def test_release_from_splot_data():
'''
test release_from_splot_data by creating file with fake data
'''
test_data = \
('-7.885776000000000E+01 4.280546000000000E+01 4.4909252E+01\n'
'-7.885776000000000E+01 4.279556000000000E+01 4.4909252E+01\n'
'-8.324346000000000E+01 4.196396000000001E+01 3.0546749E+01\n')
here = os.path.dirname(__file__)
td_file = os.path.join(here, 'test_data.txt')
with open(td_file, 'w') as td:
td.write(test_data)
exp = np.asarray((44.909252, 44.909252, 30.546749), dtype=int)
exp_num_elems = exp.sum()
rel = release_from_splot_data(datetime(2015, 1, 1), td_file)
assert rel.num_elements == exp_num_elems
assert len(rel.start_position) == exp_num_elems
cumsum = np.cumsum(exp)
for ix in xrange(len(cumsum) - 1):
assert np.all(rel.start_position[cumsum[ix]] ==
rel.start_position[cumsum[ix]:cumsum[ix + 1]])
assert np.all(rel.start_position[0] == rel.start_position[:cumsum[0]])
os.remove(td_file)
def test_release_from_splot_data():
'''
test release_from_splot_data by creating file with fake data
'''
test_data = \
('-7.885776000000000E+01 4.280546000000000E+01 4.4909252E+01\n'
'-7.885776000000000E+01 4.279556000000000E+01 4.4909252E+01\n'
'-8.324346000000000E+01 4.196396000000001E+01 3.0546749E+01\n')
here = os.path.dirname(__file__)
td_file = os.path.join(here, 'test_data.txt')
with open(td_file, 'w') as td:
td.write(test_data)
exp = np.asarray((44.909252, 44.909252, 30.546749),
dtype=int)
exp_num_elems = exp.sum()
rel = release_from_splot_data(datetime(2015, 1, 1), td_file)
assert rel.num_elements == exp_num_elems
assert len(rel.start_position) == exp_num_elems
cumsum = np.cumsum(exp)
for ix in xrange(len(cumsum) - 1):
assert np.all(rel.start_position[cumsum[ix]] ==
rel.start_position[cumsum[ix]:cumsum[ix + 1]])
assert np.all(rel.start_position[0] == rel.start_position[:cumsum[0]])
os.remove(td_file)
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 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 make_model(images_dir=os.path.join(base_dir, 'images2')):
print('initializing the model')
start_time = datetime(int(sys.argv[1]), int(sys.argv[2]), int(sys.argv[3]),
int(sys.argv[4]), int(sys.argv[5]))
mapfile = get_datafile(os.path.join(base_dir, './brazil-coast.bna'))
gnome_map = MapFromBNA(mapfile, refloat_halflife=6) # hours
# # the image output renderer
# global renderer
#duration = timedelta(minutes=5)
#timestep = timedelta(minutes=5)
duration = timedelta(minutes=5)
timestep = timedelta(minutes=5)
endtime = start_time + duration
steps = duration.total_seconds() / timestep.total_seconds()
print("Total step: %.4i " % (steps))
model = Model(start_time=start_time,
duration=duration,
time_step=timestep,
map=gnome_map,
uncertain=False,
cache_enabled=False)
oil_name = 'GENERIC MEDIUM CRUDE'
wd = UniformDistribution(low=.0002, high=.0002)
subs = GnomeOil(oil_name, initializers=plume_initializers(distribution=wd))
#print 'adding a spill'
#spill = point_line_release_spill(num_elements=122,
# start_position=(-35.14,
# -9.40, 0.0),
# release_time=start_time)
#model.spills += spill
#spill2 = spatial_release_spill(-35.14,-9.40, 0.0, start_time)
#model.spills += spill2
#print 'load nc'
#netcdf_file = os.path.join(base_dir, 'maceio.nc')
#relnc = InitElemsFromFile(netcdf_file,release_time=start_time)
#relnc = InitElemsFromFile(netcdf_file,index=5)
#spillnc = Spill(release=relnc)
#print spillnc.release.num_elements
#print spillnc.release.name
#print spillnc.substance
#print relnc._init_data['age']
#print relnc.release_time
#model.spills += spillnc
#model._load_spill_data()
#for sc in model.spills.items():
# sc.prepare_for_model_run()
#print(relnc.num_elements)
#print(relnc.num_released)
# add particles - it works
print('adding particles')
# Persistent oil spill in contiguous zone border
if int(sys.argv[6]) == 1:
release = release_from_splot_data(start_time, 'contiguous.txt')
print("Adding new particles")
model.spills += Spill(release=release, substance=subs)
# Particles from previows simulation step
try:
f = open('step.txt')
f.close()
release2 = release_from_splot_data(start_time, 'step.txt')
model.spills += Spill(release=release2, substance=subs)
except IOError:
print('No previous step, using only contiguous.txt')
#assert rel.num_elements == exp_num_elems
#assert len(rel.start_position) == exp_num_elems
#cumsum = np.cumsum(exp)
#for ix in xrange(len(cumsum) - 1):
# assert np.all(rel.start_position[cumsum[ix]] ==
# rel.start_position[cumsum[ix]:cumsum[ix + 1]])
#assert np.all(rel.start_position[0] == rel.start_position[:cumsum[0]])
#spnc = Spill(release=None)
#spnc.release = relnc
print('adding a RandomMover:')
#model.movers += RandomMover(diffusion_coef=10000, uncertain_factor=2)
model.movers += RandomMover(diffusion_coef=10000)
print('adding a current mover:')
# # this is HYCOM currents
curr_file = get_datafile(os.path.join(base_dir, 'corrente15a28de09.nc'))
model.movers += GridCurrentMover(curr_file, num_method='Euler')
print('adding a grid wind mover:')
wind_file = get_datafile(os.path.join(base_dir, 'vento15a28de09.nc'))
#topology_file = get_datafile(os.path.join(base_dir, 'WindSpeedDirSubsetTop.dat'))
#w_mover = GridWindMover(wind_file, topology_file)
w_mover = GridWindMover(wind_file)
w_mover.uncertain_speed_scale = 1
w_mover.uncertain_angle_scale = 0.2 # default is .4
w_mover.wind_scale = 2
model.movers += w_mover
print('adding outputters')
renderer = Renderer(mapfile,
images_dir,
image_size=(900, 600),
output_timestep=timestep,
draw_ontop='forecast')
#set the viewport to zoom in on the map:
#renderer.viewport = ((-37, -11), (-34, -8)) #alagoas
renderer.viewport = ((-55, -34), (-30, 5)) #1/4 N alagoas
model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'step.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file,
which_data='standard',
surface_conc='kde')
return model
