def append_fields(self, names, arr, dtypes=None, units=None,
descriptions=None):
# This makes the names now a list of tuples of names and titles,
# so that the dtype constructor can use them
self.units.update(zip(names, units))
names = zip(descriptions, names)
self._data = append_fields(self._data, names, arr, dtypes)
def append_fields(self,
names,
arr,
dtypes=None,
units=None,
descriptions=None):
# This makes the names now a list of tuples of names and titles,
# so that the dtype constructor can use them
self.units.update(zip(names, units))
names = zip(descriptions, names)
self._data = append_fields(self._data, names, arr, dtypes)
h_convergence)
from metpy import remote_mesonet_data
from metpy.constants import C2F
from metpy.cbook import append_fields
from metpy.vis import station_plot
from metpy.tools.oban import gaussian_filter
# TODO: Find a way to fix the bad convergence values at the edge of the
# masked data
data = read_mesonet_data('data/200905082110.mdf',
fields=('STID', 'TIME', 'TAIR', 'RELH', 'WSPD',
'WDIR'))
#Calculate dewpoint in F from relative humidity and temperature
dewpt = C2F(dewpoint(data['TAIR'], data['RELH'] / 100.))
data = append_fields(data, ('dewpoint', ), (dewpt, ))
#Convert temperature and dewpoint to Farenheit
data['TAIR'] = C2F(data['TAIR'])
u, v = get_wind_components(data['WSPD'], data['WDIR'])
data = append_fields(data, ('u', 'v'), (u, v))
fig = plt.figure(figsize=(20, 12))
ax = fig.add_subplot(1, 1, 1)
m = Basemap(lon_0=-99,
lat_0=35,
lat_ts=35,
resolution='i',
projection='stere',
urcrnrlat=37.,
from metpy import (read_mesonet_data, dewpoint, get_wind_components,
h_convergence)
from metpy import remote_mesonet_data
from metpy.constants import C2F
from metpy.cbook import append_fields
from metpy.vis import station_plot
from metpy.tools.oban import gaussian_filter
# TODO: Find a way to fix the bad convergence values at the edge of the
# masked data
data = read_mesonet_data('data/200905082110.mdf',
fields=('STID', 'TIME', 'TAIR', 'RELH', 'WSPD', 'WDIR'))
#Calculate dewpoint in F from relative humidity and temperature
dewpt = C2F(dewpoint(data['TAIR'], data['RELH']/100.))
data = append_fields(data, ('dewpoint',), (dewpt,))
#Convert temperature and dewpoint to Farenheit
data['TAIR'] = C2F(data['TAIR'])
u,v = get_wind_components(data['WSPD'], data['WDIR'])
data = append_fields(data, ('u', 'v'), (u, v))
fig = plt.figure(figsize=(20,12))
ax = fig.add_subplot(1,1,1)
m = Basemap(lon_0=-99, lat_0=35, lat_ts=35, resolution='i',
projection='stere', urcrnrlat=37., urcrnrlon=-94.25, llcrnrlat=33.7,
llcrnrlon=-103., ax=ax)
m.bluemarble()
#Objectively analyze wind components
