def test_update_from_dict(self):
gmap = GnomeMap()
json_ = {'map_bounds': [(-10, 10), (10, 10), (10, -10), (-10, -10)]}
assert np.all(gmap.map_bounds != json_['map_bounds'])
gmap.update_from_dict(json_)
assert np.all(gmap.map_bounds == json_['map_bounds'])
def test_new_from_dict(self, json_):
context = json_['json_']
dict_ = GnomeMap.deserialize(json_)
gmap = GnomeMap.new_from_dict(dict_)
u_json_ = gmap.serialize(context)
for key in json_:
assert u_json_[key] == json_[key]
def test_new_from_dict(self, json_):
context = json_['json_']
dict_ = GnomeMap.deserialize(json_)
gmap = GnomeMap.new_from_dict(dict_)
u_json_ = gmap.serialize(context)
for key in json_:
assert u_json_[key] == json_[key]
def test_update_from_dict(self):
gmap = GnomeMap()
json_ = gmap.serialize('save')
json_['map_bounds'] = [(-10, 10), (10, 10),
(10, -10), (-10, -10)]
dict_ = gnome.map.GnomeMap.deserialize(json_)
gmap.update_from_dict(dict_)
u_json_ = gmap.serialize('save')
for key in json_:
assert u_json_[key] == json_[key]
def test_on_map_array(self):
"""
a little bit more complex tests
and test of arrays of points
"""
# a concave map boundary
map_bounds = ((-40.0, 50.0), (-40.0, 58.0), (-30.0, 58.0),
(-35.0, 53.0), (-30.0, 50.0))
gmap = GnomeMap(map_bounds=map_bounds)
points = ((-35, 55, 0.), (-45, 55, 0.))
result = gmap.on_map(points)
# some points on the map:
assert np.array_equal(result, (True, False))
def test_on_map_array(self):
"""
a little bit more complex tests
and test of arrays of points
"""
# a concave map boundary
map_bounds = ((-40.0, 50.0), (-40.0, 58.0), (-30.0, 58.0),
(-35.0, 53.0), (-30.0, 50.0))
gmap = GnomeMap(map_bounds=map_bounds)
points = ((-35, 55, 0.), (-45, 55, 0.))
result = gmap.on_map(points)
# some points on the map:
assert np.array_equal(result, (True, False))
def test_on_map(self):
gmap = GnomeMap()
assert gmap.on_map((0., 0., 0.)) is True
# too big latitude
print gmap.on_map((0., 91.0, 0.))
assert gmap.on_map((0., 91.0, 0.)) is False
# too small latitude
assert gmap.on_map((0., -91.0, 0.)) is False
# too big langitude
assert gmap.on_map((0., 361.0, 0.)) is False
# too small langitude
assert gmap.on_map((0., -361.0, 0.)) is False
def test_on_map(self):
gmap = GnomeMap()
assert gmap.on_map((0., 0., 0.)) is True
# too big latitude
print gmap.on_map((0., 91.0, 0.))
assert gmap.on_map((0., 91.0, 0.)) is False
# too small latitude
assert gmap.on_map((0., -91.0, 0.)) is False
# too big langitude
assert gmap.on_map((0., 361.0, 0.)) is False
# too small langitude
assert gmap.on_map((0., -361.0, 0.)) is False
def test_update_from_dict(self):
gmap = GnomeMap()
json_ = gmap.serialize('save')
json_['map_bounds'] = [(-10, 10), (10, 10), (10, -10), (-10, -10)]
dict_ = gnome.map.GnomeMap.deserialize(json_)
gmap.update_from_dict(dict_)
u_json_ = gmap.serialize('save')
for key in json_:
assert u_json_[key] == json_[key]
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
# set up the modeling environment
start_time = datetime(2016, 9, 18, 1, 0)
model = Model(start_time=start_time,
duration=timedelta(days=3),
time_step=30 * 60,
uncertain=False)
print 'adding the map'
model.map = GnomeMap() # this is a "water world -- no land anywhere"
# renderere is only top-down view on 2d -- but it's something
renderer = Renderer(
output_dir=images_dir,
size=(1024, 768),
output_timestep=timedelta(hours=1),
)
renderer.viewport = ((-87.095, 27.595), (-87.905, 28.405))
print 'adding outputters'
model.outputters += renderer
# Also going to write the results out to a netcdf file
netcdf_file = os.path.join(base_dir, 'gulf_tamoc.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(
netcdf_file,
which_data='most',
# output most of the data associated with the elements
output_timestep=timedelta(hours=2))
print "adding Horizontal and Vertical diffusion"
# Horizontal Diffusion
model.movers += RandomMover(diffusion_coef=100000)
# vertical diffusion (different above and below the mixed layer)
model.movers += RandomVerticalMover(
vertical_diffusion_coef_above_ml=50,
vertical_diffusion_coef_below_ml=10,
horizontal_diffusion_coef_above_ml=100000,
horizontal_diffusion_coef_below_ml=100,
mixed_layer_depth=10)
print 'adding Rise Velocity'
# droplets rise as a function of their density and radius
model.movers += TamocRiseVelocityMover()
print 'adding the 3D current mover'
gc = GridCurrent.from_netCDF('HYCOM_3d.nc')
model.movers += GridCurrentMover('HYCOM_3d.nc')
# model.movers += SimpleMover(velocity=(0., 0, 0.))
# model.movers += constant_wind_mover(5, 315, units='knots')
# Wind from a buoy
w = Wind(filename='KIKT.osm')
model.movers += WindMover(w)
# Now to add in the TAMOC "spill"
print "Adding TAMOC spill"
model.spills += tamoc_spill.TamocSpill(
release_time=start_time,
start_position=(-87.5, 28.0, 2000),
num_elements=30000,
end_release_time=start_time + timedelta(days=2),
name='TAMOC plume',
TAMOC_interval=None, # how often to re-run TAMOC
)
model.spills[0].data_sources['currents'] = gc
return model
def get_gnomemap():
return GnomeMap(map_bounds=((10, 10), (15, 10), (15, 15), (10, 15)),
spillable_area=((11, 11), (14, 11), (14, 14), (11, 14)),
land_polys=None,
name="Test Map for TideflatMap")
def test_allowable_spill_position(self):
gmap = GnomeMap()
assert gmap.allowable_spill_position((18.0, -87.0, 0.)) is True
assert gmap.allowable_spill_position((370.0, -87.0, 0.)) is False
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
# set up the modeling environment
start_time = datetime(2004, 12, 31, 13, 0)
model = Model(start_time=start_time,
duration=timedelta(days=3),
time_step=30 * 60,
uncertain=False)
print 'adding the map'
model.map = GnomeMap() # this is a "water world -- no land anywhere"
# renderere is only top-down view on 2d -- but it's something
renderer = Renderer(
output_dir=images_dir,
size=(1024, 768),
output_timestep=timedelta(hours=1),
)
renderer.viewport = ((-.15, -.35), (.15, .35))
print 'adding outputters'
model.outputters += renderer
# Also going to write the results out to a netcdf file
netcdf_file = os.path.join(base_dir, 'script_plume.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(
netcdf_file,
which_data='most',
# output most of the data associated with the elements
output_timestep=timedelta(hours=2))
print "adding Horizontal and Vertical diffusion"
# Horizontal Diffusion
# model.movers += RandomMover(diffusion_coef=5)
# vertical diffusion (different above and below the mixed layer)
model.movers += RandomVerticalMover(vertical_diffusion_coef_above_ml=5,
vertical_diffusion_coef_below_ml=.11,
mixed_layer_depth=10)
print 'adding Rise Velocity'
# droplets rise as a function of their density and radius
model.movers += RiseVelocityMover()
print 'adding a circular current and eastward current'
# This is .3 m/s south
model.movers += PyCurrentMover(current=vg,
default_num_method='Trapezoid',
extrapolate=True)
model.movers += SimpleMover(velocity=(0., -0.1, 0.))
# Now to add in the TAMOC "spill"
print "Adding TAMOC spill"
model.spills += tamoc_spill.TamocSpill(
release_time=start_time,
start_position=(0, 0, 1000),
num_elements=1000,
end_release_time=start_time + timedelta(days=1),
name='TAMOC plume',
TAMOC_interval=None, # how often to re-run TAMOC
)
return model
def test_in_water(self):
gmap = GnomeMap()
assert gmap.in_water((18.0, -87.0, 0.))
assert gmap.in_water((370.0, -87.0, 0.)) is False
def test_on_land(self):
gmap = GnomeMap()
assert gmap.on_land((18.0, -87.0, 0.)) is False
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
# set up the modeling environment
start_time = datetime(2016, 9, 23, 0, 0)
model = Model(start_time=start_time,
duration=timedelta(days=2),
time_step=30 * 60,
uncertain=False)
print 'adding the map'
model.map = GnomeMap() # this is a "water world -- no land anywhere"
# renderere is only top-down view on 2d -- but it's something
renderer = Renderer(output_dir=images_dir,
image_size=(1024, 768),
output_timestep=timedelta(hours=1),
)
renderer.viewport = ((196.14, 71.89), (196.18, 71.93))
print 'adding outputters'
model.outputters += renderer
# Also going to write the results out to a netcdf file
netcdf_file = os.path.join(base_dir, 'script_arctic_plume.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file,
which_data='most',
# output most of the data associated with the elements
output_timestep=timedelta(hours=2))
print "adding Horizontal and Vertical diffusion"
# Horizontal Diffusion
model.movers += RandomMover(diffusion_coef=500)
# vertical diffusion (different above and below the mixed layer)
model.movers += RandomMover3D(vertical_diffusion_coef_above_ml=5,
vertical_diffusion_coef_below_ml=.11,
mixed_layer_depth=10)
print 'adding Rise Velocity'
# droplets rise as a function of their density and radius
model.movers += TamocRiseVelocityMover()
print 'adding a circular current and eastward current'
fn = 'hycom_glb_regp17_2016092300_subset.nc'
fn_ice = 'hycom-cice_ARCu0.08_046_2016092300_subset.nc'
iconc = IceConcentration.from_netCDF(filename=fn_ice)
ivel = IceVelocity.from_netCDF(filename=fn_ice, grid = iconc.grid)
ic = IceAwareCurrent.from_netCDF(ice_concentration = iconc, ice_velocity= ivel, filename=fn)
model.movers += PyCurrentMover(current = ic)
model.movers += SimpleMover(velocity=(0., 0., 0.))
model.movers += constant_wind_mover(20, 315, units='knots')
# Now to add in the TAMOC "spill"
print "Adding TAMOC spill"
model.spills += tamoc_spill.TamocSpill(release_time=start_time,
start_position=(196.16, 71.91, 40.0),
num_elements=1000,
end_release_time=start_time + timedelta(days=1),
name='TAMOC plume',
TAMOC_interval=None, # how often to re-run TAMOC
)
model.spills[0].data_sources['currents'] = ic
return model
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2004, 12, 31, 13, 0)
model = Model(start_time=start_time,
duration=timedelta(days=3),
time_step=30 * 60,
uncertain=False)
print 'adding the map'
model.map = GnomeMap()
# draw_ontop can be 'uncertain' or 'forecast'
# 'forecast' LEs are in black, and 'uncertain' are in red
# default is 'forecast' LEs draw on top
renderer = Renderer(
output_dir=images_dir,
# size=(800, 600),
output_timestep=timedelta(hours=1),
draw_ontop='uncertain')
renderer.viewport = ((-76.5, 37.), (-75.8, 38.))
print 'adding outputters'
model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'script_plume.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file,
which_data='most',
output_timestep=timedelta(hours=2))
print 'adding two spills'
# Break the spill into two spills, first with the larger droplets
# and second with the smaller droplets.
# Split the total spill volume (100 m^3) to have most
# in the larger droplet spill.
# Smaller droplets start at a lower depth than larger
wd = WeibullDistribution(alpha=1.8, lambda_=.00456,
min_=.0002) # 200 micron min
end_time = start_time + timedelta(hours=24)
# spill = point_line_release_spill(num_elements=10,
# amount=90, # default volume_units=m^3
# units='m^3',
# start_position=(-76.126872, 37.680952,
# 1700),
# release_time=start_time,
# end_release_time=end_time,
# element_type=plume(distribution=wd,
# density=600)
# )
spill = subsurface_plume_spill(
num_elements=10,
start_position=(-76.126872, 37.680952, 1700),
release_time=start_time,
distribution=wd,
amount=90, # default volume_units=m^3
units='m^3',
end_release_time=end_time,
density=600)
model.spills += spill
wd = WeibullDistribution(alpha=1.8, lambda_=.00456,
max_=.0002) # 200 micron max
spill = point_line_release_spill(
num_elements=10,
amount=90,
units='m^3',
start_position=(-76.126872, 37.680952, 1800),
release_time=start_time,
element_type=plume(distribution=wd, substance_name='oil_crude'))
model.spills += spill
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=50000)
print 'adding a RiseVelocityMover:'
model.movers += RiseVelocityMover()
print 'adding a RandomVerticalMover:'
model.movers += RandomVerticalMover(vertical_diffusion_coef_above_ml=5,
vertical_diffusion_coef_below_ml=.11,
mixed_layer_depth=10)
# print 'adding a wind mover:'
# series = np.zeros((2, ), dtype=gnome.basic_types.datetime_value_2d)
# series[0] = (start_time, (30, 90))
# series[1] = (start_time + timedelta(hours=23), (30, 90))
# wind = Wind(timeseries=series, units='knot')
#
# default is .4 radians
# w_mover = gnome.movers.WindMover(wind, uncertain_angle_scale=0)
#
# model.movers += w_mover
print 'adding a simple mover:'
s_mover = SimpleMover(velocity=(0.0, -.3, 0.0))
model.movers += s_mover
return model
def test_on_land(self):
gmap = GnomeMap()
assert gmap.on_land((18.0, -87.0, 0.)) is False
def test_allowable_spill_position(self):
gmap = GnomeMap()
assert gmap.allowable_spill_position((18.0, -87.0, 0.)) is True
assert gmap.allowable_spill_position((370.0, -87.0, 0.)) is False
def test_in_water(self):
gmap = GnomeMap()
assert gmap.in_water((18.0, -87.0, 0.))
assert gmap.in_water((370.0, -87.0, 0.)) is False
