67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
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import time
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import cartopy.crs as ccrs
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import matplotlib.pyplot as plt
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import numpy as np
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import requests
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from dateutil.parser import parse
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from dateutil.tz import tzutc, tzlocal
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from matplotlib.colors import LinearSegmentedColormap
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from mpl_toolkits.axes_grid1 import make_axes_locatable
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from scipy.interpolate import griddata
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def get_latest_glotec():
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r = requests.get('https://services.swpc.noaa.gov/experimental/products/glotec/geojson_2d_urt.json')
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r.raise_for_status()
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index_json = r.json()[-1]
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data_url = 'https://services.swpc.noaa.gov' + index_json['url']
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r2 = requests.get(data_url)
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r2.raise_for_status()
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return r2.json()
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def plot_glotec_map(data: dict, lon_range: list, lat_range: list):
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lons = []
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lats = []
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tec_values = []
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for feature in data['features']:
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lon, lat = feature['geometry']['coordinates']
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tec = feature['properties']['tec']
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lons.append(lon)
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lats.append(lat)
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tec_values.append(tec)
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lons = np.array(lons)
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lats = np.array(lats)
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tec_values = np.array(tec_values)
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lon_grid, lat_grid = np.meshgrid(np.linspace(lon_range[0], lon_range[1], 100), np.linspace(lat_range[0], lat_range[1], 100))
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# Interpolate the TEC values onto the regular grid
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tec_grid = griddata((lons, lats), tec_values, (lon_grid, lat_grid), method='linear')
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proj = ccrs.PlateCarree()
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f, ax = plt.subplots(1, 1, subplot_kw=dict(projection=proj))
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colors = ['#33184a', '#4454c3', '#4294ff', '#1ad2d2', '#3cf58e', '#9cfe40', '#dde037', '#fdac34', '#f26014', '#ca2a04', '#7A0403']
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custom_cmap = LinearSegmentedColormap.from_list('custom', colors)
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h = ax.pcolormesh(lon_grid, lat_grid, tec_grid, cmap=custom_cmap, vmin=0, vmax=100, transform=proj)
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ax.coastlines()
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timestamp_utc = parse(data['time_tag'])
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timestamp_local = timestamp_utc.replace(tzinfo=tzutc()).astimezone(tzlocal())
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plt.title(timestamp_local.strftime(f'%H:%M %m-%d-%Y {time.tzname[0]}'), fontsize=12, y=1.04)
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plt.suptitle('Global Total Electron Content', fontsize=16, y=0.87)
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divider = make_axes_locatable(ax)
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ax_cb = divider.new_horizontal(size='5%', pad=0.1, axes_class=plt.Axes)
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f.add_axes(ax_cb)
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cb = plt.colorbar(h, cax=ax_cb)
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plt.rc('text', usetex=True)
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cb.set_label('VTEC ($10^{16}*\\mathrm{m}^{-2}$)')
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return tec_grid, plt
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