def test_general_interface():
# Settings:
t0 = 0.
dt = .001
tf = .01
# Run simulation:
b1 = ODE(lambda y, t:(100-t)/.1)
i1 = PopulationInterface()
b1_i1 = Connection(b1, i1, 1, weights=.005)
network = Network([b1, i1], [b1_i1])
network.run(dt, tf=tf, t0=t0)
np.testing.assert_almost_equal(b1.curr_firing_rate, 9.99949999997, 10)
def test_delay_distribution():
# Settings:
t0 = 0.
dt = .001
tf = .1
# Create populations:
b1 = ExternalPopulation('100*Heaviside(t)')
i1 = InternalPopulation(v_min=0, v_max=.02, dv=.001, update_method='exact')
# Create connections:
b1_i1 = Connection(b1, i1, 1, weights=.005, delays=((0,.05),(.5,.5)))
# Create and run simulation:
simulation = Network([b1, i1], [b1_i1])
simulation.run(dt=dt, tf=tf, t0=t0)
true_ans = np.array([0.38560647739319964, 5.229266329159536])
np.testing.assert_almost_equal(np.array(i1.get_firing_rate([.04, .09])), true_ans, 8)
def test_general_interface():
# Settings:
t0 = 0.
dt = .001
tf = .01
# Run simulation:
b1 = ODE(lambda y, t:(100-t)/.1)
i1 = PopulationInterface()
b1_i1 = Connection(b1, i1, 1, weights=.005)
network = Network([b1, i1], [b1_i1])
network.run(dt, tf=tf, t0=t0)
# Tests:
final_firing_rate = 9.99949999997
np.testing.assert_almost_equal(b1.curr_firing_rate, final_firing_rate, 10)
np.testing.assert_almost_equal(i1.source_firing_rate_dict[0], final_firing_rate, 10)
assert len(i1.source_connection_list) == 1
assert i1.source_connection_list[0] == b1_i1
def test_delay_singlepop():
# Settings:
t0 = 0.
dt = .001
tf = .005
# Create simulation:
b1 = ExternalPopulation('Heaviside(t)*100')
i1 = InternalPopulation(v_min=0, v_max=.02, dv=.001, update_method='exact')
b1_i1 = Connection(b1, i1, 1, weights=.005, delays=2*dt, delay_queue=[0,0,50])
# # DEBUG:
# b1_i1 = Connection(b1, i1, 1, weights=.005, delays=((0,.001, .002),(0,0,1.)), delay_queue=[0,0,50])
simulation = Network([b1, i1], [b1_i1])
simulation.run(dt=dt, tf=tf, t0=t0)
true_ans = np.array([0, 0.0, 0.0, 0.00066516669656511084, 0.025842290308637855, 0.08117342489138904])
np.testing.assert_almost_equal(i1.firing_rate_record, true_ans, 12)
def test_restart_interal():
# Run part-way and serialize:
b1 = ExternalPopulation('100', record=True)
i1 = InternalPopulation(v_min=0, v_max=.02, dv=.001)
b1_i1 = Connection(b1, i1, 1, weights=.005, delays=0.0)
simulation = Network([b1, i1], [b1_i1])
simulation.run(dt=.001, tf=.01, t0=0)
i1_str = i1.to_json()
b1_str = b1.to_json()
# Rehydrate and continue run:
b2 = ExternalPopulation(**json.loads(b1_str))
i2 = InternalPopulation(**json.loads(i1_str))
simulation2 = Network([b2, i2], [Connection(b2, i2, 1, weights=.005, delays=0.0)])
simulation2.run(dt=.001, tf=.02, t0=.01)
# Run straight through, for comparison:
b3 = ExternalPopulation('100', record=True)
i3 = InternalPopulation(v_min=0, v_max=.02, dv=.001)
simulation3 = Network([b3, i3], [Connection(b3, i3, 1, weights=.005, delays=0.0)])
simulation3.run(dt=.001, tf=.02, t0=0)
# Test:
for y1, y2 in zip(i1.firing_rate_record, i3.firing_rate_record):
np.testing.assert_almost_equal(y1, y2, 8)
b3.to_json(StringIO.StringIO())
i3.to_json(StringIO.StringIO())
b1_i1.to_json(StringIO.StringIO())
def test_general_interface():
# Settings:
t0 = 0.
dt = .001
tf = .01
# Run simulation:
b1 = ODE(lambda y, t: (100 - t) / .1)
i1 = PopulationInterface()
b1_i1 = Connection(b1, i1, 1, weights=.005)
network = Network([b1, i1], [b1_i1])
network.run(dt, tf=tf, t0=t0)
# Tests:
final_firing_rate = 9.99949999997
np.testing.assert_almost_equal(b1.curr_firing_rate, final_firing_rate, 10)
np.testing.assert_almost_equal(i1.source_firing_rate_dict[0],
final_firing_rate, 10)
assert len(i1.source_connection_list) == 1
assert i1.source_connection_list[0] == b1_i1
def test_delay_doublepop():
# Settings:
t0 = 0.
dt = .001
tf = .010
# Create populations:
b1 = ExternalPopulation(50)
i1 = InternalPopulation(v_min=0, v_max=.02, dv=.001, update_method='exact')
i2 = InternalPopulation(v_min=0, v_max=.02, dv=.001, update_method='exact')
# Create connections:
b1_i1 = Connection(b1, i1, 2, weights=.005)
i1_i2 = Connection(i1, i2, 20, weights=.005, delays=2*dt)
# Create and run simulation:
simulation = Network([b1, i1, i2], [b1_i1, i1_i2])
simulation.run(dt=dt, tf=tf, t0=t0)
true_ans = np.array([0, 0.0, 0.0, 0.0, 1.9089656152757652e-13, 1.9787511418980406e-10, 9.5007650186649266e-09, 1.3334881090883857e-07, 1.0103767575651715e-06, 5.3604521936092067e-06, 2.2383604753409621e-05])
np.testing.assert_almost_equal(i2.firing_rate_record, true_ans, 12)
def run(simulation_dict, run_dict, result_dict, rank=None):
t0 = run_dict['t0']
dt = run_dict['dt']
tf = run_dict['tf']
number_of_processes = run_dict.get('number_of_processes', 1)
simulation = Network(**simulation_dict)
if rank is None:
simulation.run(dt=dt, tf=tf, t0=t0)
else:
address_config_dict = {}
rank_address_function = lambda rank:"ipc://%s" % (5559+rank)
for ii in range(number_of_processes):
address_config_dict[ii] = rank_address_function(ii)
simulation.run(dt=dt, tf=tf, t0=t0, synchronization_harness=SynchronizationHarness(rank, address_config_dict, number_of_processes))
result_dict[rank] = {}
for p in simulation.population_list:
result_dict[rank][p.gid] = p.firing_rate_record
from dipde.visualization import visualize
dv = .0001
update_method = 'approx'
approx_order = 1
tol = 1e-14
b1 = ExternalPopulation('100', record=True)
i1 = InternalPopulation(v_min=0,
v_max=.02,
dv=dv,
update_method=update_method,
approx_order=approx_order,
tol=tol)
i2 = InternalPopulation(v_min=0,
v_max=.02,
dv=dv,
update_method=update_method,
approx_order=approx_order,
tol=tol)
b1_i1 = Connection(b1, i1, 1, weights=.005, delays=0.0)
b1_i2 = Connection(b1, i2, 2, weights=.005, delays=0.0)
network = Network([b1, i1, i2], [b1_i1, b1_i2])
network.run(dt=.0001, tf=.1, t0=0)
print i1.get_firing_rate(.1)
visualize(network, show=True)
print network.to_dict()
#
#
b1 = ExternalPopulation(bgfr, record=False)
i1 = InternalPopulation(tau_m=.05, v_min=0, v_max=1, dv=dv, update_method = 'gmres')
# i1 = InternalPopulation(tau_m=.05, v_min=0, v_max=1, dv=dv, update_method = 'gmres', p0=(i_tmp.edges.tolist(), p0), initial_firing_rate=f0)
b1_i1 = Connection(b1, i1, nsyn_bg, weights=weight, delays=0.0)
i1_i1 = Connection(i1, i1, nsyn_recc, weights=weight, delays=0.0)
#
# be = ExternalPopulation(get_infinitesimal_perturbation(.1,.0005,.001), record=False)
# be_i1 = Connection(be, i1, 1, weights=weight, delays=0.0)
#
#
def chirp_fcn(n):
print n.t, ss_fr, n.population_list[1].curr_firing_rate
network = Network([b1, i1], [b1_i1, i1_i1], update_callback=chirp_fcn)
network.run(tf=5, dt=.0001)
i1.plot()
plt.show()
# def chirp(n):
# print n.t
#
# network = Network([b1, i1], [b1_i1, i1_i1], update_callback=chirp)
# network.run(tf=5, dt=.0001)
#
# ss_fr = i1.firing_rate_record[-1]
#
# # print ss_fr
# i1.plot()
# plt.show()
b4_i4 = Connection(b4, i4, 1, weights=.005)
network = Network([b1, b2, b3, b4, i1, i2, i3, i4], [b1_i1, b2_i2, b3_i3, b4_i4])
address_config_dict = {}
rank_address_function = lambda rank:"ipc://%s" % (5559+rank)
for ii in range(number_of_processes):
address_config_dict[ii] = rank_address_function(ii)
run_dict = {'t0':t0,
'dt':dt,
'tf':tf,
'synchronization_harness':SynchronizationHarness(rank, address_config_dict, number_of_processes)}
t0 = time.time()
network.run(**run_dict)
print time.time() - t0
# profile = profile_simulation(simulation, run_dict, logging=False)
# total_time = extract_value(profile, 'simulation.py', 'run')
# parallel_overhead = extract_value(profile, 'distributedconfiguration.py', 'update')
# parallel_win = extract_value(profile, 'internalpopulation.py', 'update')
# if rank == 0: print 'total time: %s' % total_time
# if rank == 0: print 'parallel_overhead: %s' % parallel_overhead
# print 'parallel_win: %s' % parallel_win
# 1001 0.001 0.000 0.193 0.000 distributedconfiguration.py:28(update)
# if rank == 0:
# import matplotlib
# matplotlib.use('Qt4Agg')
# import matplotlib.pyplot as plt
from dipde.internals.internalpopulation import InternalPopulation
from dipde.internals.externalpopulation import ExternalPopulation
from dipde.internals.network import Network
from dipde.internals.connection import Connection as Connection
from dipde.visualization import visualize
dv = .0001
update_method = 'approx'
approx_order = 1
tol = 1e-14
b1 = ExternalPopulation('100', record=True)
i1 = InternalPopulation(v_min=0, v_max=.02, dv=dv, update_method=update_method, approx_order=approx_order, tol=tol)
i2 = InternalPopulation(v_min=0, v_max=.02, dv=dv, update_method=update_method, approx_order=approx_order, tol=tol)
b1_i1 = Connection(b1, i1, 1, weights=.005, delays=0.0)
b1_i2 = Connection(b1, i2, 2, weights=.005, delays=0.0)
network = Network([b1, i1, i2], [b1_i1, b1_i2])
network.run(dt=.0001, tf=.1, t0=0)
print i1.get_firing_rate(.1)
visualize(network, show=True)
print network.to_dict()
