop over the completed jobs, then their lists of `links`. Collect the urls ending with `subsetted.nc4` (which indicates a subset containing valid data)." ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 24, + "id": "11cebb4b", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:27.735502Z", @@ -1981,26 +1726,25 @@ }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "74\n" - ] + "data": { + "text/plain": [ + "74" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "job_links = []\n", - "\n", - "for j in list(completed.values()):\n", - " for l in j['links']:\n", - " if l['href'].endswith(\"subsetted.nc4\"):\n", - " job_links.append(l)\n", + "links = [l for l in job.get(\"links\") if l.get(\"href\").endswith(\"subsetted.nc4\")]\n", "\n", - "print(len(job_links))" + "len(links)" ] }, { "cell_type": "markdown", + "id": "ac2df306", "metadata": {}, "source": [ "##### Prepare subset data for further analysis\n", @@ -2010,30 +1754,120 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 25, + "id": "3f518b15", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:28.814911Z", "start_time": "2021-03-15T21:11:28.811051Z" - } + }, + "scrolled": true }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "74\n" - ] + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " title \\\n", + "0 20190101031001-JPL-L2P_GHRSST-SSTskin-MODIS_A-... \n", + "1 20190101141501-JPL-L2P_GHRSST-SSTskin-MODIS_A-... \n", + "2 20190102021501-JPL-L2P_GHRSST-SSTskin-MODIS_A-... \n", + "3 20190102132001-JPL-L2P_GHRSST-SSTskin-MODIS_A-... \n", + "4 20190103030000-JPL-L2P_GHRSST-SSTskin-MODIS_A-... \n", + "\n", + " start end \\\n", + "0 2019-01-01T03:10:01.000Z 2019-01-01T03:15:00.000Z \n", + "1 2019-01-01T14:15:01.000Z 2019-01-01T14:20:00.000Z \n", + "2 2019-01-02T02:15:01.000Z 2019-01-02T02:19:59.000Z \n", + "3 2019-01-02T13:20:01.000Z 2019-01-02T13:24:59.000Z \n", + "4 2019-01-03T03:00:00.000Z 2019-01-03T03:04:59.000Z \n", + "\n", + " href \n", + "0 https://harmony.earthdata.nasa.gov/service-res... \n", + "1 https://harmony.earthdata.nasa.gov/service-res... \n", + "2 https://harmony.earthdata.nasa.gov/service-res... \n", + "3 https://harmony.earthdata.nasa.gov/service-res... \n", + "4 https://harmony.earthdata.nasa.gov/service-res... " + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "subsets_df = pd.DataFrame(data=[{**l, **l['temporal']} for l in job_links])\n", + "subsets = pd.DataFrame([{**l, **l.get(\"temporal\")} for l in links])\n", "\n", - "print(subsets_df.index.size)" + "subsets[['title', 'start', 'end', 'href']].head()" ] }, { "cell_type": "markdown", + "id": "2085ddec", "metadata": {}, "source": [ "**Select day/drop night observations**\n", @@ -2043,7 +1877,8 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 26, + "id": "7f3bbf59", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:29.427130Z", @@ -2075,13 +1910,14 @@ } ], "source": [ - "subsets_df['daytime'] = subsets_df['href'].apply(lambda x: 'MODIS_A-N' not in x)\n", + "subsets['daytime'] = subsets.href.apply(lambda x: \"MODIS_A-N\" not in x)\n", "\n", - "subsets_df.info()" + "subsets.info()" ] }, { "cell_type": "markdown", + "id": "de751161", "metadata": {}, "source": [ "And finally, reformat the *start* timestamps as a new column containing pandas datetime objects instead of strings. Then, add one more column containing a date object (rather than the full datetime timestamp) which we'll use to aggregate the data before plotting." @@ -2089,7 +1925,8 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 27, + "id": "d8cb606f", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:30.052517Z", @@ -2103,23 +1940,22 @@ "datetime.date(2019, 1, 1)" ] }, - "execution_count": 30, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Add new 'datetime' column so that we aren't working with strings:\n", - "subsets_df['datetime'] = pd.to_datetime(subsets_df['start'])\n", + "subsets['datetime'] = pd.to_datetime(subsets.start)\n", "\n", - "# Add new 'date' column for aggregation during the final steps of the workflow:\n", - "subsets_df['date'] = subsets_df.datetime.apply(lambda x: x.date()).tolist()\n", + "subsets['date'] = subsets.datetime.apply(lambda x: x.date())\n", "\n", - "subsets_df.date.iloc[0]" + "subsets.date.iloc[0]" ] }, { "cell_type": "markdown", + "id": "4e1aa1ed", "metadata": {}, "source": [ "### Accessing outputs from your subset request\n", @@ -2129,7 +1965,8 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 28, + "id": "7364e88b", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:30.530313Z", @@ -2145,6 +1982,7 @@ }, { "cell_type": "markdown", + "id": "4e7d3e6f", "metadata": {}, "source": [ "This function should handle downloads reliably--test by downloading the first netCDF subset from our table (*subsets_df*):" @@ -2152,7 +1990,8 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 29, + "id": "2dd99df7", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:30.749873Z", @@ -2164,45 +2003,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "# File already exists. Skipping...\n", - "(20190101031001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4)\n", - "\n", - "The first file downloaded successfully: True\n" + "resources/data/20190101031001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n" ] } ], "source": [ "def download_target_file(url: str, force: bool=False):\n", - " # Determine the target path for the download\n", - " target_file = join(target_dir, basename(url))\n", - " if isfile(target_file) and force is False:\n", - " print(f\"# File already exists. Skipping...\\n({basename(url)})\\n\")\n", - " return\n", - " print(f\"# File downloading...\\n({basename(url)})\\n\")\n", - " # Open a remote connection for download stream/write to disk:\n", - " with requests.get(url) as r:\n", - " # Raise exception if response has status other than '2xx':\n", - " if not r.status_code // 100 == 2: \n", - " raise Exception(r.text)\n", - " else:\n", - " # Otherwise write the file to disk:\n", - " with open(target_file, 'wb') as f:\n", - " for chunk in r.iter_content(chunk_size=1024):\n", - " if chunk:\n", - " f.write(chunk)\n", - " \n", - "\n", - "# Test the download function by passing the URL for the first subset in the `subsets` table:\n", - "download_target_file(url=subsets_df['href'].iloc[0])\n", - "\n", - "# Join the string path to the target file that should have just downloaded.\n", - "test_nc4 = join(target_dir, basename(subsets_df['href'].iloc[0]))\n", - "\n", - "print(\"The first file downloaded successfully:\", isfile(test_nc4))" + " target_file = os.path.join(target_dir, os.path.basename(url))\n", + " if not os.path.isfile(target_file) or force is True:\n", + " with requests.get(url) as r:\n", + " if not r.status_code // 100 == 2: \n", + " raise Exception(r.text)\n", + " else:\n", + " with open(target_file, 'wb') as f:\n", + " for chunk in r.iter_content(chunk_size=1024):\n", + " if chunk:\n", + " f.write(chunk)\n", + " return target_file\n", + "\n", + "test_download = download_target_file(subsets.href.iloc[0])\n", + "\n", + "!ls $test_download" ] }, { "cell_type": "markdown", + "id": "7407a23a", "metadata": {}, "source": [ "Make sure you can dump the header of that file with *ncdump*. (The output below is truncated.)" @@ -2210,7 +2036,8 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 30, + "id": "b1e955f1", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:31.255051Z", @@ -2228,7 +2055,7 @@ "\tni = 42 ;\r\n", "\ttime = 1 ;\r\n", "variables:\r\n", - "\tfloat lat(nj, ni) ;\r\n", + "\tfloat lat(nj, ni, time) ;\r\n", "\t\tlat:_FillValue = -999.f ;\r\n", "\t\tlat:long_name = \"latitude\" ;\r\n", "\t\tlat:standard_name = \"latitude\" ;\r\n", @@ -2237,7 +2064,7 @@ "\t\tlat:valid_max = 90.f ;\r\n", "\t\tlat:comment = \"geographical coordinates, WGS84 projection\" ;\r\n", "\t\tlat:coverage_content_type = \"coordinate\" ;\r\n", - "\tfloat lon(nj, ni) ;\r\n", + "\tfloat lon(nj, ni, time) ;\r\n", "\t\tlon:_FillValue = -999.f ;\r\n", "\t\tlon:long_name = \"longitude\" ;\r\n", "\t\tlon:standard_name = \"longitude\" ;\r\n", @@ -2246,11 +2073,12 @@ } ], "source": [ - "!ncdump -h $test_nc4 | head -20" + "!ncdump -h $test_download | head -20" ] }, { "cell_type": "markdown", + "id": "d94baa0e", "metadata": {}, "source": [ "NetCDF file format errors indicate that the download was not successful. *cat* the file for more clues. Read and plot the *sea_surface_temperature* variable:" @@ -2258,7 +2086,8 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 31, + "id": "4e2cb381", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:31.627310Z", @@ -2268,7 +2097,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -2280,12 +2109,13 @@ } ], "source": [ - "with xr.open_dataset(test_nc4) as ds:\n", + "with xr.open_dataset(test_download) as ds:\n", " ds.sea_surface_temperature[0].plot()" ] }, { "cell_type": "markdown", + "id": "163f67af", "metadata": {}, "source": [ "#### Download all the netCDF subsets\n", @@ -2295,7 +2125,8 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 32, + "id": "1effc256", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:31.843575Z", @@ -2304,275 +2135,32 @@ }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "# File already exists. Skipping...\n", - "(20190101031001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4)\n", - "\n", - "# File already exists. Skipping...\n", - "(20190101141501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4)\n", - "\n", - "# File already exists. 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Skipping...\n", - "(20190131032501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4)\n", - "\n", - "# File already exists. Skipping...\n", - "(20190131143001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4)\n", - "\n" + "100%|██████████| 74/74 [00:00<00:00, 48648.67it/s]\n" ] - } - ], - "source": [ - "for u in subsets_df['href'].tolist():\n", - " download_target_file(u)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The next cell adds a column of absolute paths to the netCDF files to the data frame *subsets_df*:" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": { - "ExecuteTime": { - "end_time": "2021-03-15T21:11:32.998900Z", - "start_time": "2021-03-15T21:11:32.988444Z" - } - }, - "outputs": [ + }, { "data": { "text/plain": [ "True" ] }, - "execution_count": 36, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "subsets_df['path'] = subsets_df['href'].apply(lambda x: abspath(join(target_dir, basename(x))))\n", + "subsets['path'] = subsets.href.progress_apply(download_target_file)\n", "\n", - "isfile(subsets_df['path'].iloc[0])" + "os.path.isfile(subsets.path.iloc[0])" ] }, { "cell_type": "markdown", + "id": "0996909d", "metadata": {}, "source": [ "#### Limit to daytime MODIS observations\n", @@ -2582,7 +2170,8 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 33, + "id": "1a7e4463", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:33.613325Z", @@ -2594,18 +2183,19 @@ "name": "stdout", "output_type": "stream", "text": [ - "37 of 74 MODIS acquisitions were collected during daytime\n" + "37 of 74 MODIS acquisitions were collected during the daytime.\n" ] } ], "source": [ - "subsets_day = subsets_df[subsets_df.daytime==True].copy()\n", + "subsets_day = subsets[subsets.daytime==True].copy()\n", "\n", - "print(subsets_day.index.size, \"of\", subsets_df.index.size, \"MODIS acquisitions were collected during daytime\")" + "print(subsets_day.index.size, \"of\", subsets.index.size, \"MODIS acquisitions were collected during the daytime.\")" ] }, { "cell_type": "markdown", + "id": "7e4ddae6", "metadata": {}, "source": [ "#### Data quality\n", @@ -2624,7 +2214,8 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 34, + "id": "a40042fd", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:34.206615Z", @@ -2634,7 +2225,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -2648,18 +2239,19 @@ "source": [ "with xr.open_dataset(subsets_day.iloc[0].path) as ds:\n", "\n", - " # Create a mask for pixels that are \n", - " quality_mask = ds.quality_level[0]==5\n", + " # Create a mask for pixels with acceptable quality or better:\n", + " quality_mask = ds.quality_level[0]>=5\n", "\n", - " # Fill pixels where ###### with np.nan:\n", + " # Fill the unqualified pixels with values of 'np.nan':\n", " masked_ds = ds.where(quality_mask)\n", "\n", - " # Plot the resulting array of sea surface temperature:\n", + " # Plot resulting masked sea surface temperature array:\n", " masked_ds.sea_surface_temperature[0].plot()" ] }, { "cell_type": "markdown", + "id": "627bc9d4", "metadata": {}, "source": [ "### Plot time series from multiple data sources\n", @@ -2677,32 +2269,8 @@ }, { "cell_type": "code", - "execution_count": 39, - "metadata": { - "ExecuteTime": { - "end_time": "2021-03-15T21:11:34.765630Z", - "start_time": "2021-03-15T21:11:34.762616Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'/Users/jmcnelis/tmp/appscitmp/tutorials/notebooks/SWOT-EA-2021/resources/data/20190101141501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4'" - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "subsets_day['path'].iloc[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 40, + "execution_count": 35, + "id": "e48b7245", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:34.971209Z", @@ -2716,41 +2284,30 @@ "16.743005371093773" ] }, - "execution_count": 40, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import warnings\n", - "\n", "def get_user_stat(netcdf, function):\n", " with xr.open_dataset(netcdf) as ds: \n", " output = function(ds)\n", " return output\n", "\n", - "\n", - "def _masked_mean(ds):\n", - " '''Produce any output stat/object you want in this function'''\n", - " # Create a mask for pixels that are \n", - " quality_mask = ds.quality_level[0]>=5\n", - " # Fill pixels with np.nan where quality_level is less than 4:\n", - " masked_ds = ds.where(quality_mask)\n", - " # Ignore warnings about calculating mean over an empty array:\n", + "def _masked_mean(dataset):\n", + " masked = dataset.where(dataset.quality_level[0]>=5)\n", " with warnings.catch_warnings():\n", " warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n", - " # Calculate mean over the XY dimensions (nj, ni in this case)\n", - " value = masked_ds['sea_surface_temperature'].mean(['nj', 'ni']).data.item()\n", - " #value = np.nanmean(masked_sst)\n", + " value = masked.sea_surface_temperature.mean(['nj','ni']).data.item()\n", " return value\n", "\n", - "val = get_user_stat(subsets_day['path'].iloc[0], function=_masked_mean)\n", - "\n", - "val-273.15 # subtract 273.15 to convert Kelvin to Celsius" + "get_user_stat(subsets_day.path.iloc[0], function=_masked_mean) - 273.15" ] }, { "cell_type": "markdown", + "id": "e1c1308d", "metadata": {}, "source": [ "That should give a reasonable value in degrees Celsius.\n", @@ -2762,7 +2319,8 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 36, + "id": "83d7ccd4", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:36.422660Z", @@ -2784,19 +2342,20 @@ "Name: sst_mean, dtype: float64" ] }, - "execution_count": 41, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "subsets_day['sst_mean'] = subsets_day['path'].apply(get_user_stat, args=(_masked_mean,))-273.15\n", + "subsets_day['sst_mean'] = subsets_day.path.apply(get_user_stat, args=(_masked_mean,)) - 273.15\n", "\n", "subsets_day['sst_mean'].describe()" ] }, { "cell_type": "markdown", + "id": "e46ad780", "metadata": {}, "source": [ "We may need to group by the date:" @@ -2804,7 +2363,8 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 37, + "id": "b0cf7608", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:36.435666Z", @@ -2885,7 +2445,7 @@ "max 17.222162" ] }, - "execution_count": 42, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } @@ -2898,6 +2458,7 @@ }, { "cell_type": "markdown", + "id": "8b8fe469", "metadata": {}, "source": [ "Now plot the two time series along the same *date* axis for visual comparison:" @@ -2905,17 +2466,19 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 38, + "id": "829b4816", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:11:36.776275Z", "start_time": "2021-03-15T21:11:36.541708Z" - } + }, + "scrolled": false }, "outputs": [ { "data": { - "image/png": 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\n", 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ffprLL7+cDRs20KlTJw4++GDuvfdeJk+evKPszTffzFNPPcXVV1/NRx99RH5+PgcccAA33XQTU6dObfXPK1dZqlYhbM+GDRvmr7zySqbDiKuqqoqSkpJMhyEppBznNuU3tym/uU35zW3Kb/PeeustvvCFLyTlXmsqq5lVsYry5euo3h6iuGMB44f0ZNKIspQ11kOhEAUF6rPMVdH5be531cxedfdh6YqttZr9bTWzjsC3gDHAEUAPoBNQCawAFgN/cPeWr0IgIiIiIiK7pL6lxcwYN4gZ4wZlOhSRrBW3wW5muwGXAz8AugBvAUuBj4GtwF5AGXAhcJWZ/Q34qbu/mOqgRURERERERHJdoh72d4EPgauBP7p7ZbyCZvZVYCKwwMwuc/d7E5TtBfwYGAYcAhQBZe6+OqrMQ8DZcW6xwt0PTBA3ZrYaaGqSxnh3n5foWhEREREREZFskKjB/v2gjdtIr/qLZjYd6NdM8QHAqcCrQAXwjSbKzADuiTnWD/g98ESQmIAFwPSYYysCXisiIiIiIiKSUXEb7K3piXb3j4CmN+D73Avuvg+AmU2iiQa7u79LuId/BzM7NvLl7IDhbHT3Jc0XkyaV94Kt65ovV9QTxr+f+nhERERERER2MXnxTljYiWYWdxUIMxtsZie2pEJ3r29J+ShnAa+6+xutvF5aoudJkNcxcZm8jtBrbHriERERERER2cXEbbADZxIegl6doMxm4PdmNiGpUcWIzJEfQPDedYATzewzM6sxsyVmNi410eWowdPAEv16AJYPg6alJx4REREREZFdTKIW2UTgQXdfFa9AZKG4B4i/QFyynAXUEv4AIYgngYuA0cAZwDag3Mwmpia8HFTUHcrOjd/LntcR+p8LRfumNy4REREREZFdRKJF54YCdwW4xzOEG8UpYWaFhBep+7O7bwxyjbtfFHOPcmAJcCMwJ0495wPnA/Tu3Zuqqqo2RJ1amzdvTk9FfS+F1c8D2xufyyuEPpdCFv+c2rO05VgyQvnNbcpvblN+c5vy27z6+npCoVCmw2i19h6/JBad3/r6+qxu0wWVqMG+O/BJgHt8EimbKmOBElo2HH4n7l5nZo8CN5tZd3f/oIky9wH3AQwbNsxLSkpaW11apCe+Eug3ElY+APVRjfa8jlA2CfbZLw0x7Lqy/XdQ2kb5zW3Kb25TfnOb8pvYBx98QEFBoiZEdguFQu06fkksOr95eXk58fecaEj8RpreyzxWn0jZVDk7cv+n2ngfizx7G++za2lqLrvmrouIiIhIDnjooYcwM95555201Tl9+nTMbMf3VVVVTJ8+nWXLliW9rsWLFzNmzBh69OhBp06d6NWrF2PGjOF3v/vdTuX++c9/cvLJJ9OnTx8KCwvp3r07o0aN4pe//CUA55xzDmbW7OP5559P+mvY1SVqsP+NYHPTz4mUTToz24fwtm+PuHttG+5TAHwbeM/dP0xWfLuE2LnsmrsuIiIiItJqkyZN4qWXXtrxfVVVFddee23SG+zz5s1j1KhRdOrUibvvvpv58+dzww030LVrV5566vO+0JdffpkjjjiCjRs3csstt7BgwQJuvfVWBg4cSHl5OQDTpk3jpZde2vE477zzAPjb3/620/GhQ4cm9TVI4iHxdwB/M7NfAD92950mMptZB+A24BjgyJZUamanRL48NPJ8nJl9DHzs7oujip4RiTHucHgzCwGz3f28yPcTCA+jfwpYC+wDXBipK6Wr2eeswdNg1YPhr9W7LiIiIiJtUd4Ltq5rvlxRTxj/furjSbNevXrRq1evlNfz85//nCFDhlBeXr5Tj/7ZZ59Nff3nO23fddddlJSUsHDhQgoLC3ccnzhx4o5y++23H/vt9/l02Pnz5wNw+OGHa4pBisXtYXf3l4DLgIuB981sjpndEHnMAd4n3BC+zN2XtLDeRyOP70W+nxn5/tqYcmcDr7t7oo+b8iOPBquAbsCtwELgXqAGGOPuc1sYp8DnvezkqXddRERERNqm50nxdyJqkNcReo1NTzwxRo4cyZFHHskzzzzD0KFD2W233Rg0aBDz5s0LdP2CBQv4yle+wp577knnzp0ZOHAg11133Y7z0UPiV69eTVlZGQCTJ0/eMbT8oYceAqBfv36cc845jeowM6ZPn54wjk2bNtGtW7edGusN8vLydirXpUuXnRrrTZWTzEiYAXe/AxgFvAKMB66IPMZHjo1y9ztbWqm7W5zHyJhyh7j74AD3Oifq+yXufoy77+PuHdx9T3f/ursvaGmcEmXwNOjcT73rIiIiItI2Ta2RFCvDozrfffddLrnkEi699FIef/xxunfvzimnnNLsXPeVK1dy0kknUVZWxh/+8AeeeOIJLr30Uqqrq5ss3717dx5//HEArrjiih1Dy0844YQ2v4bDDjuMhQsXctVVV/Hvf/8b96aX8jrssMN4++23+d73vsfSpUu1in6WaXb8gru/ALxgZnlA18jhSnevS2lkkl2KusNJ72Y6ChERERFp7xpGb8buRNQgC9ZM2rhxIy+88AL7778/AEOHDqV79+788Y9/5Kc//Wnc65YtW8b27dv59a9/zR577AHAMcccE7d8YWEhQ4YMAaB///4cccQRSXsNN910E++88w433HADN9xwA3vssQejRo3iO9/5DqeeeuqOcpdffjnLly/n3nvv5d5776WoqIgjjzySb3/723z3u98lPz8/QS2SaoHHOLh7vbtviDzUWBcRERERkdZJ1MueBWsm7b///jsa6wDdunWjW7duvPfeewC4O6FQaKcHwJe+9CU6dOjA6aefzp/+9Cc2bNiQkfgbYn7hhRdYunQp1113HSNGjOCZZ57htNNOY/LkyTvKFRUVUV5ezhtvvMGtt97KcccdxyuvvML555/P8ccfH7dnXtJDKwSISHrt4gvNiIiICPF72bOgdx1gr732anSssLCQbdu2AeHt0kaNGrXTeXdnwIABLFiwgJtvvpkzzzyTmpoahg8fzi233MLRRx+dlthjDR8+nOHDhwPhFelPOeUUZs2axSWXXMKgQYN2lDvooIM46KCDANi2bRuTJ09mzpw5/OUvf+Gb3/xmRmKXFvSwi4gkRZYvNCMiIiJp0lQvexb0rgdx6KGH8vLLL+/0aDBq1Cjmz59PVVUVzzzzDB06dOCEE05g48aNLa6nU6dObN++87SBTZs2tTrukpISLr74YgDefPPNhPVefvnlzZaT1FMPu4ikV/Q2gfG0k/+sRUREpA1ie9mzpHc9iN13351hw4YlLFNYWMgxxxzDli1bGDt2LKtWraJr165NlgPYunVro3N9+/bl9ddf3+nYn//850Axrl27lt69ezc6/vbbbwPhBe8A3n///Sa3mYstJ5mhBruIpFc7WGhGRERE0iT6g/wc+MD+nnvu4YUXXuD444+nd+/ebNy4kRtvvJEePXrsNPw82j777ENpaSlz587li1/8IsXFxZSVlVFaWsrpp5/Od7/7XX74wx/yzW9+k3/96187tnxrzvHHH0+3bt047bTTGDhwIFu3buWFF17g9ttv58tf/jJf/epXAfje977HRx99xJlnnsmgQYOoq6vj5Zdf5pZbbmG//fZj/PjxyfrxSCtoSLyIpF+WLzQjIiIiadLwQT55OfGB/SGHHEJ1dTVXXHEF3/jGN/jBD35AWVkZzz33HEVFRU1ek5eXx6xZs/jkk0/4+te/zvDhw3nyyScBOPvss7n22mt5/PHHOfHEE1mwYAHl5eWBYrnqqqsoLS3l5ptv5rjjjmP8+PHMmzePyy67jAULFuzYY/2iiy7ioIMO4le/+hVjx47lm9/8Jg888AATJ07kxRdfpHPnzsn54UirWJBV/8zsrASn64FPgeXunhMrRA0bNsxfeeWVTIcRV1VVFSUlJZkOQ1Jol8jx0ilNLzSz3yQY/qvMxZUGu0R+d2HKb25TfnOb8tu8t956iy984QvJvenWD+DpI+HYF1PeYA+FQhQUaJBxrorOb3O/q2b2qrsnnteQBYL+tj4ENLTsLep49LF6M/sDcK67NzHOVdqjNZXV3F+xknnL11NdE6K4sIBxQ3oweUR/+pYWZzo8ac+amsuu3nUREZFdT1F3OOndTEchkpWCDon/KrAGuBs4Gjgw8jwTeA84AbgCGA9MT3qUkhGLVmxgzB0VzF26li01IRzYUhNi7tK1jLmjgkUrMrevpOSAhiFwDSvGa+66iIiIiMhOgjbYfwTMdfdL3L3C3f8Teb4I+D1wvrvfCtwOnJ6qYCV91lRWM2XOMrbW1hGq33naRKje2Vpbx5Q5y1hTWZ2hCCUnRM9lV++6iIiIiMhOgjbYjwWejXPuOeBrka9fAHq2NSjJvPsrVlJbV5+wTG1dPbMqVqUpIslJObbQjIiIiIhIMgVtsG8HDo1z7tDI+Yb7qcs1B8xbvr5Rz3qsUL1TvnxdmiKSnDV4GnTup951ERGRdiLIotUimZRLv6NBF517FLjWzOqAPwEbgG7AtwnPWf9NpNyXgBXJDVEyobomFKzc9mDlROLSQjOSDOW9YGuADxCLesL4nNjQREQkIzp06MDWrVvZbbfdMh2KSFxbt26lsLAw02EkRdAe9kuBx4BbgJXAlsjzzYQb8JdFyr0O/DjJMUoGFBcG+yynuKO2xRCRLNDzpM8XMIwnryP0GpueeEREclS3bt1Yt24dn332WU71Ykr75+7U1tayadMm3n//fUpLSzMdUlIEam25+1ZgopldBxwB7At8APzD3f8TVe4vKYlS0m7ckB7MXbo24bD4gjxj/BAtWSAiWaCpbQJjaWFDEZE222OPPQBYv349tbW1GY6m5err68nLC9pnKe2NmVFcXEyfPn3o1KlTpsNJihZ1j0Ya5/9ptqC0e5NH9OexV9cRqq+LW6ZDfh6TRpSlMSoRkTgaFjBc+QDUb298XtsGiogkzR577LGj4d7eVFVVUVJSkukwJEVyMb+BP14ys2Izu9jM/mRmz5nZ/pHjp5vZgakLUTKhb2kxMycOpahDPgV5ttO5gjyjqEM+MycOpW9pcYYiFBGJEb1NYCz1rouIiEg7FKjBbma9gX8DtwL7A0cDu0dOjyK8T7vkmFEDuzF/6ggmHNaHzoUFmEHnwgImHNaH+VNHMGpgt0yHKCLyuYZe9ti57OpdFxERkXYq6JD424Eawo319Xy+jRvAYsIrxUsO6ltazIxxg5gxblCmQxERaV5Tc9nVuy4iIiLtVNAh8ccC17j7e0DsKmTrAK08JiIimRfby67edREREWnHgjbYOwKb45zbE2h/S0SKiEhuip7Lrt51ERERaceCNtj/DZwc59xxwKvJCUdERKSNGnrZyVPvuoiIiLRrQeew3wr8ycwAHokcO8jMxgLnASelIDYREZHWGTwNPlyg3nURERFp1wL1sLv748AU4NvAM5HDDwNTgR+4+/ygFZpZLzO7y8xeMrPPzMzNrF9MmYcix5t6vB2gjjwzu8LMVpvZNjP7l5nFGyEgIiK5pqg7nPSuetdFRESkXQvaw46732NmvwW+DHQDKoG/u3u8ue3xDABOJTyMvgL4RhNlZgD3xBzrB/weeCJAHTMIbzV3ZaSe04FHzeyb7v5UC+MVERERERERSbvADXYAd6/m8x721nrB3fcBMLNJNNFgd/d3gXejj5nZsZEvZye6uZl1I9xYv8ndb4scXmRmA4CbADXYRUREREREJOvFbbCb2VEtuZG7vxCwXH1L7hvlLOBVd3+jmXKjCa9qPyfm+BzgN2ZW5u6rWhmDiCTJmspq7q9Yybzl66muCVFcWMC4IT2YPKI/fUuLMx2eiIiIiEjGJephf57P91w3Gu+/His/GQE1xcy+Sngo/cUBih8M1ADvxBxvaOgfBKjBLpJBi1ZsYMqcZdTW1ROqD//TsqUmxNyla3ns1XXMnDiUUQO7ZThKEREREZHMStRgHxX1dQlwF/A6MBf4CNgHmEC4gXxhiuJrcBbhvd5/H6DsXkCVu8d+wLAp6nwjZnY+cD5A7969qaqqal2kabB5c0uXDZD2Jpdz/MGnW7nh8eWUdmxqsI0D9dzw+Cvs+50hdN+zKN3hpUUu51eU31yn/OY25Tf3Kce5LRfzG7fB7u6LG742s4eAhe4+KabYw2b2APAt4MlUBGhmhYQXqfuzu28McglNjwawRBe5+33AfQDDhg3zkpKSFkaaXtken7RdunKc7qHptz2/ltWbIVQf/0+yIA8eWV7JjHGDkl5/ttDfcG5TfnOb8pvblN/cpxzntlzLb6Bt3YCxwB/inPtD5HyqjCXcw59wsbkom4AuFtk0PkqXqPMiQnho+pg7Kpi7dC1bakI4nw9NH3NHBYtWbEh6nfOWr98xDD6eUL1Tvnxd0usWEREREWlPgjbY8wjPIW/K/qRw/jpwNrCR4Ku7vwEUAvvFHD8o8vxmkuISadfWVFYzZc4yttbWNWpAh+qdrbV1TJmzjDWV1Umtt7omFKzc9mDlRERERERyVdBt3f4C3GhmG4HH3b3OzPKBk4HrgT+nIjgz24fwtm8z3b024GXzge3AGcC1UccnAq9rhXiRsPsrVlJbl3jThtq6emZVrErq0PTiwgK2BGi0F3ds0a6TIiLJV94LtsaM9snbD+rf3flYUU8Y/3764hIRkV1G0B72i4HXCA9/32pmHwFbCS9A9xrBVm/fwcxOMbNTgEMjh46LHDs6pugZhD9UiDsc3sxCkXn0ALj7BuAXwBVmdqmZjTSzXwPHAD9tSZwiuSxTQ9PHDelBQV7CJSUoyDPGD+mZ1HpFRFqs50mQ1zFxmbyO0CuVMwNFRGRXFqgLK7LY2wgzOxY4AugOfAC85O7PtKLeR2O+nxl5XgyMjDp+NuFe8WUJ7pVP4yH5VwJbgEuAfYEVwKnunpKF8UTao0wNTZ88oj+PvbqOUH1d3DId8vOYNKIsqfVmWvTifl0Kavkk1EH7zotku8HTYNWDictYPgyalp54RERkl9OiMafu/jTwdFsrdffE3WuflzukNfdy9zrCQ/Wvb3l0IruGTA1N71tazMyJQxvtww7hnvUO+XnMnDg0pxqxsfvOlxRo33mRdqGoO5SdCysfgPrtjc/ndYT+50LRvumPTUREdglxh8SbWafW3LC114lIemVyaPqogd2YP3UEEw7rQ+fCAsygc2EBEw7rw/ypI1LaeF1TWc1V815j0DULKPvJXxh0zQKumvda0hfXi64vE4v7iUiSDJ4GFuftknrXRUQkxRJ1na02s5uBB929qrkbmdlXgJ8ALwMzkhOeiKRKpoem9y0tZsa4QWndaz22pxtS39OdqcX9RCRJ4vWyq3ddRETSINGicxcCFwAfmFl5ZAG3r5nZF81soJkdYWbfMbM7zOwd4HnC89rvS0PcItJGDUPTizrkN+ppL8gzijrk59TQ9Ez1dGvf+fRK9wgK2UU01cuu3nUREUmDuA12d38MOJjwdmiFhOeDPw0sJ7yX+YvAHGAs8CfgQHe/wN0/SnXQIpIcmRyanm4t6elOJu07nz6LVmxgzB0VzF26li01IZzPR1CMuaOCRSs2ZDpEaa8aetkbVoxX77qIiKRJwtWkIou3PQY8ZmYdgS8BPYBOQCXwtruvTXWQIpI6mRiangkt6enWvvPtT/QIiliheidUHx5BMX/qiJwZNSJp1rBivKPedRERSZvA7xDdfTuwNIWxSALaEkqkbTLV0z1uSA/mLl2b8MMC7TvfdlorQFJux1z2p9W7LiIiaZNoDrtkCQ3zFGm74sJgn08mu6d78oj+dMhP/E9tLu47n25aK0DSYvA0KOqh3nUREUkbNdiznLaEEkmOTG1jt6st7pcpWitA0qKoOxz9/9S7LiIiaaMGe5bL1EJZIrkmkz3du9LifpmSqREUIiIiIqmkdy5ZLlMLZYnkmoae7th92CHc090hPy+lPd3Ri/tVVVVRUlKSknp2VVorQERERHKRetiznIZ5iiSPerpzl9YKEBERkVzUoh52M8sDDgJKgVfcXROnU0xbQokk166yjd2uJtMjKERERERSIXAPu5ldCHwI/At4DhgYOT7PzC5OTXiSqYWyRETaG42gEBERkVwTqFvWzCYDdwK/ARYCf4w6XQGcDPwy6dEJk0f057FX1xGqr4tbRsM8RUTCNIJCREREcknQHvZLgdvd/XygPObc20R62yX5tCWUiIiIiIjIrilog70MWBDnXDVQkpRopEka5ikiIiIiIrLrCbpS2UagX5xzA4F1SYlG4tKWUCIiIiIiIruWoD3sTwJXm1n/qGNuZl2BHwLzkh2YiIiIiIiIyK4saA/7VcAxwOvAPwAnvMjcgcAG4LqURCciIiIikmvKe8HWAANUi3rC+PdTH4+IZK1APezuXgkMA24EOgDvEm7s3w182d0/TVmEIiIiIiK5pOdJkNcxcZm8jtBrbHriEZGs1WwPu5l1BG4GHnH3GcCMlEclIiIiEmNNZTX3V6xk3vL1VNeEKC4sYNyQHkwe0V+7pUj7MngarHowcRnLh0HT0hOPiGStZnvY3X07cAFQlPpwRERERBpbtGIDY+6oYO7StWypCeHAlpoQc5euZcwdFSxasSHTIYoEV9Qdys6N38ue1xH6nwtF+6Y3LhHJOkEXnVsODE5lICIiIiJNWVNZzZQ5y9haW0eo3nc6F6p3ttbWMWXOMtZUVmcoQpFWGDwNLM5bcfWui0hE0Ab7ZcCPzOybZmZtqdDMepnZXWb2kpl9ZmZuZv3ilD3CzOabWZWZVZvZa2Z2eoA6VkfuG/sY15bYRUREJP3ur1hJbV19wjK1dfXMqliVpohEkiBeL7t610UkStAG+6NAKfD/gG1mttbM3ot6rGlBnQOAU4FPgIp4hczsBOAF4EPgO8BY4H6gU8B6FgBfjnksbkGcIiIikgXmLV/fqGc9VqjeKV8eYNVtkWzSVC+7etdFJErQbd2eJbyVWzK84O77AJjZJOAbsQXMbHfgQWCmu0+NOvVMC+rZ6O5L2hKoiIiIZF51TShYue3ByolkjYZe9pUPQP129a6LSCOBGuzufk6yKnT3xGPawr4N7A3cnqx6RUREpH0qLixgS4BGe3HHoP0QIlkkesV49a6LSIygQ+LT7UhgEzA4Mm89FBmGf42Z5Qe8x4mROfI1ZrZE89dFRETap3FDelCQl3gJnYI8Y/yQnmmKSCSJGnrZyVPvuog0EuijaDM7q7ky7v5w28PZoQewG/AI4X3fXwW+DkwDSoAfNnP9k8DLwCpgH+AHQLmZnenuc5q6wMzOB84H6N27N1VVVW1+EamyefPmTIcgKaYc5zblN7cpv8l3xpCuLHlrLdtC8WfndSowvjOkNOX/fyu/uS1j+e17KXzwBvS5FLL4PWgu0N9wbsvF/Jp781PTzSzeMPYdF7t70J7v6PtOIryQXJm7r446vhA4FrjM3X8edfzXwHnA3u7+aQvqyQeWAPu6e+/myg8bNsxfeeWVwK8j3aqqqigpKcl0GJJCynFuU35zm/KbGotWbGDKnGXU1tXvtABdQZ7RIT+PmROHMmpgt5THofzmNuU39ynHua0l+TWzV919WGojarugQ+LLmngMA64F/gscnuS4KiPPT8ccXwh0AA5uyc3cvY7wSve9zKx728MTERGRdBo1sBvzp45gwmF96FxYgBl0LixgwmF9mD91RFoa6yIiIukWdNG5prZtWwMsi+zLfinhrdeS5Y2GqmOON0xgC7JwXayGa5O12r2IiIikUd/SYmaMG8SMcYMyHYqIiEhaJGPRuQrghCTcJ9q8yPOYmOOjgW3A6y25mZkVEF55/j13/7DN0YmIiIiIiIikWDL2PzkC2NKSC8zslMiXh0aejzOzj4GP3X2xu79uZg8B15lZHrCM8KJzk4AZ7r4l6l4hYLa7nxf5fgIwFngKWEt40bkLI3VNaN1LFBEREREREUmvoKvEX93E4Y7AIMK963e3sN5HY76fGXleDIyMfH0BsA64iHCjezVwqbvfGXNtfuTRYBXQDbgV2Av4jPCK8WPcfUEL4xQRERERERHJiKA97NObOFZDeB77DcCNLanU3RNvphousx24KvIIfC93XwIc05J4RERERERERLJN0EXnkjHXXURE0mxNZTX3V6xk3vL1VNeEKC4sYNyQHkwe0Z++pcWZDk9EREREEgjUEDezo8ysc5xznc3sqOSGJSIibbVoxQbG3FHB3KVr2VITwoEtNSHmLl3LmDsqWLRiQ6ZDFBEREZEEgvacLwIOinNuYOS8iIhkiTWV1UyZs4yttXWE6nfezTJU72ytrWPKnGWsqazOUIQiIiIi0pygc9gTzTkvBOqSEIuIiCTJ/RUrqa2rT1imtq6eWRWrtKe1SDOip5Z0Kajlk1AHTS0REZG0iNtgN7N+QP+oQ8OaGBZfBHwXeC/5oYmISGvNW76+Uc96rFC9U758nRrsIgksWrGBKXOWUVtXT6jeKSn4fGrJY6+uY+bEoYwa2C3TYYqISI5K1MN+NnAN4JHHXezc0+6R70OE9zkXEZEsUV0TClZue7ByIrui6KklsUL1Tqg+PLVk/tQR6mkXEZGUSNRgfwh4nnCj/DnCjfI3Y8rUAP9x902pCE5ERFqnuLCALQEa7cUdg86MEtn1aGqJiIhkWtx3au6+hvA+65jZKOBVd9+SrsBERKT1xg3pwdylaxMOiy/IM8YP6ZnGqETaF00tERGRTAu0Sry7L1ZjXUSk/Zg8oj8d8hP/E98hP49JI8rSFJFI+6OpJSIikmlBt3XDzEabWbmZvWlmK2Me76YySBERaZm+pcXMnDiUog75FOTtvNFHQZ5R1CGfmROHat6tSALFhcGmjGhqiYiIpEqgBruZHQ88BewGHAi8TXhl+N5APfBCqgIUEZHWGTWwG/OnjmDCYX3oXFiAGXQuLGDCYX2YP3WEVrYWaca4IT0afeAVS1NLREQklYJ+JDwN+BXwQ6AWuMrdl5nZAcAC4K8pik9ERNqgb2kxM8YN0vxakVaYPKI/j726jlB941XiG2hqiYiIpFLQBvuBwNWEe9O94Tp3/4+ZTSfcoP9jKgIUERERyYSGqSXR+7A3KMgzOuTnaWqJiGSP8l6wdV3z5Yp6wvj3Ux+PJEXQOez1QMjdHfgY6BN1bj2wX7IDExEREck0TS0RkXaj50mQ1zFxmbyO0GtseuKRpAjaw74C6Bf5+hVgqpm9CISAy4DVSY9MREREJAtETy2pqqqipKQk0yGJiDQ2eBqsejBxGcuHQdPSE48kRdAe9t8BX4h8fQ1wMPA+8CFwDOHh8iIiIiIiIpIJRd2h7Nz4vex5HaH/uVC0b3rjkjYJ1MPu7r+K+vpVMxsMjCG8avwz7v5miuITERERERGRIBL1sqt3vV1qtofdzDqa2SVmtmOJYXd/391nufsv1VgXERERERHJAvF62dW73m4122B39+3ATcBeqQ9HREREREREWm3wNLCYZp5619utoHPY3wL6pzIQERERERERaaPYXnb1rrdrQRvsVwPTInPXRUREREREJFtF97Krd71dC7qt24+BzsByM1sNfAB41Hl396OTHJuIiIiIiIi0VEMv+zv3qne9nQvaYK8DtLiciIiIiIhIezB4Gny4QL3r7VzQbd1GJqtCM+tFuMd+GHAIUASUufvqJsoeAUwHjgA6ACuBG9x9bjN15EXquADYF1gBXOfujyXrdYiIiIiIiGStou5w0ruZjkLaKOgc9mQaAJwKfAJUxCtkZicALwAfAt8BxgL3A50C1DGDcEP/buA4YAnwqJkd35bARURERERERNIl6JB4zKwncBlwFFAKnOjur5vZVOAld/9HwFu94O77RO45CfhGE3XtDjwIzHT3qVGnngkQZzfgR8BN7n5b5PAiMxtAeHu6pwLGKSIiIiIiIpIxgXrYzexg4DXgTGA90AeI7BNAX+CSoBW6e32AYt8G9gZuD3rfKKMJxzYn5vgcYLCZlbXiniIiIiIiIiJpFXRI/O2E92IvA74FWNS5vxOeY55MRwKbCDewXzOzkJmtNbNrzCy/mWsPBmqAd2KOvxF5PijJsYqIiIiIiIgkXdAh8UcCE9x9SxMN5o8IL+yWTD2A3YBHCM9HfxX4OjANKAF+mODavYAqd/eY45uizjdiZucD5wP07t2bqqqqVoaeeps3b850CJJiynFuU35zm/Kb25Tf3PPBp1spX76O59/+mD0KQvwvVMDIA/dm/JCedN+zKNPhSZLpbzi35WJ+gzbYEw1j7wpsTUIs0fIILy53pbv/PHLseTMrBS40s+nu/mmca42d94iPPh6Xu98H3AcwbNgwLykpaVXg6ZLt8UnbKce5TfnNbcpvblN+c8eiFRuYMudf1NbVE6p3ehUb71fXs3LpBn776kZmThzKqIHdMh2mJJn+hnNbruU36JD4pcC5cc6dCryYnHB2qIw8Px1zfCHh7d0OTnDtJqCLmcU20LtEnRcREZFWWlNZzVXzXmPQNQso+8lfGHTNAq6a9xprKqszHZpIYGsqq5kyZxlba+sI1e/c1xOqd7bW1jFlzjL9XotIRgVtsM8ATjSzhYQXnnPg62Y2GxgP3JDkuBrmm8f2lDc0whP1+L8BFAL7xRxvmLv+ZttCExER2XUtWrGBMXdUMHfpWrbUhHBgS02IuUvXMuaOChat2JDpEEUCub9iJbV1iddCrq2rZ1bFqjRFJCLSWKAGu7svBsYRXnTuN4QbzjcBI4BxLdjSLah5kecxMcdHA9uA1xNcOx/YDpwRc3wi8Lq7619dERGRVlCPpOSSecvXN/o9jhWqd8qXr0tTRCIijQXeh93d/wL8JbKfeTeg0t1XtKZSMzsl8uWhkefjzOxj4GN3XxzZ3/0h4DozywOWEV50bhIww923RN0rBMx29/MicW4ws18AV5jZ5si1pwHHAGNbE6+IiIi0rEdyxrhBaYpKpHWqa0LBym0PVq49WVNZzf0VK5m3fD3VNSGKCwsYN6QHk0f0p29pcabDE5EogRvsDdz9HRpvmdZSj8Z8PzPyvBgYGfn6AmAdcBGwD7AauNTd74y5Nj/yiHYlsIXw/vD7AiuAU939yTbGLSIisstqSY+kGuyS7YoLC9gSoNFe3LHFb5ezWnihvWU7FtqDz6e1PPbqOi20J5Jlgs5hx8z2N7PZZvYfM6uOPD8U6XFvEXe3OI+RUWW2u/tV7t7b3Tu6+wFNNNYb7nVOzLE6d7/e3fu6e6G7f9Hd/9TSOEVERORzu3KPpOSecUN6UJCXcBMhCvKM8UN6pimi1NO0FpH2J1CD3cxGAv8CvgksIdwjvgQ4EXjNzI5OUXwiIiKSJYoLg/U05lqPpOSmySP60yE/8VvhDvl5TBpRlqaIUk8L7Ym0P0F72G8HlgN93f0sd7/c3c8C+gH/jJwXERGRHLYr9khK7upbWszMiUMp6pDf6Pe6IM8o6pDPzIlDc2pOtxbaE2l/gjbYDwJujl7sDcDdNwM3k3hfdBEREckBu2KPpOS2UQO7MX/qCCYc1ofOhQWYQefCAiYc1of5U0fk3FxuTWsRaX+Cjll7H+gY51xHwovDiYiISA5r6JGMXbAKwj2SHfLzcq5HUnJf39JiZowbxIxxg6iqqqKkpCTTIaXMrrrQnkh7FrSH/WbgWjPbaYxb5PtrgJ8lOzARERHJPrtaj6RILtG0FpH2J+jHZ0cDuwPvmtkS4CPCW60dEfl6ZGRhOgB397OTHKeIiIhkiegeSRFpPyaP6M9jr64jVF8Xt4ymtYhkl6AN9iOBOuADoG/kQeR7gBFRZROvZCEiIiIiImmnaS0i7U+gBru762M2EREREZF2rmFay6yKVZQvX0f19hDFHQsYP6Qnk0aUqbEukmW0ooSIiIiIyC5E01pE2o8WNdjNrDfQG+gUe87dn0tWUCIiIiIiIiK7ukANdjPrD/wOOKzhUOTZI187kJ/06ERERERERER2UUF72GcBfYCpwNvA9lQFJCIiIiIiIiLBG+zDgXPc/bFUBiMiIiIiIiIiYUEb7O+jXnUREREREWmlNZXV3F+xknnL11NdE6K4sIBxQ3oweUR/rU4vEkdewHI/A35sZvpLEhERERGRFlm0YgNj7qhg7tK1bKkJ4cCWmhBzl65lzB0VLFqxIdMhimSloPuw/9bMDgRWm9kS4JPGRfzspEcnIiIiIiLt2prKaqbMWcbW2rpG50L1Tqi+jilzljF/6gj1tIvECLpK/DnAFUAdMJTGw+M9uWGJiIiIiEguuL9iJbV19QnL1NbVM6tilfaGF4kRdEj8tUA5sLe793T3sphH/xTGKCIiIiIi7dS85esJ1Sfu3wvVO+XL16UpIpH2I2iDvRSY6e5VKYxFRERERERyTHVNKFi57cHKiexKgjbY/wZ8IZWBiIiIiIhI7ikuDLYxVXHHoBtYiew6gjbYLwEmm9kZZlZqZnmxj1QGKSIiIiIi7dO4IT0oyLOEZQryjPFDeqYpIpH2I2hD+y1gMPAwsAGojXloj3YREREREWlk8oj+dMhP3OzokJ/HpBFlaYpIpP0IOu7kOrQSvIiIiIiItFDf0mJmThzKlDnLqK2r32kBuoI8o0N+HjMnDtWWbiJNCLoP+/RkVWhmvYAfA8OAQ4AioMzdV0eV6QesinOLLs0tfmdmq4G+TZwa7+7zWhqziIiIiIi03qiB3Zg/dQSzKlZRvnwd1dtDFHcsYPyQnkwaUabGukgcLV7Zwcw6E141fr2717aizgHAqcCrQAXwjQRlbwSeiDm2OWA9C4DpMcdWBLxWRERERESSqG9pMTPGDdJe6yItELjBbmbfJDw0/pDIoeHAMjObBTzn7o8EvNUL7r5P5J6TSNxgX+nuS4LGGGNjG64VERERERERyahAi86Z2Tjg/wEbCQ9nj17mcRVwdtAK3b2+BfGJiIiIiIiI7JKCrhJ/DfCgu38DuCPm3OtAqsa13GhmITP71MyeMLPBLbj2RDP7zMxqzGxJ5EMHERERERERkXYhaIP9C8AfIl/Hrhb/CeE57clUA9wLXACMAn5EeFu5v5vZFwJc/yRwETAaOAPYBpSb2cQkxykiIiIiIiKSEkHnsP8P6BrnXD/g46REE+HuHwDfizpUYWbzgTeAK4GEDW93vyj6ezMrB5YQXsRuTlPXmNn5wPkAvXv3pqqqqrXhp9zmzUHX3ZP2SjnObcpvblN+c5vym9uU39ynHOe2XMxv0Ab708AVZvZXPl+l3c2sEPgB8NdUBBfN3dea2d8IL3bX0mvrzOxR4GYz6x75QCC2zH3AfQDDhg3zkpKStoacUtken7SdcpzblN/cpvzmNuU3tym/uU85zm25lt+4Q+LNbKWZNawIfyWwL+Ft0WYRHhb/E+CfQC8ab5+WKkbjIfktuZY2XC8iIiIiIiKSNonmsPcDCgHcfTUwFPgzcCxQBxxFeJj54e6+PqVRAmbWB/gq8I9WXFsAfBt4z90/THZsIiIiIiIiIskWeB92d38fOC8ZlZrZKZEvD408H2dmHwMfu/tiM7ud8IcJLxGeHz8QuAKoB34Wc68QMNvdz4t8PwEYCzwFrAX2AS6M1DUhGfGLiIiIiIiIpFpzDfZUDR9/NOb7mZHnxcBIwovLfR84B9id8P7vzwHXuvuKmGvzI48Gq4BuwK3AXsBnwMvAGHdfkLRXICIiIiIiIpJCzTXYrzWzjQHu4+5+dtBK3d2aOf8b4DetuZe7LwGOCRqLiIiIiIiISDZqrsH+JcJ7ojdHC7mJiIiIiIiIJFFzDfZx7r40LZGIiIiIiIiIyA6JVokXERERERERkQwJvEq8iIiIiIiISFPWVFZzf8VK5i1fT3VNiOLCAsYN6cHkEf3pW1qc6fDaLTXYRUREREREpNUWrdjAlDnLqK2rJ1QfXt5sS02IuUvX8tir65g5cSijBnbLcJTtU9wh8e6ep/nrIiIiIiIiEs+aymqmzFnG1tq6HY31BqF6Z2ttHVPmLGNNZXWGImzfNIddREREREREWuX+ipXU1tUnLFNbV8+silVpiii3qMEuIiIiIiIirTJv+fpGPeuxQvVO+fJ1aYoot6jBLiIiIiIiIq1SXRMKVm57sHKyMzXYRUREREREpFWKC4OtY17cUeudt4Ya7CIiIiIiItIq44b0oCDPEpYpyDPGD+mZpohyixrsIiIiIiIi0iqTR/SnQ37iZmWH/DwmjShLU0S5RQ12ERERERERaZW+pcXMnDiUog75jXraC/KMog75zJw4lL6lxRmKsH1Tg11ERERERERabdTAbsyfOoIJh/Whc2EBZtC5sIAJh/Vh/tQRjBrYLdMhtlua+S8iIiIiIiJt0re0mBnjBjFj3KBMh5JT1MMuIiIiIiIikoXUYBcRERERERHJQmqwi4iIiIiIiGQhNdhFREREREREspAa7CIiIiIiIiJZSA12ERERERERkSykBruIiIiIiIhIFlKDXURERERERCQLqcEuIiIiIiIikoXS3mA3s15mdpeZvWRmn5mZm1m/mDL9IsebepQEqCPPzK4ws9Vmts3M/mVmJ6fqNYmIiIiIiIgkWyZ62AcApwKfABXNlL0R+HLMY3OAOmYA04G7geOAJcCjZnZ860IWERERERERSa+CDNT5grvvA2Bmk4BvJCi70t2XtOTmZtYN+BFwk7vfFjm8yMwGADcBT7UiZhEREREREZG0SnsPu7vXp7iK0UBHYE7M8TnAYDMrS3H9IiIiIiIiIm2W7YvO3WhmITP71MyeMLPBAa45GKgB3ok5/kbk+aCkRigiIiIiIiKSApkYEh9EDXAvsBD4GDgQ+CnwdzM7zN3fSnDtXkCVu3vM8U1R5xsxs/OB8yPfbjGzFa0NPg26AhszHYSklHKc25Tf3Kb85jblN7cpv7lPOc5tQfPbbn4HsrLB7u4fAN+LOlRhZvMJ95JfCUxMcLkBsY31huOJ6rwPuK+FoWaEmb3i7sMyHYekjnKc25Tf3Kb85jblN7cpv7lPOc5tuZjfbB8Sv4O7rwX+BgxvpugmoIuZxTbQu0SdFxEREREREclq7abBHhGv9zzaG0AhsF/M8Ya5628mOygRERERERGRZGs3DXYz6wN8FfhHM0XnA9uBM2KOTwRed/dVKQgv3drF0H1pE+U4tym/uU35zW3Kb25TfnOfcpzbci6/1nhttjRUanZK5MuvEZ6rPoXw4nIfu/tiM7ud8IcJL0WODwSuAPYEDnf3FVH3CgGz3f28qGM3AVMJL1S3DDgNuAAY6+5PpvbViYiIiIiIiLRdphadezTm+5mR58XASMLD2r8PnAPsTngVv+eAa6Mb6xH5kUe0K4EtwCXAvsAK4FQ11kVERERERKS9yEgPu4iIiIiIiIgk1m7msKeKmZ1iZo+Z2Roz22pmK8zsRjPbPaZcFzObZWYbzazazJ4xs8FN3O9nZrbQzCrNzM3snDj1djWz35jZx5F6/2Fmo1sQdyczu9XMPohc/5KZHdVEuUvN7MlIOTez6UHrSGc9qaL8Jq2e1ZH7xz7GtaS+VFCOk1ZPm15Pqii/zdbT7Osxs93N7I9m9k7kZ1MVeT2JtkhNC+W32XqC5Pcca/rf54bHvi2pM5mU34R1DDOz+8zsbTP7zMzeM7PfmVlZMutJNeU4YR0tyXFWvs9SfhPW0ZL8tu09lrvv0g9gCfBHwovUHU147ntV5HhepIwBFcD7wARgDOHh+xuBXjH32xwpO5vwivbnNFFnIfBvYD1wLnAc8CegFhgZMO7fReKcTHgtgMeBrcCXYsq9RXihvl9H4pnewp9PWupRfrM+v6sJL+h4RMyji3Lc/nOcjNej/GYsv0FeTynwCHBeJJbjo8r/UPlt9/ndm8b/Nn858vNZqvxmZ36B24AXCa/jdDTwncj9KoHeyfw9Uo7bRY5Xk4Xvs5Tftuc3Ka8nk78E2fAA9m7i2FmRpB0T+X5s5PtRUWX2JLyn+y9jrm345R2Q4BdxYuTcyKhjFklms/+5AodErj836lgB4bn6T8SJp6AVv4hpqUf5bRf5XQ3MyXQ+lePU5Litr0f5zUx+g76eBNe+BLym/OZefoERkfIXKr/Zmd84P5u+QD1wXTJ/j5TjdpHj1WTh+yzlt+35bevrcXcNiXf3j5s4/HLkuWfk+SRgvbsvirruU+BJwr+k0ferD1DtEYQ/5VkcdZ0DC4HhZtYz3oVR8dQCf4i6PgTMBUabWWEL48l0PSmj/CannmymHCelnra+npRRfhNr4/WVhOPMGOU3sTZcfzbhLW7ntqX+tlJ+42vqZ+PuawjvjtQz5nhWvscC5TiRluQ4Wym/8bUgv21+j7XLN9jjODry/Fbk+WDg9SbKvQH0MbPOLbx/HVAbSVa0msjzoGauPxhY5e6fNRFPR8KfWiVDuupJN+W3dfWcGJmjU2NmSzI9r6oZynHL6mnr60k35bcVLKzAzErN7HxgNHBHJmJphvLbBmZWBHwb+LO7V2YyljiU3zjM7AtANz7/2bRXynEczeS4vbzPUn7jiJPfNr/HUoM9RuRTjuuAZ9z9lcjhvYBPmii+KfLcpYXVrAD2iCQ12pej6kukuXiauz6odNWTNspvq+t5EriI8Bv8M4BtQLllwaJVsZTjVtXT1teTNspvm1xIuNdhI3A3cIm7P5yhWJqk/CbFOGAPwnNEs4ryG5+ZFQD3EO6deyAVdaSDchxfMzluF++zlN/4EuS3ze+x1GCPEvkE6P8BIcKLAuw4RXjuQaNLWlnVI4STOdvMBkdWDvwp0LB6YX0knvxIb0jDoyFfSY0nXfVkmvLb+nrc/SJ3f9jdK9z9T4QX8HgFuLE1MaWKctzqegK9nkxTfhvV01J/AIYTXvBmFnCXmV3QynslnfLb5vw2OJvw63uqjfdJKuW32fzeDXwFmOjuTTU2sp5y3Poct4f3Wcpvq/Pb5vdYarBHmFkn4AmgPzDa3d+POr2Jpj/9aPjEqEX/sLp7FXAy0JXwggMfA98FpkeKfBB5fpZwb0jD4+qA8Wxq4lwi6aonY5Tf5Nbj7nXAo0AvM+vewnhSQjlufT0teD0Zo/w2WU+LuPvH7v6Ku8939ynAb4HbzKxDa+6XTMpv2/MLEPn3+OvA7yJzNrOC8ps4v2Z2I3A+8F13X9jC+2cF5Ti5Oc6291nKb+vzm4z3WAUtDDgnRd6sPAYcBnzd3V+LKfIG8I0mLj0IeM/dt7S0TnevMLP9CM+jyAf+A1xOeFGCZZFiFwDR+xyuj4pnvJntFjM/4yDCi8y808Jw0lVPRii/Kaun4ZPKpj7FTCvluO31BHw9GaH8xq2nrV4h3Bu7D+HteDJC+U1qficSfj1ZMxxe+U2cXzO7EvgJcLG7/7aF984KynHKcpwV77OU37bnt83vsTwLtgzI5IPwKIM/Ep4r8rU4ZcYR/mM5OurYHoRX2L0rzjUt3YKlM+FfoHsDlP1S5N5nRx0rILzAwZNxrmnNdgVpqUf5bT/5jSn3CrBGOc7ZHAd+PcpvZvLbltcTueZRwnvidlR+cyO/wGvAvzKVT+W3xdv2XRy57qcBy2fVeyzlOPk5jqkv4++zlN+U5bdF77HUww6/Irya6g1AtZkdEXXufQ8P+XiC8H61c8zscsJDO64g/MnXLdE3M7Ojgb2BfSOHhpnZFgAPz0lpKHcj8CrhxX8GEP6UpTZy34Tc/Z9m9gfgjsinXquA7wNlhBeqiI5nGNCPz6c/HGRmp0S+fsobr6CY9npSTPltYz1mNoHwthxPAWsJ98ZdCBwKTGju9aSBcpycelr9elJM+U0gyOux8Dz1I4BnCPeklwKnAqcAP3H37c29phRSfhMI+noiZYcSXm34suZeQxopv3GY2emEd2mYDzwX87P5n7u/mYx60kA5jiNojrP8fZbyG0cL/4bb9h6rrZ+8tPcHsJrwJyNNPaZHldsL+A3heQ+fEZ7PcEgT93s+3v1iyv2G8Bun7ZHnu4C9WhB3EfBz4EPCn3r9AxjZRLmHEry+ftlSj/Kbvfkl/Eb/OeAjwv+4fEr4jf/oTOVVOU7J33CbXo/ym7H8Nvt6CC+C8xTheXI1wDrCf8MnKL/tP79RZe8k/G/0PpnOq/LbfH6bufb5ZP4eKcfZnWOy+H2W8pu0v+E2vR6L3EREREREREREsohWiRcRERERERHJQmqwi4iIiIiIiGQhNdhFREREREREspAa7CIiIiIiIiJZSA12ERERERERkSykBruIiIiIiIhIFlKDXUREJEeZ2fNm9nwLrxlpZtPNTO8RREREMkz/GYuIiEi0kcA16D2CiIhIxuk/YxEREREREZEspAa7iIhIDjCz083sbTOrMbM3zGx8zPlOZvYLM3vdzLaY2Ydm9qSZHRhVZjrh3nWAWjNzM/Oo87uZ2c1mtsrMtkeer9TweRERkdQoyHQAIiIi0jZm9nXgEeAvwGXA3sCdQAdgRaRYIbA7cD3wAbAXMAVYYmYHuvuHwCygF3AecCRQF1VHAbAAOAiYAbwGHAFMi9zrspS+SBERkV2QuXvzpURERCRrmdmLQBdgkLvXR44dDiwBFrv7yCauySfciP8IuNrdfxE5Pp1wL3sHdw9FlT8TeBg42t1fiDp+ZaR8L3ffkJIXKCIisovSEDYREZF2LNLwHg78qaGxDuDu/wBWx5Q91cz+YWZVQAioBjoDAwNUNQZYA/zdzAoaHsBCwj35RyTh5YiIiEgUDYkXERFp37oSbjB/1MS5HcfM7ETgD8Bs4FpgI1APPAV0ClBPN6AvUBvnfGnwkEVERCQINdhFRETat42EG9H7NHFuH8K94gCnA++4+zkNJ82sA+H550FUAquAU+OcXx3wPiIiIhKQGuwiIiLtmLvXmdnLwClmNj1mDns/Pm+w70Z4GHy0M4H8mGM1keciYHPU8fnAycAWd387ea9ARERE4lGDXUREpP27hvBc8nlmdi/hVeKvBT6MKjMfGGdmvwD+DBwKXAxUxdzrzcjzZWb2V6DO3V8BfgecCzxrZrcD/wI6AvsBJwHj3P2zFLw2ERGRXZZWiRcREckBZjYBmE64V/0d4CrgEgB3HxnZK/064LtACfAyMBUoB55vGCofWcTul8C3Cc+PN3e3yLlOwE8ID68vI7xo3buEt5O7PnpVeREREWk7NdhFREREREREspC2dRMRERERERHJQmqwi4iIiIiIiGQhNdhFREREREREspAa7CIiIiIiIiJZSA12ERERERERkSykBruIiIiIiIhIFlKDXURERERERCQLqcEuIiIiIiIikoX+P6dOTwnJmx21AAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] @@ -2929,27 +2492,22 @@ "source": [ "fig, ax = plt.subplots(figsize=(16, 4))\n", "\n", - "# Plot mean sea surface temperature from MODIS SST from GHRSST\n", - "subsets_day_means.plot.scatter(\n", - " x=\"date\",\n", - " y=\"sst_mean\", \n", - " label=\"SST observed by MODIS\",\n", - " s=100,\n", - " ax=ax\n", - ")\n", - "\n", - "# Plot mean sea surface temperature from the Argo floats\n", - "argo_skinny.plot.scatter(\n", - " x=\"date\",\n", - " y=\"temp_at_pres_min\",\n", - " s=100,\n", - " color=\"orange\",\n", - " marker=\"v\",\n", - " label=\"SST measured by Argo floats\",\n", - " ax=ax\n", - ")\n", - "\n", - "# Matplotlib aesthetic treatments starting from here -->\n", + "# Mean sea surface temperature from MODIS/GHRSST:\n", + "subsets_day_means.plot.scatter(x=\"date\",\n", + " y=\"sst_mean\", \n", + " label=\"L2 MODIS SST\",\n", + " s=100,\n", + " ax=ax)\n", + "\n", + "# Mean sea surface temperature from Argo floats:\n", + "argo_skinny.plot.scatter(x=\"date\",\n", + " y=\"temp_at_pres_min\",\n", + " s=100,\n", + " color=\"orange\",\n", + " marker=\"v\",\n", + " label=\"In-situ SST\",\n", + " ax=ax)\n", + "\n", "ax.set_ylabel(\"Temperature (deg C)\")\n", "ax.set_ylim(15.0, 18.0)\n", "ax.grid(alpha=0.25)" @@ -2957,6 +2515,7 @@ }, { "cell_type": "markdown", + "id": "c7f23b33", "metadata": {}, "source": [ "### MUR Level 4 SST from AWS Open Registry\n", @@ -2966,7 +2525,8 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 39, + "id": "d3bde6e0", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:12:19.508537Z", @@ -2981,36 +2541,34 @@ "\n", "dask.array\n", "Coordinates:\n", - " * time (time) datetime64[ns] 2019-01-01T09:00:00 ... 2019-01-31T09:00:00\n" + " * time (time) datetime64[ns] 2019-01-01T09:00:00 ... 2019-01-31T09:00:00\n", + "CPU times: user 6.03 s, sys: 860 ms, total: 6.89 s\n", + "Wall time: 8.05 s\n" ] } ], "source": [ + "%%time\n", "import fsspec\n", "import xarray as xr\n", "from dask.distributed import Client\n", "\n", - "# Reference the MUR L4 SST data on the AWS Open Registry\n", - "url = 's3://mur-sst/zarr'\n", + "fs = fsspec.get_mapper('s3://mur-sst/zarr', anon=True)\n", "\n", - "# Open the remote dataset from its S3 endpoint (pre-consolidated)\n", - "ds = xr.open_zarr(fsspec.get_mapper(url, anon=True), consolidated=True)\n", + "ds = xr.open_zarr(fs, consolidated=True)\n", "\n", - "# Slice the dataset along its X, Y, and T dimensions:\n", - "mur_L4_subset = ds['analysed_sst'].sel(\n", - " time=slice('2019-01-01','2019-01-31'),\n", - " lat=slice(aoi_minlat, aoi_maxlat), \n", - " lon=slice(aoi_minlon, aoi_maxlon),\n", - ").persist()\n", + "sst = ds['analysed_sst'].sel(time=slice(start_date, end_date),\n", + " lat=slice(aoi_lat_min, aoi_lat_max), \n", + " lon=slice(aoi_lon_min, aoi_lon_max), ).persist()\n", "\n", - "# Aggregate the spatial dimensions to compute the one-dimensional time series of means:\n", - "mur_L4_subset_means = mur_L4_subset.groupby(\"time\").mean([\"lon\", \"lat\"])-273.15\n", + "sst_mean = sst.groupby(\"time\").mean([\"lon\", \"lat\"]) - 273.15\n", "\n", - "print(mur_L4_subset_means)" + "print(sst_mean)" ] }, { "cell_type": "markdown", + "id": "d62d9aa6", "metadata": {}, "source": [ "Add the MUR time series to the subsets table so that they share the same time axis with the L2 time series:" @@ -3018,7 +2576,8 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 40, + "id": "6c0b38eb", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:12:19.564312Z", @@ -3027,11 +2586,12 @@ }, "outputs": [], "source": [ - "subsets_day_means['L4_MUR_SST'] = mur_L4_subset_means.compute().data" + "subsets_day_means['L4_MUR_SST'] = sst_mean.compute().data" ] }, { "cell_type": "markdown", + "id": "ede75919", "metadata": {}, "source": [ "Plot the result alongside our data processed throughout the notebook:" @@ -3039,27 +2599,29 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 41, + "id": "65fdcfbd", "metadata": { "ExecuteTime": { "end_time": "2021-03-15T21:12:19.825875Z", "start_time": "2021-03-15T21:12:19.566301Z" - } + }, + "scrolled": false }, "outputs": [ { "data": { "text/plain": [ - "Text(0.5, 1.0, 'Daily SST from L2 MODIS, L4 MUR, and in situ measurements (January 2019)')" + "Text(0.5, 1.0, 'Daily SST from L2 MODIS, L4 MUR, and in-situ measurements (Jan 2019)')" ] }, - "execution_count": 46, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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HbrbOs5Qe98R8B3yafsNa632YGg31lFL1HOz7OW3bueUnmIeMWblmwdx32JRGauOsk/Tplcf8hp7Iyg61gw4ltSlpXARUU457dF+ntf4qXfoUwNrJYFbfsyfy87PWeoGD+Tm+l3Mmk3uFIpiHPI5Y50dkd9+YkukUYICl1ow1T0GYWhNWjvZh/X2LdLBM5JD0Yi28wWG1HaWUtU1iA0w1v/QPcLITRKC1Pq2UWoKpgllRp7ULeQRzs/Cp05Vtt7MPiFZKNcLceNyCucnsaJk+U0rdr7V5rKdNm5beSqmXgE5ANKYn7yaW6RGlVIzW+nR23lcO/exgXgPL61r7BVrrE0qpPcDNSqlwna4dDqY0WNutYh1S6jcy+g/TnqcMcDQrmc4KpdTtmOpiRzDBUnbNwpSS9VRKfYs51+9prRNzXvss9XNgf/yysm6mtNazlVKfYUqoWmBuem7FfNb6W67bxdnIQ5ZYqlZ/AHyttf7cU9vVWmul1BxM797VMTfKJcjd6tWBmF5N07sCdHTwgClbsvl9uNPBvKOYqtZW1qqi9g/J0Fr/q5T6F1P1P6d+1xl7jrd+5ou6sf43mCqaS5RSn2NuJH/S7rfty0vnHOTL+j34h4vvyPLp5jXB3HAPdvDdYq0ubfNAKwvXyDrLPt9XSrXFNKH5SWet+m5mHP2uNLG8tnASjCZi954snP12uFrWJN3/jTHHIsxRm1lMr/NY9v1nuvlxWutD6RNqrZOUUidw75q1+gzTfvRPy3fvOmCzkwcajpSwvJ7Lwj6xNOl6EfM7dQNmFJH0ypGxKq+z7wzI2nv2VH4cXUceu5dzkEd37hWy8xvtFq31AaXURMxx+l0ptQhTIt4BE/jHYc6DoweX1uvD5YNykT0SIAtvsP5wn7LOUEoNxZS0ngS+w3xBW5+ij8bckGbXDMzT5P7AOEtbolswVWfPu1rRnqVE7mdLnhWm6to8zJP9zzFPRtOnP4wJCj6wrHMz5ol0XWAUphphXnNUqlbE8ursifV/mMCjCKbdp5WjJ6tJbizLcptydynTCcpSTPvb2y0l19mitV6vlNqPKZ0shvnOnO1iFetNnDvjfVuf+mZnjOoMnyFXtOnwY4llQilVBBN8DAY+VEot01pfy0Y+suINzA3S4FzY9hxMVbb+mGDhFKaduDPWwM1VLSrrMkfDg53XWheF1GPZCVOz5HOl1C1aa3dqEDiV3e9DJ99nSdi+T2tJhLPS9RN4JkB2lhcwD8lc0lofVEo1wzTJ6YWl0yKl1HZMKV+GAN+LPPE9WBzz/WL/4CW99B1bun2NaK3PW47leExJWQ/LNvZgah144gGZo+upuOX16SxuKzvHM/39rHW/MaS1IXXEfng5Z/cDSbhxzaYzCRO8DMKU/o8AriqlFgLPaq0zC3ytJf2ZttW3UkoVx9RUq4CpqfUd5v2kYKovx+D4eyNHn9NcyI+rWj8eu5ez5NGde4ULOC8htt43ZXnf6WmtX1JK/Y2pRdIHU2NvFWbUij8wwbGja8Z6fVzOyf6FYxIgC2+w/mBZA00/zA/IMczQNamlqkqpMri+YXDHakx1v/5KqfGYJ46Qsw4dsJQKfG3pPGUUplMN+yqL9uv8ppR6EjMMVFY7Z/IUR09DrTcdZRwsSz/fWVWjfMHS8cpyTJXi27XW/3hgs7MxN5ZVgJ1aa0clGFY/Y0pFGimlIjL50bZ2rrE5K5lRpufXWzA3GtnqoVlrfUEp9QSmTXIloD6m05vc1ABzo3HUSen7Ysv8h7TWs7OyYa31YaXUj5jq5CWBd7TrMcCt13FxF2mspTgub3601heAhcp04PcJ5mHYXW5l3IE8+D60vp/STpY7+w7Ic5bPWlelVCCmFs5dmE6lliul6uh0vb5mkfWhh6MAoIiDeXnhAnBFa53pw7XsXCOW6q59LOtGYUr1nga+UEo1tTz8BXNsnD3AdFXd1NXvSg1LLay8Yt3vK1rrES5T5gLLvcGHmIePZTD3PA9jArviwN2ZbML64NPV95O9RzCltC9prV9Nv0Ap9QGuHxS4I6ufmezmx1Vprcfu5bJwr/AP0FQpVdpBk50altccX9uW37zZdnmsiGmisNPJ75m1Q0W3HpSLrJE2yCJPKdNTcitMu6wfLbNLYr5gNzuoctw8p/u0/Fh9hAlwOmKq0fyjTc+InmBt8+dutdesps8Lv1peM/TGqJQqjamKdsCuenW+opRqgqk6mAC00Vrv9tCm52BuDsrjuvTY2lbuS0xJ6RAXeW2NqeZ8CAfV2jMxBDPM0/fZeWpuZflcWKv85cW1uAjzObSfrFX8frD8n91qn7MwwZ0vmZ+nOEwb8FqWkg5HrENk/eHOzi3t5rYAd1q+57IrV78PMb0Yg6lub8NyQ5aloZ7ygtY6QWu9QWs9DJiA6UAvs95brVUSHd3Qx1leHbXdi8pWJnNuGxCplLrBjbTZvka01kla6+1a63GYANkX86DMKg4oo+yGn7O0Xc9qD+fbLK9NXabyvO2YQCs395sMYH+c7GmtT1ialHTCBFsd3eiD4yimVLNGJunSsw6f9k36mZaabo567M6qOMuru58Zj+fHU/dyWbxXsDaZaetgWXvLq6fuJe09YHn9zMnympjaBnn58KnQkABZ5BmlVCfSxm57KV17nJOYD3lDlW74D6VUOczNkCd8jKk2NANTMvSxuysqpaoopQYruzEbLctKkTbkyE/p5o9M3+FCuvl+mN47bdLnAz9hnsx2s1TFS+//MAHf3Axr5ROWtuHfY25a2mqt3Qpq3GEppWqP6bl6thurvIwppRuhHAxppZS6hbT2Uk9rB+MTO6LMGLfPYqoSX8a0WcpsnfuU3fAn6ZZ1xbTFO0+6dngqbWzb2e7ky11a63Fa6wH2E6aKG8D7lnmbsrmLrzDnqLPW+vfMEmPGsfYDXlN2RdpKqTqYIXEuYYYWctdYy+sYu+1Zx/hc68Y2cvX70NLsYwOmTwX7oVbGk4NqlZ6kzNisjtrWWUu4M3Q4ZcfaGZKjG/q9mIdDd6l0Q6UpparinWYvYHq9BjNkUYYqnZbfocqWf7N0jSil6jkJvB0dy18wJcip42crM2TU6+6/lVSzMJ+hicoyJrRdvooqpTz+QEJr/R/mQeUdSqlBDvbr4+x7MQucXl9KqXYOAucQzIOdazhutpHKEghuBG50dN/hhLVNrv0DkiGk68AsB7L6mcmt/GT7Xg6yda8w25L2ZWU7lGAzTI2WjVrrPVnJg4M8ZSiBt5Rwv4x5kPuBg+XWmiBb8qB5VKEkVaxFbqit0jrGCMT07NsM87QrAdMGZ4Y1sdY6RSk1DTOm406l1DJM1aI7MU/mauU0Q1rr/5TpZKkr5st1ThZWj8CMoThZKbUe2IWpRlsR8wUZhnkamb7joeeAMUqpbZhqsHGYKo3tMdWODgHjsv2GPMxyDh7GtBP6UZlOcY5iqkHdirlpmuSl7LVzEawtwFRrXok5T0sxVTK72qU7lNVqu+lprX/IQtqDSqnOmPa+s5VST2OeQidgOkhqZ0k6SGu91PFW6JDuJiQUUw06BnMNHQcezKSqt1VT4GllOl5aj/mxDcFUd47B3Kg9odP1mkvag9Osjh39lIPjbjUqtztXsryHJVlY5f8wHe49CjRTSv2AuQGsjulbwA9znN3uKEdrvcLymb9dKdVCm3HfIQvHNC++D4EnMQ/FPldKfYH5PmqNudn/nbSOvLypNzBIKbUGU0ISj7khbIu5WXfWk7zVGkwbvmlKqS8xD5X+0Fov01onWKp5Pg/sUKYX8uKYByyrMGMv5ymt9XKl1KuYB1/7lFLfYzoOKoV5kNUUU6J0KBvXSBvgDcvv115Me8YbLelPYfrRsHofUxX4Y2U69IrDDGdzkbTe8919TyeVUr0xJWB/KaWWY0pRQ4GqmO+gOZge9j1tEKbm01Sl1ABMafYlzO/2rZjvUvtOo7JiDXAvpoNOa2nkT5bP/OfAJaXUT5jxkkMwpfTlgP/TGTuvc+RrzP3F7aQ9RHRlHjAceE8pdRvm2mmEuW6WYVtLIMuy8ZnJlfzk5F7OUlsoS/cKWus9Sqn/wzRb+E2ZTrSKYh4gXcZcZ/b7GUBaDZ0Gltf0v48z0/02gPlsNsDcy5zD9FHTGfPwupulGY+9Zpg2yF9n8rZFNkmALHJDLdLaQF3BfOB3YUog5zjpwOYFzA9xX0xHBUcxP9QTMD88njAP86W6XGudlR/63UB3TJWeaMtUxJLf7ZjSwI/tfvS6YL7gYjA/IKUwx+IfzFP1tyzVPPMNrfU6y1PRUZi8h2OeAr8KTNCmoydvuJG0Xkft/Yqpkmut+tfFMtlbh3ulvx6htd6olKqFeVp+F6aWgT/muv4Yc/5dVetqT9q4qJcwN7GbMDcWC3W6oXwy8QZmCJT2mJvCezAlhMcwJajvaK23261j7W12oZv7sHLVpv5t0koU8gWt9WWlVCtM6UdPTHu2QEzp3NeYYWsc9qiaiXGY4G0MaUPtZPWY5ur3oaUvhFbARMzn5Rqmyct9ZO3hYW76FHMD2AJz7fpirqEJwJvajBTglCXgfAnz2XsRc78zB/MZwjLvGmb4usGY75HBmBv5PA+QIbWzng2YdtYdML8zpzAPCIZimiFYZeUa+R5TLbUV5loPsqT/ADOGa+rvodb6V8sDvgmY6yEOM9zdi7jZ3MDuPS211JoZhgm0O2HaCP+LGa98dla36eZ+z1hK4Z7GdErWF/N9ehxTOvtFDncxA1ONuCdmeDRfTA2SnzDHqhPmuu2Keb97gBe11s6qy9pbCLyJ6bTJPkC2lk6nlhxqrWOVabozCfN974Np8tES83ueowDZwu3PTC7nJ7v3ckXIxr2C1nqMUuoQ5rficcy93PfAy05+x1uQcVjM9L+Pa7GtQbgKM+RbL8zDo2OYnrUn6IzDo1n1xnzO5zlZLnJI6QyjD+TyDpWqgHmq1AhTzSIYM5j4Ibt0dTHVvZpinvYcwtxYTsmsSqIynaUMxwx/UBbzxHScTjfWmyh8lFLjMD9kd7souROiULOUgKK1jvZ2XgoKS42MZkBVqQ4nhHCHUmoy5mFJpfQdRFlqDwwEmmittzlbv6Aq7Pdylqreh4FFlmZKIhd4ow1ydcwTt3M4GIcRQClVHvOEpSppJTBLgMnAK27sYzzm6f17mFK/LZieGjvlJOPi+qWUCsVUpTxCWgmCECIdpVQIphqrp9r+C6M5pkRagmMhhLsmYEorh1lnKNOje1vL/D+drFdgyb0cYB6aBGHX14XwLG9UsV6vtS4DqfX02zlIcyeml8bmOm0g+x+VUtUw1WSGO9u4Mj3uPg+8prW2diqxRilVHTNwu6uxMUUBo8w4d60x1Z3KYtp9OhpwXYhCz1JtNdfGqC6stNaOOooSQgintNbnlFIPAnUsbVT7YKreV8XUpiw049/KvZyNi0A/J80VhYfkeQmym50TBFhe7Rumx5F5nttb1p9vN38+UF8pVcWN/YuCow2mRkE1zAOS6d7NjhBCCCFE5iydyk3GdPb0NKbDr/GYgqDCRO7lLLTW72mtc9qGXmQiz9sg2+zclCDPwK4NsjIDq/+JaSw/FDiD6dxhPjBWa+20N12l1GuYatnBOt2bU0pFA1uBO7XWhbVahhBCCCGEEEIIJ/JlL9Za6xOW3ge/xozNCqb3wTGugmOL4kCczhj5n023XAghhBBCCCGEsJEvA2SlVClgEWbcw3sxJci3AyOUUgla64muVscE047mu9rnY8BjACEhIbfUrFkzO1kX+VxycjK+vr6ZJxTXHTm3BZec24JLzm3BJee24JJzW3AVtnP766+/ntZal7Kfny8DZEyPfZUxXdufs8xbq5TyBcYrpT7SWp92su5ZoJhSStmVIhdLtzwDrfWHwIcAUVFReufOnTl9DyIfiouLo2jRot7OhsgFcm4LLjm3BZec24JLzm3BJee24Cps51YpddjRfG8M8+SO+sC+dMGx1TZMD6vVXaz7FxCIacifXh3L6y6P5FAIIYQQQgghRIGSXwPk/4DqSqlidvObWF6Pulh3BXAN6G03vw/wp9b6oGeyKIQQQgghhBCiIPFKFWul1L2WP2+xvHZUSp0CTmmt1wHTMAHuSqXUZEwb5NaYbu0Xa61j020rCZijtX4EQGt9Uin1FvCiUuoisAPohWnDfHeuvzkhhBBCCCGEENclb7VBth+/a6rldR3QWmu9RSnVEhgFTAGKAIeAccAbduv6Wqb0XgYuYcaMKwvsBXpqrb/x1BsQQgghhBBCCFGweCVA1lq77FHakmYL0Ck729JaJwP/Z5mEEEIIIYQQQohM5dc2yEIIIYQQQgghRJ7Kr8M8CSGEEEIUKhcuXODkyZMkJiZ6Oys5lpKSwvHjx72dDZEL5NwWXAXh3Pr5+REUFESpUqUICgrK3jY8nCchhBBCCJFFFy5c4MSJE0RGRhIcHIxSmbZGy9eSkpLw85PbzIJIzm3Bdb2fW601SUlJXLp0iX///ZcyZcoQERGR5e1cv0dACCGEEKKAOHnyJJGRkYSEhHg7K0IIcV1SSuHv70+xYsUIDAzkv//+y1aALG2QhRBCCCG8LDExkeDgYG9nQwghCoTg4GASEhKyta4EyEIIIYQQ+cD1Xq1aCCHyi5x8n0qALIQQQgghhBBCIAGyEEIIIYQQQggBSIAshBBCCCE8bM6cOSil2Ldvn1vpExMTqV+/PkopZs6cmWn6tWvXopRCKcXKlSszLD906BA+Pj4Ztte/f38qVKjgcps//PBD6rzWrVun7kcpRXh4OM2bN2fp0qVuva+UlBRmzZpFdHQ0xYsXJzQ0lGrVqnHfffexbds2m7RLliyhVatWlC5dmuDgYCpVqkTXrl1ZsWIFAJUrV7bJi7MpM2+88QY33XQTWusMy3766SeUUpQpU4akpCSbZbVq1eL222/PsM6gQYNQSjF16tQMy0qXLs29996b+v+BAwfo378/VatWJTAwkNKlS3PrrbcycuTITPMNcOXKFV599VVuvvlmQkJCiIiIoFWrVixYsMCt9b0pp9dSds2ePRulFIcOHcrSOh9//LHH83L8+HFCQkIyXPv5jQTIQgghhBDCq15//XVOnz6d5fXCw8OZN29ehvlz584lLCzME1njpptuYvPmzWzevJmPPvqI+Ph47rnnHrZu3Zrpus8//zyPPvoorVq1Yv78+SxZsoRnn32W06dP26z/zjvv0K1bN2rUqMFHH33EsmXLGDFiBAA//vgjAIsXL07Nx+bNm4mKirLJm3VyJS4ujgkTJjBq1CiHwfScOXMA06v6d999Z7OsVatWbNmyhWvXrtnMX79+PSEhIaxfv95m/u7duzl16hStWrUC4PDhw9xyyy38+uuvjBo1iu+//553332XZs2a8eWXX2Z6LM+fP09MTAwTJkygW7dufPvtt3z66afUrFmTPn36MHDgwEy34W05uZayq3PnzmzevJly5cq5vU5uBcjlypXj0UcfZejQoR7ftkdprWWymxo0aKBFwXTu3DlvZ0HkEjm3BZec24JLzm2aXbt2eTsLHjVz5kwN6H/++SfTtPv379chISF6/vz5GtAzZszIdJ01a9ZoQPfr10+HhobqS5cu2SyvXr267t+/f4bt9evXT0dGRrrc5qpVq1LnxcTE6ObNm9uki42N1UopPXDgQJd5vHz5sg4ICNBDhgxxuDw5OTn17xtuuEF37do103TpOcpbZl5//XVdpkwZnZSU5DC/ERERunXr1jokJER3797dZvncuXM1oNetW5c679SpU1oppZ9++mldrlw5m/TTpk3TgP7111+11lqPHDlS+/n56dOnT7v9HtPr16+fDggI0Nu2bcuw7O2339aAnj17dqbb8ZacXEt5JTExUWudtWvr6tWrWdrHX3/9pQG9devWLOcvqzL7XgV+1g5iQSlBFkIIIYQQXjNo0CDuu+8+mjdvnuV177nnHpRSLFq0KHXepk2b2L9/Pw8++KAns5mqQoUKlCpVin///ddluvj4eK5du0bZsmUdLvfxSbsNP3v2rFvpcmrmzJn06tULX1/fDMuWLFnC+fPnGTx4cGoJ7blz51KXx8TEAKYattWGDRsIDQ3lySef5Pjx4zZV6tevX0/RokWpX78+YN5jUFAQRYsWzbDvzN7jsWPHmD9/PgMGDKBx48YZlj/11FPUqVOH1157LXWetWrx+vXr6dq1K2FhYZQoUYLHH3+cK1eu2Kx/+fJlhg8fTpUqVQgICKBKlSq88sorpKSkpKaxVsFfunQpTzzxBCVLlqRUqVL06dOHuLg4l/l3xtm19Ntvv9GlSxeKFStGcHAwzZs3Z8OGDRnWnzJlCpUrVyYoKIjo6Gg2bdpE5cqV6d+/f4bjkL6K9YIFC4iKiiIsLIyIiAjq16/P9OnTAVMVfN26dWzcuDG1Onjr1q0zHNMePXpQtGhRmjRpwuuvv05gYCCnTp2yyZ/WmqpVq3L//fenzqtTpw7169d3qymFt/h5OwNCCCGEEMKBIUPg11+9m4cGDeDtt3Nt85988gk///wzn3zyCZcuXcry+iEhIXTv3p158+alBsRz586lefPmVK1a1dPZBeDixYucOXOGatWquUxXsmRJqlSpwuuvv05ERASdOnWiYsWKDtNGR0czZ84cqlatyt13303NmjU9nu9///2XPXv2MH78eIfL58yZQ9GiRenSpQsRERF88sknLFy4kEGDBgFQsWJFKlWqZBOorV+/nmbNmlGtWjUqVKjA+vXrqV69OmCC5xYtWqQGv9HR0bz//vv06tWLp556iiZNmhAYGOhW3teuXUtycjJdunRxuFwpxV133cXEiRM5fvy4TXXiPn360LNnTwYPHsy2bdsYN24c8fHxzJ49G4CkpCTat2/Prl27GDlyJPXr12fLli2MHz+es2fP8sYbb9js6+mnn+bOO+9kwYIF7N27l2HDhuHr65taPT0rHF1LO3bsoGXLlkRFRTFjxgxCQkKYNm0abdq0YdOmTdxyyy2AedgxZMgQHnnkEXr06MH+/ft54IEHMg3Wf/rpJ/r06cNTTz3F5MmTSUlJYc+ePanrTZ06lT59+pCcnJwaNBcpUsRmG7179+b+++/nyy+/JCkpiejoaEaOHMmsWbMYNmxYarqVK1dy8ODBDNW1W7Vqlettr3NCAmQhhBBCCJHnzp07x7PPPsvEiRMpWbJktgJkgL59+9K2bVuOHj1KyZIl+fzzz5k4caJH82rtsCo2NpZhw4ZRvHhxnnnmmUzXW7BgAffdd19qkFm+fHk6dOjAwIEDiY6OTk03bdo07r33XoYNG8awYcMoUaIEbdu25aGHHqJdu3YeeQ/W9sk333xzhmXHjh3jhx9+4JFHHiEwMJA2bdoQGRnJnDlzUvMOJrD5+uuvSUlJwcfHh/Xr19OtWzcAWrZsyfr163n44Yc5ePAgsbGxPPXUU6nrPvjgg2zatIkPP/yQr776ioCAAKKjo+natSuPP/44QUFBTvMeGxsLmI7KnLEui42NtQmQO3XqxOuvvw5Au3btUEoxatQoXnrpJWrWrMmnn37KTz/9xLp161LbS99xxx0AjB07luHDh1O6dGmbY/Duu++mbm/v3r3MnDkztXQ1M5ldS0OHDqVixYr8+OOPBAQEANC+fXvq1avH+PHjWbJkCSkpKYwdO5aOHTvalMSWLVuW7t27u9z/li1bKFq0KG+ne/BlvcaSkpKoU6cORYoUISkpiaZNmzrcxr333sukSZNs5vXq1YsPP/yQoUOHph6H6dOnU6tWrdQSaKuoqCjef/99jh07Rvny5V3m1xskQBZCCCGEyI9yseQ2Pxg6dCjVqlXjkUceydF2brvtNipUqMCCBQuoUqUKV65coWfPnjbVg3Ni48aN+Pv7p/4fGBjIqlWr3Cqhbtq0KXv37mXNmjX88MMPbN68mTlz5jB79mxmzZpF3759AahZsyY7d+5k48aNrFy5ki1btrB48WIWLlzI+PHjUzvsyoljx44BUKpUqQzL5s+fT3Jycmp+fHx86NOnDxMnTmTv3r3UqlULMNWs582bx6+//kr16tX57bffePPNNwFo0aJFaiBq7bDLGnCCKeWdNm0aw4cPZ9myZWzatIk1a9bw/PPPM2fOHLZu3UpwcLDDvGsHPW67m6Znz542/993332MGDGCbdu2UbNmTVasWEGlSpVo1qyZTc/d7dq1Y8SIEWzZssWm5Lpz584226tfvz4JCQmcOHHCaTV5q8yupStXrrBu3TpeeuklfHx8bPLTpk0bPvnkEwCOHDnCkSNHGDdunM327777bvz8XId3jRs35ty5c/Tp04f77ruPFi1aOKz27or1oUh6gwcPZs6cOaxevZo2bdpw/PhxvvnmmwyBNKRdg/k1QJY2yEIIIYQQIk9t3bqV2bNn8+qrr3L+/Hni4uK4cOECYIKEuLg4t4IiMIFX7969mTdvHnPmzEmtIuyIn58fycnJDpdZ59sHGDfffDPbt29ny5YtfPTRR4SHh9OjR48M7S2dCQwMpEOHDrz++uts3LiRXbt2UbZsWZ599lmbdL6+vrRq1Yr/+7//44cffuDAgQPUr1+fsWPHeiTYv3r1amp+7M2dO5eKFStSt25d4uLiiIuL4+67705dZmUNeNevX8/GjRvx9fWlSZMmgClBPnjwIEeOHGH9+vWEhYXRsGHDDPuqUqUKTzzxBAsWLODIkSMMGzaMP/74g48++shp3m+44QYAl0MVHT58GCDDMF5lypRx+P/Ro0cB02P34cOH8ff3t5msJfxnzpyxWb948eI2/1uPp/X4upLZtXT27FmSk5MZP358hvy89957nDt3jpSUFI4fPw5gU7IN5hoqWbKkyzzExMTwxRdfEBsbS7du3ShVqhRt2rTh999/zzT/Vo56xI6OjqZRo0ZMmzYNMFXA/fz86NevX4a01gch9m3B8wsJkIUQQgghRJ7avXs3ycnJtG7dmmLFilGsWLHUqr9PPfUUxYoV4/z5825vr2/fvvzxxx8sX748tRTUkdKlS3P69OkMQxVBWgmrfUAVFhZGo0aNaNKkCQ8//DCff/45J06cYMyYMW7nL72aNWvSq1cvzpw5w8mTJ52mK1++PAMGDCApKYl//vknW/tKr0SJEgAZgu2ff/6Zv/76i3///Tf1XBQrVoxmzZoBMG/evNTOqmrUqEG5cuVYv34969evp1GjRqlVo+vVq0exYsVSlzVr1izT0kxfX19efvllAHbt2uU0XevWrfHx8XHablVrzTfffEPt2rUzlEieOHHC4f+RkZGpx6VKlSps377d4XTXXXe5fA9Zkdm1VLRoUXx8fHjyySed5sfHxyc1QLW/fpKTk90aLu3ee+9l3bp1nDt3jsWLF3P8+HE6dOhg0ymZK86qkg8aNIivv/6ao0ePMnPmTHr06JHhgQKYBwFApsG8t0iALIQQQggh8lSHDh1Ys2aNzfTpp58CZuzgNWvWZGkc49q1a/P4449z77330r59e6fpbrvtNpKSkhwGWl999RXlypVLrU7sahvdunVj5syZHDlyxGm6xMTEDMGZ1Z49ewgODk4t6ba2sXWUDsi06q47ateuDcCBAwds5s+ZMwelFF999VWGc/LCCy8QGxvL2rVrU9O3bNmSDRs2sH79elq2bJk6XylFs2bN+Pzzz9m3b59N9WowJbaOagVY36OrcXojIyN54IEHmDlzJtu3b8+w/J133mHXrl02HURZff755zb/L1y4EB8fn9QS4g4dOhAbG5savNpPuRnE2V9LoaGhtGzZkt9++42GDRs6zA+YUvIKFSrwxRdf2GxvyZIlNtWyMxMWFsadd97JwIEDOX78eGppeWBgYLZKd++//37Cw8N54IEH+Pfff/nf//7nMN3BgwdTewvPj6QNshBCCCGEyBUrVqzIENxFRETQtm3bDPOt1Wcdderjjvfeey/TNG3atKFt27b079+fPXv20KRJEy5evMjChQv5+uuvmTVrllvDKo0bN46vv/6aiRMnpnbYZO/8+fNUrFiRnj170qlTJypUqMCZM2dYuHAh3333HcOGDUutnluvXr3UYKlKlSpcuHCB5cuXM23aNHr27Om09+usiI6OJjAwkG3bttGiRQvABPELFy4kJiaGe+65J8M6DRo04O2332bOnDncfvvtgGlr/Pnnn3PmzBleeuklm/QtW7bkxRdfBMgQIL/66qusXr2a/v37ExUVhb+/P7///juTJk2iRIkSPPTQQy7z/+6777Jr1y5uv/12nn/+eVq1asXVq1f56quv+Pjjj3nkkUccbmP58uUMHTqUdu3asW3bNsaOHUvfvn1Tewrv3bs3s2bN4o477uC5557j5ptv5tq1a+zfv5+lS5eyZMkSQkJC3DzKWWd/Lb355pu0atWK9u3b88gjj1CuXDlOnz7Njh07SE5O5rXXXsPHx4fRo0fz6KOPMmDAAHr06MGBAwd47bXXiIiIcHkNjxo1ihMnTnDbbbdRvnx5jhw5wjvvvEODBg1S2wbXqVOHqVOn8tlnn1GtWjXCw8MzfXAEpup0//79eeutt6hfv35qLQR7W7dupXHjxi47ZvMqR4MjF/apQYMGLgeVFtevc+fOeTsLIpfIuS245NwWXHJu0+zatcvbWfComTNnasDhVLduXYfrHDx4UAN6xowZmW5/zZo1GtCrVq1ymsbZ9q5cuaJffvllXaNGDR0QEKDDwsJ0ixYt9JIlSzJsIyYmRjdv3tzh9u+//34dFBSkjx075nB5QkKCnjRpkm7btq2OjIzU/v7+Ojw8XDdt2lRPnz5dp6SkpKb94IMP9F133aUrVqyoAwMDdUhIiG7QoIGeOHGiTkhIcLh9V3lzpmfPnrp169ap/y9atEgDeu7cuU7XeeCBB3RoaKi+ePGi1lrrX3/9VQPax8cnw2d448aNGtBBQUH66tWrNsu2bNmiBw4cqOvWrasjIiK0n5+fvuGGG3S/fv30vn373Mp/fHy8fuWVV3S9evV0UFCQDgsL082bN9fz5s3LkHbWrFka0OvWrdNdunTRoaGhulixYnrw4MH68uXLNmmvXLmiR48erWvVqqUDAgJ0sWLFdKNGjfTo0aN1YmKi1tr5NWfdz8GDB13mPSvX0q5du3SvXr10qVKldEBAgI6MjNR33XWXXrZsmc16b731Vuo1c8stt+gNGzbookWL6iFDhjjN37fffqvbtWuny5YtqwMCAnSFChX0ww8/rI8ePZr6Xo8fP647duyow8LCNKBjYmJstvXPP/84fZ+bNm3SgH7vvfccLr98+bIODw/X7777rsvj5QmZfa8CP2sHsaDSbnaAUJhERUXpnTt3ejsbIhfExcVluac+cX2Qc1twybktuOTcptm9ezc33nijt7PhMUlJSZm2PxV5b+3atdx+++0cOnQo26XS18u5nT17Ng899BD//PNP6tjMBd327duJjo5m7ty5qeOCZ4Unzu3LL7/MlClTOHbsWIbxkwE+++wzBgwYQGxsbK5//2f2vaqU+kVr3ch+fv6/uoUQQgghhBA51rp1a9q0acOkSZPcqpIu8q+DBw/y/vvv07JlS4oUKcLu3buZMGECVapUyXQs5Nywc+dO9u7dy5QpU3jsscccBscAEydOZOjQofn64agEyEIIIYQQQhQS77zzDkuWLDFVSZ30Rizyv+DgYP7880/mzp3LuXPnKFasGG3atOG1117L1TbTznTr1o0TJ07Qvn17xo4d6zDNf//9x913383zzz+fx7nLGqli7YBUsS64pDpfwSXntuCSc1twyblNI1WsxfVCzm3BVdDObXarWMswT0IIIYQQQgghBBIgCyGEEEIIIYQQgATIQgghhBBCCCEEIAGyEEIIIYQQQggBSIAshBBCCCGEEEIAEiALIYQQQgghhBCABMhCCCGEEEIIIQQgAbIQQgghhPCwOXPmoJRi3759TtPMmDGDTp06ERkZSWhoKPXq1WPy5Mlcu3Yt0+2vXbsWpRRKKVauXJlh+aFDh/Dx8UEpxcyZMzMsX7lyJR07dqREiRIEBQVRs2ZNhg8fzrlz5zKkrVy5cuq+/Pz8KFGiBE2aNOGFF17g0KFDGdKPGTMGpRRJSUmp8y5cuMDo0aOpU6cOoaGhFCtWjPr16zNw4EBOnjzp8r2mpKQwa9YsoqOjKV68OKGhoVSrVo377ruPbdu22aRdsmQJrVq1onTp0gQHB1OpUiW6du3KihUrMrwXV1Nm3njjDW666Sa01qnzXG1vyZIlNuufO3eOF198kVq1ahEUFETx4sVp374933//vcP9Zfa+wPaaUEoRHBxMhQoV6NSpEzNnznR4XVWuXJk+ffrYzPv111/p3r07FStWJDAwkHLlynHbbbfxzjvvZHpcAOLj43n11Vdp2LAh4eHhBAUFUatWLZ544gmbz0PlypXp37+/W9v0pP79+1O5cuXU/48fP05ISEiGa6kwy/MAWSlVQSn1rlJqs1LqslJKK6Uq26WZbZnvaNrjxj4OOVm3a269LyGEEEII4b5x48ZRtmxZpkyZwrfffkuvXr0YOXIkvXv3dnsb4eHhzJs3L8P8uXPnEhYW5nCdCRMm0L59e4KCgpg5cybff/89//vf/5g9ezaNGzcmNjY2wzrt27dn8+bNbNiwgfnz59OlSxcWLlxIvXr1WLx4scs8Jicn06ZNGz744AMeeeQRli5dypw5c7j//vvZtGkTx44dc7n+888/z6OPPkqrVq2YP38+S5Ys4dlnn+X06dNs3bo1Nd0777xDt27dqFGjBh999BHLli1jxIgRAPz4448ALF68mM2bN6dOUVFR3HTTTTbzNm/e7DI/cXFxTJgwgVGjRmUIpvv3759hW5s3byYmJiY1TWxsLI0bN+ajjz7iscceY8WKFXz88ceEhYXRoUMHJkyYYLNNd96XffrNmzezcuVK3njjDcqXL8/jjz9OdHQ0p06dcvnetm/fTtOmTTl9+jSTJk3i+++/Z/LkydSqVSvT8wwm2IyOjmbSpEl07tyZL7/8ku+++46nnnqKzZs306NHj0y3kdfKlSvHo48+ytChQ72dlfxDa52nE9AaOAEsB74HNFDZLk01oKnddJ8l7SQ39nEIWOFgG8XcyWODBg20KJjOnTvn7SyIXCLntuCSc1twyblNs2vXLo9t69DpS/rlxb/ruqNW6MrDv9V1R63QLy/+XR86fclj+8jMzJkzNaD/+ecfp2lOnjyZYd7YsWM1oPfv3+9y+2vWrNGA7tevnw4NDdWXLtm+t+rVq+v+/ftrQM+YMSN1/o8//qiVUnrIkCEZtnngwAFdrFgx3bp1a5v5lSpV0r17986Q/uLFi7pZs2Y6ODhYx8bGps4fPXq0BnRiYqLWWuvVq1drQC9ZssThe0lOTnb6Pi9fvqwDAgIc5td+3RtuuEF37do1S/uIiYnRzZs3d7p/RyZNmqTLlCmjk5KSbOYD+uWXX850/ZiYGF28eHF94MCBDMuGDBmilVJ6zZo1qfPcfV/Wa2LVqlUZ0m3atEkHBgbqO++802a+/bl98MEHdZkyZfTVq1dd7suZO+64QxcrVkz//fffGZalpKToxYsX2+y7X79+mW7T0/r166crVapkM++vv/7SgN64cWOe5yc3Zfa9CvysHcSC3qhivV5rXUZr3Qn4wlECrfV+rfWW9BNQw7J4jpv7OW2/Da11xnozQgghhBAFxJq9J+nw9gYWbovlUkISGriUkMTCbbF0eHsDa/a6rs6bl0qVKpVhXuPGjQE4evSoW9u45557UEqxaNGi1HmbNm1i//79PPjggxnST5o0ieLFi/Pqq69mWFalShVeeOEF1q5da1My60xYWBhTp07lypUrTJ8+3Wm6s2fPAlC2bFmHy318nN+Ox8fHc+3aNbfWPXv2bLb2kVUff/wxvXr1wtfXN8vrbt26lXXr1vHCCy9QpUqVDMtfffVVihUrxsSJE1PneeJ93XrrrQwaNIhvv/2W/fv3O0139uxZihUrRmBgYJb3tW3bNlavXs1LL71EjRo1MixXStG1a9dMt9GmTRvCwsIIDQ3ljjvuyFD1uXXr1rRu3TrDuo6qbK9evZqGDRsSFBREtWrVnF6nderUoX79+nz88ccu81dY5HmArLVOyeaqfYFftNZ/eTI/XrG4AixQmU+LK3g7p0IIIYS4Thw+E8/g+Tu4kphMUoq2WZaUormSmMzg+Ts4fCbeSznM3Lp16/Dx8aFmzZpupQ8JCaF79+421aznzp1L8+bNqVq1qk3apKQk1q1bR9u2bQkKCnK4vS5dugCOq+46cvPNN1O+fHk2btzoNE3Dhg3x8/Nj4MCBLF682GE7Z2dKlixJlSpVeP3115k2bRr//vuv07TR0dHMmTOHyZMn8/fff7u9j6z4999/2bNnDy1btnS4XGtNUlJShslq9erVQNpxthcUFETbtm1Zv349ycnJgOfeV6dOnQBcnqvo6Gj27NnD//73P7Zt22aT98z88MMPgPP3lpnff/+dmJgYzp07x+zZs5k7dy4XLlwgJiaG3377Lcvb2717N506dSI4OJiFCxcyYcIE3n777dRzYK9Vq1YO2/MXRtdFJ11KqeZAddwvPQa4y9LGOUEptSVftT+O7AI+Aa7T+ARAhbvzJj9CCCGEuO7N2HCAxGTX5RCJySnM3HAwj3KUNb///jtTpkzh4YcfpkyZMm6v17dvX1avXs3Ro0dJSEjg888/p2/fvhnSnTlzhitXrth0UGTPusxRO2RnKlasyPHjx50ur1q1Kh988AH79u3jnnvuoUSJEtStW5ehQ4dm2v4YYMGCBYSGhjJo0CAqVapEZGQkjzzySIaSxWnTplG9enWGDRtGrVq1KFmyJPfff79Hgx5r++Sbb77Z4fIJEybg7++fYTp9+jSQdlwzOweXL1/mzJkzHn1fFStWBHB5roYOHUrXrl2ZPn06TZo0oUiRIrRr144ZM2akBuzOWN9bpUqVspQvq3HjxhEYGMjq1au599576d69O6tXryY4OJixY8dmeXv/93//R3h4OCtXrqRr16706tWLlStXcuLECYfpo6KiiI2NdeuaLOiuiwAZU3qcCHzqZvpvgCeB9kBv4CqwWCnVx+VaeaX+SFCZHHrlC/VG5k1+hBBCCHHdW7LzWIaSY3tJKZrFO92rvpyXjh8/zt133021atV48803s7TubbfdRoUKFViwYAHffPMNV65coWfPnhnSae362GSX1jrTnp8HDBhAbGws8+fP57HHHiMlJYXXX3+dunXr8tdfritHNm3alL179/Ldd9/x3HPPUblyZebMmcOtt97K3LlzU9PVrFmTnTt3sm7dOl5++WUaNGjA4sWLad++Pf/3f//nkfdqDZ4cVY8HePjhh9m+fXuGqWjRooB758A+jafel3W7rs5VcHAwixcv5q+//mLy5Ml07NiRn3/+mccee4xOnTrl2jUEsH79eu68887UYwVQpEgRunTpwrp167K8vc2bN9OpUydCQ0NT591www00b97cYXrrOZUAGfy8nYHMKKUCgZ7At1rr0+6so7V+0m4bi4EtwKvAfCf7eQx4DCAyMpK4uLgc5DozwVDhaTiyBLSDqhvKDyp0hYQgSMjNfBQ+Fy9e9HYWRC6Rc1twybktuOTcpklJSclSdU5H4hPcWz/+WlKO95UZayBhX8XWkTNnztC2bVu01ixbtozg4OBM17GW5iUnJ5OcnMz999/P3LlzqVSpEnfddRehoaGpPRYnJyeTlJRE0aJFCQ4O5uDBg063bx2GJzIy0iaNq/MTGxtLrVq1UpenpKSkvvf0wsPD6dWrF7169QJg6dKl9OjRg1GjRvHZZ5+5fL++vr60adOGNm3aAPD333/Ttm1bnn32WR544AGbtM2aNaNZs2aACXY6d+7M2LFjGThwIMWKFbNJa+2UyN3r4fLly6n5cbROmTJlaNCggcN1k5KSiIyMBMxxrlWrlsN0hw4dIjg4mIiICJt9ZPa+0l8TjvJmHZKrdOnSmZ7bmjVrUrNmTYYMGcLVq1cZOHAgCxYsYOnSpXTu3Nlhvq3vbf/+/W43EUi/77Nnz1KmTJkMeSldujTnzp1LnZ/+s+Vqe8ePH6dUqVIOt+foMxAQYGq3Xrp0Kde/H/JKSkpKtmK6fB8gA3cDRcla9WobWutkpdQXwESlVDmtdYa6FVrrD4EPAaKionT6pze5ouHTcGQKpFzNuMw3GBoOgeBczkMhlevnVniNnNuCS85twSXn1jh+/Dh+fjm7LQsN9OOSG0FyaIBfjveVGWspnZ+f631duHCBzp07c+bMGTZs2OB29VRrB1G+vr74+fnRv39/Jk6cyK5du1i6dKnNfq1p/Pz8aNWqFT/88ANJSUkO2yEvX74cgDZt2tjk28fHx+H7+PXXXzl27BgDBgxIXW7tzCmz937PPfdw8803s3v37iyfjzp16tCrVy/eeustzp49S+nSpR2mq1ixIo8++ihPP/00Bw8ezFDym358Z3dY17948SLh4eEZljs7TlZt27Zl1KhRLF++nLp162ZYfvXqVX744QdiYmIcdpTl6n3ZXxP2rGMmt2rVyq1zaxUWFsbw4cNZsGABe/fu5e67HTeBbNeuHSNHjuS7776jTp06TreXXvp9Fy9enJMnT2bIy8mTJylevHjq/ODgYC5cuJAh3dmzZ222V65cOU6dOuVwe0CG+efPnwfMQ47c/n7IKz4+Ptn6jbkeqlj3A05jhoXKCWt9ityrG5EVweWgykMZ2yL7BEDVhyDYcW99QgghhBCOdI0qj5+P66q+fj6KblGReZQj1y5fvkznzp05ePAgK1eupHr16tneVu3atXn88ce59957ad++vdN0Q4cO5cyZM7z00ksZlh08eJCJEyfSqlUrmjRpkuk+L126xOOPP05ISAgDBw50mu706dNcvZqxQCQ+Pp7Y2FjKlSvndN3ExESnbUb37NmTWtIKzttN79mzB3Dei3ZW1K5dG4ADBw5ka/2mTZvSsmVLXnvtNQ4ezNgW/sUXX+Ts2bM2Y/J64n1t3ryZ6dOn07Vr1wydt6V35MgRl/tyda6io6O54447mDBhQmpNBHtff/210/VjYmJYtmyZTc2aixcv8s0339iMI12pUiX+/vtvrl27ljpv/fr1GWrk3HrrrSxfvpz4+LRO+WJjY512Unbw4EECAgIc9i5e2OTrxwNKqTJAO2Cq1joxB9vxA3oA/2qt//NU/nKs/kg4OMt2nrQ9FkIIIUQ2PNqyKl/9cpSkFOedCfn7+jCgZd7dAK9YsSJDABMREUHbtm3p3r07GzduZMqUKcTHx7Nly5bUNNWqVXPaztWZ9957L9M0d9xxB+PGjWPUqFEcOnSIvn37UqxYMXbs2MFrr71GRESETY/YVqdPn2bLli1orTl//jw7duxgxowZnDp1ik8//ZTy5cs73efatWsZNGgQ/fv3p2XLlhQtWpTDhw/z7rvvcvbsWZ599lmn654/f56KFSvSs2dPOnXqRIUKFThz5gwLFy7ku+++Y9iwYaklrfXq1eO2226jW7duVKlShQsXLrB8+XKmTZtGz549Uzupyono6GgCAwPZtm0bLVq0yLD86NGjNufRqlKlSqnB5bx587jtttto2rQpw4YNo1GjRsTFxTF37lwWLVrEuHHjuP3221PXzer72r17N2FhYSQlJXH8+HFWrlzJvHnzqFOnDjNmzHD5/v73v/9x4sQJHnzwQerVq0dycjLbt29n0qRJVKtWjW7durlcf968ebRp04bGjRvz5JNP0qJFCwICAtizZw8ff/wxiYmJTkugR44cybfffssdd9zB8OHDUUoxceJELl++zKhRo1LT3XfffXz44Yc8/PDD9O/fn4MHD/Lmm2+mPiixGjFiBF988QXt2rVj6NChXLt2jdGjRzvtAG/r1q00atTIaQ/vhYqjwZFzewLutUwfYEp0B1n+j7FL96xleUMX20oCPkr3//3AQkzHXrcB9wEbLNu5z538NWjQwOWg0h61dZDWnwZo/QnmddvgvNt3IXTu3DlvZ0HkEjm3BZec24JLzm2aXbt2eWQ7P+45oWuP+E5Xe3GZrjT829Sp2ovLdO0R3+kf95zwyH4yM3PmTG2598ow1a1bV2utnS4H9KxZs1xuf82aNRrQq1atcprm4MGDGtAzZszIsOy7777T7dq100WLFtUBAQG6evXq+vnnn9dnzpzJkLZSpUqp+fLx8dFFixbVjRo10sOHD9eHDh3KkH706NEa0ImJiVprrWNjY/ULL7ygo6OjdalSpbSfn58uWbKk7tixo169erXL95mQkKAnTZqk27ZtqyMjI7W/v78ODw/XTZs21dOnT9cpKSmpaT/44AN911136YoVK+rAwEAdEhKiGzRooCdOnKgTEhIcbj8mJkY3b97cZR7s9ejRQ7du3TrDfFfnc/LkyTZpz5w5o4cNG6Zr1KihAwMDddGiRXXbtm318uXLM2zX3fdlvSasU2BgoC5fvrzu2LGjnjlzpsNjUKlSJd27d+/U/1esWKH79u2ra9asqcPCwnRAQICuWrWqfvzxx/V///3n1vG5ePGifuWVV3SDBg10SEiIDggI0DVr1tRPPfWU3r9/v82++/XrZ7Puli1b9B133KFDQ0N1SEiIvv322/XWrVsz7GPatGm6evXqOigoSN966636559/dri9VatW6QYNGuiAgABdpUoVPW3aNN2vXz9dqVIlm3SXL1/W4eHh+u2333brPV4vMvteBX7WDmJBpXOxNzZnlFLOdrpOa906XbrfAB+tdf1MtjVHa93f8n9TYAJQFygOXAa2A5O11t+7k7+oqCi9c+dOd5Lm3JXjsLQqJF81bY+7HJDq1bkoLi5O2rsVUHJuCy45twWXnNs0u3fv5sYbb/TItg6fiWfmhoMs3nmU+GtJhAb40S0qkgEtq1CpRGjmG/CApKSkAtOOUdhavXo1bdu25dChQx4plRbe99lnnzFgwAAOHjxIyZIlvZ0dj8nse1Up9YvWupH9fK98c2mtXTeQSUvneJA1F9vSWm8BbneSPP+xtkXeN13aHgshhBAixyqVCGV813qM71rP21kRBVBMTAxt2rRh0qRJblVrF/nfxIkTGTp0qDywtLgeOukq+OqPhLDK0vZYCCGEEELke++88w4VKlTI1XGBRd7477//uPvuu3n++ee9nZV8Q+q+5AfB5aDLfm/nQgghhBBCiEzVrl2bF154wdvZEB5QtmxZRo8eDTgeW7kwkhJkIYTnJCTA2bOQkuLtnAghhBBCCJFlmZYgK6UCgHuADkBToDwQBJwB9gLrgM+01rtyMZ9CiPxIa9izB77/3kxr18LVq+DrCyVLQqlS7k0lSph1hBBCCCGE8CKnAbJSKgQYCjwBFAN2A9uAU8AVTA/RVYDHgRFKqZ+Al7TWjkefFkIUDOfOwQ8/mIB45UqIjTXza9WCxx6DKlXg1Cnb6ddfzeu5c463qZQJkt0NqEuWBH//PHvLQgghhBCicHBVgrwf+A8YBXyutT7jLKFSqjnQB/heKfWc1nq6Z7MphPCa5GTYti2tlHjbNlOFOiIC7rgDRoyA9u2hUqXMt5WYCGfO2AbPJ09mDKh37TKvZ86YUmpHihZNC5hLlya4bFmoXx9q1jRThQrgI61IhBBCCCGE+1wFyIO01kvc2Yil1HijUmoMUDnn2RJCZMniCnDlaObpgiOh25HM08XGpgXEP/wAcXGmlLdxY3j5ZRMQN2kCWR3j0t8fypY1kzuSk02bZvsA2j6o/ucfAlauhMuX09YNCoIaNUywbH21TiVLmvcjhBBCCCFEOk7vbt0Nju3WOQGcyEmGhBDZENkFDnwEKdecp/EJgAp3O1525QqsW5cWFO/ebeaXLw/dupmAuE0bUw06L/n6ppUSZ+L8uXMUvXwZ/v47bfrnH/jzT/j6a0jfM2PRoo4D5xo1IDw8996PEEIIIYTI11y1QVbAncBBrfWfTtLUByprrb/JpfwJIdxRfyQcnOU6jfJNG2tba/jrr7SAeP160wN1YCC0agWPPGKC4rp1r5+SVqUgMtJMt91muywpCQ4dyhg8b9gAn3xim7ZcuYyBc82aULWqOT5CCCGEEKLActVA70HgUyDeRZqLwKdKqfs9mishRNYEl4MqD5lSYkd8AqD4/bB0HTz8MNxwg2mv+/zzcOQIDBoE331nqjOvXAnPPQf16l0/wXFm/PygenXo1AmGDIGpU2HVKjh8GOLj4fff4csvYcIE82AgKcmUOg8bBl27Qp06EBJiguQOHeCpp+C990z184QEb787IYTId+bMmYNSin379uXJ/g4dOoRSitmzZ6fOmz17Nh9//HGe7F/kL4cOHWLMmDEcOHDAo9t98sknueuuuxwumz9/PkopGjZs6NF9ZkViYiKlSpWiU6dOTtOsXr069bPi6HOTU5kdB+s+rVNAQAA1a9bkmWee4Vy6zlzHjBmDUip1bGatNVFRUUyePNljeXXGVQPCPsAsrfVBZwm01oeUUh8B/TDBtBDCW+xLkZOBfcAfwO+JcGAW6I+hWDFTXbp9e2jXzgTLhVlIiHlYUL9+xmXnzpmS5vQlz3//DRs3wqVLJk3RotCjB/TpAy1aSMdgQgjhBeXKlWPz5s1Uq1Ytdd7s2bNJSkri4Ycf9mLOhDccOnSIsWPH0qJFC6pWreqRbe7fv5/p06ezadMmh8vnzJkDwM6dO/njjz+o7+i+Ipf5+/tz//33M3XqVE6cOEGZMmUypJk7dy4hISHce++9+Pv7Z/jc5JS7x+HFF1+kS5cuJCQksHHjRv7v//6PnTt3smbNGpSDAhqlFKNGjeLhhx/mkUceoXjx4h7Lsz1Xd3INgZVubOMHoJFnsiOEyLbgchDaA9b5wtvA/4BxwBIgpDSMHg2bN5tOrT7/3FSjLuzBcWaKFYPoaBP8jhsHCxfCjh1w4QIcOwbffgt33gkLFkBMjBni6sUXTfV1IYTIa4srwAKV+bS4grdz6nGBgYE0bdqUUm70WSHck5iYiHY2kkQh9Pbbb3PzzTfTqFHGsOfIkSP8+OOPqSW31iAxMwm5UAutX79+JCcns2DBggzL4uPjWbRoEd27dycsLMzjn5usHIeqVavStGlTYmJieOmllxg+fDjr1q1j586dTtfp0qULQUFBzJw50yP5dcZVgBwOOBm01MY5S1ohRF5LTDTth198EW6+Ge6aBx8mm5LjaOApYEYQbP3VBMhNm5qOr0TOKGXaKnfuDPPmwYkTpi1z3bowebKpnh4VBW+8YQJpIYTIC5FdnDe1sXLVYWMua926NS1atOCHH36gYcOGhISEUK9ePZYsWZLpuv/99x/9+vWjfPnyBAYGUq5cOe68805OnjwJZKxi3bp1a9atW8fGjRtTq3K2bt0aSKu6aa9///5Urlw507wopRgxYgRvvPEGlSpVIjQ0lM6dO3Py5ElOnjxJz549iYiI4IYbbmDixIkZ1j948CC9e/emVKlSBAYG0qBBAxYvXmyTZt++fTz44INUqVKF4OBgqlatyqBBg2yqoAJs376dtm3bUqJECUJCQqhatSqDBw9OXe7ue7Uev6lTpzJs2LDU4xwXFwfAokWLaNq0KSEhIZQsWZIePXrw77//2myzcuXK9OnTh3nz5lGrVi2Cg4Np2bIl//zzD/Hx8QwcOJASJUpQpkwZnnvuudSqs1anT59m0KBBREZGEhgYSO3atfnwww9t0syePRulFFu2bKF3794UKVKE8uXL89RTT3H16lUA1q5dy22Wvkjatm2bev7Xrl0LwIIFC4iKiiIsLIyIiAjq16/P9OmuR6hNSEhg/vz5PPDAAw6Xz5s3j5SUFMaMGUPz5s355JNPSE5Otkmzdu1alFIsWrSIRx99lFKlSqWW8CYnJzNixAjKlStHSEgIt99+O3v27EEpxZgxY2y2s2LFCm699VaCg4OJiIiga9eu7N27N3X5LbfcQt26dZk3b16GfC5atIhLly7Rt29fwHHThMyuKVfcOQ7ONG7cGMBlswxfX1969Ojh1QD5NODGwKZUtKQVWXT4TDwjlvxBvdHfU+WFZdQb/T0jlvzB4TOumn2LQu/oUfjoI7j3XjNcUUwMvP66Ke187TWY3xPe94dHgVsD4KaHIdjNYZVE9oSGwgMPwPLl5vxMmQIBAaaNd4UKpkr77Nmm5FkIIXJL/ZGgMmnmkb7DRi/Yv38/Tz/9NM8++yyLFi2iXLly3HvvvZm2VX7wwQfZvHkzkydPZtWqVbzzzjtUqFCBy+mH90tn6tSpREVFcdNNN7F582Y2b97M1KlTPfY+5s2bx48//sjUqVN599132bBhA3379qVbt27cdNNNfPXVV3Tq1IkXXniB5cuXp64XGxtLkyZN+O2333jrrbdYunQpDRs2pHv37ixdujQ13bFjx6hQoQJvv/0233//PaNGjWL16tU2bUsvXbpE+/bt8fX1Zfbs2SxfvpxRo0ZlCDyz4pVXXuHvv//mww8/ZPHixQQFBTFt2jS6d+9OnTp1+PLLL5k6dSp//vknMTExXLx40Wb99evXM3XqVCZOnMicOXPYv38/3bt3p3fv3oSHh7Nw4UIee+wx3nzzTZvg98KFCzRv3pxly5YxZswYli1bxl133cWgQYN49913M+TzwQcfpFq1aixatIhBgwbx/vvv8+qrrwLQsGFD3n//fQDeeeed1PPfsGFDfvrpJ/r06UNMTAxLlizhiy++4NFHH019EODMli1biIuLo2XLlg6Xz507lxtvvJHGjRvTt29f/vvvP1audFwR98knn0Rrzbx581ID09GjRzNhwgT69u3L119/Tfv27enSpUuGdVesWEHnzp0JCwvjs88+44MPPuDPP/+kRYsWHD2aNtxnv3792LlzJ3/Z1WibN28eFSpU4Pbbb3eYt5xeU1k5DvYOHjSteosWLeoyXatWrfjnn3883r7chtba4QR8Bqx0tjxdupXAZ5mlu56mBg0a6Nz2454TuvaI73S1F5fpSsO/TZ2qvbhM1x7xnf5xz4lcz0NhdO7cOW9nIeuuXdN63TqtX3hB65tu0tr0Qa11ZKTWAwZo/dVXWsfFpaW/fEzrhUFaf4LWC4O1vnzce3nPQ/ny3O7dq/WoUVpXq2bOWVCQ1j17ar10qdYJCd7O3XUjX55b4RFybtPs2rXLMxvaOkjrTwPMb4D99GmA1tsGe2Y/mZg5c6YG9D///JM6LyYmRvv5+em///47dd6JEye0j4+PfuWVV1xuLzQ0VE+ZMsXp8oMHD2pAz5o1y2Z/zZs3z5B29OjR2twC2+rXr5+uVKmSy3xorTWga9SooRMTE1PnPfPMMxrQ48ePT52XmJioS5Uqpfv375867+GHH9YlS5bUp0+fttlmmzZt9M033+x0n4mJiXrDhg0a0Dt27NBaa719+3YN6N9++83peu6+V+vxi4qK0ikpKanzL168qIsUKaIfeughm7wcPHhQ+/v767feeit1fqVKlXSxYsV0XLp7kilTpmhAP/LIIzb7j4qK0q1bt079f9y4cTowMNDm2tBa6wEDBugSJUqkHutZs2ZpQI8aNcomXefOnXWNGjVS/1+zZo0G9KpVq2zSTZ48WRcrVizD8cjMa6+9ppVSOsHBb/eWLVs0oCdMmKC11jouLk4HBQXpXr162aSz5qlr164288+ePatDQ0P1oEGDbOa/8cYbGtCjR49OnXfLLbfo6tWr21x7Bw4c0H5+fvqZZ55JnXfs2DHt6+urhw0bljrv6NGj2sfHR7/44oup8+w/N5s3b870mnLG3eNg3ef06dN1YmKijo+P1ytXrtRly5bV5cqV05cvX9Zap1276d+r1lrv27dPA/qTTz7JNE+Zfa8CP2sHsaCrx4xvA3copd5SSmWor6OU8ldKTQFuB97KQYxe6Bw+E8/g+Tu4kphMUopt246kFM2VxGQGz98hJcmF2bFjrkuJf/sNYmNhxgy45x6IiEhb19qjNT5Q9SEpPfammjVh7FjT0dfmzabd9+rV0KWLGWP68cdh0ybzyEMIITzBVSmyl0uPAWrUqEGNGjVS/y9dujSlS5fOUF3XXuPGjZk8eTJTpkzhjz/+8Hrb2LZt2+Lnl9bXbe3atQFo37596jw/Pz+qV69ObGxs6rwVK1bQqVMnIiIiSEpKSp3at2/Pb7/9xgVLTaNr164xYcIEateuTXBwMP7+/qmll9bqtDVq1KBo0aIMHDiQ+fPn2+wnu7p27WpTJXvz5s1cuHCB3r172+S3QoUK1K5dm/Xr19usf+uttxKR7p7E0XGxzrc/Lk2aNKFKlSoZjsuZM2fYtWuXzfqdO3e2+b9+/fqZXkNgrqNz587Rp08fvv3220xLjq2OHTtGkSJFCAjI2IRhzpw5+Pj40KdPHwAiIiK4++67+frrrzl//nyG9N26dbP5/48//iA+Pp4ePXrYzL/33ntt/o+Pj2fHjh306tXL5tqrUqUKzZs3Z926danzypUrR9u2bfnkk09ISUkBTO/SKSkpqdWrHcnJNZXV4zBw4ED8/f0JDQ2lXbt2VK9enRUrVhAcHOxyP9b20sdysQmb0wBZa70ZeA7TivGIUmq+UuoVyzQfOAI8Djyntd6SazksgGZsOEBicorLNInJKczc4LQDcVHQpG9L3KCBGct3wADYsgV69oSvvoLTp2HtWhg+HG66yfUQTPVHQlhlr98ICQulTPvv996D48fhm2+gbVv4+GNo3twMQTVqFKRrQySEENnibNg/n4B88dDUUc+zgYGBqe1Hnfnss8/o0qULkyZN4qabbiIyMpJx48al3vzntWLFitn8bw2cHM1P/95OnjzJ3Llz8ff3t5mGDh0KwJkzZwDTw++YMWPo06cPy5YtY9u2bSxatAggdXsRERGsWbOG8uXLM3jwYCpWrEi9evX46quvsv2+ypUrZ/O/tY13mzZtUvNqDdj/+OOP1Px64risX78+w3GxBo32+7G/jgIDA93q8ComJoYvvviC2NhYunXrRqlSpWjTpg2///67y/WuXr1KYGBghvkJCQl89tln3HrrrYSHhxMXF0dcXBzdunXj6tWrfP755xnWsT/Gx48fB8zDovTse6A+d+4cWusM6wOULVuWs2fP2szr168fR48e5ccffwRM9ero6OjUhxaOZPeays5xGDFiBNu3b+f3338nLi6ODRs2cNNNN7ncD5AaQF+5ciXTtNnlapgntNZvK6V2AC8A3QBrSH8FWAu8prXekGu5K6CW7DyWoeTYXlKKZvHOo4zvWi+PciXy3LFjsGKFGX941So4f96M19u8uSkl7tjRDD2UnbGIg8tBl/2ez7PIOX9/0/P1nXeaNsmLF5sOvl55BcaPh8aNoXdvuO8+cDA8gxBCZMp+2D/IF6XHOVG6dGnef/993n//ffbu3cucOXMYPXo0pUqVYtCgQVnaVlBQEGBKadOXCNoHYbmhRIkStGzZkuHDhztcXr58eQAWLlxI3759GTFiROqyS9bhBdNp0KABX331FUlJSfz888+8+uqr9OzZk99++4169epl+b3ad+hVokQJwHSOVbduXQCSkpJSSzDDwz3TT2+JEiUoXbo0U6ZMcbi8Vq1aHtkPmJLZe++9l0uXLrF27VqGDx9Ohw4dOHLkCD5OhmosUaJEhg7SAL755hvOnj3Lxo0bMzwEAFOq+uijj9rMsz/G1oD35MmTqccY4MSJEzbpihUrhlKK//77L8N+/vvvv9RzZdW1a1ciIiKYN28eJUqU4M8//0xtm+1KZteUI9k5DpUqVXLYI3hmrA8CSpYsmeV13eUyQAbQWq8H1iulfABrTs5ord3rkkxkEJ/gXkP3+GvZ72RB5EOJiaaa7Xffmem338z88uXNOLodO8Idd9hWlxYFW5Ei0K+fmY4dM8NIzZ8PQ4bAc8+ZUubevaFrVwgL83ZuhRDXC2sp8oGPIOVavik99pRatWoxYcIEpk2bxp9//uk0XWBgYIZOpMDcmAP8+eefNGzYEIC4uDg2bdrksYDPmQ4dOrB582bq1q3rsirp5cuX8ff3t5k3a9YsJ6lNde6mTZsyfvx4li5dyu7du6lXr16O32uzZs0IDw9n37599OvXD7ANkD2lQ4cOvPvuu1SsWDFDSWp2WEt7XZUyhoWFceedd3LgwAGefvppzpw543S4o9q1a5OYmMiRI0eoUCFtmLQ5c+YQEhLC0qVL8bUbJWTOnDnMnj2b/fv3uxxnuH79+oSGhvLFF1+k9r4N8MUXX9ikCw0N5ZZbbuGLL75gzJgxqfs7fPgwmzZt4sknn7RJHxQURM+ePfn0008JCgoiICCA++67z2k+7Dm7phzxxHFwl7UzL08+NLHn9tWttU4BTuZaTgqR0EA/LrkRJIcGePbLR+Sx5GRTZXbzZlNS7OlSYlGwlC8Pzz5rpl27TKnyJ5/Agw9CSAh062bGY27TxlxDuW1xBbhyNPN0wZHQ7Uju50cIkTXpS5Gv89Lj8+fP06ZNG3r37k3t2rXx9/fn66+/5ty5c7Rr187penXq1GHq1Kl89tlnVKtWjfDwcGrVqkXHjh2JiIjg0UcfZezYsSQkJDBp0iTC8uBB5Lhx44iOjqZVq1Y88cQTVK5cmXPnzvHnn39y4MABPv74Y8AEjHPmzKF+/fpUr16dRYsWsWnTJpttffvtt3z44Yd07dqVKlWqEB8fzzvvvEN4eDi33norQI7fa5EiRZg8eTKPP/44p06domPHjoSFhfHff/+xbt06Wrdu7XToo6x45pln+Oyzz2jZsiXPPPMMtWrVIj4+nj179rBhwwa+/vrrLG2vZs2a+Pn58fHHH1O8eHECAwOpVasWkydP5sSJE9x2222UL1+eI0eO8M4779CgQQOXYwG3atUKgG3btqUGyCdPnmTFihX06dOHO+64I8M6ZcuWZfbs2cydO5exY8c63XaxYsUYMmQIEyZMIDw8nDZt2rBjxw4++ugjAJtS7fHjx9O5c2fuvPNOBg8ezKVLlxg9ejQRERE899xzGbbdr18/ZsyYwYwZM+jWrZvDJg7pLVu2jI8++sjlNWXPU8fBXVu3bsXf35+mTZvmeFvOSATmBV2jyrNwW6zLatZ+PopuUZF5mCuRI1rD/v3w88+wfbt53bEDrNWhypc3HW517GgCHCklFq7UqZNW5XrjRhMof/65eS1dGrp3h2bNoFEj0xGYkyphORLZJa30yRkvjqcqhMiEtRR53/TrvvQ4KCiIhg0bMmPGDA4fPoyPjw+1atXik08+4e67nX8HDR8+nL179zJgwAAuXbpETEwMa9eupWjRonz77bc888wz9OzZkwoVKjBq1Ch++OGH1LFyc0vFihX5+eefGTNmDC+99BKnTp2iRIkS1KtXL7WEFuDdd99Fa83LL78MQKdOnfj000+Jjo5OTVOjRg2Cg4MZP348x48fJzw8nMaNG7Nq1arUIM4T73XgwIHccMMNTJ48mQULFpCYmEhkZCStWrWiQYMGHjkuERERbNq0iXHjxjFx4kSOHj1K0aJFqVWrFt27d8/y9kqUKMF7773HxIkTiYmJITk5mTVr1tCkSRPeeecdnnnmGc6ePUvp0qVp164d48ePd7m9ypUrEx0dzTfffMM999wDwCeffEJSUhIPP/yww3Vq165Ns2bNmDt3boaxjO2NHTsWrTUfffQR77zzDk2aNGH27Nk0b97cptOzDh06sGzZMsaOHUvPnj0JCAigdevWTJo0KbV6fnrNmzenRo0a/PPPPy4757KqXr16pteUPU8eB3d8++23dOnShZCQkBxvyxnl7V4A86OoqCi9c+fOXNv+4TPxdHh7A1cSnddSD/b3ZcWQllQqEZpr+SiM4uLiMh1fLVNamx6k0wfDP/8M1p4QAwMhKsoEL40amTalN94opcS5zCPnNj9LSDBV8+fPN6/WsT+LFIFbbjHXmfV6q1Qp59fbleOwtCoku+g4xzcYuhzI9RvvAn9uCzE5t2l2797NjTfe6NmNXjkOq1pA2415HiDnRjVckT8U1nM7e/Zsnn76aY4fP56rwZnVF198Qc+ePVm/fr3T8Zc9Lb+f22PHjlGxYkW+//57h6XV9jL7XlVK/aK1ztAQOv8egQKsUolQpvZpyOD5O0hMTrEpSfbzUfj7+jC1T0MJjvOL//7LGAxbenXEz89Uke7ZMy04qVvXdMQkhCcFBpq2yF27mur7u3eba9J6Xb79NlyzlPaWLJl2PVqnslm8ObZvw2ivgLVpFKJAkg4bhfCYBx98kEmTJjF16lSef/55j25769atLFu2jCZNmhAUFMQvv/zCa6+9RtOmTWnRooVH93U9mzx5Mq1atXIrOM4JCZC95LZapVkxpCUzNxxk8c6jxF9LIjTAj25RkQxoWSV3g+Njx2DbNjOdOAG1apmgrk4dU/KUG9U1rxdnzsAvv9gGxEcs7St9fExJcKdOacHHTTeBpYdIIfKMry/Uq2emhx4y8xIS4I8/0q7d7dth5UqwDoESGZkWLFtrN2TSFslhT7hW13mbRiGEECIrfH19+fjjj9mxY4fHtx0WFsb69et5//33uXDhAqVLl6Znz568+uqrGXq9LszKlSvHY489luv7kSrWDuR2Fes8deGCCfisAfHWrXDU0vGOn5+5QT6Zru+10FATBNapkxY0161bYAJnm+p8Fy6YdsLpg+EDB9IS16hhG0xERUlPwvmYVNV0ID4efv01LWDevh3++SdtebVqtlWzGzbMeI1vG5yxFNknAKoNgMaZDxfhCXJuCy45t2lypYq1F+X3qpoi++TcFlwF7dzmahVrpZSrVt0pwHlgp9ZaujL1psREU4JkDYS3bTPVMK0PQapXh5gYiI42U4MGEBwM586ZXnP/+ivt9YcfYO7ctG2HhDgOnCtXzt+Bc0qKaRt88iT89x8BW7fCn3+aYHjv3rRjU6mSCRIee8y83nILyE2buN6Fhpoe05s3T5sXF2cemlkfCm3aZIaXAtNu+cYbbatm1xha4MZTFUIIIYRwxt1HBLMBa1Fz+nL+9PNSlFKfAQ9prV10eyo8QmtT2mkNhLdtg5074aqlQ52SJaFJE+jVywTDjRuD3QDiqYoVy3gTDSZw3r3bNnD+8UeYNy8tTXCw88DZbhw0j73v+HgT8J48CadOpf1tP506ZaaktCG1QsC0xWzcGB54IK102EXX/kIUKEWLmvG207ffOXEirX399u2mE7A5c8wyf3+oGgEVrkHZFAjxhcotYM0OCA/POAUFSYd0QmST1lqqUwohhAfkpJa0uwFyc+AT4BvgS+AEUAboCdwJDAbqAWOBw8BL2c6RcOzUqbRA2DqdPWuWBQebEs/Bg00w3KSJZ3qxLVbMDCXTrJnt/Li4jIHz2rWmd12roCDHgXOVKhkD54SEtGDWVbBr/dvZoO9hYWYInNKlTYDeuHHa/6VLQ6lSnI+MJKJOnZwdFyEKmjJloHNnM0HGntq3/gSbf4LLAMnAKsvkgK+v48A5u5N0eCcKCX9/f65cuZInveMKIURBd+XKFQIDA7O1rlttkJVSXwF7tdYZAl+l1ATgRq11N6XUeKC31rpqtnKTT3i9DfLly6ZtbPp2w4cOmWU+PibQtAbC0dHm//zQXuD8+YyB865d5kbbKigIatc2VT+tAe/58463FxCQIcC1+T/9/FKlTDXwTEh7t4JLzm0u2zoI/pgOZR+Eai/AxYtp04ULtv+7MyUmurffoCASo6Pxf+wx6NbNrc+5uH7I5zbNhQsXOHHiBJGRkQQHB1/3JckFrS2jSCPntuC63s+t1pqkpCQuXrzI6dOnKVOmjM040vactUF2N0C+AHTTWq92sKwNsEhrXUQp1Rb4VmudvXA9n8izAPnKFdNDcmws7N9vSmusbWSTLWMkV6xoGww76kQnv7twIWPgnJDgPNi1/l2kiMerasrNWMEl5zaXeXo81YQE94Lss2dJXrIE30OHzHfC/febnrujo6UqdwEgn1tbFy5c4OTJkyS6+wApH0tJScEnP/dRIrJNzm3BVRDOrZ+fH0FBQZQqVYqgTEaayek4yNeAW4AMAbJlvrXNsQ8Q7+Y2C7bERDOcUmys7fTvv2l/nz5tu07RoqZa8IsvprUbzurYpflRkSImwG/SxNs5EUJkl6fHUw0MNFPJkpkmvThyJEX/+AM+/tj0gTB9umm28dBD8OCDpoq4EAVAkSJFKFKkiLez4RHy8KPgknNbcMm5NdwNkL8AxiqlkjFtkE8CpYEewBjgY0u6BsBez2YxH0pJMVWDHQW91un48bTxR60iIuCGG8zUuLF5rVjRvFaqlP97hBZCCG/w8TE98MfEwLvvwuefw6xZMHQovPCCaTv98MNmjHJpsyyEEEKIHHA3QH4WCAcmWab0FgDPWf7+E9jsmax5UXIy/Pab89Lfo0fhml1H3cHBacFv27Zpf6cPgsPDvfN+hBCioChSBAYMMNOePSZQnjsXli41TTMefNCULNet6+2cCiGEEOI65FYb5NTEStUEmgJlgePAVq3131naoVIVgOFAI+BmIBioorU+lC7NbKCfk03s1VrXzmQfPpZ9DLTkdS8wTmv9lTt5bKSU/jn9DD8/iIxMC3QdTSVKSHu464BUHSm45NwWXJme26QkWLHCVMH+5hvzf3S0KVW+7z5Te0fkS/K5Lbjk3BZccm4LrsJ2bnPaBhkASzCcpYDYgeqY4aF+ATYA7RykGQ9Ms5tXGfgUWOrGPsYDzwMvW/ZzH/CFUupOrfXyzFZOKV8epkxJC37LlMmdMX2FEELknJ8f3HmnmU6ehE8+McHy//4HQ4ZA9+6mVPm226QZixBCCCFccvtOQSkVqpR6Sin1pVLqR6VUDcv8+5RSLkt07azXWpfRWnfCtG3OQGu9X2u9Jf0E1LAsnpNJPktjguPXtNava63XaK0HAmuA19zJoC5dGu6913QqVb68BMdCCHG9KF0annkGfv/djOH80EPw7bfQpg1UrQpjxqQNmyeEEEIIYcetAFkpdQPwOzAZE6jGYNokA9yGCUjdorVOyTyVQ32BX7TWf2WSrj0QAMy3mz8fqK+UqpLN/QshhLheKAWNGsHUqabTxAULoGZNGDcOqlQxAfMnn5jh9oQQQgghLNytYv0GkIAJjo+RNqwTwDpMT9a5RinVHFM1+yk3ktfF5HWf3XxrYF0HOOi53AmRfxw+E8+MDQdYsvMY8QlJhAb60TWqPI+2rEqlEqHezp4Q3hEcbMZPvv9+OHwY5syB2bOhTx/TPvm++0x75caNpS8JIYQQopBzN0BuCzymtf5XKWVf3/goEOnZbGXQF0jEtEHOTHEgTmfsfexsuuUZKKUeAx4DiIyMJC4uLns5FfnaxYsXvZ2FXPPz4bO8tnwPScmaon6aon4Aifz0579s2R3LC51q06iSw8u/QCjI57aw8+i5jYiAp56CJ57Ab+NGAubPx3/uXNT06STXrs213r251rOnaWojcp18bgsuObcFl5zbgkvOreFugBwAODtiEZjgNVcopQIxnXp9q7U+7c4qgKOuuV0WC2itPwQ+BIiKitKFqQe3wqYgntvDZ+J58su/uZJovfTtL3fNk1/+zYohLQt0SXJBPLfCyJVze9ddZjp/Hj77DN9ZswgeOZLgsWPNmModOkDLllCnjnTulYvkc1twybktuOTcFlxybt3vpOt3oLuTZR0xPUXnlruBomTSOVc6Z4FiSmWoJ1cs3XIhCpQZGw6QmOy6eX9icgozN0jrAiEyiIiAxx6DzZvhr79MJ1+//AKDB0P9+mYYvzvvhNdeg59+gqtXvZ1jIYQQQuQSd0uQJwNfWmLOBZZ5dZRSdwOPAF1yIW9W/YDTQKbDM1n8BQQC1bBth1zH8rrLc1kTwrm8bA+8ZOcxklJcj2melKJZvPMo47vW8+i+hShQ6tSBSZNg4kQ4eNAExNZp2TKTJiDAtFdu0cJMzZpB8YLbfEEIIYQoTNwKkLXWi5RSgzHDJD1smT0XU+36Ca31itzInFKqDGac5Klaa3erca/AdCLWGxibbn4f4E+ttRShiVy3Zu9JBs/fQWJySmrgeikhiYXbYvnql6NM7dOQ22p5ro1jfEKSe+muuZdOiEJPKTMsVNWq0LevmXf6NGzaZILlDRvgzTdNIA1Qt25awNyiBVSqJB1+CSGEENchd0uQ0VpPU0rNA24FSgNngE1a6yy35lZK3Wv58xbLa0el1CnglNZ6XbqkvS15dFq9WimVBMzRWj9iyedJpdRbwItKqYvADqAXcDumurYQuerwmXgGz9/BlcTkDMuSUjRJKckMnr/Do+2BQwP9uORGkBwa4PZHXghhr2RJ6NLFTACXL5uxlq0lzJ9+CtOnm2WRkbYBc/364Gvfx6UQQggh8pss3S1rreOBHzyw3y/s/p9qeV0HtE43vx+m1HeHi235Wqb0XgYuAU8DZYG9QE+t9TfZzbAQ7spKe2BPVXfuGlWehdtiXVaz9vNRdIvK7Q7nhShEQkIgJsZMAMnJ8OefaQHzhg3w2WdmWXi4qYptDZijo836hcniCnDlqO08n2qQst92XnAkdDuSd/kSQggh0nEaICulWmVlQ1rr9VlI61a9M631zdnZltY6Gfg/yyREnvJGe+BHW1blq1+OkpSSsdTayt/XhwEtq3hkf0IIB3x94eabzfT446A1/PuvbTvmkSNNWj8/uOWWtIC5eXMoVSpn+09JgYQEuHbN/Vfr3yEhUKsWVK8OQUE5PxaORHaBAx9ByjXnaXwCoIJU9hJCCOE9rkqQ15I2XJKzoZPSk7pjQuCd9sCVSoQytU/DDO2ewZQc+/v6MLVPwwI9xJMQ+Y5Spi1ypUrQu7eZd/as6S3bGjC/+y688YZZVqsWREWZwDorwa31Ndn5A7Is5blyZZOX2rXNq3UqVy5n7arrj4SDszLZvy/UG5n9fQghhBA55CpAvi3d30WBd4E/gYXACaAMcD9QF3g8l/InxHXHW+2Bb6tVmhVDWjJzw0EW7zxK/LUkQgP86BYVyYCWVQpkcJy+p/BifomcS/LPtZ7ChfCI4sWhc2czgRky6pdf0gLmrVvB39/0lB0YmPYaEWH7v6dfz5+HvXvTpj17YP16087aKjzcNmC2BtA1akBwcObvPbgcVHnIeSmyTwBUfQiCy3rmWAshhBDZoLTOrGAYlFKzgSSt9QAHyz4CfLTWD3k+e94RFRWld+7c6e1siFwQFxeX6wOgj1jyh1vtge+PrihDLuWAfU/hFUI1R+KVTYm5J3sKF96TF59b4UBKChw9ahs0W//+99+0dEpBxYoZS5xr14by5W1Lna8ch6VVIdmMJR3nU42i1jbIvsHQ5YAEyAWEfG4LLjm3BVdhO7dKqV+01o3s57tbhHU30NPJss8wpcpCCApne+C8HPPZur+87ilciELHxwduuMFMbdrYLouPh3/+yVjq/NNPZplVWBjUrGlb4px4FyQvAf90ozdK6bEQQoh8wt0A2QeoDqxysKwG0v5YiFSFrT1wXo/5DN7pKVwIkU5oKDRoYKb0tIZjxzKWOm/eDAsXmuVWJSCo5RnoBgRK22MhhBD5g7sB8jLgVaXUaWCR1jpZKeULdMf0FP1tbmVQiOtRYWkP7K2SXG/0FC6EcINSZgzoyEi4/XbbZVeupJU6r34dtm8naEkc/KlgcncpPRZCCJEvuBsgPwXcgKlOnaSUOgcUs6z/k2W5ECKdSiVCGd+1XoEO0LxVkuuNnsKFEDkUHAw33WSmO1vA0qrEb44gdMYJ6Pc1fPgZ9Orl7VwKIYQo5NwKkLXWp4GWSqm2QFOgHHAc2Ky1/iEX8yeEyMe8VZLrrZ7CC6O8bl8uCglLj9aJehXc1hZe2wf33QerVsGUKaYKtxBCCOEFPllJrLVepbUer7UebHmV4FiIQsxbJbldo8rj5+N6PFY/H0W3qEiP7rewWbP3JB3e3sDCbbFcSkhCk9a+vMPbG1iz96S3syiuZ/VHQnB5aDfZDCn10kvw8cfQqBH8/ru3cyeEEKKQchogK6WCsrPB7K4nhLj+hAa6V0Lr6ZLcR1tWxd/X9fO9gtZTeF5L377cvpZAUormSqJpX374TLyTLQiRieByEPO1aXvs7w+vvGJKkM+fh+hoeP992069hBBCiDzg6g7zkFLqGaVUUXc2pJRqppRaCgz1SM68aN/JS9Qb/T0jlvwhN39CuOCtklxrT+HB/r4Z9u/nowj29y1QPYV7Q1balwvhMXfcAb/9Zl6feAK6dYMzZ7ydKyGEEIWIqwD5cWAgcFwptVgp9axS6g6l1E1KqVpKqaZKqQeUUm8rpfYBazHtkj/Mg3znKqlGKIR7vFmSa+0p/P7oioQF+qEUhAX6cX90RVYMaenxoaUKm6y0LxfCo0qVgm++gTffhOXLzVBS69d7O1dCCCEKCaVdVF+yDOXUFXgEaA0EYeLH1CTAYUzv1h9qrQ/kVkbzUlhkDV3ywbdT/w/29/X4MDXCO+Li4ihatKi3s1GgOBoHGWzHfM6LYFXOrWdVeWEZ7lRuVQoOvto5V/Mi57bgyvTc/vKL6bzrwAEYORJGjAA/6XzveiCf24JLzm3BVdjOrVLqF611I/v5Lot+tNbJWuuvtNadgKKYHqy7A72BDkAlrXUVrfULBSU4dkSqEQrhnJTkFkzeal8uhI1bboEdO6B3bxg71oytHBvr7VwJIYQowNy+s9FaXwO25WJe8q3cGKZGiIKkMIz5XNh0jSrPwm2xLqtZS0/hIk+Eh8PcudC2LQweDDffbHq77trV2zkTQghRAGVpmKfCzNPD1AghRH4mPYWLfOfBB01pctWqpvOuxx+Hq1e9nSshhBAFjATIbpJqhEKIwkR6Chf5Uo0asGkTPPssTJ1qhoPavdvbuRJCCFGASIDsBqlGKIQojKR9uciXAgLgjTdg2TL47z/TTnnmTBkzWQghhEdIsagbpBqhEKKwkvblIt/q1MmMmfzgg/Doo7BqFUyfDoWoB1YhhBCeJyXILkg1QiGEECIfK1cOVq6EV1+Fr76CqCjYssXbuRJCCHEdy1KArJTyUUrVU0rFKKUKbMSokGqEQgghxHXBxwdeeAF++sn836IFvPYapKR4N19CCCGuS24HyEqpx4H/gN+AH4FalvlLlFJP5U72vKN66TD+HNue8V3rScmxEEIIcT1o2hR27oTu3eHFF6FdOzh+3Nu5EkIIcZ1xK0BWSj0KTAGWAL0whaxWG4DuHs+ZEEIIIURWFC0KCxfCjBmmt+ubb4bvvvN2roQQQlxH3C1BfhZ4Q2v9GLDYbtkeLKXJQgghhBBepRQMGAA//wxly5rOvJ57Dq5d83bOhBBCXAfcDZCrAN87WRYPFPVIboQQQgghPKFOHdi6FQYPhjffhGbN4J9/vJ0rIYQQ+Zy7AfJpoLKTZbWAox7JjRBCCCGEpwQHw/vvw+LFcOAANGwI8+Z5O1dCCCHyMXfHQf4GGKWUWgsctszTSqmSwDOYtslCCCGEEPlP165wyy3Quzf07Qvr18N770FgoLdzJnJicQW44kYZTXAkdDuS+/kRQhQI7pYgjwASgD+BHwANvAPsBpKBcbmSOyGEEEIIT7jhBvjxR9PD9cyZEBMDR6UC3HUtsgv4BLhO4xMAFe7Om/wIIQoEt0qQtdZnlFKNgCFAe2C/Zd33gLe01hdyLYdCCCGE8LjDZ+KZseEAS3YeIz4hidBAP7pGlefRllUL7hCHfn4wYQI0agT9+plS5S++gJYtvZ0zkR31R8LBWa7TKF+oNzJv8iOEKBAyLUFWSgUopd4Camutx2utW2ita2qtb9Vaj5XgWAghhLi+rNl7kg5vb2DhtlguJSShgUsJSSzcFkuHtzewZu9Jb2cxd91zj+nAq0gRuP12U91aa2/nSmRVcDmo8pDzUmSfAKj6EASXzdt8CSGua5kGyFrra8BAIDj3syOEEEKI3HT4TDyD5+/gSmIySSm2QWFSiuZKYjKD5+/g8Jl4L+Uwj9SpA9u3Q8eO8OST0L8/XLni7VyJrKo/EpST21kpPRZCZIO7bZB3AvVzMyNCCCGEyH0zNhwgMTnFZZrE5BRmbjiYRznyoogIWLIExoyBuXOhRQs4fDiztUR+4qwUWUqPhRDZ5G6A/BzwvFLqTqWUyskOlVIVlFLvKqU2K6UuK6W0Uqqyk7RNlVIrlFJxSql4pdQfSqn73NjHIct27aeuOcm7EEIIcb1bsvNYhpJje0kpmsU7C0kHVj4+MHo0fP017Ntn2if/+KO3cyWywlEpspQeCyGyyd0A+QugBPA1cFUpFauU+jfdlJXHrdWBnsA5YIOzREqpzsB64D/gAeBuYAYQ5OZ+vgdutZvWZSGfQgghRIETn5DkXrpr7qUrMLp0gW3boFQpaNsW3nxT2iVfL+xLkaX0WAiRA+6Og7waM7STJ6zXWpcBUEoNANrZJ1BKhQOzgKla6yHpFv2Qhf2c1lpvyUlGhRBCiIImNNCPS24EyaEB7t4iFCC1apnOu/r3h+eeM22UZ86E0ALaq3dBkr5Hayk9FkLkgLvDPPX31A611q4bPhk9gFLAG57arxBCCCGga1R5Fm6LdVnN2s9H0S0qMg9zlY+Eh8OXX8Jrr8HLL8OuXbB4MVSt6u2cCVespcj7pkvpsRAiR9ytYp3XWgBngfqWdsdJlmrdo5VSvm5u4y5LG+cEpdQWaX8shBBCwKMtq+Lv6/rn39/XhwEtq+RRjvIhpeDFF2H5cvj3X9Mu+fvvvZ0rkZn6IyGsspQeCyFyxK0SZKVU38zSaK3n5jw7qcoDIcACYDzwC9AGGAkUBZ7JZP1vgO3AQaAM8ASwWCn1oNZ6vqMVlFKPAY8BREZGEhcXl+M3IfKfixcvejsLIpfIuS245Nx6VoQvvHtvTV5bvoekZE1Suna2fkrh56t4oVNNInwTc/23MN+f26ZN8fnxR0L79MGnY0eujhhBwjPPmABauOSdcxsMrX6BBCAhzgv7Lxzy/edWZJucW0NpNzqgUEo5qxadurLW2t2S3fTbHYDpeKuK1vpQuvkrgbbAc1rrN9PN/wB4BCiltT6fhf34AluAslrrGzJLHxUVpXfu3On2+xDXj7i4OIoWLertbIhcIOe24JJzmzsOn4ln5oaDLN55lPhrSYQG+NEtKpIBLatQqUTetLm9bs5tfDwMGAALF0L37jBrlqmKLZy6bs6tyDI5twVXYTu3SqlftNaN7Oe72wOHo3pWJYA7MT1M98lB3hw5Y3ldZTd/JfA/oC6wyd2Naa2TlVJfABOVUuW01sc9k00hhBDi+lSpRCjju9ZjfNd63s5K/hcaCgsWmKrWw4bB7t2mXXLNmt7OmRBCCA9zqw2y1vqwg2mH1noc8CnwrIfz9Zd113bzrXWa3Onoy551XRmzQQghhBBZo5Tp2XrlSjhxAho3hm+/9XauhBBCeJgnOunaAHT2wHbSW2J57WA3vz1wFfgzKxtTSvlhesb+V2v9X45zJ4QQQojC6Y474JdfoFo1uOsuGDsWUrLz3F4IIUR+5IlBDpsCl7KyglLqXsuft1heOyqlTgGntNbrtNZ/KqVmA+OUUj7ADkwnXQOA8VrrS+m2lQTM0Vo/Yvn/fuBuYDkQi+mk63HLvu7P3lsUQgghhLCoVAk2boT//Q/GjIEdO2DuXIiI8HbOhBBC5JC7vViPcjA7AKiHKT1+L4v7/cLu/6mW13VAa8vfA4GjwJOYIPcQ8KzWeordur6WyeogUBqYDBQHLmN6tO6gtZYxGoQQQgiRc8HBMHu2aZf87LMQHQ1LlsCNN3o7Z0IIIXLA3RLkMQ7mJQCHgVeAV7OyU611puMjaK2vASMsk9vb0lpvAW7PSn6EEEIIIbJMKXjySbj5ZujRwwTJc+bAPfd4O2dCCCGyyd1OunwcTMFa69pa6zFa64TczqgQQgghRL7UqpVpl1ynjhkG6uWXITnZ27kSQgiRDW4FyEqpVkqpMCfLwpRSrTybLSGEEEKI60iFCrB+vRkvecIEuPNOOHfO27kSQgiRRe72Yr0GqONkWS3LciGEEEKIwiswEGbMgOnTYfVq0z7599+9nSshhBBZ4G4bZFdthgMBqUckhBBCCAHw2GNQv76pbn3rrfDxx9Crl7dz5VxSEly6lL3p4kWH8yO0hoCAtCkw0PZ/R1NO0wQFQZMmEOaw0qMQQrjFaYCslKoMVE03q5GDatbBwMPAv57PmhBC5E+Hz8QzY8MBluw8RnxCEqGBfnSNKs+jLatSqUSot7MnhMgPbr3VtEvu0QPuuw9+/NH0cK21mVJS0v52Ns8TaRITMw9uE7LQlUxgoAlA7adSpcxreDiEhpJw7RpBPj5w7ZrZ/rVrjqcLFzJPk5X8hYdDnz4wcKDpPE0IIbLIVQlyP2A0oC3Tu9iWJGvL/0mYcYaFEKLAW7P3JIPn7yAxOYWkFA3ApYQkFm6L5atfjjK1T0Nuq1Xay7kUQuQL5cqZwPiZZ2Dq1MzTu6KUmXx80v52539/fxM0WgPZiAiIjHQc5GY2hYaa7bnhalwcQUWL5uw9W2ltOj1zFURfuwZnzsCCBabE/oMPTK/iAwea0vtQeXgphHCP0lo7XqBUJaAyJgj+ERME77JLlgD8rbU+m4t5zHNRUVF6586d3s6GyAVxcXEU9dQPtshX8uLcHj4TT4e3N3Al0XmrkmB/X1YMaSklyR4kn9uCq1Cd24sXTZCXPnh1J8C1TtcZr57bs2dh3jzTFnz3bihSJK1U+aabvJOnAqRQfW4LmcJ2bpVSv2itG9nPd1qCrLU+jBnnGKXUbcAvWutLuZdFIYTI32ZsOEBicorLNInJKczccJDxXevlUa6EuL6kb6JQzC+Rc0n+haOJQni4t3NQeBQvDk8/DU89BT/9ZALljz4ypfhNm5pAuWdPCAnxdk6FEPmQu+Mgr5PgWAhR2C3ZeSy1WrUzSSmaxTuP5lGOhLi+rNl7kg5vb2DhtlguJSShSWui0OHtDazZe9LbWRQFiVLQsiXMnw9Hj8Kbb0JcHDz0EJQvD08+CX/+6e1cCiHyGXeHeUIp1V4ptVgptUspdcBu2p+bmRRCiPwgPiHJvXTX3EsnRGFy+Ew8g+fv4EpicoYHTUkpmiuJyQyev4PDZ+K9lENRoJUoYdqC79oF69ZB587w4Yemt/HmzWHOHLhyxdu5FELkA24FyEqpTsByIASoDezB9Fx9A5ACrM+tDAohRH4RGujeyHihAe6OoCdE4ZGVJgpC5BqloFUr+OQTU6r8xhtw+jT0729KlZ9+Gv76y9u5FEJ4kbslyCOB94FOlv9HaK1bA3UBX+A7z2dNCCHyl65R5fHzcd1Zjp+PoltUZB7lSIjrhzRREPlOyZLw7LOwZw+sWQMdO8K0aVCvHrRoYTr6klJlIQoddwPk2sA3mNJijaVzL63138AYTAAthBAF2qMtq+Lv6/pr09/XhwEtq+RRjoS4fkgTBZFvKQWtW5shoo4cgcmT4eRJ6NvXDIk1ZIjpDVsIUSi4GyCnAEnajAl1CqiYbtkxoJqnMyaEEPlNpRKhTO3TkGB/3wwlyX4+imB/X6b2aViwe+IVIpukiYK4LpQqBc8/D3v3mjGs27UzvV/XqWOqZs+fD1evejuXQohc5G6AvBczJjLAz8AQpVQ5pVQp4DngkOezJoQQ+c9ttUqzYkhL7o+uSFigH0pBWKAf90dXZMWQltxWq7S3syhEviRNFMR1RSm47TZYuNC0VZ40CY4fhwcfNKXK1qrZQogCR5lC4UwSKfU4UElrPUwpdQvwA1DEsjgZeEBr/WXuZTNvRUVF6Z07d3o7GyIXFLYB0AsTObcFl5zbguHwmXg6vL2BK4nJqfMqhGqOxKcFzcH+vqwY0lJqYRQABfJzm5ICa9eacZUXL4bERFOq/L//mXGVfX29ncM8USDPrQAK37lVSv2itW5kP9/dcZDf11oPs/z9C1AfGAg8AzQoSMGxEEIIITxPmiiI656PD9x+O3z2mWmr/Npr5vWBB+Dmm+Hbb8GNgichRP6WaYCslApQSj2tlKpnnae1PqK1nqm1fkdrvSt3syiEEEKIgkCaKIgCo3RpGD4c/vkHvvwSrl2Du+4y1bK3bfN27oQQOeBuFesrQHutdaEY71iqWBdcha3qSGEi57bgknNbcMm5LbgK3blNTIQZM2DMGDh1ylS5njABqhW8fmwL3bktRArbuXVWxdrdriJ3A1WBQhEgCyGEEEII4TZ/fxg82HTi9frrZlq8GAYNghEjTO/YIn9bXAGuuDEOe3AkdDuS+/kRXuNuL9ajgJFKqfq5mRkhhBBCCCGuW+HhMHYs7NsHDz8M779vSpEnTIDLl72dO+FKZBfwCXCdxicAKtydN/kRXuNugDwcCAN2KqX2KaU2KKXWp5vW5WIehRBCCCGEuH6UKwfTpsEff5iOvV5+GWrUgI8+guTkzNcXea/+SFCZhEbKF+qNzJv8CK9xN0BOBnYBG4BYIMkyzzql5EruhBBCCCGEuF7deCMsWQIbNkDFijBggOnxetky6fE6vwkuB1Uecl6K7BMAVR+C4LJ5my+R59wd5qm11vo2V1NuZ1QIIYQQQojrUosWsGmT6fE6IQHuvNP0eL19u7dzJtJzVYospceFhruddAkhhBBCCCGySyno3h26dIEPPzRtlaOjoVcveOWVAtnjdbYkJ8Px4/DvvxAba16PHoWwMIiMNFP58ua1dGnw9fXcvq2lyAc+gpRrafOl9LhQcTtAVkpFAs8BrYASwF1a6z+VUkOAzVrrrbmTRSGEEEIIIQoIf394/HHo2xcmT4Y33oBFi0yP1yNHQsmS3s5h7jp/Pi3wdTQdPQpJSbbrhIWZTs5S7Fp1+vpC2bK2QXP6v62vRYqYBxTuqD8SDs6ynSelx4WKWwGyUqoupv1xMrAZiAKsFfQrAdHAA7mRQSGEEEIIIQqc8HAYN84ExmPGwHvvwezZMHw4DBkCISFezmA2JCbCsWPOg99//4ULF2zX8fODChVMG+2WLc1r+umGG0yAm5wMJ06Y7R89aibr38eOwT//wNq1EBeXMV+hoRmDZvu/y5WDgICMpchSelzouFuC/AZmLOT2wFUgXZ0DNgETPZwvIYQQQgghCr5y5WD6dBMUv/ii6fH6/fdh/Hjo18+zVYhz6v/bu/c4Kcv6/+Ovzx5YcBHBBURQkINpJhoeM6TUr3koK0yzVEr7CVqa38ws89DPY6WlZSc6eMgSy29W8rUy1NRsM4kUNE9hiRAihSJrsOKyh8/3j+seGWZPs8vM3DPXvp+Px/WYnXvu+55r5j0ze1/3fd3X3dRE9RNPwLp1nRu+K1eGhmruUd6GhtDQnTw5nHed2/gdMya/11hdHRq0Y8fCfvt1P99rr23ZcM6+XbUKHn443G7a1HnZUaPC+seMhNZ2GA40OAw6CGofC4+NHAlV+Y5zLJUo3wbywcCJ7r7BzHI/wf8GtEtFRERERKS/ske8/uxn4bTT4Gtfg6uvhne/O/8uwlujvT00Hp97LpRly7b8e906ts2ef9CgzY3dww/fsuGbua2vL369s22zDUyZEkp33OGVV7o+Ep2ZtmIQrNsI3grXf2TzsrW1YadGV125s2+33bb75y+V9vbwOtesyats194ejtZvt124zZS+3N922/LaqdMP+TaQe7qM00hgYwHqIiIiIiIysM2YEY5y/uIX4YjyMcfAIYfAV74C+++/9et/7bXQ2M1t/D73HCxfvuWR1Zoa2GUXmDQpDCg2eTLNI0dSv8ceoQE8alRlHk01C0e2Gxpgr726nmfjavjtdJh6O6xt7fqo9FNPwb33du42DqGh2FMDety4cPR8UDeXleqKOzQ399zQ/fe/N//98sudj+hDyGzkSNhhhzDQ2f77w6hRtLS3M7ilJbyeV18Nt6tXb76/fn1+lycbOjT/BvV224WeBaNG5f8+FFm+DeRFwMeAX3Xx2AnAQwWrkYiIiIjIQGYGxx8P739/30e8doeXXur+KPDq1VvOP2xYWN9ee8Gxx4bG8OTJ4XbnnUMjOUtrUxMMH17wl1x2huwIH1gW/t61l3nXrw/va3dHpBsbw9+trZ2XHT26c8N56NCQYVcN4I3dHJccNiysa/TocPT87W/ffD+3bL99l0d5X29qYnBP2XZ0hAZ6dgM6U3q7v2rV5r9zG9rbbAMf/zicd144Op8y8zz2ApjZO4HfAQ8APwFuBC4A3gJ8GHhHTKNYT5s2zZcsWZJ2NaQImpqaGD4QftQHIGUbL2UbL2UbL2VbYP/5D1xzTRjxurU1DOw1e3ZodOU2gJctgw0btlx+p502N3onT97y7+2371P3bWXbTx0dsHZt1w3o7Ns1a8L8tbVbNmozR3u7KqNGweDBW13FkmWbaWi/+mp4zd/5Dtx6a9gZM3s2fO5zoYdCkZnZo+7e6YT2vBrIyQreA1wHZO+yWg6c5e6/7UNFdgLOB/YD9gaGABPdfXkX874NuBR4G1ALLAO+6O639fIcVclznEE4P3opcLm7/yKfOqqBHC/9qMdL2cZL2cZL2cZL2RbJiy+GEa9vvHHLrrN1dV03fidPDl2kC9B4ylC2RbZpUzhK3JdLUxVIqtk+91w43/7mm8PR5VNOgc9/vudzybdSdw3kvK+D7O6/AX5jZlOA0cBad1/aj7pMIXTLfpRw6agjuqnwe4A7CEesTyKMnL0HkM83/ArgPOCi5Hk+DNxuZse4+139qLOIiIiISLrGjg1drs89FxYtCo3fyZNDt9RKPBdYOhs0qG/nJcdi8uTw2b744nB98Ouvhx/+EE46CS68MAxiVyJ5H0Eu2BOaVbl7R/L3bOB6co4gm9m2wHPAT9z9nD6ufzSwErjK3S/Jmn4fMMrduzkTfzMdQY6X9nrGS9nGS9nGS9nGS9nGS9nGq6yyXb06jOL+3e+GgeWOOy40nvfeu2BP0d0R5Lx3NZnZrmb2IzN71syak9ubkyPKecs0jnvxQWAU4frLfXUkMAiYlzN9HjDVzCb2Y50iIiIiIiJSCjvuGI4kL18ejiDfcw+89a3wvveF3hNFlFcD2cwOAR4HjgEWAnOT2/cCTySDeBXSwcArhAbtE2bWZmYrzeySLq7DnOstQAvwj5zpTyW3exS4riIiIiIiIlJoI0fClVfCihVw+eXw0ENw4IFw5JFhdPAiyPcI8rXAEmCCu3/U3T/r7h8FdgEeo39HensyFtiGcP7xzcDhwI+ALwDX9LLs9kCTd+47/krW4yIiIiIiIlIJhg+HL3whHFH+ylfgscfgHe+Ad74zXIu6gKcN5ztI1x7Ah9x9izHj3X29mV0N/LRgNQqqCINxXeTuX0um/d7MGoCzzOxSd3+1m2UN6Ood6nEYODM7HTgdYNy4cTQ1NfWr4lLe1q9fn3YVpEiUbbyUbbyUbbyUbbyUbbwqJts5c+Dkkxl0yy0M/uY3qTriCNr224/XP/MZ2o48cqtH/863gfwC4bzergwCVm1VLTpbm9zemzP9HuDjhG7Uf+pm2VeAEWZmOUeRR2Q93om7/wD4AYRBusrmBHUpOGUbL2UbL2UbL2UbjxVrm7m+cRnzl7zIiJpW1rXVMnPaWObMmMSEhvq0qycFpO9tvCom2+HD4fzz4Zxz4OabqbnqKoaeeGI4T/nii+HYY/s9snu+S10NXGZm47InJvcvAb7Ur2fvXuZ84dwjwZndAT0N9PUUUMeW12uGzeceP711VRMRERGRbA8sXcNR1zVy26KVbGhpw4ENLW3ctmglR13XyANL16RdRRGJUV0dnHEGPPtsuIbya6/B8cfD1Klw663Q1tbnVebbQH4nsC3wnJn93sz+x8x+T7gU01DgEDP7cVJ+1OdadDY/uT0qZ/qRwOvAkz0su4BwzeSTc6bPAp509+cLUD8REZGCWLG2mYvnP8Gel9zNxM//hj0vuZuL5z/BirXNaVdNJC8r1jZz5rzFbGxtp61jy2MbbR3OxtZ2zpy3WJ9pESme2lo45RR4+mn46U/D0eNZs8L1k2+6CTZtyntV+TaQDwbagdXABOCA5HY14WjujJzSIzM73syOB/ZNJh2dTHsngLs/SRic63Iz+5yZHW5mVwGzgauzz4VORri+MXPf3dcAXwcuMLNzzewQM/sucBhwYZ6vV0REpOh01E1icH3jMlrbe76KZ2t7Bzc06hiFiBRZdTV8+MPw+ONwxx0wbBicdhrsuivMnQuvv97rKvJqILv7xD6USXms8vakfDy5Pze5f1nWPGcAXwPOBu4CPgCc6+6X5qyrOinZLgKuBD4F3A1MB05w91/l83pFRESKTUfdJBbzl7zY6TOcq63DuWNJoYesERHpRlUVzJwJjzwCd90F48bBWWfBpEnw9a9Dc/f/W/t35vJWcnfrphySNc8md7/Y3Xd290Hu/iZ3/0Y36zo1Z1q7u1/p7hPcvc7d93L3nxf/lYmIiORHR90kFs0t+Z3j17yp7+cCiohsFTM4+uhw/eT77oPdd4dzz4WJE7tdJN9RrJP1287AzoRLMG3B3e/vc4VFREQGqL4cdbti5p4lqpVI39XX1bAhj0Zy/aA+bXaWtewRu5tb2qivq9GI3SLlzAwOOyyUhx6Ca66B+fO7nDWvXyozmwTcSjj3GDaPJu1svu5wbjdnERER6YaOukksZk4by22LVva4w6emyjh22rhuH68kDyxdw5nzFtPa3vHGa86MHfCLR1cxd9Y+HLrb6JRrKSLdmj49lG6ul5xvF+sbgPHAOYSRpQ9NymFZtyIiIpKn+rr8jqbFdNRN4jRnxiRqq3vepKytrmL2jO67NFYKjR0gEr98G8j7A//t7t9y93vd/cHcUsxKioiIxGbmtLHUVHW99zojpqNuEq8JDfXMnbUPQ2qrO32ma6qMIbXVzJ21TxRdjzV2gEj88m0gv0C4trCIiIgUwEA66ibxO3S30Sw4ZwYnHjCeoXU1mMHQuhpOPGA8C86ZEU2XY43YLRK/fPttfQk438zud3f1GREREdlKmaNuuecyQjjqVltdFc1RNxkYJjTUc8XMPbli5p40NTUxfPjwtKtUcBo7QCR+eTWQ3f0WM9sdWG5mC4F1nWfxUwpeOxERkYhljrrd0Pg8dyxZRfOmNuoH1XDstHHMnjFRjWORMjMQR+wWGWjyHcX6VOACoB3Yh87drXvuayIiIiJdyj7qJiLlbaCN2C0yEOV7DvJlwB3AKHcf5+4Tc8qkItZRRERERCR1GjtAJH75NpAbgLnu3lTEuoiIiIiIlK2BNGK3yECVbwP5j8Cbi1kREREREZFyN1BG7BYZqPIdQeBTwM/MbB2wgM6DdOHuPV8UTkREREQkAho7QCRe+TaQn0luf9zN496HdYmIiIiIiIiUnXwbtZejkapFREREREQkYvleB/nSItdDREREREREJFX5DtL1BjMbamYTzKy2GBUSERERERERSUPeDWQzO8bMFgOvAsuAqcn0G8zspCLVT0RERERERKQk8mogm9lM4H+Bl4HzgewLvz0PnFLwmomIiIiIiIiUUL5HkC8BfujuRwDX5Tz2JKAx7kVERERERKSi5dtAfjPwP8nfuaNZrwMaClYjERERERERkRTke5mn/wAju3lsF+ClgtRGRERERES6tGJtM9c3LmP+khdpbmmjvq6GmdPGMmfGJCY01KddPZEo5HsE+V7gAjMbnjXNzawO+CTw20JXTEREREREggeWruGo6xq5bdFKNrS04cCGljZuW7SSo65r5IGla9KuokgUum0gm9kyM9s7uXsRMAZYCtxA6Gb9eeAxYCfg0qLWUkRERERkgFqxtpkz5y1mY2s7bR1bnu3Y1uFsbG3nzHmLWbG2OaUaisSjpyPIuwB1AO6+HNgH+DXwLqAdeAewEDjQ3V8sai1FRERERAao6xuX0dre0eM8re0d3ND4fIlqJBKvvK+D7O4vuPtp7r6Tuw9y9x3d/WPuvrKYFRQRERERGcjmL3mx05HjXG0dzh1LVpWoRiLx6q2B3PM3UUREREREiqq5pS2/+TblN5+IdK+3UawvM7OX81iPu/sphaiQiIiIiIhsVl9Xw4Y8Gsn1g/K9QI2IdKe3b9FbgZY81qMjzSIiIiIiRTBz2lhuW7Syx27WNVXGsdPGlbBWInHqrYE8090XlaQmIiIiIiLSyZwZk/jFo6to62jvdp7a6ipmz5hYwlqJxCnvQbpERERERKT0JjTUM3fWPgypraamyrZ4rKbKGFJbzdxZ+zChoT6lGorEQw1kEREREZEyd+huo1lwzgxOPGA8Q+tqMIOhdTWceMB4Fpwzg0N3G512FUWioDP5RUREREQqwISGeq6YuSdXzNwz7aqIRKvbBrK76+iyiIiIiIiIDBglbwSb2U5m9i0ze9jMXjMzN7NdcubZJZneVRmex3Ms72bZmUV6WSIiIiIiIlLh0uhiPQU4AXgUaASO6GHeLwN35kxbn+fz3A1cmjNtaZ7LioiIiIiIyACTRgP5D+6+A4CZzabnBvIyd1/Yz+d5eSuWFRERERERkQGm5F2s3b2j1M8pIiIiIiIi0ptyH4jry2bWZmavmtmdZja1D8u+NznHucXMFur8YxEREREREelJuV7mqQX4PnAP8BKwO3Ah8CczO8Ddn+ll+V8BfwGeB3YAPgncYWYfcfd5XS1gZqcDpwOMGzeOpqamQrwOKTPr1+d7CrtUGmUbL2UbL2UbL2UbL2UbL2UbmLun9+ThHOTrgYnuvryXeXcGngLudPdZfXyeamAhMMbdd+5t/mnTpvmSJUv68hRSIZqamhg+fHja1ZAiULbxUrbxUrbxUrbxUrbxGmjZmtmj7r5f7vRy72L9BndfCfwR2L8fy7YDtwM7mdmOha6biIiIiIiIVL6KaSAnDOjvIW9LbtM7ZC4iIiIiIiJlq2IayGY2HpgO/Lkfy9YAHwT+6e7/KnTdREREREREpPKlMkiXmR2f/Llvcnu0mb0EvOTuD5rZtYTG+8OEQbp2Ay4AOoAv5ayrDfiRu5+W3D8ReD9wF7CSMEjXWclznVjM1yUiIiIiIiKVK61RrG/PuT83uX0QOIQwGNcngFOBbYGXgfuBy9x9ac6y1UnJeB4YDXwV2B54jTCi9VHufnfBXoGIiIiIiIhEJZUGsrtbL4/fBNzUn3W5+0LgsP7XTkRERERERAaiijkHWURERERERKSY1EAWERERERERQQ1kEREREREREUANZBERERERERFADWQRERERERERQA1kEREREREREUANZBEREREREREgpesgi4iIiIiISLBibTPXNy5j/pIXaW5po76uhpnTxjJnxiQmNNSnXb0BRQ1kERERERGRlDywdA1nzltMa3sHbR0OwIaWNm5btJJfPLqKubP24dDdRqdcy4FDXaxFRERERERSsGJtM2fOW8zG1vY3GscZbR3OxtZ2zpy3mBVrm1Oq4cCjBrKIiIiIiEgKrm9cRmt7R4/ztLZ3cEPj8yWqkaiBLCIiIiIikoL5S17sdOQ4V1uHc8eSVSWqkaiBLCIiIiIikoLmlrb85tuU33yy9dRAFhERERERSUF9XX5jJtcP0tjKpaIGsoiIiIiISApmThtLTZX1OE9NlXHstHElqpGogSwiIiIiIpKCOTMmUVvdc5OstrqK2TMmlqhGogayiIiIiIhICiY01DN31j4Mqa3udCS5psoYUlvN3Fn7MKGhPqUaDjxqIIuIiIiIiKTk0N1Gs+CcGZx4wHiG1tVgBkPrajjxgPEsOGcGh+42Ou0qDig621tERERERCRFExrquWLmnlwxc8+0qzLg6QiyiIiIiIiICGogi4iIiIiIiABqIIuIiIiIiIgAaiCLiIiIiIiIAGogi4iIiIiIiABqIIuIiIiIiIgAaiCLiIiIiIiIAGogi4iIiIiIiABqIIuIiIiIiIgAaiCLiIiIiIiIAGogi4iIiIiIiABqIIuIiIiIiIgAaiCLiIiIiIiIACk0kM1sJzP7lpk9bGavmZmb2S458+ySTO+qDM/jOarM7AIzW25mr5vZ42Z2XLFek4iIiIiIiFS+NI4gTwFOANYBjb3M+2XgoJyyPo/nuAK4FPg2cDSwELjdzN7dvyqLiIiIiIhI7GpSeM4/uPsOAGY2Gziih3mXufvCvqzczEYD5wFXufs1yeQHzGwKcBVwVz/qLCIiIiIiIpEr+RFkd+8o8lMcCQwC5uVMnwdMNbOJRX5+ERERERERqUDlPkjXl82szcxeNbM7zWxqHsu8BWgB/pEz/ankdo+C1lBERERERESikEYX63y0AN8H7gFeAnYHLgT+ZGYHuPszPSy7PdDk7p4z/ZWsxzsxs9OB0zPPb2ZP9rfyUtZGAi+nXQkpCmUbL2UbL2UbL2UbL2Ubr4GW7YSuJpZlA9ndVwMfz5rUaGYLCEeBLwJm9bC4AbmN48z0np7zB8APAMzsEXffr0+VloqgbOOlbOOlbOOlbOOlbOOlbOOlbINy72L9BndfCfwR2L+XWV8BRphZboN4RNbjIiIiIiIiIluomAZyorujw9meAuqAyTnTM+ceP13oSomIiIiIiEjlq5gGspmNB6YDf+5l1gXAJuDknOmzgCfd/fk8nu4Hfa+hVAhlGy9lGy9lGy9lGy9lGy9lGy9lC1jnsaxK8KRmxyd//hfhXOMzCYNxveTuD5rZtYTG+8PJ9N2AC4DtgAPdfWnWutqAH7n7aVnTrgLOIQzstRj4EHAG8H53/1VxX52IiIiIiIhUorQG6bo95/7c5PZB4BBCN+lPAKcC2xJGU7sfuCy7cZyoTkq2i4ANwKeAMcBS4AQ1jkVERERERKQ7qRxBFhERERERESk3FXMOsoiIiIiIiEgxqYEskjIzG2JmM8xsZNp1kcIyM/3GRsrMqrP+zr2soFQwMxtsZseY2RnJfeUrUgG0PRWvUm9PaeOtjJnZrmb2BTO7x8w+lnZ9pHDM7EAzu87M/gY0A9cDo1KulhSAmU02sy+Z2V+AO81stpkNSbtesvXMbD8zu9rMHgLuMrMLzWyK61ylimdm083s62b2LGEMkzuBywGUb+XT9lS8tD0VrzS3p9IapEt6kOwl+SRhkLIxSfmrmdW6e2uadZOtk3yxnwYmAA8BtwC/B55195dSrJoUgJltD9wIDAXuAcYTLpkw3czOdfd1Zmba4K4sZjaMsNG1H7CK8J0dBVwBHGlmJ7j7v5VtZUmODJ8A/BR4DVgC/JhwuchbgWfMbIi7b0yvltIXud9BbU/Fo4tstT0Via7+d6a9PaUGcorMrAGYSrg+88vJNHP3DjN7N/Aq4XJV1wIHAjsAL2gjrPx1k22Vu280s+XAWmC2uy9NpnekWF3pg66yzXJt8tgHgMbku/wIcA3wN+BqfXfLl5mNALZ193/mPLQBWA9cCvwa2ODurWa2BPgq8C5gHmCA8i1DXWXr7m5mjwFHEK528a8k12GELFcnv9n6n1vmknzHu/vjWdO0PRWBbrLV9lQEuso2S6rbU+pinQIzm2Zm9xGORNwK3GtmJ+f8UH/Q3Q919z8QLos1FZiUUpUlT71km/nRfoCwF3sEQPKlH5F9TqOUnx6yrUoerwf2AO5y9wezFv0V4Zrup5jZ+FLXW3pmZiOTHB8kbGhdlDSQ3pB8d89291vcfR2h8QSwAnid0IBGG2blJc9sl7r779x9ZdYRxfHAdmze2aFzkMuQmY03swvMbClhB8ftZna/mR0JW3SN1/ZUhektWzZ/N7U9VWHyyBYz24aUt6fUQC4hC4YQrtM8GDgYOA54DrgOOCuZr9bd12d9we8GhgFvAZ0PVY7yzTbxO8L1vc8zs9vN7EXgPuBaM3tzSSsuvepDtiOBdmCX5H6mh84KYDkwGTigFHWWPjmV0H26jZDpm4HhsOXgTNndbN19k5nVAIcDfyb8Rkv5OZU8ss2wzYPArCd0oV8O2vFRjsxsR+Biwm/xzcD7gKsIv8M3mtlhyXzV2p6qLPlkm5WbtqcqSB7ZHp7M2kDK21NqIJdI1tHhg4Ajge+6+yPuvhD4CPAn4EKAzF5sd29Pbh8ndA/aN9mrImWkL9km/gy8BOxOGFDiKuBR4Ezgl2a2e2a9pXsV0pU+ZrsKeAKYamaDk0ZUtbu3Ec6RqgX2NA3YVRayNpifBr4HnAJ8GdifkFeXG88WBg35GbCG0GXzP8AhZlaXPK7vbcr6m21WQ3gMYePs2aJXVvok6/s1GqgGrga+7u4L3f0mQnfMEcChsMV2lLanylxfs01oe6oC9CHbQ5L5/kXK21NqIG8lM9vGzLZL/u72C5j1z3h7oJ7QTSDz2EbCXu7RZnZczvoz/+j/SPjnPq6355LCKEa2SYOrHZgLnA+cAXzH3ecAxxLyPTtnvVJgBc52lJl9MPnhvovww32NmY1z9/bkOz2Y0KDal7DhLUXSh2wzG8x3ufu57v4C8AdCflN7WHY0YWfIxYSG11jCIE9nZ6pQkBcinRQ726zpuxO2jyyZrm2lEsgn36zf5CeAM9z9dnd/PVmmyt3/QRhwbUhuN1ttT6WnGNlmbU99B21PpabA2Q62zQPo/ZYUt6f0o98PZrajmc0xs8WEDaXjIO8v4A6Ec9Z2TNaV+cF+BHgGeK+Z1Xax3J2Ef9pTMtXo/yuQ7hQ7W2BQsr6vuftv3L0lszFH2BM6nzBgjP5pF1gJvrfV7v6/wBeBjwKLzGwlofF0L/Bz4E3JnlD99hbQVmZLsrFVRei69Xfg7YRumF1Z6O6fdve57n4LoYvYA8AnkudUd9wCKnG2md/cakK37JeT51KmRdLffN29w93bsn9Lk/NP30rYobk02aDu6v+otqdKoNjZkrRh3P3r2p4qrSJnm+lFOx+4kpS2pzSKdR8lh/OvBaYD/yT8o93Fehk5L+vx9YTuPfsTRmHLfGnXAo3AfxGOVDUl0zPrXEDYk7IH8Fv9wy68EmU7BGhJlqsmDDThiZfNrA3YwcwGufumYrzOgahE2W4HvAJ8hdBgOgpYDdzj7svM7HZgWdKQ1lHkAulvttmy8ugws98Tzi0eDbyaHKXwrHk9Z9lXLYyE/H4zG+ruG7b2NUmQQraZdQ4j/O99piAvRLpUoHw7knVlfldPJuzYuCd5PPv7qu2pEilRtm/8H9X2VOmUItus3+avEi7dVfLtKR3F6IKZjTWzM8zs/5vZVNs8Sq156FbZDnwXOJrQXeDthH+4PQ38kdkZ8QyhG8H+yf3Mh6kNeAyYmDXvGz/u7r6SsJfmQDObaGZvNrMJhXvVA0OZZdue7E3zZF3bES4Xcz/hn7f0QRlkm9mb3ebuD7v7Je7+veTHfAJwGPCzHo5qSDeKka11P8rp3YQ8J0Pve8STjYVjCL0JdE5jH5VptnsTzi0f1P9XJlCafJN1tSe/sycDN7n7itxltT1VWGWWrbanCijtbLO+q+ltT7m7SlYhnFP2AmGD+FHC5TvOB4Z2M/+XCH3h35b5XmY9VtXF/IMJI+w9knk8swxwImGDe++c6cMJo/T9FtgI/IWwgT4v7ferkko5ZZtMGwHsSui+ewChy8jzwGFpv1eVVsopW0JDeRtC971RhL2s9yVlh7Tfq0orxc62i+V3JOwMuQio7eLxEYRLxIwm7DD5XlK3Y3KfT6Xisq1Obn+S1Gd02u9RJZdS5Zv1W/xVwuA+U3qYdzjanoouW7Q9FXO2qWxPpR5EORXCsP/Lkg2ebQn94b9E6EZ5QTJPTXI7KLk9KPlx/VgP630nYRCBK5P75yX/pA/L+ZCcnXwop2UtO5pwKZnVyfMsA35E2CivT/s9q5RSRtnuk9zfCfgasJgw0uom4K/ACWgDu1Kzzf7eziAcrXqCcO7yfcC+ab9XlVZKkO3lJP/0Cd3mM5k+TBiQbXjOuqcA3yYM8vMUYcPhz4S93/reVma2tTnLjwCWAI9nlk37varEUsp8k+lTCaemfaGHZbU9FWG2hMG4tD0VYbbJPKlsT6UeRjkUNh8RmkPoA79b1mPDgVuTH9ROe5yTeV4jbDTV5Uz/VPLYfwiXg/lIMn0KYaOqkWSPSfLD3Qg8lNzP/DMflnygzgZ2Tvu9qrRSbtlm5VpD6CLyZeBjwPi036tKK+WWbU6dhhEa1Mq2vLM9CRjcxfJfJOz0+CDhWroXJ9OHJN/by5Js9Ztc+dlelEx/Y6MvyXhM2u9VJZa08iU0dJ8jOepP6C1wKPCerHm0PRVXtpleO3Voeyq2bHO/tyXfnko9lCKGPYaw9+goYNs8l/kssD77w5L8/R5CF8r358yf6Y51P2HDeZfkfm1yOzUJegw53QyAdxD+SS9LvtT3A0tJuiioKNuBWJRtvKUCsjVC1+n3AbcT9oh3EM61WpI7v4qyHSilAvKdTujieQNhA/93wLrkeW5CRxGV7QAsynYr37+0AyzCB2J7wp6OZmAl4dIOC4G9kse7fcMJRwXWkuxZZPMelTGEjeDvkuxlzvlgfJrQ1e7w3p4j5/neTLio+e8J3RkOTPv9K+eibOMtyjbeUmHZ3kZoOD0PXE34x64NMGU7IEul5EvYWZnZ6bGSsMF9FNrxoWwHYFG2BXof065AgT8URrjEympgJjCecEmH54FngZHdLJf5AJwFvAgcm9zPdLmqA35M2NM8pIvldk0CPqsPdd1ioB8VZTtQi7KNt1RKtlnL7UVybqqKsh3IpRLyzVrmKMIRru3Sft8qoSjbeIuyLVypqMs8mdkOZvZxM/uZmb23i1mGAKcBN7v7fHf/p7v/DriU0L3q9Kx1WTLseA2bL3f1BOHk/rcn9z25bQOeBN4EtGbW4cl1vNz974RuAtPN7CAz+6iZ7dfTa8la1nuab6BQtvFStvGKJdus5f7q7k19ehMipWzjFkO+WcsscPffuPurfX8n4qNs46VsS6diGshmdiZwJ2GAjeOB/cysLnkscw2stxAGP1qVTB+cTH+EMFz5sWY2Cd64kniHh2tstSXX+HqUsJfl0GSe9sx1ugjnKnUAY7PqVGtmu5nZdMJJ6B8m9KG/mbBXRPKgbOOlbOOlbOOlbOOmfOOlbOOlbEurrBrIZlZtZnubWX32tOTPDxBGMjuL0Jf+7YSR1WDz63idcC2tGcn99uR2OeEDMwXYPVlvjZkdbWY3mtmLwHXu3ky4/MPeZnY4bHGkaHdC94TXs6q8K/BDwii2DnwDOI4wQttl/X8n4qNs46Vs46Vs46Vs46Z846Vs46Vsy4iXQT9vwqA3dxAu2v4v4AHg+OSxzGVxRmbN/2nCMOSZa8pm+rNvQzjJ+xWSIcOT6TOA9YQ9H2cn074BvATcBXwG2DWZviNh8J3FwLuBwYQ9KSuBa3KebxjwLmBU2u9huRZlG29RtvEWZRtvUbZxF+Ubb1G28RZlW34lzQ+DJWUQ4TpYjwKHAEcnYa0FTk7mrc5Z9m1JyCd1sd63JssuJexl+Szwj+SD8DTw7awPQEPmg5ezjn2ARYQT1R8iXMT610BD2oFVQlG28RZlG29RtvEWZRt3Ub7xFmUbb1G25V1K8QHYBvhgEv484P8BE3NC3pT5ECTTaoAHgaXdrLM+Ce2bwDZZH7TMHo13AL9MAv0bcAGhW8GfgB8m8/Q4jDhhj8lHgAuBg9MOqhyLso23KNt4i7KNtyjbuIvyjbco23iLsq3MUswPhBGGGG8E/g78DLiF0H3gb8AOyXwnE0ZEG5EdWBJKB3BMN+v/OeGk88y1uizn8SE59+uAfwMfSvtNr/SibOMtyjbeomzjLco27qJ84y3KNt6ibCu7FHuQrguBfxJGNZsFzAHeS7gu1yeSeUYT9nBMSu5n6rSQ0BXghG7WfTehz/6Erh50943wxjDmEwgXzX4NuK/fr0ayKdt4Kdt4Kdt4Kdu4Kd94Kdt4KdsKVVOsFbu7J0OSP+HuLVkP/c7MHgH2T+6vI+w52Y3Q/z5jNeHDcTiEgD3ZBZJoJBz+3wP4Y85jmNmxwBhgBOEE8gZglru/3MW6pA+UbbyUbbyUbbyUbdyUb7yUbbyUbWUr6hFkd3/E3VuSvRcGYGYNQG3Wcz+W3N8zud+eLLsBeAoYb2bb5wbp7n8jnHR+sJmNM7OJZjYuexZgNvAh4K/AR939IX0oCkPZxkvZxkvZxkvZxk35xkvZxkvZVq6iHUHOlhNEA3AgcEby2GNm9gKwr5kNc/f/mFm1h4tSryd0O9gd+JOZVbl7h5kNAYYSPjjvIXRPmAHcS+jvD2EEuAXunn29rty6yFZStvFStvFStvFStnFTvvFStvFStpWn2Ocgv8HMMs91EWHktflZDy8A9gKmZ2bPut0ENAMkH4oRwKXAHwgfgsy8FwH/nVmhu2/K/VBIcSjbeCnbeCnbeCnbuCnfeCnbeCnbCuMlHBEM2BdoYfNFqmuT27cSRmK7HxiaTNuecAL6X5P7mQtl1wI/BK4E9i1l/VWU7UAsyjbeomzjLco27qJ84y3KNt6ibCunZN7skjCzXxJOQt/Xc/ZqmNkRwB3Ac4TrhO1P+CCd6u5/KFklpV+UbbyUbbyUbbyUbdyUb7yUbbyUbeUoWQPZzA4jdCE4yd1/nkyrJVxAe72HbgMHE64HdhDwPPB94G4vZSte+kzZxkvZxkvZxkvZxk35xkvZxkvZVpZSNpAXEIYjnwOMIgxb/j5gGXCeu/8zma/W3VtLUikpCGUbL2UbL2UbL2UbN+UbL2UbL2VbWUrSQDazg4CHgFcIw5ePAp4hXKz6Jnd/rOiVkKJQtvFStvFStvFStnFTvvFStvFStpWnJJd5AtYQ9pD8hnAC+gLf8qLZUrmUbbyUbbyUbbyUbdyUb7yUbbyUbYUp6SBdIiIiIiIiIuWqZNdBFhERERERESlnaiCLiIiIiIiIoAayiIiIiIiICKAGsoiIiIiIiAigBrKIiIiIiIgIoAayiIiIiIiICKAGsoiIiIiIiAigBrKIiIiIiIgIAP8HtQq3GS5Mf8YAAAAASUVORK5CYII=\n", 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\n", "text/plain": [ "
" ] @@ -3073,49 +2635,370 @@ "source": [ "fig, ax = plt.subplots(figsize=(16, 5))\n", "\n", - "# Plot the L4 SST from MUR (hosted by AWS Open Registry)\n", - "subsets_day_means.plot.line(\n", - " x=\"date\",\n", - " y=\"L4_MUR_SST\",\n", - " color=\"red\",\n", - " label=\"L4 MUR SST (AWS Open Registry)\",\n", - " ax=ax,\n", - ")\n", - "\n", - "# Plot the L2 SST from GHRSST (subset through Harmony API)\n", - "subsets_day_means.plot.scatter(\n", - " x=\"date\",\n", - " y=\"sst_mean\", \n", - " label=\"L2 MODIS SST (EOSDIS Cloud)\",\n", - " s=100,\n", - " ax=ax\n", - ")\n", - "\n", - "# Plot the in situ temps measured at the surface during Argo profiles (accessed from ArgoVis)\n", - "argo_skinny.plot.scatter(\n", - " x=\"date\",\n", - " y=\"temp_at_pres_min\",\n", - " s=100,\n", - " color=\"orange\",\n", - " marker=\"v\",\n", - " label=\"In situ measurements (ArgoVis API)\",\n", - " ax=ax\n", - ")\n", - "\n", - "# Matplotlib aesthetic treatments starting from here -->\n", + "# L4 MUR SST from AWS Open Registry:\n", + "subsets_day_means.plot.line(x=\"date\",\n", + " y=\"L4_MUR_SST\",\n", + " color=\"red\",\n", + " label=\"L4 MUR SST (AWS Open Registry)\",\n", + " ax=ax)\n", + "\n", + "# L2 MODIS SST from Harmony API:\n", + "subsets_day_means.plot.scatter(x=\"date\",\n", + " y=\"sst_mean\", \n", + " label=\"L2 MODIS SST (EOSDIS Cloud)\",\n", + " s=100,\n", + " ax=ax)\n", + "\n", + "# In-situ SST from ArgoVis API:\n", + "argo_skinny.plot.scatter(x=\"date\",\n", + " y=\"temp_at_pres_min\",\n", + " s=100,\n", + " color=\"orange\",\n", + " marker=\"v\",\n", + " label=\"In-situ measurements (ArgoVis API)\",\n", + " ax=ax)\n", + "\n", "plt.xticks(rotation=15)\n", "ax.set_xlabel(None)\n", "ax.set_xlim(subsets_day_means.date.iloc[0], subsets_day_means.date.iloc[-1])\n", "ax.set_ylabel(\"Temperature (deg C)\")\n", "ax.set_ylim(15.0, 18.0)\n", "ax.grid(alpha=0.25)\n", - "ax.set_title(\"Daily SST from L2 MODIS, L4 MUR, and in situ measurements (January 2019)\")" + "ax.set_title(\"Daily SST from L2 MODIS, L4 MUR, and in-situ measurements (Jan 2019)\")" + ] + }, + { + "cell_type": "markdown", + "id": "3fca642b", + "metadata": {}, + "source": [ + "## Results\n", + "\n", + "The size of the L2 MODIS subsets in total and individually:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, + "id": "c67e525a", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8.9M\tresources/data\r\n" + ] + } + ], + "source": [ + "!du -sh resources/data" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "8ade350a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "136K\tresources/data/20190101031001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "124K\tresources/data/20190101141501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "128K\tresources/data/20190102021501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "116K\tresources/data/20190102132001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "140K\tresources/data/20190103030000-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "120K\tresources/data/20190103140501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "124K\tresources/data/20190104020501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "120K\tresources/data/20190104034001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "124K\tresources/data/20190104034501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "108K\tresources/data/20190104131001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "108K\tresources/data/20190104144501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "140K\tresources/data/20190105025001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "116K\tresources/data/20190105135000-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "128K\tresources/data/20190106033000-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "112K\tresources/data/20190106143501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "136K\tresources/data/20190107023501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "124K\tresources/data/20190107134001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "132K\tresources/data/20190108032000-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "124K\tresources/data/20190108142000-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "128K\tresources/data/20190109022501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "120K\tresources/data/20190109132501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "136K\tresources/data/20190110030501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "120K\tresources/data/20190110141001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "128K\tresources/data/20190111021000-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "108K\tresources/data/20190111131500-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "104K\tresources/data/20190111145500-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "140K\tresources/data/20190112025501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + "132K\tresources/data/20190112140001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4\r\n", + "124K\tresources/data/20190113020001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4\r\n", + 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resources/data/*subsetted.nc4" + ] + }, + { + "cell_type": "markdown", + "id": "c354c3ce", + "metadata": {}, + "source": [ + "## Next steps\n", + "\n", + "Check performance of direct s3 access to MUR from PO.DAAC archive in netCDF format:" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "2b9a174b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "31\n" + ] + } + ], + "source": [ + "import s3fs\n", + "\n", + "def begin_s3_direct_access(url=\"https://archive.podaac.earthdata.nasa.gov/s3credentials\"):\n", + " response = requests.get(url).json()\n", + " return s3fs.S3FileSystem(key=response['accessKeyId'],\n", + " secret=response['secretAccessKey'],\n", + " token=response['sessionToken'],\n", + " client_kwargs={'region_name':'us-west-2'})\n", + "\n", + "fs = begin_s3_direct_access()\n", + "\n", + "cloud = os.path.join(\"podaac-ops-cumulus-protected/\", \"MUR-JPL-L4-GLOB-v4.1/\", \"*201901*.nc\")\n", + "\n", + "files = fs.glob(cloud)\n", + "\n", + "print(len(files))" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "a46a9dbe", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Dimensions: (time: 31, lat: 78, lon: 45)\n", + "Coordinates:\n", + " * time (time) datetime64[ns] 2019-01-01T09:00:00 ... 2019-01-31T09...\n", + " * lat (lat) float32 37.71 37.72 37.73 37.74 ... 38.46 38.47 38.48\n", + " * lon (lon) float32 -13.26 -13.25 -13.24 ... -12.84 -12.83 -12.82\n", + "Data variables:\n", + " analysed_sst (time, lat, lon) float32 dask.array\n", + " mask (time, lat, lon) float32 dask.array\n", + "Attributes: (12/47)\n", + " Conventions: CF-1.5\n", + " title: Daily MUR SST, Final product\n", + " summary: A merged, multi-sensor L4 Foundation SST anal...\n", + " references: http://podaac.jpl.nasa.gov/Multi-scale_Ultra-...\n", + " institution: Jet Propulsion Laboratory\n", + " history: created at nominal 4-day latency; replaced nr...\n", + " ... ...\n", + " project: NASA Making Earth Science Data Records for Us...\n", + " publisher_name: GHRSST Project Office\n", + " publisher_url: http://www.ghrsst.org\n", + " publisher_email: ghrsst-po@nceo.ac.uk\n", + " processing_level: L4\n", + " cdm_data_type: grid\n", + "CPU times: user 4.62 s, sys: 388 ms, total: 5.01 s\n", + "Wall time: 19.9 s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "var = ['analysed_sst', 'mask']\n", + "lats = [aoi_lat_min, aoi_lat_max]\n", + "lons = [aoi_lon_min, aoi_lon_max]\n", + "\n", + "mur = xr.open_mfdataset(\n", + " paths=[fs.open(f) for f in files],\n", + " combine='by_coords',\n", + " engine='h5netcdf',\n", + " chunks='auto',\n", + " cache=False,\n", + " decode_cf=True,\n", + " mask_and_scale=True,\n", + " preprocess=lambda x: x[var].sel(lat=slice(*lats), lon=slice(*lons)))\n", + "\n", + "print(mur)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "4e161da8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "dask.array\n", + "Coordinates:\n", + " * time (time) datetime64[ns] 2019-01-01T09:00:00 ... 2019-01-31T09:00:00\n", + "CPU times: user 63.7 ms, sys: 3.85 ms, total: 67.5 ms\n", + "Wall time: 66.2 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "sst_mean = mur.analysed_sst.groupby(\"time\").mean([\"lon\",\"lat\"]) - 273.15\n", + "\n", + "print(sst_mean)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "d84c70eb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 4.2 s, sys: 773 ms, total: 4.97 s\n", + "Wall time: 22.1 s\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%%time\n", + "\n", + "fig, ax = plt.subplots(figsize=(16, 5))\n", + "\n", + "sst_mean.compute().plot(ax=ax, color=\"red\")\n", + "\n", + "plt.xticks(rotation=15)\n", + "ax.set_xlim(sst_mean.time.min(), sst_mean.time.max())\n", + "ax.set_xlabel(None)\n", + "ax.set_ylim(15.0, 18.0)\n", + "ax.set_ylabel(\"Temperature (deg C)\")\n", + "ax.set_title(\"Daily L4 MUR SST from PO.DAAC Cloud (Jan 2019)\")\n", + "ax.grid(alpha=0.25)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "676e7d6b", "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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