def from_netCDF(
cls,
filename=None,
extrapolate=False,
time_offset=0,
current_scale=1,
uncertain_duration=24 * 3600,
uncertain_time_delay=0,
uncertain_along=0.5,
uncertain_across=0.25,
uncertain_cross=0.25,
default_num_method="Trapezoid",
**kwargs
):
wind = GridWind.from_netCDF(filename, **kwargs)
return cls(
wind=wind,
filename=filename,
extrapolate=extrapolate,
time_offset=time_offset,
current_scale=current_scale,
uncertain_along=uncertain_along,
uncertain_across=uncertain_across,
uncertain_cross=uncertain_cross,
default_num_method=default_num_method,
)
def test_gen_varnames(self):
import netCDF4 as nc4
from gnome.environment import GridCurrent, GridWind, IceVelocity
ds = nc4.Dataset('testname', 'w', diskless=True, persist=False)
ds.createDimension('y', 5)
ds.createDimension('x', 5)
ds.createVariable('x', 'f8', dimensions=('x', 'y'))
ds['x'].standard_name = 'eastward_sea_water_velocity'
ds.createVariable('y', 'f8', dimensions=('x', 'y'))
ds['y'].standard_name = 'northward_sea_water_velocity'
ds.createVariable('xw', 'f8', dimensions=('x', 'y'))
ds['xw'].long_name = 'eastward_wind'
ds.createVariable('yw', 'f8', dimensions=('x', 'y'))
ds['yw'].long_name = 'northward_wind'
ds.createVariable('ice_u', 'f8', dimensions=('x', 'y'))
ds.createVariable('ice_v', 'f8', dimensions=('x', 'y'))
names = GridCurrent._gen_varnames(dataset=ds)
assert names[0] == names.u == 'x'
assert names[1] == names.v == 'y'
names = GridWind._gen_varnames(dataset=ds)
assert names[0] == names.u == 'xw'
assert names[1] == names.v == 'yw'
names = IceVelocity._gen_varnames(dataset=ds)
assert names[0] == names.u == 'ice_u'
assert names[1] == names.v == 'ice_v'
curr_file = os.path.join(s_data, 'staggered_sine_channel.nc')
gc = GridCurrent.from_netCDF(filename=curr_file)
assert gc.u == gc.variables[0]
assert gc.varnames[0] == 'u'
def from_netCDF(cls,
filename=None,
time_offset=0,
wind_scale=1,
uncertain_duration=24 * 3600,
uncertain_time_delay=0,
uncertain_along=.5,
uncertain_across=.25,
uncertain_cross=.25,
default_num_method='RK2',
**kwargs):
wind = GridWind.from_netCDF(filename, **kwargs)
return cls(wind=wind,
filename=filename,
time_offset=time_offset,
wind_scale=wind_scale,
uncertain_along=uncertain_along,
uncertain_across=uncertain_across,
uncertain_cross=uncertain_cross,
default_num_method=default_num_method)
def from_netCDF(cls,
filename=None,
time_offset=0,
scale_value=1,
uncertain_duration=24 * 3600,
uncertain_time_delay=0,
uncertain_along=.5,
uncertain_across=.25,
uncertain_cross=.25,
default_num_method='RK2',
**kwargs):
wind = GridWind.from_netCDF(filename, **kwargs)
return cls(wind=wind,
filename=filename,
time_offset=time_offset,
scale_value=scale_value,
uncertain_along=uncertain_along,
uncertain_across=uncertain_across,
uncertain_cross=uncertain_cross,
default_num_method=default_num_method)
def test_gen_varnames(self):
import netCDF4 as nc4
from gnome.environment import GridCurrent, GridWind, IceVelocity
ds = nc4.Dataset('testname', 'w', diskless=True, persist=False)
ds.createDimension('y', 5)
ds.createDimension('x', 5)
ds.createVariable('x', 'f8', dimensions=('x', 'y'))
ds['x'].standard_name = 'eastward_sea_water_velocity'
ds.createVariable('y', 'f8', dimensions=('x', 'y'))
ds['y'].standard_name = 'northward_sea_water_velocity'
ds.createVariable('xw', 'f8', dimensions=('x', 'y'))
ds['xw'].long_name = 'eastward_wind'
ds.createVariable('yw', 'f8', dimensions=('x', 'y'))
ds['yw'].long_name = 'northward_wind'
ds.createVariable('ice_u', 'f8', dimensions=('x', 'y'))
ds.createVariable('ice_v', 'f8', dimensions=('x', 'y'))
names = GridCurrent._gen_varnames(dataset=ds)
assert names[0] == names.u == 'x'
assert names[1] == names.v == 'y'
names = GridWind._gen_varnames(dataset=ds)
assert names[0] == names.u == 'xw'
assert names[1] == names.v == 'yw'
names = IceVelocity._gen_varnames(dataset=ds)
assert names[0] == names.u == 'ice_u'
assert names[1] == names.v == 'ice_v'
curr_file = os.path.join(s_data, 'staggered_sine_channel.nc')
gc = GridCurrent.from_netCDF(filename=curr_file)
assert gc.u == gc.variables[0]
assert gc.varnames[0] == 'u'
def from_netCDF(cls,
filename=None,
extrapolate=False,
time_offset=0,
current_scale=1,
uncertain_duration=24 * 3600,
uncertain_time_delay=0,
uncertain_along=.5,
uncertain_across=.25,
uncertain_cross=.25,
default_num_method='Trapezoid',
**kwargs):
wind = GridWind.from_netCDF(filename, **kwargs)
return cls(wind=wind,
filename=filename,
extrapolate=extrapolate,
time_offset=time_offset,
current_scale=current_scale,
uncertain_along=uncertain_along,
uncertain_across=uncertain_across,
uncertain_cross=uncertain_cross,
default_num_method=default_num_method)
def __init__(self,
filename=None,
wind=None,
time_offset=0,
uncertain_duration=3,
uncertain_time_delay=0,
uncertain_speed_scale=2.,
uncertain_angle_scale=0.4,
wind_scale=1,
default_num_method='RK2',
extrapolation_is_allowed=False,
**kwargs):
"""
Initialize a PyWindMover
:param filename: absolute or relative path to the data file(s):
could be a string or list of strings in the
case of a multi-file dataset
:param wind: Environment object representing wind to be
used. If this is not specified, a GridWind object
will attempt to be instantiated from the file
:param active_range: Range of datetimes for when the mover should be
active
:type active_range: 2-tuple of datetimes
:param wind_scale: Value to scale wind data
:param uncertain_duration: how often does a given uncertain element
get reset
:param uncertain_time_delay: when does the uncertainly kick in.
:param uncertain_cross: Scale for uncertainty perpendicular to the flow
:param uncertain_along: Scale for uncertainty parallel to the flow
:param time_offset: Time zone shift if data is in GMT
:param num_method: Numerical method for calculating movement delta.
Choices:('Euler', 'RK2', 'RK4')
Default: RK2
"""
self.wind = wind
self.make_default_refs = False
self.filename = filename
if self.wind is None:
if filename is None:
raise ValueError("must provide a filename or wind object")
else:
self.wind = GridWind.from_netCDF(filename=self.filename,
**kwargs)
self.extrapolation_is_allowed = extrapolation_is_allowed
self.uncertain_duration = uncertain_duration
self.uncertain_time_delay = uncertain_time_delay
self.uncertain_speed_scale = uncertain_speed_scale
self.wind_scale = wind_scale
self.time_offset = time_offset
# also sets self._uncertain_angle_units
self.uncertain_angle_scale = uncertain_angle_scale
(super(PyWindMover, self)
.__init__(default_num_method=default_num_method, **kwargs))
self.array_types.update({'windages',
'windage_range',
'windage_persist'})
def __init__(self,
filename=None,
wind=None,
time_offset=0,
uncertain_duration=3,
uncertain_time_delay=0,
uncertain_speed_scale=2.,
uncertain_angle_scale=0.4,
scale_value=1,
default_num_method='RK2',
**kwargs):
"""
Initialize a PyWindMover
:param filename: absolute or relative path to the data file(s):
could be a string or list of strings in the
case of a multi-file dataset
:param wind: Environment object representing wind to be
used. If this is not specified, a GridWind object
will attempt to be instantiated from the file
:param active_range: Range of datetimes for when the mover should be
active
:type active_range: 2-tuple of datetimes
:param scale_value: Value to scale wind data
:param uncertain_duration: how often does a given uncertain element
get reset
:param uncertain_time_delay: when does the uncertainly kick in.
:param uncertain_cross: Scale for uncertainty perpendicular to the flow
:param uncertain_along: Scale for uncertainty parallel to the flow
:param time_offset: Time zone shift if data is in GMT
:param num_method: Numerical method for calculating movement delta.
Choices:('Euler', 'RK2', 'RK4')
Default: RK2
"""
(super(PyWindMover,
self).__init__(default_num_method=default_num_method, **kwargs))
self.wind = wind
self.make_default_refs = False
self.filename = filename
if self.wind is None:
if filename is None:
raise ValueError("must provide a filename or wind object")
else:
self.wind = GridWind.from_netCDF(filename=self.filename,
**kwargs)
self.uncertain_duration = uncertain_duration
self.uncertain_time_delay = uncertain_time_delay
self.uncertain_speed_scale = uncertain_speed_scale
self.scale_value = scale_value
self.time_offset = time_offset
# also sets self._uncertain_angle_units
self.uncertain_angle_scale = uncertain_angle_scale
self.array_types.update({
'windages': gat('windages'),
'windage_range': gat('windage_range'),
'windage_persist': gat('windage_persist')
})
# dataset=ds_c,
grid_topology={
'node_lon': 'lonc',
'node_lat': 'latc'
})
c_mover = PyCurrentMover(current=g_curr, default_num_method='RK4')
model.movers += c_mover
print 'creating wind MFDataset'
ds_w = nc4.MFDataset(file_list_w)
print 'adding a WindMover (Euler):'
g_wind = GridWind.from_netCDF(
filename=file_list_w,
# dataset=ds_w,
grid_topology={
'node_lon': 'lonc',
'node_lat': 'latc'
})
w_mover = PyWindMover(wind=g_wind, default_num_method='Euler')
model.movers += w_mover
model.environment += g_wind
water = Water(temperature=290.0, salinity=33.0)
waves = Waves(g_wind)
model.weatherers += Evaporation(water=water, wind=g_wind)
model.weatherers += NaturalDispersion(waves=waves)
# print 'adding a CurrentMover (Trapeziod/RK4):'
# c_mover = GridCurrentMover(os.path.join(setup.Data_Dir,setup.CurrCatFile),
# os.path.join(setup.Data_Dir,setup.CurrTopoFile),