def test_reverse_10_times_then_start_point(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting, end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point, end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react( start_point = starting,
hit_point = int4d,
end_point = ending,
feature = intersection['feature'],
distance = distance,
angle = angle,
azimuth = difference['azimuth'],
reverse_azimuth = difference['reverse_azimuth'],
reverse_distance = 9999999999999999999999999999)
# Should be start location
assert final_point.longitude == starting.longitude
assert final_point.latitude == starting.latitude
assert final_point.depth == starting.depth
def test_reverse_distance_traveled(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting, end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point, end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react( start_point = starting,
hit_point = int4d,
end_point = ending,
feature = intersection['feature'],
distance = distance,
angle = angle,
azimuth = difference['azimuth'],
reverse_azimuth = difference['reverse_azimuth'],
reverse_distance = 0.000001)
# Resulting point should be VERY close to the hit point.
assert abs(int4d.latitude - final_point.latitude) < 0.005
assert abs(int4d.longitude - final_point.longitude) < 0.005
def test_reverse_up_left(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting, end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point, end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react( start_point = starting,
hit_point = int4d,
end_point = ending,
feature = intersection['feature'],
distance = distance,
angle = angle,
azimuth = difference['azimuth'],
reverse_azimuth = difference['reverse_azimuth'])
# Resulting latitude should be between the startpoint and the intersection point
assert final_point.latitude > int4d.latitude
assert final_point.latitude < starting.latitude
# Resulting longitude should be between the startpoint and the intersection point
assert final_point.longitude < int4d.longitude
assert final_point.longitude > starting.longitude
def test_reverse_half_distance_until_in_water(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting, end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point, end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react( start_point = starting,
hit_point = int4d,
end_point = ending,
feature = intersection['feature'],
distance = distance,
angle = angle,
azimuth = difference['azimuth'],
reverse_azimuth = difference['reverse_azimuth'],
reverse_distance = 40000)
# Should be in water
assert s.intersect(start_point=final_point.point, end_point=final_point.point) is None
def test_reverse_distance_traveled(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting,
end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point,
end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react(start_point=starting,
hit_point=int4d,
end_point=ending,
feature=intersection['feature'],
distance=distance,
angle=angle,
azimuth=difference['azimuth'],
reverse_azimuth=difference['reverse_azimuth'],
reverse_distance=0.000001)
# Resulting point should be VERY close to the hit point.
assert abs(int4d.latitude - final_point.latitude) < 0.005
assert abs(int4d.longitude - final_point.longitude) < 0.005
def test_reverse_left(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.1, longitude=-74.91, depth=0)
ending = Location4D(latitude=39.1, longitude=-74.85, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting, end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point, end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react( start_point = starting,
hit_point = int4d,
end_point = ending,
feature = intersection['feature'],
distance = distance,
angle = angle,
azimuth = difference['azimuth'],
reverse_azimuth = difference['reverse_azimuth'])
# Since we are on a stright horizonal line, the latitude will change only slightly
assert abs(final_point.latitude - starting.latitude) < 0.005
# Resulting longitude should be between the startpoint and the intersection point
assert final_point.longitude < int4d.longitude
assert final_point.longitude > starting.longitude
def test_reverse_12_times_then_start_point(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting,
end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point,
end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react(start_point=starting,
hit_point=int4d,
end_point=ending,
feature=intersection['feature'],
distance=distance,
angle=angle,
azimuth=difference['azimuth'],
reverse_azimuth=difference['reverse_azimuth'],
reverse_distance=9999999999999999999999999999)
# Should be start location
assert final_point.longitude == starting.longitude
assert final_point.latitude == starting.latitude
assert final_point.depth == starting.depth
def test_reverse_half_distance_until_in_water(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting,
end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point,
end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react(start_point=starting,
hit_point=int4d,
end_point=ending,
feature=intersection['feature'],
distance=distance,
angle=angle,
azimuth=difference['azimuth'],
reverse_azimuth=difference['reverse_azimuth'],
reverse_distance=40000)
# Should be in water
assert s.intersect(start_point=final_point.point,
end_point=final_point.point) is None
def test_reverse_up_left(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.05, longitude=-75.34, depth=0)
ending = Location4D(latitude=38.96, longitude=-75.315, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting,
end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point,
end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react(start_point=starting,
hit_point=int4d,
end_point=ending,
feature=intersection['feature'],
distance=distance,
angle=angle,
azimuth=difference['azimuth'],
reverse_azimuth=difference['reverse_azimuth'])
# Resulting latitude should be between the startpoint and the intersection point
assert final_point.latitude > int4d.latitude
assert final_point.latitude < starting.latitude
# Resulting longitude should be between the startpoint and the intersection point
assert final_point.longitude < int4d.longitude
assert final_point.longitude > starting.longitude
def test_reverse_left(self):
s = Shoreline(type='reverse')
starting = Location4D(latitude=39.1, longitude=-74.91, depth=0)
ending = Location4D(latitude=39.1, longitude=-74.85, depth=0)
difference = AsaGreatCircle.great_distance(start_point=starting,
end_point=ending)
angle = AsaMath.azimuth_to_math_angle(azimuth=difference['azimuth'])
distance = difference['distance']
intersection = s.intersect(start_point=starting.point,
end_point=ending.point)
int4d = Location4D(point=intersection['point'])
final_point = s.react(start_point=starting,
hit_point=int4d,
end_point=ending,
feature=intersection['feature'],
distance=distance,
angle=angle,
azimuth=difference['azimuth'],
reverse_azimuth=difference['reverse_azimuth'])
# Since we are on a stright horizonal line, the latitude will change only slightly
assert abs(final_point.latitude - starting.latitude) < 0.005
# Resulting longitude should be between the startpoint and the intersection point
assert final_point.longitude < int4d.longitude
assert final_point.longitude > starting.longitude
class ForceParticle(object):
from paegan.transport.shoreline import Shoreline
from paegan.transport.bathymetry import Bathymetry
def __str__(self):
return self.part.__str__()
def __init__(self, part, remotehydro, common_variables, timevar_pickle_path, times, start_time, models,
release_location_centroid, usebathy, useshore, usesurface,
get_data, n_run, read_lock, has_read_lock, read_count,
point_get, data_request_lock, has_data_request_lock, reverse_distance=None, bathy=None,
shoreline_path=None, cache=None, time_method=None):
"""
This is the task/class/object/job that forces an
individual particle and communicates with the
other particles and data controller for local
cache updates
"""
assert cache != None
self.cache_path = cache
self.bathy = bathy
self.common_variables = common_variables
self.localpath = self.cache_path
self.release_location_centroid = release_location_centroid
self.part = part
self.times = times
self.start_time = start_time
self.models = models
self.usebathy = usebathy
self.useshore = useshore
self.usesurface = usesurface
self.get_data = get_data
self.n_run = n_run
self.read_lock = read_lock
self.has_read_lock = has_read_lock
self.read_count = read_count
self.point_get = point_get
self.data_request_lock = data_request_lock
self.has_data_request_lock = has_data_request_lock
self.shoreline_path = shoreline_path
self.timevar_pickle_path = timevar_pickle_path
# Set common variable names
self.uname = common_variables.get("u", None)
self.vname = common_variables.get("v", None)
self.wname = common_variables.get("w", None)
self.temp_name = common_variables.get("temp", None)
self.salt_name = common_variables.get("salt", None)
self.xname = common_variables.get("x", None)
self.yname = common_variables.get("y", None)
self.zname = common_variables.get("z", None)
self.tname = common_variables.get("time", None)
self.reverse_distance = reverse_distance
if time_method is None:
time_method = 'interp'
self.time_method = time_method
def need_data(self, i):
"""
Method to test if cache contains the data that
the particle needs
"""
logger.debug("Checking cache for data availability at %s." % self.part.location.logstring())
try:
# Tell the DataController that we are going to be reading from the file
with self.read_lock:
self.read_count.value += 1
self.has_read_lock.append(os.getpid())
self.dataset.opennc()
# Test if the cache has the data we need
# If the point we request contains fill values,
# we need data
cached_lookup = self.dataset.get_values('domain', timeinds=[np.asarray([i])], point=self.part.location)
logger.debug("Type of result: %s" % type(cached_lookup))
logger.debug("Double mean of result: %s" % np.mean(np.mean(cached_lookup)))
logger.debug("Type of Double mean of result: %s" % type(np.mean(np.mean(cached_lookup))))
if type(np.mean(np.mean(cached_lookup))) == np.ma.core.MaskedConstant:
need = True
logger.debug("I NEED data. Got back: %s" % cached_lookup)
else:
need = False
logger.debug("I DO NOT NEED data")
except StandardError:
# If the time index doesnt even exist, we need
need = True
logger.debug("I NEED data (no time index exists in cache)")
finally:
self.dataset.closenc()
with self.read_lock:
self.read_count.value -= 1
self.has_read_lock.remove(os.getpid())
return need # return true if need data or false if dont
def linterp(self, setx, sety, x):
"""
Linear interp of model data values between time steps
"""
if math.isnan(sety[0]) or math.isnan(setx[0]):
return np.nan
#if math.isnan(sety[0]):
# sety[0] = 0.
#if math.isnan(sety[1]):
# sety[1] = 0.
return sety[0] + (x - setx[0]) * ( (sety[1]-sety[0]) / (setx[1]-setx[0]) )
def data_interp(self, i, timevar, currenttime):
"""
Method to streamline request for data from cache,
Uses linear interpolation bewtween timesteps to
get u,v,w,temp,salt
"""
if self.active.value == True:
while self.get_data.value == True:
logger.debug("Waiting for DataController to release cache file so I can read from it...")
timer.sleep(4)
pass
if self.need_data(i+1):
# Acquire lock for asking for data
self.data_request_lock.acquire()
self.has_data_request_lock.value = os.getpid()
try:
# Do I still need data?
if self.need_data(i+1):
# Tell the DataController that we are going to be reading from the file
with self.read_lock:
self.read_count.value += 1
self.has_read_lock.append(os.getpid())
# Open netcdf file on disk from commondataset
self.dataset.opennc()
# Get the indices for the current particle location
indices = self.dataset.get_indices('u', timeinds=[np.asarray([i-1])], point=self.part.location )
self.dataset.closenc()
with self.read_lock:
self.read_count.value -= 1
self.has_read_lock.remove(os.getpid())
# Override the time
# get the current time index data
self.point_get.value = [indices[0] + 1, indices[-2], indices[-1]]
# Request that the data controller update the cache
self.get_data.value = True
# Wait until the data controller is done
if self.active.value == True:
while self.get_data.value == True:
logger.debug("Waiting for DataController to update cache with the CURRENT time index")
timer.sleep(4)
pass
# get the next time index data
self.point_get.value = [indices[0] + 2, indices[-2], indices[-1]]
# Request that the data controller update the cache
self.get_data.value = True
# Wait until the data controller is done
if self.active.value == True:
while self.get_data.value == True:
logger.debug("Waiting for DataController to update cache with the NEXT time index")
timer.sleep(4)
pass
except StandardError:
logger.warn("Particle failed to request data correctly")
raise
finally:
# Release lock for asking for data
self.has_data_request_lock.value = -1
self.data_request_lock.release()
# Tell the DataController that we are going to be reading from the file
with self.read_lock:
self.read_count.value += 1
self.has_read_lock.append(os.getpid())
try:
# Open netcdf file on disk from commondataset
self.dataset.opennc()
# Grab data at time index closest to particle location
u = [np.mean(np.mean(self.dataset.get_values('u', timeinds=[np.asarray([i])], point=self.part.location ))),
np.mean(np.mean(self.dataset.get_values('u', timeinds=[np.asarray([i+1])], point=self.part.location )))]
v = [np.mean(np.mean(self.dataset.get_values('v', timeinds=[np.asarray([i])], point=self.part.location ))),
np.mean(np.mean(self.dataset.get_values('v', timeinds=[np.asarray([i+1])], point=self.part.location )))]
# if there is vertical velocity inthe dataset, get it
if 'w' in self.dataset.nc.variables:
w = [np.mean(np.mean(self.dataset.get_values('w', timeinds=[np.asarray([i])], point=self.part.location ))),
np.mean(np.mean(self.dataset.get_values('w', timeinds=[np.asarray([i+1])], point=self.part.location )))]
else:
w = [0.0, 0.0]
# If there is salt and temp in the dataset, get it
if self.temp_name != None and self.salt_name != None:
temp = [np.mean(np.mean(self.dataset.get_values('temp', timeinds=[np.asarray([i])], point=self.part.location ))),
np.mean(np.mean(self.dataset.get_values('temp', timeinds=[np.asarray([i+1])], point=self.part.location )))]
salt = [np.mean(np.mean(self.dataset.get_values('salt', timeinds=[np.asarray([i])], point=self.part.location ))),
np.mean(np.mean(self.dataset.get_values('salt', timeinds=[np.asarray([i+1])], point=self.part.location )))]
# Check for nans that occur in the ocean (happens because
# of model and coastline resolution mismatches)
if np.isnan(u).any() or np.isnan(v).any() or np.isnan(w).any():
# Take the mean of the closest 4 points
# If this includes nan which it will, result is nan
uarray1 = self.dataset.get_values('u', timeinds=[np.asarray([i])], point=self.part.location, num=2)
varray1 = self.dataset.get_values('v', timeinds=[np.asarray([i])], point=self.part.location, num=2)
uarray2 = self.dataset.get_values('u', timeinds=[np.asarray([i+1])], point=self.part.location, num=2)
varray2 = self.dataset.get_values('v', timeinds=[np.asarray([i+1])], point=self.part.location, num=2)
if 'w' in self.dataset.nc.variables:
warray1 = self.dataset.get_values('w', timeinds=[np.asarray([i])], point=self.part.location, num=2)
warray2 = self.dataset.get_values('w', timeinds=[np.asarray([i+1])], point=self.part.location, num=2)
w = [warray1.mean(), warray2.mean()]
else:
w = [0.0, 0.0]
if self.temp_name != None and self.salt_name != None:
temparray1 = self.dataset.get_values('temp', timeinds=[np.asarray([i])], point=self.part.location, num=2)
saltarray1 = self.dataset.get_values('salt', timeinds=[np.asarray([i])], point=self.part.location, num=2)
temparray2 = self.dataset.get_values('temp', timeinds=[np.asarray([i+1])], point=self.part.location, num=2)
saltarray2 = self.dataset.get_values('salt', timeinds=[np.asarray([i+1])], point=self.part.location, num=2)
temp = [temparray1.mean(), temparray2.mean()]
salt = [saltarray1.mean(), saltarray2.mean()]
u = [uarray1.mean(), uarray2.mean()]
v = [varray1.mean(), varray2.mean()]
# Linear interp of data between timesteps
currenttime = date2num(currenttime)
timevar = timevar.datenum
u = self.linterp(timevar[i:i+2], u, currenttime)
v = self.linterp(timevar[i:i+2], v, currenttime)
w = self.linterp(timevar[i:i+2], w, currenttime)
if self.temp_name != None and self.salt_name != None:
temp = self.linterp(timevar[i:i+2], temp, currenttime)
salt = self.linterp(timevar[i:i+2], salt, currenttime)
if self.temp_name is None:
temp = np.nan
if self.salt_name is None:
salt = np.nan
#logger.info(self.dataset.get_xyind_from_point('u', self.part.location, num=1))
except StandardError:
logger.error("Error in data_interp method on ForceParticle")
raise
finally:
self.dataset.closenc()
with self.read_lock:
self.read_count.value -= 1
self.has_read_lock.remove(os.getpid())
return u, v, w, temp, salt
def data_nearest(self, i, currenttime):
"""
Method to streamline request for data from cache,
Uses nearest time to get u,v,w,temp,salt
"""
if self.active.value == True:
while self.get_data.value == True:
logger.debug("Waiting for DataController to release cache file so I can read from it...")
timer.sleep(4)
pass
if self.need_data(i):
# Acquire lock for asking for data
self.data_request_lock.acquire()
self.has_data_request_lock.value = os.getpid()
try:
if self.need_data(i):
with self.read_lock:
self.read_count.value += 1
self.has_read_lock.append(os.getpid())
# Open netcdf file on disk from commondataset
self.dataset.opennc()
# Get the indices for the current particle location
indices = self.dataset.get_indices('u', timeinds=[np.asarray([i-1])], point=self.part.location )
self.dataset.closenc()
with self.read_lock:
self.read_count.value -= 1
self.has_read_lock.remove(os.getpid())
# Override the time
self.point_get.value = [indices[0]+1, indices[-2], indices[-1]]
# Request that the data controller update the cache
# DATA CONTOLLER STARTS
self.get_data.value = True
# Wait until the data controller is done
if self.active.value == True:
while self.get_data.value == True:
logger.debug("Waiting for DataController to update cache...")
timer.sleep(4)
pass
except StandardError:
raise
finally:
self.has_data_request_lock.value = -1
self.data_request_lock.release()
# Tell the DataController that we are going to be reading from the file
with self.read_lock:
self.read_count.value += 1
self.has_read_lock.append(os.getpid())
try:
# Open netcdf file on disk from commondataset
self.dataset.opennc()
# Grab data at time index closest to particle location
u = np.mean(np.mean(self.dataset.get_values('u', timeinds=[np.asarray([i])], point=self.part.location )))
v = np.mean(np.mean(self.dataset.get_values('v', timeinds=[np.asarray([i])], point=self.part.location )))
# if there is vertical velocity inthe dataset, get it
if 'w' in self.dataset.nc.variables:
w = np.mean(np.mean(self.dataset.get_values('w', timeindsf=[np.asarray([i])], point=self.part.location )))
else:
w = 0.0
# If there is salt and temp in the dataset, get it
if self.temp_name != None and self.salt_name != None:
temp = np.mean(np.mean(self.dataset.get_values('temp', timeinds=[np.asarray([i])], point=self.part.location )))
salt = np.mean(np.mean(self.dataset.get_values('salt', timeinds=[np.asarray([i])], point=self.part.location )))
# Check for nans that occur in the ocean (happens because
# of model and coastline resolution mismatches)
if np.isnan(u).any() or np.isnan(v).any() or np.isnan(w).any():
# Take the mean of the closest 4 points
# If this includes nan which it will, result is nan
uarray1 = self.dataset.get_values('u', timeinds=[np.asarray([i])], point=self.part.location, num=2)
varray1 = self.dataset.get_values('v', timeinds=[np.asarray([i])], point=self.part.location, num=2)
if 'w' in self.dataset.nc.variables:
warray1 = self.dataset.get_values('w', timeinds=[np.asarray([i])], point=self.part.location, num=2)
w = warray1.mean()
else:
w = 0.0
if self.temp_name != None and self.salt_name != None:
temparray1 = self.dataset.get_values('temp', timeinds=[np.asarray([i])], point=self.part.location, num=2)
saltarray1 = self.dataset.get_values('salt', timeinds=[np.asarray([i])], point=self.part.location, num=2)
temp = temparray1.mean()
salt = saltarray1.mean()
u = uarray1.mean()
v = varray1.mean()
if self.temp_name is None:
temp = np.nan
if self.salt_name is None:
salt = np.nan
#logger.info(self.dataset.get_xyind_from_point('u', self.part.location, num=1))
except StandardError:
logger.error("Error in data_nearest on ForceParticle")
raise
finally:
self.dataset.closenc()
with self.read_lock:
self.read_count.value -= 1
self.has_read_lock.remove(os.getpid())
return u, v, w, temp, salt
def __call__(self, proc, active):
self.active = active
if self.usebathy == True:
self._bathymetry = Bathymetry(file=self.bathy)
self._shoreline = None
if self.useshore == True:
self._shoreline = Shoreline(file=self.shoreline_path, point=self.release_location_centroid, spatialbuffer=0.25)
# Make sure we are not starting on land. Raises exception if we are.
self._shoreline.intersect(start_point=self.release_location_centroid, end_point=self.release_location_centroid)
self.proc = proc
part = self.part
if self.active.value == True:
while self.get_data.value == True:
logger.debug("Waiting for DataController to start...")
timer.sleep(10)
pass
# Initialize commondataset of local cache, then
# close the related netcdf file
try:
with self.read_lock:
self.read_count.value += 1
self.has_read_lock.append(os.getpid())
self.dataset = CommonDataset.open(self.localpath)
self.dataset.closenc()
except StandardError:
logger.warn("No cache file: %s. Particle exiting" % self.localpath)
raise
finally:
with self.read_lock:
self.read_count.value -= 1
self.has_read_lock.remove(os.getpid())
# Calculate datetime at every timestep
modelTimestep, newtimes = AsaTransport.get_time_objects_from_model_timesteps(self.times, start=self.start_time)
# Load Timevar from pickle serialization
f = open(self.timevar_pickle_path,"rb")
timevar = pickle.load(f)
f.close()
if self.time_method == 'interp':
time_indexs = timevar.nearest_index(newtimes, select='before')
elif self.time_method == 'nearest':
time_indexs = timevar.nearest_index(newtimes)
else:
logger.warn("Method for computing u,v,w,temp,salt not supported!")
try:
assert len(newtimes) == len(time_indexs)
except AssertionError:
logger.error("Time indexes are messed up. Need to have equal datetime and time indexes")
raise
# loop over timesteps
# We don't loop over the last time_index because
# we need to query in the time_index and set the particle's
# location as the 'newtime' object.
for loop_i, i in enumerate(time_indexs[0:-1]):
if self.active.value == False:
raise ValueError("Particle exiting due to Failure.")
newloc = None
# if need a time that is outside of what we have
#if self.active.value == True:
# while self.get_data.value == True:
# logger.info("Waiting for DataController to get out...")
# timer.sleep(4)
# pass
# Get the variable data required by the models
if self.time_method == 'nearest':
u, v, w, temp, salt = self.data_nearest(i, newtimes[loop_i])
elif self.time_method == 'interp':
u, v, w, temp, salt = self.data_interp(i, timevar, newtimes[loop_i])
else:
logger.warn("Method for computing u,v,w,temp,salt not supported!")
#logger.info("U: %.4f, V: %.4f, W: %.4f" % (u,v,w))
#logger.info("Temp: %.4f, Salt: %.4f" % (temp,salt))
# Get the bathy value at the particles location
if self.usebathy == True:
bathymetry_value = self._bathymetry.get_depth(part.location)
else:
bathymetry_value = -999999999999999
# Age the particle by the modelTimestep (seconds)
# 'Age' meaning the amount of time it has been forced.
part.age(seconds=modelTimestep[loop_i])
# loop over models - sort these in the order you want them to run
for model in self.models:
movement = model.move(part, u, v, w, modelTimestep[loop_i], temperature=temp, salinity=salt, bathymetry_value=bathymetry_value)
newloc = Location4D(latitude=movement['latitude'], longitude=movement['longitude'], depth=movement['depth'], time=newtimes[loop_i+1])
logger.debug("%s - moved %.3f meters (horizontally) and %.3f meters (vertically) by %s with data from %s" % (part.logstring(), movement['distance'], movement['vertical_distance'], model.__class__.__name__, newtimes[loop_i].isoformat()))
if newloc:
self.boundary_interaction(particle=part, starting=part.location, ending=newloc,
distance=movement['distance'], angle=movement['angle'],
azimuth=movement['azimuth'], reverse_azimuth=movement['reverse_azimuth'],
vertical_distance=movement['vertical_distance'], vertical_angle=movement['vertical_angle'])
logger.debug("%s - was forced by %s and is now at %s" % (part.logstring(), model.__class__.__name__, part.location.logstring()))
part.note = part.outputstring()
# Each timestep, save the particles status and environmental variables.
# This keep fields such as temp, salt, halted, settled, and dead matched up with the number of timesteps
part.save()
# We won't pull data for the last entry in locations, but we need to populate it with fill data.
part.fill_environment_gap()
if self.usebathy == True:
self._bathymetry.close()
if self.useshore == True:
self._shoreline.close()
return part
def boundary_interaction(self, **kwargs):
"""
Returns a list of Location4D objects
"""
particle = kwargs.pop('particle')
starting = kwargs.pop('starting')
ending = kwargs.pop('ending')
# shoreline
if self.useshore:
intersection_point = self._shoreline.intersect(start_point=starting.point, end_point=ending.point)
if intersection_point:
# Set the intersection point.
hitpoint = Location4D(point=intersection_point['point'], time=starting.time + (ending.time - starting.time))
particle.location = hitpoint
# This relies on the shoreline to put the particle in water and not on shore.
resulting_point = self._shoreline.react(start_point=starting,
end_point=ending,
hit_point=hitpoint,
reverse_distance=self.reverse_distance,
feature=intersection_point['feature'],
distance=kwargs.get('distance'),
angle=kwargs.get('angle'),
azimuth=kwargs.get('azimuth'),
reverse_azimuth=kwargs.get('reverse_azimuth'))
ending.latitude = resulting_point.latitude
ending.longitude = resulting_point.longitude
ending.depth = resulting_point.depth
logger.debug("%s - hit the shoreline at %s. Setting location to %s." % (particle.logstring(), hitpoint.logstring(), ending.logstring()))
# bathymetry
if self.usebathy:
if not particle.settled:
bintersect = self._bathymetry.intersect(start_point=starting, end_point=ending)
if bintersect:
pt = self._bathymetry.react(type='reverse', start_point=starting, end_point=ending)
logger.debug("%s - hit the bottom at %s. Setting location to %s." % (particle.logstring(), ending.logstring(), pt.logstring()))
ending.latitude = pt.latitude
ending.longitude = pt.longitude
ending.depth = pt.depth
# sea-surface
if self.usesurface:
if ending.depth > 0:
#logger.debug("%s - rose out of the water. Setting depth to 0." % particle.logstring())
ending.depth = 0
particle.location = ending
return