def setUp(self):
dx = dy = 0.25
T0 = 693596.5 # '1900-01-01 12:00'
self.grid_time = numpy.arange(10) + T0
self.grid_height = numpy.arange(0)
self.grid_lat = numpy.arange(-90., 90., dy) + dy / 2.
self.grid_lon = numpy.arange(0., 360., dx) + dx / 2.
self.grid_N = numpy.arange(self.grid_time.size)
self.grid_K = numpy.arange(self.grid_height.size)
self.grid_J = numpy.arange(self.grid_lat.size)
self.grid_I = numpy.arange(self.grid_lon.size)
#
x, y = self.grid_lon, self.grid_lat
xx, yy = numpy.meshgrid(x, y)
t = 0
k = 2 * numpy.pi / 180
l = 2 * numpy.pi / 720
w = 2 * numpy.pi / 365.25
self.grid_SST = numpy.cos(k * xx * l * yy - w * t)
self.grid_dSSTdx = -k * l * yy * numpy.sin(k * xx * l * yy - w * t)
self.grid_d2SSTdx2 = -(k * l * yy)**2 * numpy.cos(k * xx * l * yy -
w * t)
self.grid_dSSTdy = -k * l * xx * numpy.sin(k * xx * l * yy - w * t)
self.grid_d2SSTdy2 = -(k * l * xx)**2 * numpy.cos(k * xx * l * yy -
w * t)
self.grid_grad = self.grid_dSSTdx + 1j * self.grid_dSSTdy
#
l = 2 * numpy.pi / 45
self.grid_UV = (numpy.sin(k * xx) + numpy.cos(l * yy) + 1j *
(numpy.cos(k * xx) + numpy.sin(l * yy)))
self.grid_curl = -k * numpy.sin(k * xx) - (-l * numpy.sin(l * yy))
self.grid_div = k * numpy.cos(k * xx) + l * numpy.cos(l * yy)
#
self.grid = data.Grid()
self.grid.name = 'Test dataset'
self.grid.dimensions = dict(n=self.grid_time.size,
k=self.grid_height.size,
j=self.grid_lat.size,
i=self.grid_lon.size)
var_list = [
'time', 'height', 'latitude', 'longitude',
'sea_surface_temperature'
]
for var in var_list:
self.grid.variables[var] = data.get_standard_variable(var)
self.grid.variables['time'].data = self.grid_time
self.grid.variables['time'].canonical_units = ('days since 0001-01-01'
' UTC')
self.grid.variables['height'].data = self.grid_height
self.grid.variables['latitude'].data = self.grid_lat
self.grid.variables['longitude'].data = self.grid_lon
self.grid.variables['sea_surface_temperature'] = self.grid_SST
def setUp(self):
self.connection = dado.Connection(user='******', password='******',
db='dado')
self.sequence = dado.Sequence(self.connection)
self.variable = data.get_standard_variable('sea_water_temperature')
self.level_raw = dado.Level(id=0, name='raw', temporal='NULL',
horizontal_x='NULL', horizontal_y='NULL', vertical='NULL',
description='Raw (level 0) data.')
self.project_dummy = dado.Project(id=0, parent=None, name='dummy',
description='A dummy project for testing purposes.')
self.station_dummy = dado.Station(project=self.project_dummy,
id=0, name='free',
description='A free station for the dummy project.')
def setUp(self):
dx = dy = 0.25
T0 = 693596.5 # '1900-01-01 12:00'
self.grid_time = numpy.arange(10) + T0
self.grid_height = numpy.arange(0)
self.grid_lat = numpy.arange(-90., 90., dy) + dy / 2.
self.grid_lon = numpy.arange(0., 360., dx) + dx / 2.
self.grid_N = numpy.arange(self.grid_time.size)
self.grid_K = numpy.arange(self.grid_height.size)
self.grid_J = numpy.arange(self.grid_lat.size)
self.grid_I = numpy.arange(self.grid_lon.size)
#
x, y = self.grid_lon, self.grid_lat
xx, yy = numpy.meshgrid(x, y)
t = 0
k = 2 * numpy.pi / 180
l = 2 * numpy.pi / 720
w = 2 * numpy.pi / 365.25
self.grid_SST = numpy.cos(k * xx * l * yy - w * t)
self.grid_dSSTdx = - k * l * yy * numpy.sin(k * xx * l * yy - w * t)
self.grid_d2SSTdx2 = -(k*l*yy)**2 * numpy.cos(k * xx * l * yy - w * t)
self.grid_dSSTdy = - k * l * xx * numpy.sin(k * xx * l * yy - w * t)
self.grid_d2SSTdy2 = -(k*l*xx)**2 * numpy.cos(k * xx * l * yy - w * t)
self.grid_grad = self.grid_dSSTdx + 1j * self.grid_dSSTdy
#
l = 2 * numpy.pi / 45
self.grid_UV = (numpy.sin(k * xx) + numpy.cos(l * yy) +
1j * (numpy.cos(k * xx) + numpy.sin(l * yy)))
self.grid_curl = -k * numpy.sin(k * xx) - (- l * numpy.sin(l * yy))
self.grid_div = k * numpy.cos(k * xx) + l * numpy.cos(l * yy)
#
self.grid = data.Grid()
self.grid.name = 'Test dataset'
self.grid.dimensions = dict(
n = self.grid_time.size,
k = self.grid_height.size,
j = self.grid_lat.size,
i = self.grid_lon.size
)
var_list = ['time', 'height', 'latitude', 'longitude',
'sea_surface_temperature']
for var in var_list:
self.grid.variables[var] = data.get_standard_variable(var)
self.grid.variables['time'].data = self.grid_time
self.grid.variables['time'].canonical_units = ('days since 0001-01-01'
' UTC')
self.grid.variables['height'].data = self.grid_height
self.grid.variables['latitude'].data = self.grid_lat
self.grid.variables['longitude'].data = self.grid_lon
self.grid.variables['sea_surface_temperature'] = self.grid_SST
def test_get_standard_variable(self):
var = data.get_standard_variable('sea_surface_temperature')
self.assertEqual('sea_surface_temperature', var.standard_name)
self.assertEqual('K', var.canonical_units)
def test_connection_datavars_insert(self):
var_list = ['sea_water_temperature', 'sea_water_salinity', 'depth']
for var in var_list:
self.connection.datavars_insert(data.get_standard_variable(var))
def update(self, dat, append=False, smooth=False, report=True, **kwargs):
"""
Updates bulk fluxes.
Parameters
----------
dat : odv.Sequence()
ODV data object.
append : boolean, optional
Sets whether calculated parameters are appended to data
sequence. Default is `False`.
smooth : boolean, optional
If 'True' (default), smoothes data using a boxcar moving
average.
report : boolean, optional
Returns
-------
Nothing
"""
# Checks data fields and uses the following wind components in order
# of preference:
# . ['alongchannel_wind', 'crosschannel_wind'];
# . ['eastward_wind', 'northward_wind']
fields = dat.fields.keys()
if ('alongchannel_wind' in fields) & ('crosschannel_wind' in fields):
_wind = ('alongchannel_wind', 'crosschannel_wind')
elif ('eastward_wind' in fields) & ('northward_wind' in fields):
wind = ('eastward_wind', 'northward_wind')
else:
raise ValueError('Noooo!!!!!')
# Assings data to some variables.
U_O = dat[_wind[0]].data + 1j * dat[_wind[1]].data
T_O = dat['air_temperature'].data
SLP = dat['air_pressure_at_sea_level'].data
SST = dat['sea_water_temperature'].data
SSU = 0
try:
q_O = dat['specific_humidity'].data
except:
q_O = self.relative2specific_humidity(
dat['relative_humidity'].data, SST, SLP)
# Makes some units conversion
if dat['air_pressure_at_sea_level'].units != 'hPa':
raise ValuError('Invalid unit for pressure.')
#
units = dict(
U_O=dat[_wind[0]].units,
T_O=dat['air_temperature'].units,
q_O='kg kg-1',
SLP='hPa',
SST=dat['sea_water_temperature'].units,
SSU=dat[_wind[0]].units
)
# Smoothes data using moving average.
if smooth:
window = ones(29.) #hanning(29.)
window /= window.sum()
U_O = convolve(U_O.real, window, mode='same') + \
1j * convolve(U_O.imag, window, mode='same')
T_O = convolve(T_O, window, mode='same')
q_O = convolve(q_O, window, mode='same')
SLP = convolve(SLP, window, mode='same')
SST = convolve(SST, window, mode='same')
#SSU = convolve(SSU, window, mode='same')
print 'Smooooooth'
# Calculates bulk_fluxes
Tau, QH, QE, dU10, dtheta10, dq10, L, zeta = \
self.bulk_fluxes(U_O, T_O, q_O, SLP, SST, SSU, units=units,
result='all', **kwargs)
# Apppends data to class items.
self.__setitem__('Tau_x', data.get_standard_variable(
'surface_downward_northward_stress', data=Tau.imag,
string_format='{:.4f}'))
self.__setitem__('Tau_y', data.get_standard_variable(
'surface_downward_eastward_stress', data=Tau.real,
string_format='{:.4f}'))
self.__setitem__('QH', data.get_standard_variable(
'surface_downward_sensible_heat_flux', data=QH))
self.__setitem__('QE', data.get_standard_variable(
'surface_downward_latent_heat_flux', data=QE))
#
CD = self.C_D(dU10)
self.__setitem__('CD', data.get_standard_variable(
'surface_drag_coefficient_for_momentum_in_air', data=CD))
CH = self.C_H(dU10, zeta=zeta)
self.__setitem__('CH', data.get_standard_variable(
'surface_drag_coefficient_for_heat_in_air', data=CH))
CE = self.C_E(dU10)
self.__setitem__('CE', data.Variable(
standard_name='surface_drag_coefficient_for_evaporation_in_air',
data=CE, units='1'))
#
if append:
dat['surface_downward_northward_stress'] = self.__getitem__('Tau_x')
dat['surface_downward_eastward_stress'] = self.__getitem__('Tau_y')
dat['surface_downward_sensible_heat_flux'] = self.__getitem__('QH')
dat['surface_downward_latent_heat_flux'] = self.__getitem__('QE')
#
dat['surface_drag_coefficient_for_momentum_in_air'] = \
self.__getitem__('CD')
dat['surface_drag_coefficient_for_heat_in_air'] = \
self.__getitem__('CH')
dat['surface_drag_coefficient_for_evaporation_in_air'] =\
self.__getitem__('CE')
#
if report:
print r'\Delta \theta', nanmin(dtheta10), nanmean(dtheta10), nanmax(dtheta10)
#
return -1
def test_get_standard_variable(self):
var = data.get_standard_variable('sea_surface_temperature')
self.assertEqual('sea_surface_temperature', var.standard_name)
self.assertEqual('K', var.canonical_units)
