def __init__(self,
release_time=None,
start_position=None,
plume_data=None,
end_release_time=None,
**kwargs):
'''
:param num_elements: total number of elements to be released
:type num_elements: integer
:param start_position: initial location the elements are released
:type start_position: 3-tuple of floats (long, lat, z)
:param release_time: time the LEs are released
:type release_time: datetime.datetime
:param start_positions: locations the LEs are released
:type start_positions: (num_elements, 3) numpy array of float64
-- (long, lat, z)
'''
super(VerticalPlumeRelease, self).__init__(release_time=release_time,
**kwargs)
self.start_position = np.array(start_position,
dtype=world_point_type).reshape((3, ))
plume = Plume(position=start_position, plume_data=plume_data)
time_step_delta = timedelta(hours=1).total_seconds()
self.plume_gen = PlumeGenerator(release_time=release_time,
end_release_time=end_release_time,
time_step_delta=time_step_delta,
plume=plume)
if self.num_elements:
self.plume_gen.set_le_mass_from_total_le_count(self.num_elements)
def __init__(self, release_time, num_elements, start_position,
plume_data, end_release_time, name=None):
'''
:param num_elements: total number of elements to be released
:type num_elements: integer
:param start_position: initial location the elements are released
:type start_position: 3-tuple of floats (long, lat, z)
:param release_time: time the LEs are released
:type release_time: datetime.datetime
:param start_positions: locations the LEs are released
:type start_positions: (num_elements, 3) numpy array of float64
-- (long, lat, z)
'''
super(VerticalPlumeRelease, self).__init__(release_time,
num_elements, name)
self.start_position = np.array(start_position,
dtype=world_point_type).reshape((3, ))
plume = Plume(position=start_position, plume_data=plume_data)
time_step_delta = timedelta(hours=1).total_seconds()
self.plume_gen = PlumeGenerator(release_time=release_time,
end_release_time=end_release_time,
time_step_delta=time_step_delta,
plume=plume)
if self.num_elements:
self.plume_gen.set_le_mass_from_total_le_count(self.num_elements)
class VerticalPlumeRelease(Release, Serializable):
'''
An Underwater Plume spill class -- a continuous release of particles,
controlled by a contained spill generator object.
- plume model generator will have an iteration method. This will provide
flexible looping and list comprehension behavior.
'''
_state = copy.deepcopy(Release._state)
# what kinds of customized state attributes would we like to add here?
# _state.add(update=['start_position'], save=['start_position'])
def __init__(self, release_time, num_elements, start_position,
plume_data, end_release_time, name=None):
'''
:param num_elements: total number of elements to be released
:type num_elements: integer
:param start_position: initial location the elements are released
:type start_position: 3-tuple of floats (long, lat, z)
:param release_time: time the LEs are released
:type release_time: datetime.datetime
:param start_positions: locations the LEs are released
:type start_positions: (num_elements, 3) numpy array of float64
-- (long, lat, z)
'''
super(VerticalPlumeRelease, self).__init__(release_time,
num_elements, name)
self.start_position = np.array(start_position,
dtype=world_point_type).reshape((3, ))
plume = Plume(position=start_position, plume_data=plume_data)
time_step_delta = timedelta(hours=1).total_seconds()
self.plume_gen = PlumeGenerator(release_time=release_time,
end_release_time=end_release_time,
time_step_delta=time_step_delta,
plume=plume)
if self.num_elements:
self.plume_gen.set_le_mass_from_total_le_count(self.num_elements)
def _plume_elem_coords(self, current_time, time_step):
'''
Return a list of positions for all elements released within
current_time + time_step
'''
next_time = current_time + timedelta(seconds=time_step)
elem_counts = self.plume_gen.elems_in_range(current_time, next_time)
for coord, count in zip(self.plume_gen.plume.coords, elem_counts):
for c in (coord,) * count:
yield tuple(c)
def num_elements_to_release(self, current_time, time_step):
'''
Return number of particles released in current_time + time_step
'''
return len([e for e in self._plume_elem_coords(current_time,
time_step)])
def set_newparticle_positions(self, num_new_particles,
current_time, time_step, data_arrays):
'''
Set positions for new elements added by the SpillContainer
'''
coords = [e for e in self._plume_elem_coords(current_time, time_step)]
self.coords = np.asarray(tuple(coords),
dtype=world_point_type).reshape((-1, 3))
if self.coords.shape[0] != num_new_particles:
raise RuntimeError('The Specified number of new particals does not'
' match the number calculated from the '
'time range.')
self.num_released += num_new_particles
data_arrays['positions'][-self.coords.shape[0]:, :] = self.coords
class VerticalPlumeRelease(Release):
'''
An Underwater Plume spill class -- a continuous release of particles,
controlled by a contained spill generator object.
- plume model generator will have an iteration method. This will provide
flexible looping and list comprehension behavior.
'''
def __init__(self,
release_time=None,
start_position=None,
plume_data=None,
end_release_time=None,
**kwargs):
'''
:param num_elements: total number of elements to be released
:type num_elements: integer
:param start_position: initial location the elements are released
:type start_position: 3-tuple of floats (long, lat, z)
:param release_time: time the LEs are released
:type release_time: datetime.datetime
:param start_positions: locations the LEs are released
:type start_positions: (num_elements, 3) numpy array of float64
-- (long, lat, z)
'''
super(VerticalPlumeRelease, self).__init__(release_time=release_time,
**kwargs)
self.start_position = np.array(start_position,
dtype=world_point_type).reshape((3, ))
plume = Plume(position=start_position, plume_data=plume_data)
time_step_delta = timedelta(hours=1).total_seconds()
self.plume_gen = PlumeGenerator(release_time=release_time,
end_release_time=end_release_time,
time_step_delta=time_step_delta,
plume=plume)
if self.num_elements:
self.plume_gen.set_le_mass_from_total_le_count(self.num_elements)
def _plume_elem_coords(self, current_time, time_step):
'''
Return a list of positions for all elements released within
current_time + time_step
'''
next_time = current_time + timedelta(seconds=time_step)
elem_counts = self.plume_gen.elems_in_range(current_time, next_time)
for coord, count in zip(self.plume_gen.plume.coords, elem_counts):
for c in (coord, ) * count:
yield tuple(c)
def num_elements_to_release(self, current_time, time_step):
'''
Return number of particles released in current_time + time_step
'''
return len(
[e for e in self._plume_elem_coords(current_time, time_step)])
def set_newparticle_positions(self, num_new_particles, current_time,
time_step, data_arrays):
'''
Set positions for new elements added by the SpillContainer
'''
coords = [e for e in self._plume_elem_coords(current_time, time_step)]
self.coords = np.asarray(tuple(coords),
dtype=world_point_type).reshape((-1, 3))
if self.coords.shape[0] != num_new_particles:
raise RuntimeError('The Specified number of new particals does not'
' match the number calculated from the '
'time range.')
self.num_released += num_new_particles
data_arrays['positions'][-self.coords.shape[0]:, :] = self.coords
