def test_seed_cone(self):
o = OceanDrift(loglevel=20)
o.seed_cone(time=[datetime.now(),
datetime.now() + timedelta(hours=3)],
number=100,
lat=[60.5, 60.6],
lon=[4.4, 4.5])
self.assertAlmostEqual(o.elements_scheduled.lon[50], 4.450, 2)
def test_seed_cone(self):
# Some cases with expected outcome
lon0 = 3
lon1 = 4
lon2 = 5
lat0 = 60
lat1 = 60.2
lat2 = 60.4
lon_vec = np.array([lon0, lon1, lon2])
lat_vec = np.array([lat0, lat1, lat2])
t0 = datetime.now()
t1 = t0 + timedelta(hours=6)
t2 = t1 + timedelta(hours=6)
t_vec = [t0, t1, t2]
r0 = 1000
r1 = 2000
number_config = 222
cases = [
{
'lon': lon0,
'lat': lat0,
'time': t0,
'number': None,
'expected': number_config
},
{
'lon': lon0,
'lat': lat0,
'time': t0,
'number': 12,
'expected': 12,
'maxlat': lat0
},
{
'lon': lon0,
'lat': lat0,
'time': t0,
'radius': 1000,
'number': 12,
'expected': 12,
'maxlat': lat0 + .013
},
{
'lon': lon0,
'lat': lat0,
'time': [t0, t1],
'maxtime': t1,
'number': 12,
'expected': 12
},
{
'lon': lon0,
'lat': lat0,
'time': t_vec,
'number': 12,
'expected': 'error'
},
{
'lon': lon_vec,
'lat': lat_vec,
'time': t0,
'number': None,
'expected': 'error'
},
{
'lon': lon0,
'lat': lat0,
'time': t0,
'wind_drift_factor': .05,
'number': None,
'expected': number_config
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': t0,
'number': None,
'expected': number_config
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': t0,
'number': 12,
'expected': 12
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': t0,
'radius': 0,
'number': 200,
'expected': 200,
'maxlat': lat1
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': t0,
'radius': 2000,
'number': 200,
'expected': 200,
'maxlat': lat1 + .024
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': t0,
'radius': [1000, 2000],
'number': 200,
'expected': 200,
'maxlat': lat1 + .024
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': t0,
'radius': [1000, 2000, 3000],
'number': 200,
'expected': 'error'
},
#'wind_drift_factor': [.01, .02, .03],
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': [t0, t1],
'number': None,
'expected': number_config,
'maxtime': t1
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': [t0, t1],
'radius': [r0, r1],
'number': None,
'expected': number_config,
'maxtime': t1
},
{
'lon': [lon0, lon1],
'lat': [lat0, lat1],
'time': [t0, t1],
'radius': [r0, r0],
'number': None,
'expected': number_config,
'maxtime': t1
},
]
for case in cases:
o = OceanDrift(loglevel=50)
o._set_config_default('seed:number', number_config)
expected = case['expected']
del case['expected']
if 'maxlat' in case:
maxlat = case['maxlat']
del case['maxlat']
else:
maxlat = None
if 'maxtime' in case:
maxtime = case['maxtime']
del case['maxtime']
else:
maxtime = None
if expected == 'error':
with self.assertRaises(ValueError):
n = o.seed_cone(**case)
else:
o.seed_cone(**case)
self.assertEqual(o.num_elements_total(), expected)
if maxlat is not None:
self.assertAlmostEqual(o.elements_scheduled.lat.max(),
maxlat, 2)
if maxtime is not None:
self.assertEqual(
o.elements_scheduled_time.max().replace(microsecond=0),
maxtime.replace(microsecond=0))
if 'wind_drift_factor' in case:
self.assertEqual(
np.array(case['wind_drift_factor']).max().astype(
np.float32),
o.elements_scheduled.wind_drift_factor.max())
from datetime import datetime, timedelta
from opendrift.models.oceandrift import OceanDrift
from opendrift.readers.reader_constant import Reader as ConstantReader
#%%
# Mixed Layer Depth of 20m West of 3 deg E, and 50m to the east
r1 = ConstantReader({'ocean_mixed_layer_thickness': 20})
r2 = ConstantReader({'ocean_mixed_layer_thickness': 50})
r1.xmax = 3
r2.xmin = 3
#%%
# First with Sundby1983 parameterization of diffusivity, based on wind and MLD
o = OceanDrift(loglevel=50)
o.seed_cone(lon=[2, 4], lat=[60, 60], time=datetime.now(), number=5000)
o.add_reader([r1, r2])
o.set_config('environment:constant:y_wind', 8) # Some wind for mixing
o.set_config('drift:vertical_mixing', True)
o.set_config('vertical_mixing:diffusivitymodel', 'windspeed_Sundby1983')
# Increasing background diffusivity beyond default (1.2e-5) to avoid artefact due to sharp gradient at MLD
o.set_config('vertical_mixing:background_diffusivity', 0.001)
o.run(duration=timedelta(hours=48))
o.animation_profile()
#%%
# .. image:: /gallery/animations/example_mixed_layer_depth_0.gif
#%%
# Same, but with Large1994 parameterization of diffusivity
o = OceanDrift(loglevel=50)
print('=' * 70)
lats = np.linspace(60, 61, 100)
lons = np.linspace(4, 4.8, 100)
o.seed_elements(lon=lons, lat=lats, time=time)
o.run(steps=1)
o.plot(buffer=.2, fast=True)
#%%
# Seeding 100 elements between two points with seed_cone() (achieving the same as previous example)
print('\n' + '=' * 70)
print(
'Seeding 100 elements between two points with seed_cone() (achieving the same as previous example):'
)
print('o.seed_cone(lon=[4, 4.8], lat=[60, 61], number=100, time=time)')
print('=' * 70)
o.seed_cone(lon=[4, 4.8], lat=[60, 61], number=100, time=time)
o.run(steps=1)
o.plot(buffer=.2, fast=True)
#%%
# Seeding 1000 elements along cone with radius/uncertainty increasing linearly from 0 to 5000 m
print('\n' + '=' * 70)
print(
'Seeding 1000 elements along cone with radius/uncertainty\n increasing linearly from 0 to 5000 m:'
)
print(
'o.seed_cone(lon=[4, 4.8], lat=[60, 61], number=1000, radius=[0, 5000], time=time)'
)
print('=' * 70)
o.seed_cone(lon=[4, 4.8],
lat=[60, 61],
