def main(traj_limit=None):
# add script execution to infotaxis database
add_script_execution(script_id=SCRIPT_ID,
session=session,
multi_use=True,
notes=SCRIPT_NOTES)
session.commit()
# get wind tunnel connection and models
wt_session = imp.load_source('connect',
os.path.join(WT_REPO, 'db_api',
'connect.py')).session
wt_models = imp.load_source('models',
os.path.join(WT_REPO, 'db_api', 'models.py'))
for experiment_id in EXPERIMENT_IDS:
for odor_state in ODOR_STATES:
# make geom_config_group
geom_config_group_id = '{}_{}_odor_{}'.format(
GEOM_CONFIG_GROUP_ID, experiment_id, odor_state)
geom_config_group = session.query(
models.GeomConfigGroup).get(geom_config_group_id)
# make simulation
r = INSECT_PARAMS_DICT[experiment_id]['r']
d = INSECT_PARAMS_DICT[experiment_id]['d']
sim_id = SIMULATION_ID.format(r, d, experiment_id, odor_state)
sim_description = SIMULATION_DESCRIPTION.format(
experiment_id, odor_state)
sim = models.Simulation(id=sim_id, description=sim_description)
sim.env, sim.dt = ENV, DT
sim.heading_smoothing = 0
sim.geom_config_group = geom_config_group
# make plume
if 'fruitfly' in experiment_id:
pl = CollimatedPlume(env=ENV, dt=DT)
elif 'mosquito' in experiment_id:
pl = SpreadingGaussianPlume(env=ENV, dt=DT)
pl.set_params(**PLUME_PARAMS_DICT[experiment_id])
if odor_state in ('none', 'afterodor'):
pl.set_params(threshold=-1)
pl.initialize()
pl.generate_orm(models, sim=sim)
# make insect
ins = Insect(env=ENV, dt=DT)
ins.set_params(**INSECT_PARAMS_DICT[experiment_id])
ins.loglike_function = LOGLIKE
ins.initialize()
ins.generate_orm(models, sim=sim)
# add simulation and ongoing run
sim.ongoing_run = models.OngoingRun(trials_completed=0)
session.add(sim)
session.commit()
# loop through all geom_configs in group, look up corresponding trajectory,
# and discretize it
for gctr, geom_config in enumerate(geom_config_group.geom_configs):
# get trajectory id from geom_config and trajectory from wind tunnel database
traj_id = geom_config.extension_real_trajectory.real_trajectory_id
traj = wt_session.query(wt_models.Trajectory).get(traj_id)
# get positions from traj
positions = traj.positions(wt_session)
# create discretized version of trajectory
trial = TrialFromPositionSequence(positions, pl, ins)
# add timepoints to trial and generate data model
trial.add_timepoints(models,
session=session,
heading_smoothing=sim.heading_smoothing)
trial.generate_orm(models)
# bind simulation, geom_config
trial.orm.simulation = sim
trial.orm.geom_config = geom_config
# update ongoing run
sim.ongoing_run.trials_completed += 1
session.add(sim)
session.commit()
if traj_limit and (gctr == traj_limit - 1):
break
# update total number of trials
sim.total_trials = gctr + 1
session.add(sim)
session.commit()
def main(INSECT_PARAMS,
SCRIPTNOTES,
threshold=None,
sim_ids=None,
sim_descs=None,
expts=None,
odor_states=None,
traj_limit=None):
# add script execution to database
add_script_execution(SCRIPTID,
session=session,
multi_use=True,
notes=SCRIPTNOTES)
if expts is None:
expts = EXPERIMENTS
if odor_states is None:
odor_states = ODOR_STATES
for expt in expts:
if '0.3mps' in expt:
w = 0.3
elif '0.4mps' in expt:
w = 0.4
elif '0.6mps' in expt:
w = 0.6
insect_params = INSECT_PARAMS.copy()
insect_params['w'] = w
for odor_state in odor_states:
print('Running simulation for expt "{}" with odor "{}"...'.format(
expt, odor_state))
# get geom_config_group for this experiment and odor state
geom_config_group_id = GEOM_CONFIG_GROUP_ID.format(
expt, odor_state)
geom_config_group = session.query(
models.GeomConfigGroup).get(geom_config_group_id)
# get wind tunnel copy simulation so we can match plume and insect
# note we select the first simulation that is of this type and
# corresponds to the right geom_config_group, since we only use the
# plume from it, which is independent of insect parameters used
#
# for instance, the plume bound to a simulation in which the insect
# had D = 0.6 and that bound to a simulation where D = 0.4 will be
# the same, since it is only the insect's
# internal model that has changed
wt_copy_sims = session.query(models.Simulation).\
filter(models.Simulation.geom_config_group == geom_config_group).\
filter(models.Simulation.id.like(
WIND_TUNNEL_DISCRETIZED_SIMULATION_ID_PATTERN))
# get plume from corresponding discretized real wind tunnel trajectory
if 'fruitfly' in expt:
pl = CollimatedPlume(env=ENV,
dt=-1,
orm=wt_copy_sims.first().plume)
elif 'mosquito' in expt:
pl = SpreadingGaussianPlume(env=ENV,
dt=-1,
orm=wt_copy_sims.first().plume)
if threshold is not None:
print('Setting plume detectability threshold to '
'{}'.format(threshold))
pl.set_params(threshold=threshold)
# create insect
# note: we will actually make a new insect for each trial,
# since the dt's vary;
# here we set dt=-1, since this doesn't get stored in the db anyhow
ins = Insect(env=ENV, dt=-1)
ins.set_params(**insect_params)
ins.generate_orm(models)
# create simulation
if sim_ids is None:
sim_id = SIMULATION_ID.format(insect_params['r'],
insect_params['d'], expt,
odor_state)
else:
sim_id = sim_ids[(expt, odor_state)]
if sim_descs is None:
sim_desc = SIMULATION_DESCRIPTION.format(expt, odor_state)
else:
sim_desc = sim_descs[(expt, odor_state)]
sim = models.Simulation(id=sim_id, description=sim_desc)
sim.env = ENV
sim.dt = -1
sim.total_trials = len(geom_config_group.geom_configs)
sim.heading_smoothing = 0
sim.geom_config_group = geom_config_group
sim.plume = pl.orm
sim.insect = ins.orm
session.add(sim)
# create ongoing run
ongoing_run = models.OngoingRun(trials_completed=0,
simulations=[sim])
session.add(ongoing_run)
session.commit()
# generate trials
for gctr, geom_config in enumerate(geom_config_group.geom_configs):
if gctr == traj_limit:
break
# make new plume and insect with proper dts
ins = Insect(env=ENV,
dt=geom_config.extension_real_trajectory.avg_dt)
ins.set_params(**insect_params)
ins.loglike_function = LOGLIKE
# set insect starting position
ins.set_pos(geom_config.start_idx, is_idx=True)
# initialize plume and insect and create trial
pl.initialize()
ins.initialize()
trial = Trial(pl=pl, ins=ins, nsteps=geom_config.duration)
# run trial
for step in xrange(geom_config.duration - 1):
trial.step()
# save trial
trial.add_timepoints(models,
session=session,
heading_smoothing=sim.heading_smoothing)
trial.generate_orm(models)
trial.orm.geom_config = geom_config
trial.orm.simulation = sim
session.add(trial.orm)
# update ongoing_run
ongoing_run.trials_completed = gctr + 1
session.add(ongoing_run)
session.commit()
def main(traj_limit=None):
# add script execution to database
add_script_execution(SCRIPTID, session=session, multi_use=True, notes=SCRIPTNOTES)
for expt in EXPERIMENTS:
if '0.3mps' in expt:
w = 0.3
elif '0.4mps' in expt:
w = 0.4
elif '0.6mps' in expt:
w = 0.6
insect_params = INSECT_PARAMS.copy()
insect_params['w'] = w
for odor_state in ODOR_STATES:
print('Running simulation for expt "{}" with odor "{}"...'.
format(expt, odor_state))
# get geom_config_group for this experiment and odor state
geom_config_group_id = GEOM_CONFIG_GROUP_ID.format(expt, odor_state)
geom_config_group = session.query(models.GeomConfigGroup).get(geom_config_group_id)
# get wind tunnel copy simulation so we can match plume and insect
# note we select the first simulation that is of this type and corresponds to the
# right geom_config_group, since we only use the plume from it, which is independent
# of what insect parameters were used
#
# for instance, the plume bound to a simulation in which the insect had D = 0.6 and that
# bound to a simulation where D = 0.4 will be the same, since it is only the insect's
# internal model that has changed
wt_copy_sims = session.query(models.Simulation).\
filter(models.Simulation.geom_config_group == geom_config_group).\
filter(models.Simulation.id.like(WIND_TUNNEL_DISCRETIZED_SIMULATION_ID_PATTERN))
# get plume from corresponding discretized real wind tunnel trajectory
if 'fruitfly' in expt:
pl = CollimatedPlume(env=ENV, dt=-1, orm=wt_copy_sims.first().plume)
elif 'mosquito' in expt:
pl = SpreadingGaussianPlume(env=ENV, dt=-1, orm=wt_copy_sims.first().plume)
# create insect
# note: we will actually make a new insect for each trial, since the dt's vary;
# here we just set dt=-1, since this doesn't get stored in the db anyhow
ins = Insect(env=ENV, dt=-1)
ins.set_params(**insect_params)
ins.generate_orm(models)
# create simulation
sim_id = SIMULATION_ID.format(insect_params['r'],
insect_params['d'],
expt, odor_state)
sim_desc = SIMULATION_DESCRIPTION.format(expt, odor_state)
sim = models.Simulation(id=sim_id, description=sim_desc)
sim.env = ENV
sim.dt = -1
sim.total_trials = len(geom_config_group.geom_configs)
sim.heading_smoothing = 0
sim.geom_config_group = geom_config_group
sim.plume = pl.orm
sim.insect = ins.orm
session.add(sim)
# create ongoing run
ongoing_run = models.OngoingRun(trials_completed=0, simulations=[sim])
session.add(ongoing_run)
session.commit()
# generate trials
for gctr, geom_config in enumerate(geom_config_group.geom_configs):
if gctr == traj_limit:
break
# make new plume and insect with proper dts
ins = Insect(env=ENV, dt=geom_config.extension_real_trajectory.avg_dt)
ins.set_params(**insect_params)
ins.loglike_function = LOGLIKE
# set insect starting position
ins.set_pos(geom_config.start_idx, is_idx=True)
# initialize plume and insect and create trial
pl.initialize()
ins.initialize()
trial = Trial(pl=pl, ins=ins, nsteps=geom_config.duration)
# run trial
for step in xrange(geom_config.duration - 1):
trial.step()
# save trial
trial.add_timepoints(models, session=session, heading_smoothing=sim.heading_smoothing)
trial.generate_orm(models)
trial.orm.geom_config = geom_config
trial.orm.simulation = sim
session.add(trial.orm)
# update ongoing_run
ongoing_run.trials_completed = gctr + 1
session.add(ongoing_run)
session.commit()
