2.3 KiB
2.3 KiB
The simplest example of requesting and plotting AWIPS gridded data with Matplotlib and Cartopy.
from awips.dataaccess import DataAccessLayer
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
%matplotlib inline
DataAccessLayer.changeEDEXHost("edex-cloud.unidata.ucar.edu")
request = DataAccessLayer.newDataRequest()
request.setDatatype("grid")
request.setLocationNames("RAP13")
request.setParameters("T")
request.setLevels("2.0FHAG")
cycles = DataAccessLayer.getAvailableTimes(request, True)
times = DataAccessLayer.getAvailableTimes(request)
fcstRun = DataAccessLayer.getForecastRun(cycles[-1], times)
response = DataAccessLayer.getGridData(request, [fcstRun[0]])
grid = response[0]
data = grid.getRawData()
lons, lats = grid.getLatLonCoords()
bbox = [lons.min(), lons.max(), lats.min(), lats.max()]
def make_map(bbox, projection=ccrs.PlateCarree()):
fig, ax = plt.subplots(figsize=(16, 9),
subplot_kw=dict(projection=projection))
ax.set_extent(bbox)
ax.coastlines(resolution='50m')
gl = ax.gridlines(draw_labels=True)
gl.xlabels_top = gl.ylabels_right = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
return fig, ax
with pcolormesh
cmap = plt.get_cmap('rainbow')
fig, ax = make_map(bbox=bbox)
cs = ax.pcolormesh(lons, lats, data, cmap=cmap)
cbar = fig.colorbar(cs, shrink=0.7, orientation='horizontal')
cbar.set_label(str(grid.getLocationName()) +" " \
+ str(grid.getLevel()) + " " \
+ str(grid.getParameter()) \
+ " (" + str(grid.getUnit()) + ") " \
+ "valid " + str(grid.getDataTime().getRefTime()))
with contourf
fig2, ax2 = make_map(bbox=bbox)
cs2 = ax2.contourf(lons, lats, data, 80, cmap=cmap,
vmin=data.min(), vmax=data.max())
cbar2 = fig2.colorbar(cs2, shrink=0.7, orientation='horizontal')
cbar2.set_label(str(grid.getLocationName()) +" " \
+ str(grid.getLevel()) + " " \
+ str(grid.getParameter()) \
+ " (" + str(grid.getUnit()) + ") " \
+ "valid " + str(grid.getDataTime().getRefTime()))