def test_exceptions():
"""
Test ValueError exception thrown if improper input arguments
"""
with pytest.raises(ValueError):
RandomMover(diffusion_coef=-1000)
with pytest.raises(ValueError):
RandomMover(uncertain_factor=0)
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2012, 9, 15, 12, 0)
mapfile = get_datafile(os.path.join(base_dir, './LongIslandSoundMap.BNA'))
gnome_map = MapFromBNA(mapfile, refloat_halflife=6) # hours
# # the image output renderer
# global renderer
# one hour timestep
model = Model(start_time=start_time,
duration=timedelta(hours=48),
time_step=3600,
map=gnome_map,
uncertain=True,
cache_enabled=True)
netcdf_file = os.path.join(base_dir, 'script_long_island.nc')
scripting.remove_netcdf(netcdf_file)
print 'adding outputters'
model.outputters += Renderer(mapfile, images_dir, size=(800, 600))
model.outputters += NetCDFOutput(netcdf_file, which_data='all')
print 'adding a spill'
spill = point_line_release_spill(num_elements=1000,
start_position=(-72.419992, 41.202120,
0.0),
release_time=start_time)
model.spills += spill
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=500000, uncertain_factor=2)
print 'adding a wind mover:'
series = np.zeros((5, ), dtype=datetime_value_2d)
series[0] = (start_time, (10, 45))
series[1] = (start_time + timedelta(hours=18), (10, 90))
series[2] = (start_time + timedelta(hours=30), (10, 135))
series[3] = (start_time + timedelta(hours=42), (10, 180))
series[4] = (start_time + timedelta(hours=54), (10, 225))
wind = Wind(timeseries=series, units='m/s')
model.movers += WindMover(wind)
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, r"./LI_tidesWAC.CUR"))
tide_file = get_datafile(os.path.join(base_dir, r"./CLISShio.txt"))
c_mover = CatsMover(curr_file, tide=Tide(tide_file))
model.movers += c_mover
model.environment += c_mover.tide
print 'viewport is:', [
o.viewport for o in model.outputters if isinstance(o, Renderer)
]
return model
def allWeatherers(timeStep, start_time, duration, weatheringSteps, map, uncertain, data_path, curr_path, wind_path, map_path, reFloatHalfLife, windFile, currFile, tidalFile, num_elements, depths, lat, lon, output_path, wind_scale, save_nc, timestep_outputs, weatherers, td):
print 'initializing the model:'
model = Model(time_step=timeStep, start_time=start_time, duration=duration)
print 'adding the map:'
map_folder = os.path.join(data_path, map_path)
if not(os.path.exists(map_folder)):
print('The map folder is incorrectly set:', map_folder)
mapfile = get_datafile( os.path.join(map_folder,map) )
model.map = MapFromBNA(mapfile, refloat_halflife=reFloatHalfLife)
print 'adding a renderer'
model.outputters += Renderer(mapfile, output_path, size=(800, 600), output_timestep=timedelta(hours=1))
if save_nc:
nc_outputter = NetCDFOutput(netcdf_file, which_data='most', output_timestep=timedelta(hours=1))
model.outputters += nc_outputter
print 'adding a wind mover:'
wind_file = get_datafile(os.path.join(data_path, wind_path, windFile))
wind = GridWindMover(wind_file)
wind.wind_scale = wind_scale
model.movers += wind
print 'adding a current mover: '
curr_file = get_datafile(os.path.join(data_path, curr_path, currFile))
model.movers += GridCurrentMover(curr_file, num_method='RK4')
if td:
random_mover = RandomMover(diffusion_coef=10000)
model.movers += random_mover
print 'adding spill'
model.spills += point_line_release_spill(num_elements=num_elements, start_position=(lon, lat, 0), release_time=start_time, end_release_time=start_time + duration)
print 'adding weatherers'
water = Water(280.92)
wind = constant_wind(20.0, 117, 'knots')
waves = Waves(wind, water)
model.weatherers += Evaporation(water, wind)
model.weatherers += Emulsification(waves)
model.weatherers += NaturalDispersion(waves, water)
return model
def model(sample_model_fcn, output_filename):
"""
Use fixture model_surface_release_spill and add a few things to it for the
test
"""
model = sample_model_fcn['model']
model.cache_enabled = True
model.spills += \
point_line_release_spill(num_elements=5,
start_position=sample_model_fcn['release_start_pos'],
release_time=model.start_time,
end_release_time=model.start_time + model.duration,
substance=test_oil,
amount=1000,
units='kg')
water = Water()
model.movers += RandomMover(diffusion_coef=100000)
model.movers += constant_wind_mover(1.0, 0.0)
model.weatherers += Evaporation(water=water, wind=model.movers[-1].wind)
model.outputters += NetCDFOutput(output_filename)
model.rewind()
return model
def setup_model():
print 'initializing the model'
# start with default time,duration...this will be changed when model is run
model = Model(
) #change to use all defaults and set time_step also in Setup_TAP!!
mapfile = os.path.join(setup.MapFileDir, setup.MapFileName)
print 'adding the map: ', mapfile
model.map = MapFromBNA(mapfile, refloat_halflife=0.0) # seconds
print 'adding a GridCurrentMover:'
c_mover = GridCurrentMover(filename=setup.curr_fn, extrapolate=True)
model.movers += c_mover
print 'adding a WindMover:'
w = Wind(filename=setup.wind_fn)
w_mover = WindMover(w)
# w_mover = GridWindMover(wind_file=setup.w_filelist)
model.movers += w_mover
if setup.diff_coef is not None:
print 'adding a RandomMover:'
random_mover = RandomMover(diffusion_coef=setup.diff_coef) #in cm/s
model.movers += random_mover
return model
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2015, 9, 24, 3, 0)
# 1 day of data in file
# 1/2 hr in seconds
model = Model(start_time=start_time,
duration=timedelta(hours = 48),
time_step=3600)
mapfile = get_datafile(os.path.join(base_dir, 'Perfland.bna'))
print 'adding the map'
model.map = MapFromBNA(mapfile, refloat_halflife=1, raster_size=1024*1024) # seconds
# 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(mapfile, images_dir, image_size=(800, 600),
output_timestep=timedelta(hours=1),
timestamp_attrib={'size': 'medium', 'color':'uncert_LE'})
renderer.set_timestamp_attrib(format='%a %c')
renderer.graticule.set_DMS(True)
# renderer.viewport = ((-124.25, 47.5), (-122.0, 48.70))
print 'adding outputters'
model.outputters += renderer
print 'adding a spill'
# for now subsurface spill stays on initial layer
# - will need diffusion and rise velocity
# - wind doesn't act
# - start_position = (-76.126872, 37.680952, 5.0),
spill1 = point_line_release_spill(num_elements=5000,
start_position=(0.0,
0.0,
0.0),
release_time=start_time)
model.spills += spill1
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=50000)
print 'adding a wind mover:'
model.movers += constant_wind_mover(13, 270, units='m/s')
print 'adding a current mover:'
# curr_file = get_datafile(os.path.join(base_dir, 'COOPSu_CREOFS24.nc'))
#
# # uncertain_time_delay in hours
# c_mover = GridCurrentMover(curr_file)
# c_mover.uncertain_cross = 0 # default is .25
#
# model.movers += c_mover
return model
def CurrentsAndWinds(timeStep, start_time, duration, weatheringSteps, mapfile, uncertain, data_path, curr_path, wind_path, map_path, reFloatHalfLife, windFile, currFile, tidalFile, num_elements, depths, lat, lon, output_path, wind_scale, save_nc, timestep_outputs, weatherers, td):
print 'initializing the model:'
model = Model(time_step=timeStep, start_time=start_time, duration=duration)
print 'adding the map:'
print (data_path, map_path, mapfile)
mapfile = get_datafile(os.path.join(data_path, map_path, mapfile))
model.map = MapFromBNA(mapfile, refloat_halflife=reFloatHalfLife)
print 'adding a renderer'
model.outputters += Renderer(mapfile, output_path, size=(800, 600), output_timestep=timedelta(hours=timestep_outputs))
if save_nc:
nc_outputter = NetCDFOutput('currentsAndWinds_example.nc', which_data='standard', output_timestep=timedelta(hours=timestep_outputs))
model.outputters += nc_outputter
print 'adding a wind mover:'
wind_file = get_datafile(os.path.join(data_path, wind_path, windFile))
wind = GridWindMover(wind_file)
wind.wind_scale = wind_scale
model.movers += wind
print 'adding a current mover: '
curr_file = get_datafile(os.path.join(data_path, curr_path, currFile))
model.movers += GridCurrentMover(curr_file, num_method='RK4')
if td:
random_mover = RandomMover(diffusion_coef=10000)
model.movers += random_mover
print 'adding spill'
model.spills += point_line_release_spill(num_elements=num_elements, start_position=(lon, lat, 0), release_time=start_time, end_release_time=start_time + duration)
return model
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2012, 10, 25, 0, 1)
# start_time = datetime(2015, 12, 18, 06, 01)
# 1 day of data in file
# 1/2 hr in seconds
model = Model(start_time=start_time,
duration=timedelta(hours=6),
time_step=900)
mapfile = get_datafile(os.path.join(base_dir, 'nyharbor.bna'))
print 'adding the map'
'''TODO: sort out MapFromBna's map_bounds parameter...
it does nothing right now, and the spill is out of bounds'''
model.map = MapFromBNA(mapfile, refloat_halflife=0.0) # seconds
# 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(mapfile, images_dir, image_size=(1024, 768))
# renderer.viewport = ((-73.5, 40.5), (-73.1, 40.75))
# renderer.viewport = ((-122.9, 45.6), (-122.6, 46.0))
print 'adding outputters'
model.outputters += renderer
print 'adding a spill'
# for now subsurface spill stays on initial layer
# - will need diffusion and rise velocity
# - wind doesn't act
# - start_position = (-76.126872, 37.680952, 5.0),
spill1 = point_line_release_spill(num_elements=1000,
start_position=(-74.15, 40.5, 0.0),
release_time=start_time)
model.spills += spill1
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=50000)
print 'adding a wind mover:'
model.movers += constant_wind_mover(4, 270, units='m/s')
print 'adding a current mover:'
# url is broken, fix and include the following section
# url = ('http://geoport.whoi.edu/thredds/dodsC/clay/usgs/users/jcwarner/Projects/Sandy/triple_nest/00_dir_NYB05.ncml')
# # cf = roms_field('nos.tbofs.fields.n000.20160406.t00z_sgrid.nc')
# cf = GridCurrent.from_netCDF(url)
# renderer.add_grid(cf.grid)
# renderer.delay = 25
# u_mover = PyCurrentMover(cf, default_num_method='Euler')
# model.movers += u_mover
#
return model
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'creating the maps'
mapfile = get_datafile(os.path.join(base_dir, 'LowerMississippiMap.bna'))
gnome_map = MapFromBNA(mapfile, refloat_halflife=6) # hours
print 'initializing the model'
start_time = datetime(2012, 9, 15, 12, 0)
# default to now, rounded to the nearest hour
model = Model(time_step=600,
start_time=start_time,
duration=timedelta(days=1),
map=gnome_map,
uncertain=True)
print 'adding outputters'
model.outputters += Renderer(mapfile, images_dir, image_size=(800, 600))
netcdf_file = os.path.join(base_dir, 'script_lower_mississippi.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file, which_data='all')
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=10000)
print 'adding a wind mover:'
series = np.zeros((5, ), dtype=datetime_value_2d)
series[0] = (start_time, (2, 45))
series[1] = (start_time + timedelta(hours=18), (2, 90))
series[2] = (start_time + timedelta(hours=30), (2, 135))
series[3] = (start_time + timedelta(hours=42), (2, 180))
series[4] = (start_time + timedelta(hours=54), (2, 225))
w_mover = WindMover(Wind(timeseries=series, units='m/s'))
model.movers += w_mover
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, 'LMiss.CUR'))
c_mover = CatsMover(curr_file)
# but do need to scale (based on river stage)
c_mover.scale = True
c_mover.scale_refpoint = (-89.699944, 29.494558)
# based on stage height 10ft (range is 0-18)
c_mover.scale_value = 1.027154
model.movers += c_mover
print 'adding a spill'
spill = point_line_release_spill(num_elements=1000,
start_position=(-89.699944, 29.494558,
0.0),
release_time=start_time)
model.spills += spill
return model
def test_to_dict(self, json_):
'added a to_dict() method - test this method'
items = [SimpleMover(velocity=(i * 0.5, -1.0, 0.0)) for i in range(2)]
items.extend([RandomMover() for i in range(2)])
mymovers = OrderedCollection(items, dtype=Mover)
self._to_dict_assert(mymovers, items, json_)
class TestRandomMover:
"""
gnome.RandomMover() test
"""
num_le = 5
# start_pos = np.zeros((num_le,3), dtype=basic_types.world_point_type)
start_pos = (0., 0., 0.)
rel_time = datetime.datetime(2012, 8, 20, 13) # yyyy/month/day/hr/min/sec
model_time = sec_to_date(date_to_sec(rel_time) + 1)
time_step = 15 * 60 # seconds
mover = RandomMover()
def reset_pos(self):
self.pSpill['positions'] = (0., 0., 0.)
print self.pSpill['positions']
def test_string_representation_matches_repr_method(self):
"""
Just print repr and str
"""
print
print repr(self.mover)
print str(self.mover)
assert True
def test_id_matches_builtin_id(self):
# It is not a good assumption that the obj.id property
# will always contain the id(obj) value. For example it could
# have been overloaded with, say, a uuid1() generator.
# assert id(self.mover) == self.mover.id
pass
def test_change_diffusion_coef(self):
self.mover.diffusion_coef = 200000
assert self.mover.diffusion_coef == 200000
def test_change_uncertain_factor(self):
self.mover.uncertain_factor = 3
assert self.mover.uncertain_factor == 3
def test_prepare_for_model_step(self):
"""
Simply tests the method executes without exceptions
"""
pSpill = sample_sc_release(self.num_le, self.start_pos)
self.mover.prepare_for_model_step(pSpill, self.time_step,
self.model_time)
assert True
def make_models():
print 'initializing the model'
# start_time = datetime(2015, 12, 18, 06, 01)
# 1 day of data in file
# 1/2 hr in seconds
models = []
start_time = datetime(2012, 10, 27, 0, 30)
duration_hrs=23
time_step=450
num_steps = duration_hrs * 3600 / time_step
names = [
'Euler',
'Trapezoid',
'RK4',
]
mapfile = get_datafile(os.path.join(base_dir, 'long_beach.bna'))
print 'gen map'
map = MapFromBNA(mapfile, refloat_halflife=0.0) # seconds
fn = ('00_dir_roms_display.ncml.nc4')
curr = GridCurrent.from_netCDF(filename=fn)
models = []
for method in names:
mod = Model(start_time=start_time,
duration=timedelta(hours=duration_hrs),
time_step=time_step)
mod.map = map
spill = point_line_release_spill(num_elements=1000,
start_position=(-74.1,
39.7525,
0.0),
release_time=start_time)
mod.spills += spill
mod.movers += RandomMover(diffusion_coef=100)
mod.movers += PyGridCurrentMover(current=curr, default_num_method=method)
images_dir = method + '-' + str(time_step / 60) + 'min-' + str(num_steps) + 'steps'
renderer = Renderer(mapfile, images_dir, image_size=(1024, 768))
renderer.delay = 25
# renderer.add_grid(curr.grid)
mod.outputters += renderer
netCDF_fn = os.path.join(base_dir, images_dir + '.nc')
mod.outputters += NetCDFOutput(netCDF_fn, which_data='all')
models.append(mod)
print 'returning models'
return models
def test_full_run(self):
'just check that all data arrays work correctly'
s = Spill(InitElemsFromFile(testdata['nc']['nc_output']))
model = Model(start_time=s.release_time,
time_step=self.time_step.total_seconds(),
duration=timedelta(days=2))
model.spills += s
model.movers += RandomMover()
# setup model run
for step in model:
if step['step_num'] == 0:
continue
for sc in model.spills.items():
for key in sc.data_arrays.keys():
# following keys will not change with run
if key in ('status_codes', 'mass', 'init_mass', 'id',
'spill_num',
'last_water_positions'): # all water map
assert np.all(sc[key] == s.release._init_data[key])
def make_model(images_dir):
print 'initializing the model'
timestep = timedelta(minutes=15) # this is already default
start_time = datetime(2012, 9, 15, 12, 0)
model = Model(timestep, start_time)
# timeseries for wind data. The value is interpolated if time is between
# the given datapoints
series = np.zeros((4, ), dtype=datetime_value_2d)
series[:] = [(start_time, (5, 180)),
(start_time + timedelta(hours=6), (10, 180)),
(start_time + timedelta(hours=12), (12, 180)),
(start_time + timedelta(hours=18), (8, 180))]
wind = Wind(timeseries=series, units='m/s')
model.environment += wind
# include a wind mover and random diffusion
print 'adding movers'
model.movers += [WindMover(wind), RandomMover()]
# add particles
print 'adding particles'
release = release_from_splot_data(start_time,
'GL.2013267._LE_WHOLELAKE.txt')
model.spills += Spill(release)
# output data as png images and in netcdf format
print 'adding outputters'
netcdf_file = os.path.join(base_dir, 'script_example.nc')
# ignore renderer for now
model.outputters += [
Renderer(images_dir=images_dir,
size=(800, 800),
projection_class=GeoProjection),
NetCDFOutput(netcdf_file)
]
print 'model complete'
return model
def test_random_mover():
"""
Make sure diffusion doesn't move the LEs marked as on_tideflat
"""
start_time = datetime(2012, 11, 10, 0)
sc = sample_sc_release(10, (0.0, 0.0, 0.0), start_time)
D = 100000
rand = RandomMover(diffusion_coef=D)
model_time = start_time
time_step = 1000 # quite random
sc.release_elements(time_step, model_time)
print "status codes"
print sc['status_codes']
delta = run_one_timestep(sc, rand, time_step, model_time)
print "delta:", delta
assert np.all(delta[:, 0] != 0.0)
assert np.all(delta[:, 1] != 0.0)
assert np.all(delta[:, 2] == 0.0)
# now set the on_tideflat code on half the elements
sc['status_codes'][5:] = oil_status.on_tideflat
delta = run_one_timestep(sc, rand, time_step, model_time)
# only the first 5 should move
assert np.all(delta[:5, 0] != 0.0)
assert np.all(delta[:5, 1] != 0.0)
assert np.all(delta[5:, 0] == 0.0)
assert np.all(delta[5:, 1] == 0.0)
# no change to depth
assert np.all(delta[:, 2] == 0.0)
def test_serialize_deserialize(json_, output_filename):
'''
todo: this behaves in unexpected ways when using the 'model' testfixture.
For now, define a model in here for the testing - not sure where the
problem lies
'''
s_time = datetime(2014, 1, 1, 1, 1, 1)
model = Model(start_time=s_time)
model.spills += point_line_release_spill(num_elements=5,
start_position=(0, 0, 0),
release_time=model.start_time)
o_put = NetCDFOutput(output_filename)
model.outputters += o_put
model.movers += RandomMover(diffusion_coef=100000)
# ==========================================================================
# o_put = [model.outputters[outputter.id]
# for outputter in model.outputters
# if isinstance(outputter, NetCDFOutput)][0]
# ==========================================================================
model.rewind()
print "step: {0}, _start_idx: {1}".format(-1, o_put._start_idx)
for ix in range(2):
model.step()
print "step: {0}, _start_idx: {1}".format(ix, o_put._start_idx)
dict_ = o_put.deserialize(o_put.serialize(json_))
o_put2 = NetCDFOutput.new_from_dict(dict_)
if json_ == 'save':
assert o_put == o_put2
else:
# _start_idx and _middle_of_run should not match
assert o_put._start_idx != o_put2._start_idx
assert o_put._middle_of_run != o_put2._middle_of_run
assert o_put != o_put2
if os.path.exists(o_put.netcdf_filename):
print '\n{0} exists'.format(o_put.netcdf_filename)
def test_variance1(start_loc, time_step):
"""
After a few timesteps the variance of the particle positions should be
similar to the computed value: var = Dt
"""
num_le = 1000
start_time = datetime.datetime(2012, 11, 10, 0)
sc = sample_sc_release(num_le, start_loc, start_time)
D = 100000
num_steps = 10
rand = RandomMover(diffusion_coef=D)
model_time = start_time
for i in range(num_steps):
model_time += datetime.timedelta(seconds=time_step)
sc.release_elements(time_step, model_time)
rand.prepare_for_model_step(sc, time_step, model_time)
delta = rand.get_move(sc, time_step, model_time)
# print "delta:", delta
sc['positions'] += delta
# print sc['positions']
# compute the variances:
# convert to meters
pos = FlatEarthProjection.lonlat_to_meters(sc['positions'], start_loc)
var = np.var(pos, axis=0)
# D converted to meters^s/s
expected = 2.0 * (D * 1e-4) * num_steps * time_step
assert np.allclose(var, (expected, expected, 0.), rtol=0.1)
def make_model():
duration_hrs = 48
time_step = 900
num_steps = duration_hrs * 3600 / time_step
mod = Model(start_time=t,
duration=timedelta(hours=duration_hrs),
time_step=time_step)
spill = point_line_release_spill(num_elements=1000,
amount=1600,
units='kg',
start_position=(0.5, 0.5, 0.0),
release_time=t,
end_release_time=t + timedelta(hours=4))
mod.spills += spill
method = 'Trapezoid'
images_dir = method + '-' + str(
time_step / 60) + 'min-' + str(num_steps) + 'steps'
renderer = Renderer(output_dir=images_dir, image_size=(800, 800))
renderer.delay = 5
renderer.add_grid(g)
renderer.add_vec_prop(vg)
renderer.graticule.set_max_lines(max_lines=0)
mod.outputters += renderer
mod.movers += PyCurrentMover(current=vg,
default_num_method=method,
extrapolate=True)
mod.movers += RandomMover(diffusion_coef=10)
netCDF_fn = os.path.join(base_dir, images_dir + '.nc')
mod.outputters += NetCDFOutput(netCDF_fn, which_data='all')
return mod
def make_modelF(timeStep, start_time, duration, weatheringSteps, map, uncertain, data_path, curr_path, wind_path, map_path, reFloatHalfLife, windFile, currFile, num_elements, depths, lat, lon, output_path, wind_scale, save_nc, timestep_outputs, weatherers, td, dif_coef,temp_water):
print 'initializing the model:'
model = Model(time_step=timeStep, start_time=start_time, duration=duration, uncertain=uncertain)
print 'adding the map:'
mapfile = get_datafile(os.path.join(data_path, map_path, map))
model.map = MapFromBNA(mapfile, refloat_halflife=reFloatHalfLife)
print 'adding a renderer'
if save_nc:
scripting.remove_netcdf(output_path+'/'+'output.nc')
nc_outputter = NetCDFOutput(output_path+'/'+'output.nc', which_data='standard', output_timestep=timedelta(hours=timestep_outputs))
model.outputters += nc_outputter
print 'adding a wind mover:'
wind_file = get_datafile(os.path.join(data_path, wind_path, windFile))
wind = GridWindMover(wind_file)
# wind.wind_scale = wind_scale
model.movers += wind
print 'adding a current mover:'
curr_file = get_datafile(os.path.join(data_path, curr_path, currFile))
model.movers += GridCurrentMover(curr_file, num_method='RK4')
if td:
random_mover = RandomMover(diffusion_coef=dif_coef)
model.movers += random_mover
print 'adding spill'
model.spills += point_line_release_spill(num_elements=num_elements, start_position=(lon, lat, 0), release_time=start_time, end_release_time=start_time + duration)#, substance='AD04001', amount=9600000, units='kg')
if weatherers:
print 'adding weatherers'
water = Water(temp_water)
wind = constant_wind(0.0001, 0, 'knots')
waves = Waves(wind, water)
model.weatherers += Evaporation(water, wind)
# model.weatherers += Emulsification(waves)
model.weatherers += NaturalDispersion(waves, water)
return model
def main(RootDir, Data_Dir, StartSite, RunSite, NumStarts, RunStarts,
ReleaseLength, TrajectoryRunLength, StartTimeFiles, TrajectoriesPath,
NumLEs, MapFileName, refloat, current_files, wind_files,
diffusion_coef, model_timestep, windage_range, windage_persist,
OutputTimestep):
timingRecord = open(os.path.join(RootDir, "timing.txt"), "w")
count = len(StartTimeFiles) * len(RunStarts)
timingRecord.write("This file tracks the time to process " + str(count) +
" gnome runs")
# model timing
release_duration = timedelta(hours=ReleaseLength)
run_time = timedelta(hours=TrajectoryRunLength)
# initiate model
model = Model(duration=run_time, time_step=model_timestep, uncertain=False)
# determine boundary for model
print "Adding the map:", MapFileName
mapfile = get_datafile(os.path.join(Data_Dir, MapFileName))
# model.map = MapFromBNA(mapfile, refloat_halflife=refloat) no, model map needs to inclde mudflats. later
# loop through seasons
for Season in StartTimeFiles:
timer1 = datetime.now()
SeasonName = Season[1]
start_times = open(Season[0], 'r').readlines()[:NumStarts]
SeasonTrajDir = os.path.join(RootDir, TrajectoriesPath, SeasonName)
if not os.path.isdir(SeasonTrajDir):
print "Creating directory: ", SeasonTrajDir
make_dir(SeasonTrajDir)
print " Season:", SeasonName
# get and parse start times in this season
start_dt = []
for start_time in start_times:
start_time = [int(i) for i in start_time.split(',')]
start_time = datetime(start_time[0], start_time[1], start_time[2],
start_time[3], start_time[4])
start_dt.append(start_time)
## loop through start times
for time_idx in RunStarts:
timer2 = datetime.now()
gc.collect()
model.movers.clear()
## set the start location
start_time = start_dt[time_idx]
end_time = start_time + run_time
model.start_time = start_time
print " ", start_time, "to", end_time
## get a list of the only data files needed for the start time (less data used)
## note: requires data files in year increments
#Todo: needs fixing before real run
years = range(start_time.year, end_time.year + 1)
years = [str(i) for i in years]
wind = [s for s in wind_files if any(xs in s for xs in years)]
current = [
s for s in current_files if any(xs in s for xs in years)
]
#Todo: add mudflats. Does it work like this?
topology = {'node_lon': 'x', 'node_lat': 'y'}
## add wind movers
w_mover = PyWindMover(filename=wind)
model.movers += w_mover
## add current movers
current_mover = gs.GridCurrent.from_netCDF(current,
grid_topology=topology)
c_mover = PyCurrentMover(current=current_mover)
model.movers += c_mover
tideflat = Matroos_Mudflats(current, grid_topology=topology)
land_map = gs.MapFromBNA(mapfile)
model.map = TideflatMap(land_map, tideflat)
## add diffusion
model.movers += RandomMover(diffusion_coef=diffusion_coef)
## loop through start locations
timer3 = datetime.now()
#Todo: can it deal with the test.location.txt file??
start_position = [float(i) for i in StartSite.split(',')]
OutDir = os.path.join(RootDir, TrajectoriesPath, SeasonName,
'pos_%03i' % (RunSite + 1))
make_dir(OutDir)
print " ", RunSite, time_idx
print " Running: start time:", start_time,
print "at start location:", start_position
## set the spill to the location
spill = surface_point_line_spill(
num_elements=NumLEs,
start_position=(start_position[0], start_position[1], 0.0),
release_time=start_time,
end_release_time=start_time + release_duration,
windage_range=windage_range,
windage_persist=windage_persist)
# print "adding netcdf output"
netcdf_output_file = os.path.join(
OutDir,
'pos_%03i-t%03i_%08i.nc' %
(RunSite + 1, time_idx, int(start_time.strftime('%y%m%d%H'))),
)
model.outputters.clear()
model.outputters += NetCDFOutput(
netcdf_output_file,
output_timestep=timedelta(hours=OutputTimestep))
model.spills.clear()
model.spills += spill
model.full_run(rewind=True)
timer4 = datetime.now()
diff = round((timer4 - timer3).total_seconds() / 60, 2)
timingRecord.write("\t\t" + str(RunSite) + " took " + str(diff) +
" minutes to complete")
diff = round((timer4 - timer1).total_seconds() / 3600, 2)
count = len(RunStarts)
timingRecord.write("\t" + str(SeasonName) + " took " + str(diff) +
" hours to finish " + str(count) + " Gnome runs")
#OutDir.close
timingRecord.close
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2015, 9, 24, 1, 1)
# start_time = datetime(2015, 12, 18, 06, 01)
# 1 day of data in file
# 1/2 hr in seconds
model = Model(start_time=start_time,
duration=timedelta(hours=47),
time_step=300)
mapfile = get_datafile(os.path.join(base_dir, 'columbia_river.bna'))
print 'adding the map'
model.map = MapFromBNA(mapfile, refloat_halflife=0.0) # seconds
# 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(mapfile, images_dir, image_size=(600, 1200))
renderer.delay = 15
# renderer.viewport = ((-123.35, 45.6), (-122.68, 46.13))
# renderer.viewport = ((-122.9, 45.6), (-122.6, 46.0))
print 'adding outputters'
model.outputters += renderer
print 'adding a spill'
# for now subsurface spill stays on initial layer
# - will need diffusion and rise velocity
# - wind doesn't act
# - start_position = (-76.126872, 37.680952, 5.0),
spill1 = continuous_release_spill(initial_elements=10000,
num_elements=400,
start_position=(-122.625, 45.609, 0.0),
release_time=start_time,
end_position=(-122.6, 45.605, 0.0),
end_release_time=start_time +
timedelta(seconds=36000))
model.spills += spill1
print 'adding a RandomMover:'
# model.movers += RandomMover(diffusion_coef=10000)
print 'adding a wind mover:'
series = []
for i in [(1, (5, 90)), (7, (5, 180)), (13, (5, 270)), (19, (5, 0)),
(25, (5, 90))]:
series.append((start_time + timedelta(hours=i[0]), i[1]))
wind1 = WindTS.constant_wind('wind1', 0.5, 0, 'm/s')
wind2 = WindTS(timeseries=series, units='knots', extrapolate=True)
# wind = Wind(timeseries=series, units='knots')
model.movers += PyWindMover(wind=wind1)
print 'adding a current mover:'
# url = ('http://geoport.whoi.edu/thredds/dodsC/clay/usgs/users/jcwarner/Projects/Sandy/triple_nest/00_dir_NYB05.ncml')
# test = GridCurrent.from_netCDF(name='gc1', filename=url)
curr_file = get_datafile('COOPSu_CREOFS24.nc')
curr = GridCurrent.from_netCDF(
name='gc2',
filename=curr_file,
)
c_mover = PyGridCurrentMover(curr,
extrapolate=True,
default_num_method='Trapezoid')
# renderer.add_grid(curr.grid)
# renderer.add_vec_prop(curr)
model.movers += c_mover
print 'adding a random mover'
model.movers += RandomMover(diffusion_coef=1000)
# curr_file = get_datafile(os.path.join(base_dir, 'COOPSu_CREOFS24.nc'))
# c_mover = GridCurrentMover(curr_file)
# model.movers += c_mover
return model
def make_model(images_dir=os.path.join(base_dir, 'images')):
# create the maps:
print 'creating the maps'
mapfile = get_datafile(os.path.join(base_dir, './MassBayMap.bna'))
gnome_map = MapFromBNA(
mapfile,
refloat_halflife=1, # hours
raster_size=2048 * 2048 # about 4 MB
)
renderer = Renderer(
mapfile,
images_dir,
image_size=(800, 800),
)
print 'initializing the model'
start_time = datetime(2016, 3, 9, 15)
# 1 hour in seconds
# Default to now, rounded to the nearest hour
model = Model(time_step=3600,
start_time=start_time,
duration=timedelta(days=6),
map=gnome_map,
uncertain=True)
print 'adding outputters'
model.outputters += renderer
# netcdf_file = os.path.join(base_dir, 'script_boston.nc')
# scripting.remove_netcdf(netcdf_file)
# model.outputters += NetCDFOutput(netcdf_file, which_data='all')
# model.outputters += KMZOutput(os.path.join(base_dir, 'script_boston.kmz'))
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=100000)
print 'adding a wind mover:'
series = np.zeros((2, ), dtype=datetime_value_2d)
series[0] = (start_time, (5, 180))
series[1] = (start_time + timedelta(hours=18), (5, 180))
w = Wind(filename=os.path.join(base_dir, '22NM_WNW_PortAngelesWA.nws'))
w_mover = WindMover(w)
model.movers += w_mover
model.environment += w_mover.wind
# print 'adding a cats shio mover:'
# curr_file = get_datafile(os.path.join(base_dir, r"./EbbTides.cur"))
# tide_file = get_datafile(os.path.join(base_dir, r"./EbbTidesShio.txt"))
# c_mover = CatsMover(curr_file, tide=Tide(tide_file))
# # this is the value in the file (default)
# c_mover.scale_refpoint = (-70.8875, 42.321333)
# c_mover.scale = True
# c_mover.scale_value = -1
# model.movers += c_mover
# # TODO: cannot add this till environment base class is created
# model.environment += c_mover.tide
print 'adding a spill'
end_time = start_time + timedelta(hours=12)
spill = point_line_release_spill(num_elements=100,
start_position=(-70.911432, 42.369142,
0.0),
release_time=start_time,
end_release_time=end_time)
model.spills += spill
return model
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
from gnome.movers import RandomMover
l_spills = [point_line_release_spill(10, (0, 0, 0),
datetime.now().replace(microsecond=0),
name='sp1'),
point_line_release_spill(15, (0, 0, 0),
datetime.now().replace(microsecond=0),
name='sp2'),
point_line_release_spill(20, (0, 0, 0),
datetime.now().replace(microsecond=0),
name='sp3'),
point_line_release_spill(5, (0, 0, 0),
datetime.now().replace(microsecond=0),
name='sp4')]
l_mv = [SimpleMover(velocity=(1, 2, 3)), RandomMover()]
def define_mdl(test=0):
'''
WebAPI will update/replace nested objects so do that for the test as well
Setup some test cases:
0 - empty model w/ no changes
1 - model with l_mv and l_spills but no changes
2 - empty model but add l_mv and l_spills to json_ so it changed
3 - add l_mv and l_spills to model, then delete some elements and update
via json
'''
def get_json(mdl):
json_ = mdl.serialize()
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2014, 6, 9, 0, 0)
mapfile = get_datafile(os.path.join(base_dir, 'PassamaquoddyMap.bna'))
gnome_map = MapFromBNA(mapfile, refloat_halflife=1) # hours
# # the image output renderer
# global renderer
# one hour timestep
model = Model(start_time=start_time,
duration=timedelta(hours=24), time_step=360,
map=gnome_map, uncertain=False, cache_enabled=True)
print 'adding outputters'
renderer = Renderer(mapfile, images_dir, size=(800, 600),
# output_timestep=timedelta(hours=1),
draw_ontop='uncertain')
renderer.viewport = ((-67.15, 45.), (-66.9, 45.2))
model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'script_passamaquoddy.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file, which_data='all')
print 'adding a spill'
spill = point_line_release_spill(num_elements=1000,
start_position=(-66.991344, 45.059316,
0.0),
release_time=start_time)
model.spills += spill
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=30000, uncertain_factor=2)
print 'adding a wind mover:'
series = np.zeros((5, ), dtype=datetime_value_2d)
series[0] = (start_time, (5, 90))
series[1] = (start_time + timedelta(hours=18), (5, 180))
series[2] = (start_time + timedelta(hours=30), (5, 135))
series[3] = (start_time + timedelta(hours=42), (5, 180))
series[4] = (start_time + timedelta(hours=54), (5, 225))
wind = Wind(timeseries=series, units='m/s')
model.movers += WindMover(wind)
print 'adding a current mover:'
curr_file = get_datafile(os.path.join(base_dir, 'PQBayCur.nc4'))
topology_file = get_datafile(os.path.join(base_dir, 'PassamaquoddyTOP.dat')
)
tide_file = get_datafile(os.path.join(base_dir, 'EstesHead.txt'))
cc_mover = CurrentCycleMover(curr_file, topology_file,
tide=Tide(tide_file))
model.movers += cc_mover
model.environment += cc_mover.tide
print 'viewport is:', [o.viewport
for o in model.outputters
if isinstance(o, Renderer)]
return model
def make_model(images_dir=os.path.join(base_dir, 'images')):
# create the maps:
print 'creating the maps'
mapfile = get_datafile(os.path.join(base_dir, 'DelawareRiverMap.bna'))
gnome_map = MapFromBNA(mapfile, refloat_halflife=1) # hours
renderer = Renderer(mapfile, images_dir, image_size=(800, 800),
projection_class=GeoProjection)
print 'initializing the model'
start_time = datetime(2012, 8, 20, 13, 0)
# 15 minutes in seconds
# Default to now, rounded to the nearest hour
model = Model(time_step=900, start_time=start_time,
duration=timedelta(days=1),
map=gnome_map, uncertain=False)
print 'adding outputters'
model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'script_delaware_bay.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file, which_data='all')
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=100000)
print 'adding a wind mover:'
# wind_file = get_datafile(os.path.join(base_dir, 'ConstantWind.WND'))
# wind = Wind(filename=wind_file)
series = np.zeros((2, ), dtype=datetime_value_2d)
series[0] = (start_time, (5, 270))
series[1] = (start_time + timedelta(hours=25), (5, 270))
wind = Wind(timeseries=series, units='m/s')
# w_mover = WindMover(Wind(timeseries=series, units='knots'))
w_mover = WindMover(wind)
model.movers += w_mover
print 'adding a cats shio mover:'
curr_file = get_datafile(os.path.join(base_dir, 'FloodTides.cur'))
tide_file = get_datafile(os.path.join(base_dir, 'FloodTidesShio.txt'))
c_mover = CatsMover(curr_file, tide=Tide(tide_file))
# this is the value in the file (default)
c_mover.scale_refpoint = (-75.081667, 38.7995)
c_mover.scale = True
c_mover.scale_value = 1
model.movers += c_mover
# TODO: cannot add this till environment base class is created
model.environment += c_mover.tide
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, 'Offshore.cur'))
c_mover = CatsMover(curr_file)
# but do need to scale (based on river stage)
c_mover.scale = True
c_mover.scale_refpoint = (-74.7483333, 38.898333)
c_mover.scale_value = .03
model.movers += c_mover
#
# these are from windows they don't match Mac values...
# pat1Angle 315;
# pat1Speed 30; pat1SpeedUnits knots;
# pat1ScaleToValue 0.314426
#
# pat2Angle 225;
# pat2Speed 30; pat2SpeedUnits knots;
# pat2ScaleToValue 0.032882
# scaleBy WindStress
print 'adding a component mover:'
# if only using one current pattern
# comp_mover = ComponentMover(curr_file1, None, wind)
#
# todo: following is not working when model is saved out - fix
# comp_mover = ComponentMover(curr_file1, curr_file2,
# Wind(timeseries=series, units='m/s'))
# comp_mover = ComponentMover(curr_file1, curr_file2,
# wind=Wind(filename=wind_file))
curr_file1 = get_datafile(os.path.join(base_dir, 'NW30ktwinds.cur'))
curr_file2 = get_datafile(os.path.join(base_dir, 'SW30ktwinds.cur'))
comp_mover = ComponentMover(curr_file1, curr_file2, wind)
comp_mover.scale_refpoint = (-75.263166, 39.1428333)
comp_mover.pat1_angle = 315
comp_mover.pat1_speed = 30
comp_mover.pat1_speed_units = 1
# comp_mover.pat1ScaleToValue = .314426
comp_mover.pat1_scale_to_value = .502035
comp_mover.pat2_angle = 225
comp_mover.pat2_speed = 30
comp_mover.pat2_speed_units = 1
# comp_mover.pat2ScaleToValue = .032882
comp_mover.pat2_scale_to_value = .021869
model.movers += comp_mover
print 'adding a spill'
end_time = start_time + timedelta(hours=12)
spill = point_line_release_spill(num_elements=1000,
release_time=start_time,
# end_release_time=end_time,
start_position=(-75.262319,
39.142987, 0.0),
)
model.spills += spill
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 make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2013, 5, 18, 0)
model = Model(start_time=start_time,
duration=timedelta(days=8),
time_step=4 * 3600,
uncertain=False)
mapfile = get_datafile(os.path.join(base_dir, 'mariana_island.bna'))
print 'adding the map'
model.map = MapFromBNA(mapfile, refloat_halflife=6) # hours
#
# Add the outputters -- render to images, and save out as netCDF
#
print 'adding renderer'
model.outputters += Renderer(
mapfile,
images_dir,
size=(800, 600),
)
# draw_back_to_fore=True)
# print "adding netcdf output"
# netcdf_output_file = os.path.join(base_dir,'mariana_output.nc')
# scripting.remove_netcdf(netcdf_output_file)
# model.outputters += NetCDFOutput(netcdf_output_file, which_data='all')
#
# Set up the movers:
#
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=10000)
print 'adding a simple wind mover:'
model.movers += constant_wind_mover(5, 315, units='m/s')
print 'adding a current mover:'
# # this is HYCOM currents
curr_file = get_datafile(os.path.join(base_dir, 'HYCOM.nc'))
model.movers += GridCurrentMover(curr_file,
num_method=numerical_methods.euler)
# #
# # Add some spills (sources of elements)
# #
print 'adding four spill'
model.spills += point_line_release_spill(num_elements=NUM_ELEMENTS // 4,
start_position=(145.25, 15.0,
0.0),
release_time=start_time)
model.spills += point_line_release_spill(num_elements=NUM_ELEMENTS // 4,
start_position=(146.25, 15.0,
0.0),
release_time=start_time)
model.spills += point_line_release_spill(num_elements=NUM_ELEMENTS // 4,
start_position=(145.75, 15.25,
0.0),
release_time=start_time)
model.spills += point_line_release_spill(num_elements=NUM_ELEMENTS // 4,
start_position=(145.75, 14.75,
0.0),
release_time=start_time)
return model
def make_model(uncertain=False, mode='gnome'):
'''
Create a model from the data in sample_data/boston_data
It contains:
- the GeoProjection
- wind mover
- random mover
- cats shio mover
- cats ossm mover
- plain cats mover
'''
start_time = datetime(2013, 2, 13, 9, 0)
model = Model(start_time=start_time,
duration=timedelta(days=2),
time_step=timedelta(minutes=30).total_seconds(),
uncertain=uncertain,
map=MapFromBNA(testdata['boston_data']['map'],
refloat_halflife=1),
mode=mode)
print 'adding a spill'
start_position = (144.664166, 13.441944, 0.0)
end_release_time = start_time + timedelta(hours=6)
spill_amount = 1000.0
spill_units = 'kg'
model.spills += point_line_release_spill(num_elements=1000,
start_position=start_position,
release_time=start_time,
end_release_time=end_release_time,
amount=spill_amount,
units=spill_units,
substance=test_oil)
spill = model.spills[-1]
spill_volume = spill.get_mass() / spill.substance.density_at_temp()
# need a scenario for SimpleMover
# model.movers += SimpleMover(velocity=(1.0, -1.0, 0.0))
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=100000)
print 'adding a wind mover:'
series = np.zeros((2, ), dtype=datetime_value_2d)
series[0] = (start_time, (5, 180))
series[1] = (start_time + timedelta(hours=18), (5, 180))
w_mover = WindMover(Wind(timeseries=series, units='m/s'))
model.movers += w_mover
model.environment += w_mover.wind
print 'adding a cats shio mover:'
c_mover = CatsMover(testdata['boston_data']['cats_curr2'],
tide=Tide(testdata['boston_data']['cats_shio']))
# c_mover.scale_refpoint should automatically get set from tide object
c_mover.scale = True # default value
c_mover.scale_value = -1
# tide object automatically gets added by model
model.movers += c_mover
print 'adding a cats ossm mover:'
c_mover = CatsMover(testdata['boston_data']['cats_curr2'],
tide=Tide(testdata['boston_data']['cats_ossm']))
c_mover.scale = True # but do need to scale (based on river stage)
c_mover.scale_refpoint = (-70.65, 42.58333, 0.0)
c_mover.scale_value = 1.
print 'adding a cats mover:'
c_mover = CatsMover(testdata['boston_data']['cats_curr3'])
c_mover.scale = True # but do need to scale (based on river stage)
c_mover.scale_refpoint = (-70.78333, 42.39333, 0.0)
# the scale factor is 0 if user inputs no sewage outfall effects
c_mover.scale_value = .04
model.movers += c_mover
# TODO: seg faulting for component mover - comment test for now
# print "adding a component mover:"
# comp_mover = ComponentMover(testdata['boston_data']['component_curr1'],
# testdata['boston_data']['component_curr2'],
# w_mover.wind)
# TODO: callback did not work correctly below - fix!
# comp_mover = ComponentMover(component_file1,
# component_file2,
# Wind(timeseries=series, units='m/s'))
# comp_mover.ref_point = (-70.855, 42.275)
# comp_mover.pat1_angle = 315
# comp_mover.pat1_speed = 19.44
# comp_mover.pat1_speed_units = 1
# comp_mover.pat1ScaleToValue = .138855
# comp_mover.pat2_angle = 225
# comp_mover.pat2_speed = 19.44
# comp_mover.pat2_speed_units = 1
# comp_mover.pat2ScaleToValue = .05121
# model.movers += comp_mover
print 'adding a Weatherer'
model.environment += Water(311.15)
skim_start = start_time + timedelta(hours=3)
model.weatherers += [
Evaporation(),
Skimmer(spill_amount * .5,
spill_units,
efficiency=.3,
active_range=(skim_start, skim_start + timedelta(hours=2))),
Burn(0.2 * spill_volume,
1.0, (skim_start, InfDateTime('inf')),
efficiency=0.9)
]
model.outputters += \
CurrentJsonOutput(model.find_by_attr('_ref_as', 'current_movers',
model.movers, allitems=True))
return model
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2012, 9, 15, 12, 0)
mapfile = get_datafile(os.path.join(base_dir, './LongIslandSoundMap.BNA'))
gnome_map = MapFromBNA(mapfile, refloat_halflife=6) # hours
# # the image output renderer
# global renderer
# one hour timestep
model = Model(start_time=start_time,
duration=timedelta(hours=48), time_step=3600,
map=gnome_map, uncertain=False, cache_enabled=False)
print 'adding a spill'
et = floating_weathering(substance='FUEL OIL NO.6')
spill = point_line_release_spill(num_elements=1000,
start_position=(-72.419992,
41.202120, 0.0),
release_time=start_time,
amount=1000,
units='kg',
element_type=et)
spill.amount_uncertainty_scale = 1.0
model.spills += spill
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=500000, uncertain_factor=2)
print 'adding a wind mover:'
series = np.zeros((5, ), dtype=datetime_value_2d)
series[0] = (start_time, (10, 45))
series[1] = (start_time + timedelta(hours=18), (10, 90))
series[2] = (start_time + timedelta(hours=30), (10, 135))
series[3] = (start_time + timedelta(hours=42), (10, 180))
series[4] = (start_time + timedelta(hours=54), (10, 225))
wind = Wind(timeseries=series, units='m/s',
speed_uncertainty_scale=0.5)
model.movers += WindMover(wind)
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, r"./LI_tidesWAC.CUR"))
tide_file = get_datafile(os.path.join(base_dir, r"./CLISShio.txt"))
c_mover = CatsMover(curr_file, tide=Tide(tide_file))
model.movers += c_mover
model.environment += c_mover.tide
print 'adding Weatherers'
water_env = Water(311.15)
model.environment += water_env
model.weatherers += [Evaporation(water_env, wind),
Dispersion(),
Burn(),
Skimmer()]
print 'adding outputters'
model.outputters += WeatheringOutput()
return model
