def test_runge_kutta(self):
number = 50
# With Euler
o = OceanDrift3D(loglevel=20, seed=0)
norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() + '14Jan2016_NorKyst_z_3d/NorKyst-800m_ZDEPTHS_his_00_3Dsubset.nc')
o.fallback_values['land_binary_mask'] = 0
o.add_reader([norkyst])
z=-40*np.random.rand(number)
o.seed_elements(5, 62.5, number=number, radius=5000, z=z,
time=norkyst.start_time)
o.run(steps=4*3, time_step=timedelta(minutes=15))
# With Runge-Kutta
o2 = OceanDrift3D(loglevel=20, seed=0)
o2.fallback_values['land_binary_mask'] = 0
o2.add_reader([norkyst])
z=-40*np.random.rand(number)
o2.seed_elements(5, 62.5, number=number, radius=5000, z=z,
time=norkyst.start_time)
o2.set_config('drift:scheme', 'runge-kutta')
o2.run(steps=4*3, time_step=timedelta(minutes=15))
# And finally repeating the initial run to check that indetical
o3 = OceanDrift3D(loglevel=20, seed=0)
norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() + '14Jan2016_NorKyst_z_3d/NorKyst-800m_ZDEPTHS_his_00_3Dsubset.nc')
o3.fallback_values['land_binary_mask'] = 0
o3.add_reader([norkyst])
z=-40*np.random.rand(number)
o3.seed_elements(5, 62.5, number=number, radius=5000, z=z,
time=norkyst.start_time)
o3.run(steps=4*3, time_step=timedelta(minutes=15))
# Check that we get some difference with Runge-Kutta:
self.assertAlmostEqual((o2.elements.lon-o.elements.lon).max(),
0.0015, 3)
# Check that runs with Euler are identical
self.assertEqual((o3.elements.lon-o.elements.lon).max(), 0)
def test_MFDataset(self):
reader_basemap = reader_basemap_landmask.Reader(llcrnrlon=13.5,
llcrnrlat=67.1,
urcrnrlon=14.6,
urcrnrlat=67.7,
resolution='i',
projection='merc')
o = OceanDrift3D(loglevel=0)
o.set_config('general:basemap_resolution', 'i')
nordicMF = reader_ROMS_native.Reader(
o.test_data_folder() +
'2Feb2016_Nordic_sigma_3d/Nordic_subset_day*.nc')
nordicMF_all = reader_ROMS_native.Reader(
o.test_data_folder() + '2Feb2016_Nordic_sigma_3d/Nordic_subset.nc')
lon = 14.0
lat = 67.3
#nordic3d = reader_ROMS_native.Reader(o.test_data_folder() +
# '2Feb2016_Nordic_sigma_3d/Nordic-4km_SLEVELS_avg_00_subset2Feb2016.nc')
#o.add_reader(nordic3d) # Slightly different results
# Subset is made with ncks, and should give identical result
# e0=0, e1=20, x0=40, x1=70
# ncks -d eta_rho,0,$e1 -d eta_psi,0,$e1 -d eta_v,0,$e1 -d eta_u,0,$e1 -d xi_rho,$x0,$x1 -d xi_psi,$x0,$x1 -d xi_v,$x0,$x1 -d xi_u,$x0,$x1 Nordic-4km_SLEVELS_avg_00_subset2Feb2016.nc Nordic_subset.nc -O --fl_fmt=netcdf4_classic
# ncks -O -d ocean_time,0 Nordic_subset.nc Nordic_subset_day1.nc
o.add_reader([reader_basemap, nordicMF_all])
o.seed_elements(lon,
lat,
number=100,
radius=5000,
time=nordicMF_all.start_time)
o.run(steps=48, time_step=3600)
# Same run, with multi-file dataset
o2 = OceanDrift3D(loglevel=30)
o2.set_config('general:basemap_resolution', 'i')
o2.add_reader([reader_basemap, nordicMF])
o2.seed_elements(lon,
lat,
number=100,
radius=5000,
time=nordicMF_all.start_time)
o2.run(steps=48, time_step=3600)
#o.plot(filename='o1.png', background='sea_floor_depth_below_sea_level')
#o2.plot(filename='o2.png', background='sea_floor_depth_below_sea_level')
self.assertEqual(o.num_elements_active(), 67)
self.assertEqual(o2.num_elements_active(), 67)
self.assertEqual(o.num_elements_deactivated(), 33)
self.assertEqual(o2.num_elements_deactivated(), 33)
self.assertEqual(o.elements.lon[0], o2.elements.lon[0])
def test_truncate_ocean_model(self):
o = OceanDrift3D(loglevel=30)
reader_nordic = reader_ROMS_native.Reader(o.test_data_folder() + \
'2Feb2016_Nordic_sigma_3d/Nordic-4km_SLEVELS_avg_00_subset2Feb2016.nc')
o.add_reader(reader_nordic)
o.seed_elements(lon=15.0,
lat=71.1,
radius=0,
number=10,
z=np.linspace(-90, 0, 10),
time=reader_nordic.start_time)
o.set_config('general:use_basemap_landmask', False)
o.run(steps=5)
o2 = OceanDrift3D(loglevel=30)
o2.add_reader(reader_nordic)
o2.set_config('drift:truncate_ocean_model_below_m', 50)
o2.seed_elements(lon=15.0,
lat=71.1,
radius=0,
number=10,
z=np.linspace(-90, 0, 10),
time=reader_nordic.start_time)
o2.set_config('general:use_basemap_landmask', False)
o2.run(steps=5)
o3 = OceanDrift3D(loglevel=30)
o3.add_reader(reader_nordic)
o3.set_config('drift:truncate_ocean_model_below_m', 50)
o3.seed_elements(lon=15.0,
lat=71.1,
radius=0,
number=10,
z=np.linspace(-90, 0, 10),
time=reader_nordic.start_time)
o3.set_config('general:use_basemap_landmask', False)
o3.run(steps=5)
# Final depths should not be affected
self.assertIsNone(
np.testing.assert_array_almost_equal(o.elements.z, o3.elements.z))
# Surface elements should not be affected
self.assertEqual(o.elements.lat[-1], o3.elements.lat[-1])
# Elements at 90m depth should be somewht affected
self.assertNotEqual(o.elements.lat[0], o3.elements.lat[0])
# For second run, only elements below 50m should be equal
self.assertEqual(o2.elements.lat[1], o2.elements.lat[2])
self.assertNotEqual(o2.elements.lat[8], o2.elements.lat[9])
def test_lift_above_seafloor(self):
# See an element at some depth, and progapate towards coast
# (shallower water) and check that it is not penetrating seafloor
o = OceanDrift3D(loglevel=30, proj4='+proj=merc')
o.max_speed = 100
reader_norkyst = reader_netCDF_CF_generic.Reader(
o.test_data_folder() +
'14Jan2016_NorKyst_z_3d/NorKyst-800m_ZDEPTHS_his_00_3Dsubset.nc')
reader_norkyst.buffer = 200
o.add_reader([reader_norkyst],
variables='sea_floor_depth_below_sea_level')
o.fallback_values['x_sea_water_velocity'] = 100 # Pure eastward motion
o.fallback_values['y_sea_water_velocity'] = 0
o.fallback_values['land_binary_mask'] = 0
o.seed_elements(3.0, 62.0, z=-200, time=reader_norkyst.start_time)
o.set_config('processes:turbulentmixing', False)
o.run(steps=26, time_step=30)
seafloor_depth, status = o.get_property(
'sea_floor_depth_below_sea_level')
z, status = o.get_property('z')
# Uncomment to plot
#import matplotlib.pyplot as plt
#plt.plot(-seafloor_depth, label='Seafloor depth')
#plt.plot(z, label='Element depth')
#plt.legend(loc='best')
#plt.show()
# Check that element has not penetrated seafloor
self.assertFalse(
o.elements.z < -o.environment.sea_floor_depth_below_sea_level)
self.assertAlmostEqual(o.elements.z, -160.06, 1)
def test_lazy(self):
o = OceanDrift3D()
w = 'http://thredds.met.no/thredds/dodsC/meps25files/meps_det_pp_2_5km_20191128T06Z.nc'
o.add_readers_from_list([w], lazy=True) # Works if lazy=False
o.fallback_values['x_sea_water_velocity'] = .3
o.fallback_values['y_sea_water_velocity'] = .3
o.seed_elements(lon=4.6, lat=60, radius=1000, number=1000,
time=datetime(2019, 11, 28, 12))
print(o)
o.run(steps=1, outfile='test.nc') # Fails for Python3
assert os.path.exists('test.nc')
itime = []
dt = time[0]
while dt < time[-1]:
itime.append(dt)
dt += timedelta(hours=1)
ilon = np.interp([calendar.timegm(t.timetuple()) for t in itime],
[calendar.timegm(t.timetuple()) for t in time],
lon)
ilat = np.interp([calendar.timegm(t.timetuple()) for t in itime],
[calendar.timegm(t.timetuple()) for t in time],
lat)
lon = ilon
lat = ilat
time = itime
o = OceanDrift3D()
o.set_config('drift:stokes_drift', with_stokes)
o.max_speed = 5 # Due to future seeding!
del o.fallback_values['x_sea_water_velocity']
del o.fallback_values['y_sea_water_velocity']
del o.fallback_values['x_wind']
del o.fallback_values['y_wind']
# Forcing data
if forcing == 'norshelf':
# NB: waves only for 5 months of 2011
#waves = '/lustre/storeA/project/fou/om/retrospect/retrospect_data/waves/ECwave_%Y.nc'
current = 'http://thredds.met.no/thredds/dodsC/retrospect/qck/control_qck_%Y%m.ncml'
readerURL = time[0].strftime(current)
#!/usr/bin/env python
from opendrift.readers import reader_netCDF_CF_generic
from opendrift.models.oceandrift3D import OceanDrift3D
o = OceanDrift3D(loglevel=0) # Set loglevel to 0 for debug information
# Arome
reader_arome = reader_netCDF_CF_generic.Reader(
'http://thredds.met.no/thredds/dodsC/meps25files/meps_det_extracted_2_5km_latest.nc'
)
# Norkyst
reader_norkyst = reader_netCDF_CF_generic.Reader(
'http://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be')
o.add_reader([reader_norkyst, reader_arome])
# Seeding some particles
lon = 4.8
lat = 60.0
# Outside Bergen
time = None
time = reader_arome.start_time
# Seed elements at defined position and time
import numpy as np
z = -np.random.rand(1000) * 50 # Giving elements a random depth
o.seed_elements(lon, lat, z=z, radius=0, number=1000, time=time)