def test_network_sim():
"""
Test single trajectory without using simtypes
"""
session, net = tools.db.get_network(45)
handler = erfs.MeanfieldHandler(net)
# somewhat legacy parameters for this test run
std_pars = {
"show_results": False,
"id": net.id,
"sig_start": 0.,
# noise parameters
mpr.W_NOISE: 0., # sigma_w
mpr.EL_NOISE: 0., # = sigma_L
mpr.P_EE: 0.5, # recurrent connectivity p
"cores": 4, # cores to use for sim
"sig_center": 0.3,
"sig_len": 1000.,
"sig_weight": .4,
"sig_width": .2,
"sig_rate": 2000.,
"base_seed_run": 25757712619,
"base_seed": 29529492,
# runtime
"tmax": 2000.,
}
handler.set_states({
mpr.W_J:
net.e.paramset.parameters['w_0'] + net.e.paramset.parameters['w_1']
})
sim = NestSimulator(handler, cores=4)
sim.set_paramset("bump")
sim.set_params("gen", **std_pars)
sim_ret = sim.run()
print "E-rate after offset: ", sim_ret["pop_rate"]["e"]
print "I-rate after offset: ", sim_ret["pop_rate"]["i"]
print "Averaged maximal E-rate after offset: ", max(sim_ret["shape_mean"])
np.testing.assert_almost_equal(sim_ret["pop_rate"]["e"],
6.07852487681,
decimal=10)
np.testing.assert_almost_equal(sim_ret["pop_rate"]["i"],
4.81666666667,
decimal=10)
np.testing.assert_almost_equal(max(sim_ret["shape_mean"]),
42.245566508,
decimal=10)
def test_simtype_drift():
"""Test the SimDrift simtype"""
session, net = tools.db.get_network(45)
# get meanfield handler (abstracts network parameter handling) and set connectivity parameter
handler = erfs.MeanfieldHandler(net)
# get simulation type
btype = session.query(cb.SimType).filter(cb.SimType.name == "drift").one()
# get simulation wrapper
# set to_memory = False to save simulation to hdf5 file
wrapper = btype.get_wrapper(to_memory=True, session=session)
reps = 1
initials = 2
tmax = 2000.
# parameters used for this example
gen_params = {
# noise parameters
mpr.EL_NOISE: 0.,
mpr.P_EE: 1., # 1mV of noise on the leak reversal potentials
mpr.W_NOISE: 0.,
# run parameters
"cores": 4, # cores to use for sim
"tmax": tmax, # runtime
"base_seed": 1, # seed for connectivity noise
"base_seed_run": 1, # seed for run noise
"reps": reps, # do only 1 repetition
"initials": initials
}
# run the simulation
wrapper.run(handler, **gen_params)
assert wrapper.data_file['dirs'].shape == (initials, reps, int(tmax))
np.testing.assert_array_almost_equal(
wrapper.data_file['dirs'][:, :, -1].flatten(),
[6.210974216461182, 396.7076110839844])
def test_simtype_bump():
"""Test the SimBump simtype"""
session, net = tools.db.get_network(45)
# get meanfield handler (abstracts network parameter handling) and set connectivity parameter
handler = erfs.MeanfieldHandler(net)
# get simulation type
btype = session.query(cb.SimType).filter(cb.SimType.name == "bump").one()
# get simulation wrapper
# set to_memory = False to save simulation to hdf5 file
wrapper = btype.get_wrapper(to_memory=True, session=session)
tmax = 2000.
# parameters used for this example
gen_params = {
# noise parameters
mpr.EL_NOISE: 0.,
mpr.P_EE: 1., # 1mV of noise on the leak reversal potentials
mpr.W_NOISE: 0.,
# run parameters
"cores": 4, # cores to use for sim
"tmax": tmax, # runtime
"base_seed": 1, # seed for connectivity noise
"base_seed_run": 1, # seed for run noise
"sig_center": 0.3, # center of signal
}
# run the simulation
wrapper.run(handler, **gen_params)
assert wrapper.data_file['dirs'].shape == (int(tmax),)
np.testing.assert_almost_equal(
wrapper.data_file['dirs'][-1],
239.6555633544922)
import matplotlib.pyplot as pl
import classes.base as cb
import meanfield.error_functions as erfs
import tools.db
from classes.static import MeanfieldParameters as mpr
# to show all network ids: tools.db.print_networks()
session, net = tools.db.get_network(48)
# get meanfield handler (abstracts network parameter handling) and set connectivity parameter
handler = erfs.MeanfieldHandler(net)
# get simulation type
btype = session.query(cb.SimType).filter(cb.SimType.name == "bump").one()
# get simulation wrapper
# set to_memory = False to save simulation to hdf5 file
wrapper = btype.get_wrapper(to_memory=True, session=session)
# parameters for simulation
sim_params = {
"cores": 4, # cores to use for sim
"sig_center": 0.3, # center of signal
"tmax": 8000., # runtime
"base_seed": 1, # seed for connectivity noise
"base_seed_run": 1, # seed for run noise
# network noise parameters
mpr.W_NOISE: 0., # sigma_w
mpr.EL_NOISE: 0., # = sigma_L
mpr.P_EE: 0.5, # recurrent connectivity p