The simplest example of requesting and plotting AWIPS gridded data with Matplotlib and Cartopy.
In [5]:
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¶
In [26]:
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¶
In [19]:
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()))
