process_version = "1.0E" vapname = "mmcg" site = "sgp" facility = "I7" level = "c0" ncfile = sys.argv[1] odir = sys.argv[2] cf_alt = 320.0 / 1000.0 cf_lat = dms_to_d([36.0, 36.0, 18.35]) cf_lon = -1.0*dms_to_d([97.0, 29.0, 10.69]) #mync=netCDF4.Dataset(ncfile) #myradar=radar.Radar(mync) myradar = pyart.io.read_netcdf(ncfile) print myradar.time['data'][0] cp = corner_to_point([myradar.location['latitude']['data'], myradar.location['longitude']['data']], [cf_lat, cf_lon]) #mync.close() mygrids = grid.pyGrid( (myradar,), nxyz=(241, 241, 35), xyzr=((-120000 - cp[0], 120000 - cp[0]), (-120000 - cp[1], 120000 - cp[1]), (0, 17000)), params=['reflectivity_horizontal'], toa=20000, origin=[cf_lat, cf_lon, cf_alt], qrf=my_qrf) # plot for testing... refl = mygrids.fields['reflectivity_horizontal']['data'] refl = np.ma.masked_equal(refl, -9999.0) fig = plt.figure() ax = fig.add_subplot(111)
process_version = "1.0E" vapname = "mmcg" site = "sgp" facility = "I7" level = "c0" ncfile = sys.argv[1] odir = sys.argv[2] cf_alt = 320.0 / 1000.0 cf_lat = dms_to_d([36.0, 36.0, 18.35]) cf_lon = -1.0 * dms_to_d([97.0, 29.0, 10.69]) #mync=netCDF4.Dataset(ncfile) #myradar=radar.Radar(mync) myradar = pyart.io.read_netcdf(ncfile) print myradar.time['data'][0] cp = corner_to_point([ myradar.location['latitude']['data'], myradar.location['longitude']['data'] ], [cf_lat, cf_lon]) #mync.close() mygrids = grid.pyGrid((myradar, ), nxyz=(241, 241, 35), xyzr=((-120000 - cp[0], 120000 - cp[0]), (-120000 - cp[1], 120000 - cp[1]), (0, 17000)), params=['reflectivity_horizontal'], toa=20000, origin=[cf_lat, cf_lon, cf_alt], qrf=my_qrf) # plot for testing... refl = mygrids.fields['reflectivity_horizontal']['data'] refl = np.ma.masked_equal(refl, -9999.0) fig = plt.figure()
import vispy import vispy.app # from vispy.scene.widgets import ViewBox from vispy.scene.visuals import Mesh from vispy.scene.visuals import Text from vispy.geometry import MeshData from vispy.scene import STTransform, MatrixTransform, ChainTransform from matplotlib.cm import ScalarMappable from matplotlib.colors import Normalize import glob loc_ka = (33.73732, -101.84326) loc_88d = (33.654140472412109, -101.81416320800781) dx_ka, dy_ka = corner_to_point(loc_ka, loc_88d) #meters #------------------- # Selection of interesting times #------------------- # filenames = glob.glob('/data/20140607/Ka2/Ka2140608031*')#[5:10] # filenames_88d = glob.glob('/data/20140607/88D/KLBB20140608_031*') # t_start = datetime.datetime(2014,6,8,3,16,29) # filenames = glob.glob('/data/20140607/Ka2/Ka2140608033*')#[5:10] # filenames_88d = glob.glob('/data/20140607/88D/KLBB20140608_033*') # t_start = datetime.datetime(2014,6,8,3,39,05)