################################################################################
### Add a projection
if fln>0.0:
net.projections.append(Projection(id='proj_%s_%s'%(src,tgt),
presynaptic=src,
postsynaptic=tgt,
synapse='ampa',
weight=fln))
#net.projections[0].random_connectivity=RandomConnectivity(probability=0.5)
print(net)
net.id = 'TestNetwork'
print(net.to_json())
new_file = net.to_json_file('Example1_%s.json'%net.id)
################################################################################
### Export to some formats
### Try:
### python Example1.py -graph2
from neuromllite.NetworkGenerator import check_to_generate_or_run
from neuromllite import Simulation
import sys
check_to_generate_or_run(sys.argv, Simulation(id='SimExample1',network=new_file))
input_source_i = InputSource(id='Inh_in',
neuroml2_input='PulseGenerator',
parameters={
'amplitude': 'inh_input',
'delay': 'input_delay',
'duration': 'input_duration'
})
net.input_sources.append(input_source_i)
net.inputs.append(
Input(id='Inh_stim',
input_source=input_source_i.id,
population=inh_pop.id,
percentage=100))
# Save to JSON format
net.id = 'WC'
new_file = net.to_json_file('WC.json')
sim = Simulation(id='SimWC',
duration='100',
dt='0.005',
network=new_file,
recordRates={'all': '*'},
plots2D={
'E-I': {
'x_axis': 'Excitatory/0/Exc/r',
'y_axis': 'Inhibitory/0/Inh/r'
}
})
sim.to_json_file('SimWC.nmllite.json')
inh_syn = Synapse(id='rsInh',
lems_source_file='figure1b_Parameters.xml')
net.synapses.append(exc_syn)
net.synapses.append(inh_syn)
#### Weak GBA
syns = {exc_pop.id: exc_syn.id, inh_pop.id: inh_syn.id}
W = [['wee', 'wie'], ['wei', 'wii']]
# Add internal connections
pops = [exc_pop, inh_pop]
internal_connections(pops, W, syns)
# Save to JSON format
net.id = 'Joglekar_figure1b'
new_file = net.to_json_file('Joglekar_figure1c.json')
sim = Simulation(id='SimJoglekar_figure1b',
duration='2',
dt='0.02',
network=new_file,
recordVariables={'r': {
'all': '*'
}})
sim.to_json_file('SimJoglekar_figure1c.nmllite.json')
check_to_generate_or_run(sys.argv, sim)
# Open data file
################################################################################
### Add a projection
net.projections.append(
Projection(id="proj0",
presynaptic=p0.id,
postsynaptic=p1.id,
synapse="ampa"))
net.projections[0].random_connectivity = RandomConnectivity(probability=0.5)
################################################################################
### Save to JSON format
print(net)
net.id = "TestNetwork"
print(net.to_json())
new_file = net.to_json_file("Example1_%s.json" % net.id)
################################################################################
### Export to some formats, e.g. try:
### python Example1.py -graph2
from neuromllite.NetworkGenerator import check_to_generate_or_run
from neuromllite import Simulation
import sys
check_to_generate_or_run(sys.argv,
Simulation(id="SimExample1", network=new_file))
percentage=100))
exc_syn = Synapse(id='rsExc', lems_source_file='Demirtas_Parameters.xml')
inh_syn = Synapse(id='rsInh', lems_source_file='Demirtas_Parameters.xml')
net.synapses.append(exc_syn)
net.synapses.append(inh_syn)
syns = {exc_pop.id: exc_syn.id, inh_pop.id: inh_syn.id}
W = [['wee', 'wie'], ['wei', 'wii']]
# Add internal connections
pops = [exc_pop, inh_pop]
internal_connections(pops, W)
# Save to JSON format
net.id = 'Demirtas_network'
new_file = net.to_json_file('Demirtas_network.json')
sim = Simulation(id='SimDemirtas_network',
duration='1000',
dt='0.1',
network=new_file,
recordVariables={
'r': {
'all': '*'
},
'e': {
'all': '*'
},
'f': {
'all': '*'