def run(self, tstop=None):
# TODO: Check if cells/connections need to be rebuilt.
# Create the networ
dipde_pops = [p.dipde_obj for p in self._graph.populations]
dipde_conns = [c.dipde_obj for c in self._graph.connections]
#print dipde_pops
#print dipde_conns
#exit()
self._dipde_network = dipde.Network(population_list=dipde_pops,
connection_list=dipde_conns)
#self._dipde_network = dipde.Network(population_list=self._graph.populations,
# connection_list=self._graph.connections)
if tstop is None:
tstop = self.tstop
#print tstop, self.dt
#print self._graph.populations
#exit()
print("running simulation...")
self._dipde_network.run(t0=0.0, tf=tstop, dt=self.dt)
# TODO: make record_rates optional?
self.__record_rates()
print("done simulation.")
def run(self, duration=None):
# TODO: Check if cells/connections need to be rebuilt.
# Create the networ
self._dipde_network = dipde.Network(population_list=self.populations, connection_list=self.__connection_list)
if duration is None:
duration = self.duration
print "running simulation..."
self._dipde_network.run(t0=0.0, tf=duration, dt=self.dt)
# TODO: make record_rates optional?
self.__record_rates()
print "done simulation."
def run(self, tstop=None):
# TODO: Check if cells/connections need to be rebuilt.
# Create the network
dipde_pops = [p.dipde_obj for p in self._graph.populations]
dipde_conns = [c.dipde_obj for c in self._graph.connections]
self._dipde_network = dipde.Network(population_list=dipde_pops,
connection_list=dipde_conns)
if tstop is None:
tstop = self.tstop
self.io.log_info("Running simulation.")
self._dipde_network.run(t0=0.0, tf=tstop, dt=self.dt)
# TODO: make record_rates optional?
self.__record_rates()
self.io.log_info("Finished simulation.")
def test_equvalent_discrete():
import dipde
test_list = [.001,
{'distribution': 'delta', 'loc': 0},
'{"distribution":"delta", "loc":0}',
([0], [1]),
sps.rv_discrete(values=([0], [1]))]
for p0 in test_list:
print p0
i1 = dipde.InternalPopulation(v_min=0, v_max=.02, dv=.001, p0=p0)
b1 = dipde.ExternalPopulation('100')
b1_i1 = dipde.Connection(b1, i1, 1, weights=.005)
network = dipde.Network([b1, i1], [b1_i1])
network.run(dt=.001, tf=.2)
np.testing.assert_almost_equal(i1.firing_rate_record[-1], 5.39156805318, 10)
def test_equvalent_continuous():
import dipde
test_list = [dipde.InternalPopulation(v_min=0, v_max=.02, dv=.001, p0=sps.norm(scale=.003)),
dipde.InternalPopulation(v_min=0, v_max=.02, dv=.001, p0=sps.norm(loc=0, scale=.003)),
dipde.InternalPopulation(v_min=0, v_max=.02, dv=.001, p0=(sps.norm(loc=0, scale=.003), 25)),
dipde.InternalPopulation(v_min=0, v_max=.02, dv=.001,
p0={"distribution": "norm", "loc": 0, "scale": 0.003}),
dipde.InternalPopulation(v_min=0, v_max=.02, dv=.001,
p0={"distribution": "norm", "loc": 0, "scale": 0.003, "N": 25}),
dipde.InternalPopulation(v_min=0, v_max=.02, dv=.001,
p0='{"distribution":"norm", "loc":0, "scale":0.003, "N":25}')]
for i1 in test_list:
b1 = dipde.ExternalPopulation('100')
b1_i1 = dipde.Connection(b1, i1, 1, weights=.005)
network = dipde.Network([b1, i1], [b1_i1])
network.run(dt=.001, tf=.2)
np.testing.assert_almost_equal(i1.firing_rate_record[-1], 5.3915680916372484, 10)