def test_serialize_deserialize(tide, json_):
"""
test serialize/deserialize/update_from_dict doesn't raise errors
"""
c_cats = CatsMover(curr_file, tide=tide)
toserial = c_cats.serialize(json_)
dict_ = c_cats.deserialize(toserial)
# check our CatsMover attributes
if json_ == 'webapi':
assert toserial['filename'] == basename(toserial['filename'])
else:
# in save context, we expect a full path to file
assert toserial['filename'] != basename(toserial['filename'])
if tide:
assert 'tide' in toserial
dict_['tide'] = tide # no longer updating properties of nested objects
assert c_cats.tide is tide
if json_ == 'webapi':
assert (toserial['tide']['filename'] ==
basename(toserial['tide']['filename']))
else:
assert (toserial['tide']['filename'] !=
basename(toserial['tide']['filename']))
c_cats.update_from_dict(dict_)
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, 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_new_from_dict_curronly():
"""
test to_dict function for Wind object
create a new wind object and make sure it has same properties
"""
c_cats = CatsMover(curr_file)
dict_ = c_cats.to_dict('create')
c2 = CatsMover.new_from_dict(dict_)
assert c_cats == c2
def test_exception_new_from_dict():
"""
test exceptions raised for new_from_dict
"""
c_cats = CatsMover(curr_file)
dict_ = c_cats.to_dict('create')
dict_.update({'tide': td})
with pytest.raises(KeyError):
CatsMover.new_from_dict(dict_)
def test_new_from_dict_tide():
"""
test to_dict function for Wind object
create a new wind object and make sure it has same properties
"""
c_cats = CatsMover(curr_file, tide=td)
dict_ = c_cats.to_dict('create')
dict_.update({'tide': td})
c2 = CatsMover.new_from_dict(dict_)
assert c_cats == c2
def test_serialize_deserialize(tide):
"""
test serialize/deserialize/update_from_dict doesn't raise errors
"""
c_cats = CatsMover(curr_file, tide=tide)
toserial = c_cats.serialize('webapi')
dict_ = c_cats.deserialize(toserial)
if tide:
assert 'tide' in toserial
dict_['tide'] = tide # no longer updating properties of nested objects
assert c_cats.tide is tide
c_cats.update_from_dict(dict_)
def test_save_load(tide):
"""
test save/loading with and without tide
"""
saveloc = tempfile.mkdtemp()
c_cats = CatsMover(curr_file, tide=tide)
save_json, zipfile_, _refs = c_cats.save(saveloc)
assert validate_save_json(save_json, zipfile.ZipFile(zipfile_), c_cats)
loaded = CatsMover.load(zipfile_)
assert loaded == c_cats
def test_serialize_deserialize(tide):
"""
test serialize/deserialize/update_from_dict doesn't raise errors
"""
c_cats = CatsMover(curr_file, tide=tide)
serial = c_cats.serialize()
assert validate_serialize_json(serial, c_cats)
# check our CatsMover attributes
deser = CatsMover.deserialize(serial)
assert deser == c_cats
def test_serialize_deserialize(tide):
"""
test serialize/deserialize/update_from_dict doesn't raise errors
"""
c_cats = CatsMover(curr_file, tide=tide)
serial = c_cats.serialize()
assert validate_serialize_json(serial, c_cats)
# check our CatsMover attributes
deser = CatsMover.deserialize(serial)
assert deser == c_cats
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 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:'
if setup.curr_fn.endswith('.nc'):
c_mover = GridCurrentMover(filename=setup.curr_fn, extrapolate=True)
elif setup.curr_fn.endswith('.cur'):
tide = Tide(setup.tide_fn)
c_mover = CatsMover(filename=setup.curr_fn, tide=tide)
model.movers += c_mover
print 'adding a WindMover:'
if setup.wind_fn is not None:
w = Wind(filename=setup.wind_fn)
w_mover = WindMover(w)
elif setup.wind_data is not None:
w_mover = constant_wind_mover(setup.wind_data[0],
setup.wind_data[1],
units='knots')
# 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 test_serialize_deserialize(tide, json_):
"""
test serialize/deserialize/update_from_dict doesn't raise errors
"""
c_cats = CatsMover(curr_file, tide=tide)
toserial = c_cats.serialize(json_)
dict_ = c_cats.deserialize(toserial)
# check our CatsMover attributes
if json_ == 'webapi':
assert toserial['filename'] == basename(toserial['filename'])
else:
# in save context, we expect a full path to file
assert toserial['filename'] != basename(toserial['filename'])
if tide:
assert 'tide' in toserial
dict_['tide'] = tide # no longer updating properties of nested objects
assert c_cats.tide is tide
if json_ == 'webapi':
assert (toserial['tide']['filename'] == basename(
toserial['tide']['filename']))
else:
assert (toserial['tide']['filename'] != basename(
toserial['tide']['filename']))
c_cats.update_from_dict(dict_)
def test_uncertain_loop():
"""
test one time step with uncertainty on the spill
checks there is non-zero motion.
"""
pSpill = sample_sc_release(num_le, start_pos, rel_time, uncertain=True)
cats = CatsMover(curr_file, tide=td)
u_delta = _uncertain_loop(pSpill, cats)
_assert_move(u_delta)
return u_delta
def test_loop():
"""
test one time step with no uncertainty on the spill
checks there is non-zero motion.
also checks the motion is same for all LEs
"""
pSpill = sample_sc_release(num_le, start_pos, rel_time)
cats = CatsMover(curr_file, tide=td)
delta = _certain_loop(pSpill, cats)
_assert_move(delta)
assert np.all(delta[:, 0] == delta[0, 0]) # lat move matches for all LEs
assert np.all(delta[:, 1] == delta[0, 1]) # long move matches for all LEs
assert np.all(delta[:, 2] == 0) # 'z' is zeros
return delta
def test_serialize_deserialize_curronly(do):
"""
test to_dict function for Wind object
create a new wind object and make sure it has same properties
"""
c_cats = CatsMover(curr_file)
json_ = c_cats.serialize(do)
dict_ = c_cats.deserialize(json_)
if do == 'create':
c2 = CatsMover.new_from_dict(dict_)
assert c_cats == c2
else:
c_cats.from_dict(dict_)
def test_serialize_deserialize_tide(do):
"""
test to_dict function for Wind object
create a new wind object and make sure it has same properties
"""
c_cats = CatsMover(curr_file, tide=td)
json_ = c_cats.serialize(do)
dict_ = c_cats.deserialize(json_)
if do == 'create':
dict_.update({'tide': td})
c2 = CatsMover.new_from_dict(dict_)
assert c_cats == c2
else:
assert json_['tide'] == td.serialize(do)
c_cats.from_dict(dict_)
assert c_cats.tide is td
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(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
import numpy as np
import pytest
# from gnome.basic_types import oil_status
from gnome.utilities import time_utils
from gnome.environment import Tide
from gnome.spill import SpatialRelease, Spill, point_line_release_spill
from gnome.movers import CatsMover
from gnome.outputters import CurrentJsonOutput
from ..conftest import testdata
td = Tide(filename=testdata['CatsMover']['tide'])
c_cats = CatsMover(testdata['CatsMover']['curr'], tide=td)
rel_time = datetime(2012, 9, 15, 12)
time_step = 15 * 60 # seconds
model_time = time_utils.sec_to_date(time_utils.date_to_sec(rel_time))
@pytest.fixture(scope='function')
def model(sample_model, output_dir):
model = sample_model['model']
rel_start_pos = sample_model['release_start_pos']
rel_end_pos = sample_model['release_end_pos']
model.cache_enabled = True
model.uncertain = True
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = datetime(2013, 2, 13, 9, 0)
# 1/2 hr in seconds
model = Model(start_time=start_time,
duration=timedelta(days=2),
time_step=30 * 60,
uncertain=False)
print 'adding the map'
mapfile = get_datafile(os.path.join(base_dir, 'GuamMap.bna'))
model.map = MapFromBNA(mapfile, refloat_halflife=6) # hours
print 'adding outputters'
renderer = Renderer(mapfile, images_dir, image_size=(800, 600))
renderer.viewport = ((144.6, 13.4), (144.7, 13.5))
model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'script_guam.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file, which_data='all')
print 'adding a spill'
end_time = start_time + timedelta(hours=6)
spill = point_line_release_spill(num_elements=10,
start_position=(144.664166,
13.441944, 0.0),
release_time=start_time,
end_release_time=end_time)
model.spills += spill
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=50000)
print 'adding a wind mover:'
series = np.zeros((4, ), dtype=datetime_value_2d)
series[0] = (start_time, (5, 135))
series[1] = (start_time + timedelta(hours=23), (5, 135))
series[2] = (start_time + timedelta(hours=25), (5, 0))
series[3] = (start_time + timedelta(hours=48), (5, 0))
wind = Wind(timeseries=series, units='knot')
w_mover = WindMover(wind)
model.movers += w_mover
model.environment += w_mover.wind
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, 'OutsideWAC.cur'))
c_mover = CatsMover(curr_file)
c_mover.scale = True
c_mover.scale_refpoint = (144.601, 13.42)
c_mover.scale_value = .15
model.movers += c_mover
print 'adding a cats shio mover:'
curr_file = get_datafile(os.path.join(base_dir, 'WACFloodTide.cur'))
tide_file = get_datafile(os.path.join(base_dir, 'WACFTideShioHts.txt'))
c_mover = CatsMover(curr_file, tide=Tide(tide_file))
# this is different from the value in the file!
c_mover.scale_refpoint = (144.621667, 13.45)
c_mover.scale = True
c_mover.scale_value = 1
# will need the fScaleFactor for heights files
# c_mover.time_dep.scale_factor = 1.1864
c_mover.tide.scale_factor = 1.1864
model.movers += c_mover
model.environment += c_mover.tide
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
renderer = Renderer(mapfile,
images_dir,
size=(800, 800),
projection_class=GeoProjection)
print 'initializing the model'
start_time = datetime(2013, 3, 12, 10, 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_boston.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:'
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:'
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 cats ossm mover:'
# ossm_file = get_datafile(os.path.join(base_dir,
# r"./MerrimackMassCoastOSSM.txt"))
curr_file = get_datafile(
os.path.join(base_dir, r"./MerrimackMassCoast.cur"))
tide_file = get_datafile(
os.path.join(base_dir, r"./MerrimackMassCoastOSSM.txt"))
c_mover = CatsMover(curr_file, tide=Tide(tide_file))
# but do need to scale (based on river stage)
c_mover.scale = True
c_mover.scale_refpoint = (-70.65, 42.58333)
c_mover.scale_value = 1.
model.movers += c_mover
model.environment += c_mover.tide
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, r"MassBaySewage.cur"))
c_mover = CatsMover(curr_file)
# but do need to scale (based on river stage)
c_mover.scale = True
c_mover.scale_refpoint = (-70.78333, 42.39333)
# the scale factor is 0 if user inputs no sewage outfall effects
c_mover.scale_value = .04
model.movers += c_mover
# pat1Angle 315;
# pat1Speed 19.44; pat1SpeedUnits knots;
# pat1ScaleToValue 0.138855
#
# pat2Angle 225;
# pat2Speed 19.44; pat2SpeedUnits knots;
# pat2ScaleToValue 0.05121
#
# scaleBy WindStress
print "adding a component mover:"
component_file1 = get_datafile(os.path.join(base_dir, r"./WAC10msNW.cur"))
component_file2 = get_datafile(os.path.join(base_dir, r"./WAC10msSW.cur"))
comp_mover = ComponentMover(component_file1, component_file2, 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.scale_refpoint = (-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 spill'
end_time = start_time + timedelta(hours=12)
spill = point_line_release_spill(num_elements=1000,
start_position=(-70.911432, 42.369142,
0.0),
release_time=start_time,
end_release_time=end_time)
model.spills += spill
return model
def test_certain_uncertain():
"""
make sure certain and uncertain loop results in different deltas
"""
delta = test_loop()
u_delta = test_uncertain_loop()
print
print delta
print u_delta
assert np.all(delta[:, :2] != u_delta[:, :2])
assert np.all(delta[:, 2] == u_delta[:, 2])
c_cats = CatsMover(curr_file)
0
def test_default_props():
"""
test default properties
"""
assert c_cats.uncertain_duration == 48.0
assert c_cats.uncertain_time_delay == 0
assert c_cats.up_cur_uncertain == 0.3
assert c_cats.down_cur_uncertain == -0.3
assert c_cats.right_cur_uncertain == 0.1
assert c_cats.left_cur_uncertain == -0.1
assert c_cats.scale is False
def make_model(uncertain=False, geojson_output=False):
print 'initializing the model'
start_time = datetime(2012, 9, 15, 12, 0)
mapfile = testdata["lis"]["map"]
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=uncertain,
cache_enabled=False)
print 'adding a spill'
spill = point_line_release_spill(num_elements=1000,
start_position=(-72.419992, 41.202120,
0.0),
release_time=start_time,
amount=1000,
substance=test_oil,
units='kg')
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, (20, 45))
series[1] = (start_time + timedelta(hours=18), (20, 90))
series[2] = (start_time + timedelta(hours=30), (20, 135))
series[3] = (start_time + timedelta(hours=42), (20, 180))
series[4] = (start_time + timedelta(hours=54), (20, 225))
wind = Wind(timeseries=series, units='m/s', speed_uncertainty_scale=0.05)
model.movers += WindMover(wind)
print 'adding a cats mover:'
c_mover = CatsMover(testdata["lis"]["cats_curr"],
tide=Tide(testdata["lis"]["cats_tide"]))
model.movers += c_mover
model.environment += c_mover.tide
print 'adding Weatherers'
rel_time = model.spills[0].get('release_time')
skim_start = rel_time + timedelta(hours=4)
amount = spill.amount
units = spill.units
# define skimmer/burn cleanup options
skimmer = Skimmer(0.3 * amount,
units=units,
efficiency=0.3,
active_start=skim_start,
active_stop=skim_start + timedelta(hours=4))
# thickness = 1m so area is just 20% of volume
volume = spill.get_mass() / spill.get('substance').get_density()
burn = Burn(0.2 * volume, 1.0, active_start=skim_start, efficiency=.9)
c_disp = ChemicalDispersion(0.1,
efficiency=0.5,
active_start=skim_start,
active_stop=skim_start + timedelta(hours=1))
water_env = Water(311.15)
model.environment += water_env
model.weatherers += [Evaporation(water_env, wind), c_disp, burn, skimmer]
print 'adding outputters'
model.outputters += WeatheringOutput()
if geojson_output:
model.outputters += TrajectoryGeoJsonOutput()
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, 'SanJuanMap.bna'))
gnome_map = MapFromBNA(mapfile, refloat_halflife=1,
raster_size=1024 * 1024)
renderer = Renderer(mapfile,
images_dir,
size=(800, 800),
projection_class=GeoProjection)
renderer.viewport = ((-66.24, 18.39), (-66.1, 18.55))
print 'initializing the model'
start_time = datetime(2014, 9, 3, 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_san_juan.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:'
series = np.zeros((2, ), dtype=datetime_value_2d)
series[0] = (start_time, (0, 270))
series[1] = (start_time + timedelta(hours=18), (0, 270))
wind = Wind(timeseries=series, units='m/s')
w_mover = WindMover(wind)
model.movers += w_mover
print 'adding a cats shio mover:'
# need to add the scale_factor for the tide heights file
curr_file = get_datafile(os.path.join(base_dir, 'EbbTides.cur'))
tide_file = get_datafile(os.path.join(base_dir, 'EbbTidesShioHt.txt'))
c_mover = CatsMover(curr_file, tide=Tide(tide_file, scale_factor=.15))
# this is the value in the file (default)
c_mover.scale_refpoint = (-66.116667, 18.458333)
c_mover.scale = True
c_mover.scale_value = 1.0
# c_mover.tide.scale_factor = 0.15
model.movers += c_mover
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, 'Offshore.cur'))
c_mover = CatsMover(curr_file)
# this is the value in the file (default)
# c_mover.scale_refpoint = (-66.082836, 18.469334)
c_mover.scale_refpoint = (-66.084333333, 18.46966667)
c_mover.scale = True
c_mover.scale_value = 0.1
model.movers += c_mover
print 'adding a spill'
end_time = start_time + timedelta(hours=12)
spill = point_line_release_spill(num_elements=1000,
release_time=start_time,
start_position=(-66.16374,
18.468054, 0.0),
# start_position=(-66.129099,
# 18.465332, 0.0),
# end_release_time=end_time,
)
model.spills += spill
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
renderer = Renderer(mapfile, images_dir, size=(800, 800),
projection_class=GeoProjection)
print 'initializing the model'
start_time = datetime(2013, 3, 12, 10, 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_boston.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:'
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:'
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 cats ossm mover:'
#ossm_file = get_datafile(os.path.join(base_dir,
# r"./MerrimackMassCoastOSSM.txt"))
curr_file = get_datafile(os.path.join(base_dir,
r"./MerrimackMassCoast.cur"))
tide_file = get_datafile(os.path.join(base_dir,
r"./MerrimackMassCoastOSSM.txt"))
c_mover = CatsMover(curr_file, tide=Tide(tide_file))
# but do need to scale (based on river stage)
c_mover.scale = True
c_mover.scale_refpoint = (-70.65, 42.58333)
c_mover.scale_value = 1.
model.movers += c_mover
model.environment += c_mover.tide
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, r"MassBaySewage.cur"))
c_mover = CatsMover(curr_file)
# but do need to scale (based on river stage)
c_mover.scale = True
c_mover.scale_refpoint = (-70.78333, 42.39333)
# the scale factor is 0 if user inputs no sewage outfall effects
c_mover.scale_value = .04
model.movers += c_mover
# print "adding a component mover:"
# component_file1 = os.path.join( base_dir, r"./WAC10msNW.cur")
# component_file2 = os.path.join( base_dir, r"./WAC10msSW.cur")
print 'adding a spill'
end_time = start_time + timedelta(hours=12)
spill = point_line_release_spill(num_elements=1000,
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, uncertain=False):
'''
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
'''
mapfile = get_datafile(os.path.join(datafiles, './MassBayMap.bna'))
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(mapfile, refloat_halflife=1))
print 'adding a renderer'
model.outputters += Renderer(mapfile, images_dir, size=(800, 600))
print 'adding a spill'
start_position = (144.664166, 13.441944, 0.0)
end_release_time = start_time + timedelta(hours=6)
model.spills += point_line_release_spill(num_elements=1000,
start_position=start_position,
release_time=start_time,
end_release_time=end_release_time)
# 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:'
d_file1 = get_datafile(os.path.join(datafiles, './EbbTides.cur'))
d_file2 = get_datafile(os.path.join(datafiles, './EbbTidesShio.txt'))
c_mover = CatsMover(d_file1, tide=Tide(d_file2))
# 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:'
d_file1 = get_datafile(os.path.join(datafiles,
'./MerrimackMassCoast.cur'))
d_file2 = get_datafile(os.path.join(datafiles,
'./MerrimackMassCoastOSSM.txt'))
c_mover = CatsMover(d_file1, tide=Tide(d_file2))
c_mover.scale = True # but do need to scale (based on river stage)
c_mover.scale_refpoint = (-70.65, 42.58333)
c_mover.scale_value = 1.
#model.movers += c_mover
#model.environment += c_mover.tide
print 'adding a cats mover:'
d_file1 = get_datafile(os.path.join(datafiles, 'MassBaySewage.cur'))
c_mover = CatsMover(d_file1)
c_mover.scale = True # but do need to scale (based on river stage)
c_mover.scale_refpoint = (-70.78333, 42.39333)
# the scale factor is 0 if user inputs no sewage outfall effects
c_mover.scale_value = .04
model.movers += c_mover
print 'adding a Weatherer'
weatherer = Weatherer()
model.weatherers += weatherer
return model
'''
Run the following save/load test on multiple pygnome objects so collect tests
here and parametrize it by the objects
'''
base_dir = os.path.dirname(__file__)
# For WindMover test_save_load in test_wind_mover
g_objects = (
GridCurrent.from_netCDF(testdata['GridCurrentMover']['curr_tri']),
Tide(testdata['CatsMover']['tide']),
Wind(filename=testdata['ComponentMover']['wind']),
Wind(timeseries=(sec_to_date(24 * 60 * 60), (0, 0)), units='mps'),
Water(temperature=273),
RandomMover(),
CatsMover(testdata['CatsMover']['curr']),
CatsMover(testdata['CatsMover']['curr'],
tide=Tide(testdata['CatsMover']['tide'])),
ComponentMover(testdata['ComponentMover']['curr']),
ComponentMover(testdata['ComponentMover']['curr'],
wind=Wind(filename=testdata['ComponentMover']['wind'])),
RandomMover3D(),
SimpleMover(velocity=(10.0, 10.0, 0.0)),
map.MapFromBNA(testdata['MapFromBNA']['testmap'], 6),
NetCDFOutput(os.path.join(base_dir, u'xtemp.nc')),
Renderer(testdata['Renderer']['bna_sample'],
os.path.join(base_dir, 'output_dir')),
WeatheringOutput(),
spill.PointLineRelease(release_time=datetime.now(),
num_elements=10,
start_position=(0, 0, 0)),
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, 'SanJuanMap.bna'))
gnome_map = MapFromBNA(mapfile,
refloat_halflife=1,
raster_size=1024 * 1024)
renderer = Renderer(mapfile,
images_dir,
image_size=(800, 800),
projection_class=GeoProjection)
renderer.viewport = ((-66.24, 18.39), (-66.1, 18.55))
print 'initializing the model'
start_time = datetime(2014, 9, 3, 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_san_juan.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:'
series = np.zeros((2, ), dtype=datetime_value_2d)
series[0] = (start_time, (0, 270))
series[1] = (start_time + timedelta(hours=18), (0, 270))
wind = Wind(timeseries=series, units='m/s')
w_mover = WindMover(wind)
wind.extrapolation_is_allowed = True
model.movers += w_mover
print 'adding a cats shio mover:'
# need to add the scale_factor for the tide heights file
curr_file = get_datafile(os.path.join(base_dir, 'EbbTides.cur'))
tide_file = get_datafile(os.path.join(base_dir, 'EbbTidesShioHt.txt'))
c_mover = CatsMover(curr_file, tide=Tide(tide_file, scale_factor=.15))
# this is the value in the file (default)
c_mover.scale_refpoint = (-66.116667, 18.458333)
c_mover.scale = True
c_mover.scale_value = 1.0
# c_mover.tide.scale_factor = 0.15
model.movers += c_mover
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, 'Offshore.cur'))
c_mover = CatsMover(curr_file)
# this is the value in the file (default)
# c_mover.scale_refpoint = (-66.082836, 18.469334)
c_mover.scale_refpoint = (-66.084333333, 18.46966667)
c_mover.scale = True
c_mover.scale_value = 0.1
model.movers += c_mover
print 'adding a spill'
end_time = start_time + timedelta(hours=12)
spill = point_line_release_spill(
num_elements=1000,
release_time=start_time,
start_position=(-66.16374, 18.468054, 0.0),
# start_position=(-66.129099,
# 18.465332, 0.0),
# end_release_time=end_time,
)
model.spills += spill
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_start=skim_start,
active_stop=skim_start + timedelta(hours=2)),
Burn(0.2 * spill_volume, 1.0, skim_start,
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')):
# 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, 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:'
series = np.zeros((2, ), dtype=datetime_value_2d)
series[0] = (start_time, (5, 270))
series[1] = (start_time + timedelta(hours=18), (5, 270))
wind_file = get_datafile(os.path.join(base_dir, r"ConstantWind.WND"))
# wind = Wind(filename=wind_file)
wind = Wind(timeseries=series, units='m/s')
w_mover = WindMover(wind)
#w_mover = WindMover(Wind(timeseries=series, units='knots'))
model.movers += w_mover
print 'adding a cats shio mover:'
curr_file = get_datafile(os.path.join(base_dir, r"./FloodTides.cur"))
tide_file = get_datafile(os.path.join(base_dir, r"./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,
r"./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
#
# pat1Angle 315; pat1Speed 30; pat1SpeedUnits knots; pat1ScaleToValue 0.314426 # these are from windows they don't match Mac values...
# pat2Angle 225; pat2Speed 30; pat2SpeedUnits knots; pat2ScaleToValue 0.032882
# scaleBy WindStress
print 'adding a component mover:'
curr_file1 = get_datafile(os.path.join(base_dir, r"NW30ktwinds.cur"))
curr_file2 = get_datafile(os.path.join(base_dir, r"SW30ktwinds.cur"))
comp_mover = ComponentMover(curr_file1, curr_file2, 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))
comp_mover.ref_point = (-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,
start_position=(-75.262319,
39.142987, 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'
start_time = datetime(2013, 2, 13, 9, 0)
# 1/2 hr in seconds
model = Model(start_time=start_time,
duration=timedelta(days=2),
time_step=30 * 60,
uncertain=False)
print 'adding the map'
mapfile = get_datafile(os.path.join(base_dir, 'GuamMap.bna'))
model.map = MapFromBNA(mapfile, refloat_halflife=6) # hours
print 'adding outputters'
renderer = Renderer(mapfile, images_dir, image_size=(800, 600))
renderer.viewport = ((144.6, 13.4), (144.7, 13.5))
model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'script_guam.nc')
scripting.remove_netcdf(netcdf_file)
model.outputters += NetCDFOutput(netcdf_file, which_data='all')
print 'adding a spill'
end_time = start_time + timedelta(hours=6)
spill = point_line_release_spill(num_elements=10,
start_position=(144.664166, 13.441944,
0.0),
release_time=start_time,
end_release_time=end_time)
model.spills += spill
print 'adding a RandomMover:'
model.movers += RandomMover(diffusion_coef=50000)
print 'adding a wind mover:'
series = np.zeros((4, ), dtype=datetime_value_2d)
series[0] = (start_time, (5, 135))
series[1] = (start_time + timedelta(hours=23), (5, 135))
series[2] = (start_time + timedelta(hours=25), (5, 0))
series[3] = (start_time + timedelta(hours=48), (5, 0))
wind = Wind(timeseries=series, units='knot')
w_mover = WindMover(wind)
model.movers += w_mover
model.environment += w_mover.wind
print 'adding a cats mover:'
curr_file = get_datafile(os.path.join(base_dir, 'OutsideWAC.cur'))
c_mover = CatsMover(curr_file)
c_mover.scale = True
c_mover.scale_refpoint = (144.601, 13.42)
c_mover.scale_value = .15
model.movers += c_mover
print 'adding a cats shio mover:'
curr_file = get_datafile(os.path.join(base_dir, 'WACFloodTide.cur'))
tide_file = get_datafile(os.path.join(base_dir, 'WACFTideShioHts.txt'))
c_mover = CatsMover(curr_file, tide=Tide(tide_file))
# this is different from the value in the file!
c_mover.scale_refpoint = (144.621667, 13.45)
c_mover.scale = True
c_mover.scale_value = 1
# will need the fScaleFactor for heights files
# c_mover.time_dep.scale_factor = 1.1864
c_mover.tide.scale_factor = 1.1864
model.movers += c_mover
model.environment += c_mover.tide
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 test_all_movers(start_time, release_delay, duration):
'''
Tests that all the movers at least can be run
Add new ones as they come along!
'''
model = Model()
model.time_step = timedelta(hours=1)
model.duration = timedelta(seconds=model.time_step * duration)
model.start_time = start_time
start_loc = (1., 2., 0.) # random non-zero starting points
# a spill - release after 5 timesteps
release_time = (start_time +
timedelta(seconds=model.time_step * release_delay))
model.spills += point_line_release_spill(num_elements=10,
start_position=start_loc,
release_time=release_time)
# the land-water map
model.map = gnome.map.GnomeMap() # the simplest of maps
# simple mover
model.movers += SimpleMover(velocity=(1., -1., 0.))
assert len(model.movers) == 1
# random mover
model.movers += RandomMover(diffusion_coef=100000)
assert len(model.movers) == 2
# wind mover
series = np.array((start_time, (10, 45)), dtype=datetime_value_2d).reshape(
(1, ))
model.movers += WindMover(Wind(timeseries=series,
units='meter per second'))
assert len(model.movers) == 3
# CATS mover
model.movers += CatsMover(testdata['CatsMover']['curr'])
assert len(model.movers) == 4
# run the model all the way...
num_steps_output = 0
for step in model:
num_steps_output += 1
print 'running step:', step
# test release happens correctly for all cases
if release_delay < duration:
# at least one get_move has been called after release
assert np.all(model.spills.LE('positions')[:, :2] != start_loc[:2])
elif release_delay == duration:
# particles are released after last step so no motion,
# only initial _state
assert np.all(model.spills.LE('positions') == start_loc)
else:
# release_delay > duration so nothing released though model ran
assert len(model.spills.LE('positions')) == 0
# there is the zeroth step, too.
calculated_steps = (model.duration.total_seconds() / model.time_step) + 1
assert num_steps_output == calculated_steps
