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')):
# create the maps:
print 'creating the maps'
mapfile = gs.get_datafile(os.path.join(base_dir, './MassBayMap.bna'))
gnome_map = gs.MapFromBNA(
mapfile,
refloat_halflife=1, # hours
raster_size=2048 * 2048 # about 4 MB
)
renderer = gs.Renderer(mapfile,
images_dir,
image_size=(800, 800),
projection_class=GeoProjection)
print 'initializing the model'
# start_time = datetime(2013, 3, 12, 10, 0)
start_time = "2013-03-12T10:00"
# 15 minutes in seconds
# Default to now, rounded to the nearest hour
model = gs.Model(time_step=gs.minutes(15),
start_time=start_time,
duration=gs.days(1),
map=gnome_map,
uncertain=True)
print 'adding outputters'
model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'script_boston.nc')
gs.remove_netcdf(netcdf_file)
model.outputters += gs.NetCDFOutput(netcdf_file, which_data='all')
model.outputters += gs.KMZOutput(
os.path.join(base_dir, 'script_boston.kmz'))
print 'adding a RandomMover:'
model.movers += gs.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=25), (5, 180))
# w_mover = WindMover(Wind(timeseries=series, units='m/s'))
# model.movers += w_mover
# model.environment += w_mover.wind
w_mover = gs.constant_wind_mover(5, 180, units='m/s')
model.movers += w_mover
print 'adding a cats shio mover:'
curr_file = gs.get_datafile(os.path.join(base_dir, r"./EbbTides.cur"))
tide_file = gs.get_datafile(os.path.join(base_dir, r"./EbbTidesShio.txt"))
c_mover = gs.CatsMover(curr_file, tide=gs.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 = gs.get_datafile(
os.path.join(base_dir, "MerrimackMassCoast.cur"))
tide_file = gs.get_datafile(
os.path.join(base_dir, "MerrimackMassCoastOSSM.txt"))
c_mover = gs.CatsMover(curr_file, tide=gs.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 = gs.get_datafile(os.path.join(base_dir, "MassBaySewage.cur"))
c_mover = gs.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 = gs.get_datafile(os.path.join(base_dir, "WAC10msNW.cur"))
component_file2 = gs.get_datafile(os.path.join(base_dir, "WAC10msSW.cur"))
comp_mover = gs.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 = gs.asdatetime(start_time) + gs.hours(12)
spill = gs.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
# gs.set_verbose('info')
# pf = gs.PrintFinder()
rel_time = "2019-04-18T21:00:00"
model = gs.Model(
name='Whale Drift',
time_step=3600,
start_time=rel_time,
duration=gs.days(3),
)
mapfile = gs.get_datafile(os.path.join(base_dir, 'coast.bna'))
model.map = gs.MapFromBNA(mapfile, refloat_halflife=float("inf"))
# nam = gs.PyWindMover("NAM_5K.nc")
# nam.active_range = (gs.MinusInfTime(),
# gs.asdatetime("2019-04-19T22:00"))
# model.movers += nam
# gfs = gs.PyWindMover("GFS_Global_0p5deg-4-18.nc")
# model.movers += gfs
windfile = gs.get_datafile(
os.path.join(base_dir, '28NM SSW San Francisco CA-4-18.nws'))
forecast = gs.wind_mover_from_file(windfile)
#forecast.active_range = (gs.asdatetime("2019-04-19T22:01"),
# gs.InfTime())
print 'Loading current'
topology = {'grid_type': 'rgrid', 'node_lon': 'x', 'node_lat': 'y'}
current = gs.GridCurrent.from_netCDF(os.path.join(data_dir, currentfile),
grid_topology=topology)
angle = TimeseriesData.constant(name='angle', data=17.0, units='degrees')
current.angle = angle
current_mover = PyCurrentMover(current=current)
print 'Adding map'
tideflat = Matroos_Mudflats(os.path.join(data_dir, currentfile),
grid_topology=topology)
mapfile = 'Waddensea_ijsselmeer_6.bna'
land_map = gs.MapFromBNA(mapfile)
model.map = TideflatMap(land_map, tideflat)
print 'Adding current'
model.movers += current_mover
print 'Adding RandomMover'
model.movers += gs.RandomMover(diffusion_coeff=50000)
print 'adding a wind mover:'
model.movers += gs.constant_wind_mover(**Wind)
print 'adding spill'
spill = gs.surface_point_line_spill(num_elements=100,
def make_model(images_dir=os.path.join(base_dir, 'images')):
print 'initializing the model'
start_time = "1985-01-01T13:31"
model = gs.Model(start_time=start_time,
duration=gs.days(2),
time_step=gs.hours(1))
mapfile = gs.get_datafile(os.path.join(base_dir, 'ak_arctic.bna'))
print 'adding the map'
model.map = gs.MapFromBNA(mapfile, refloat_halflife=0.0) # seconds
print 'adding outputters'
renderer = gs.Renderer(mapfile, images_dir, image_size=(1024, 768))
renderer.set_viewport(((-165, 69), (-161.5, 70)))
# model.outputters += renderer
netcdf_file = os.path.join(base_dir, 'script_ice.nc')
gs.remove_netcdf(netcdf_file)
model.outputters += gs.NetCDFOutput(netcdf_file, which_data='all')
print 'adding a spill'
# For a subsurfce spill, you would need to add vertical movers:
# - gs.RiseVelocityMover
# - gs.RandomVerticalMover
spill1 = gs.point_line_release_spill(num_elements=1000,
start_position=(-163.75, 69.75, 0.0),
release_time=start_time)
model.spills += spill1
print 'adding the ice movers'
fn = [
gs.get_datafile('arctic_avg2_0001_gnome.nc'),
gs.get_datafile('arctic_avg2_0002_gnome.nc'),
]
gt = {'node_lon': 'lon', 'node_lat': 'lat'}
ice_aware_curr = gs.IceAwareCurrent.from_netCDF(filename=fn,
grid_topology=gt)
ice_aware_wind = gs.IceAwareWind.from_netCDF(
filename=fn,
grid=ice_aware_curr.grid,
)
method = 'RK2'
i_c_mover = gs.PyCurrentMover(current=ice_aware_curr,
default_num_method=method)
i_w_mover = gs.PyWindMover(wind=ice_aware_wind, default_num_method=method)
# shifting to -360 to 0 longitude
ice_aware_curr.grid.node_lon = ice_aware_curr.grid.node_lon[:] - 360
model.movers += i_c_mover
model.movers += i_w_mover
print 'adding an Ice RandomMover:'
model.movers += IceAwareRandomMover(
ice_concentration=ice_aware_curr.ice_concentration,
diffusion_coef=50000)
# to visualize the grid and currents
# renderer.add_grid(ice_aware_curr.grid)
# renderer.add_vec_prop(ice_aware_curr)
return model