def initialize(self, num_new_particles, spill, data_arrays, substance):
"""
Update values of 'rise_vel' and 'droplet_diameter' data arrays for
new particles. First create a droplet_size array sampled from specified
distribution, then use the cython wrapped (C++) function to set the
'rise_vel' based on droplet size and properties like LE_density,
water density and water_viscosity:
gnome.cy_gnome.cy_rise_velocity_mover.rise_velocity_from_drop_size()
"""
drop_size = np.zeros((num_new_particles, ), dtype=np.float64)
le_density = np.zeros((num_new_particles, ), dtype=np.float64)
self.distribution.set_values(drop_size)
data_arrays['droplet_diameter'][-num_new_particles:] = drop_size
# Don't require a water object
# water_temp = spill.water.get('temperature')
# le_density[:] = substance.density_at_temp(water_temp)
if spill.water is not None:
water_temp = spill.water.get('temperature')
le_density[:] = substance.density_at_temp(water_temp)
else:
le_density[:] = substance.density_at_temp()
# now update rise_vel with droplet size - dummy for now
rise_velocity_from_drop_size(
data_arrays['rise_vel'][-num_new_particles:],
le_density, drop_size,
self.water_viscosity, self.water_density)
def initialize(self, num_new_particles, spill, data_arrays, substance):
"""
Update values of 'rise_vel' and 'droplet_diameter' data arrays for
new particles. First create a droplet_size array sampled from specified
distribution, then use the cython wrapped (C++) function to set the
'rise_vel' based on droplet size and properties like LE_density,
water density and water_viscosity:
gnome.cy_gnome.cy_rise_velocity_mover.rise_velocity_from_drop_size()
"""
drop_size = np.zeros((num_new_particles, ), dtype=np.float64)
le_density = np.zeros((num_new_particles, ), dtype=np.float64)
self.distribution.set_values(drop_size)
data_arrays['droplet_diameter'][-num_new_particles:] = drop_size
# Don't require a water object
# water_temp = spill.water.get('temperature')
# le_density[:] = substance.density_at_temp(water_temp)
if spill.water is not None:
water_temp = spill.water.get('temperature')
le_density[:] = substance.density_at_temp(water_temp)
else:
le_density[:] = substance.density_at_temp()
# now update rise_vel with droplet size - dummy for now
rise_velocity_from_drop_size(
data_arrays['rise_vel'][-num_new_particles:], le_density,
drop_size, self.water_viscosity, self.water_density)
def set_newparticle_values(self, num_new_particles, current_time,
time_step, data_arrays):
"""
SpillContainer will release elements and initialize all data_arrays
to default initial value. The SpillContainer gets passed as input and
the data_arrays for 'position' get initialized correctly by the release
object: self.release.set_newparticle_positions()
If a Spill Amount is given, the Spill object also sets the 'mass' data
array; else 'mass' array remains '0'
:param int num_new_particles: number of new particles that were added.
Always greater than 0
:param current_time: current time
:type current_time: datetime.datetime
:param time_step: the time step, sometimes used to decide how many
should get released.
:type time_step: integer seconds
:param data_arrays: dict of data_arrays provided by the SpillContainer.
Look for 'positions' array in the dict and update positions for
latest num_new_particles that are released
:type data_arrays: dict containing numpy arrays for values
Also, the set_newparticle_values() method for all element_type gets
called so each element_type sets the values for its own data correctly
"""
mass_fluxes = [tam_drop.mass_flux for tam_drop in self.droplets]
delta_masses, proportions, total_mass = self._get_mass_distribution(mass_fluxes, time_step)
# set up LE distribution, the number of particles in each 'release point'
LE_distribution = [int(num_new_particles * p) for p in proportions]
diff = num_new_particles - sum(LE_distribution)
for i in range(0, diff):
LE_distribution[i % len(LE_distribution)] += 1
# compute release point location for each droplet
positions = [self.start_position + FlatEarthProjection.meters_to_lonlat(d.position, self.start_position) for d in self.droplets]
for p in positions:
p[0][2] -= self.start_position[2]
# for each release location, set the position and mass of the elements released at that location
total_rel = 0
for mass_dist, n_LEs, pos, droplet in zip(delta_masses, LE_distribution, positions, self.droplets):
start_idx = -num_new_particles + total_rel
if start_idx == 0:
break
end_idx = start_idx + n_LEs
if end_idx == 0:
end_idx = None
# print '{0} to {1}'.format(start_idx, end_idx)
if start_idx == end_idx:
continue
data_arrays['positions'][start_idx:end_idx] = pos
data_arrays['mass'][start_idx:end_idx] = mass_dist / n_LEs
data_arrays['init_mass'][start_idx:end_idx] = mass_dist / n_LEs
data_arrays['density'][start_idx:end_idx] = droplet.density
data_arrays['droplet_diameter'][start_idx:end_idx] = np.random.normal(droplet.radius * 2, droplet.radius * 0.15, (n_LEs))
v = data_arrays['rise_vel'][start_idx:end_idx]
rise_velocity_from_drop_size(v,
data_arrays['density'][start_idx:end_idx],
data_arrays['droplet_diameter'][start_idx:end_idx],
0.0000013, 1020)
data_arrays['rise_vel'][start_idx:end_idx] = v
total_rel += n_LEs
self.num_released += num_new_particles
self.amount_released += total_mass
