num_elites = 3,
seed = 12345,
simulator = simulator,
nogui = nogui,
known_target_values = known_target_values)
else:
simulator = 'jNeuroML_NEURON'
cont = NeuroMLController('RunOnePyr',
neuroml_file,
'network',
sim_time,
0.01,
simulator,
generate_dir = './temp')
sim_vars = OrderedDict(known_target_values)
t, v = cont.run_individual(sim_vars, show=(not nogui))
print("Have run individual instance...")
peak_threshold = 0
analysis_var = {'peak_delta': 0,
'baseline': 0,
'dvdt_threshold': 0,
'peak_threshold': peak_threshold}
max_evaluations=100,
num_selected=10,
num_offspring=10,
mutation_rate=0.5,
num_elites=3,
seed=12345,
simulator=simulator,
nogui=nogui,
known_target_values=known_target_values,
)
else:
simulator = "jNeuroML_NEURON"
cont = NeuroMLController("RunOnePyr", neuroml_file, "network", sim_time, 0.01, simulator, generate_dir="./temp")
sim_vars = OrderedDict(known_target_values)
t, v = cont.run_individual(sim_vars, show=(not nogui))
print("Have run individual instance...")
peak_threshold = 0
analysis_var = {"peak_delta": 0, "baseline": 0, "dvdt_threshold": 0, "peak_threshold": peak_threshold}
example_run_analysis = analysis.NetworkAnalysis(v, t, analysis_var, start_analysis=0, end_analysis=sim_time)
analysis = example_run_analysis.analyse()
pp.pprint(analysis)
nogui = '-nogui' in sys.argv
if '-compare' in sys.argv:
compare(
'NT_AllenIzh__s12345_p200_m600_s80_o60_m0.1_e2_Mon_Nov_30_12.30.28_2015/AllenIzh__s12345_p200_m600_s80_o60_m0.1_e2.Pop0.v.dat'
)
#### Run simulation with one HH cell
elif '-one' in sys.argv:
simulator = 'jNeuroML_NEURON'
#simulator = 'jNeuroML'
cont = NeuroMLController('AllenTest',
'prototypes/RS/AllenTest.net.nml',
'network_RS', 1500, 0.01, simulator)
sim_vars = OrderedDict(example_vars_hh)
t, v = cont.run_individual(sim_vars, show=(not nogui))
#### Run simulation with multiple HH cells
elif '-mone' in sys.argv:
simulator = 'jNeuroML_NEURON'
#simulator = 'jNeuroML'
dataset = 471141261
ref = 'network_%s_HH' % (dataset)
cont = NeuroMLController('AllenTest', 'prototypes/RS/%s.net.nml' % ref,
mutation_rate=mutation_rate,
num_elites=num_elites,
simulator=simulator,
nogui=nogui)
if __name__ == '__main__':
nogui = '-nogui' in sys.argv
if '-one' in sys.argv:
simulator = 'jNeuroML_NEURON'
#simulator = 'jNeuroML'
cont = NeuroMLController(prefix, 'models/RS/SSTest.net.nml',
'network_RS', sim_time, 0.01, simulator)
sim_vars = OrderedDict([
('cell:RS/channelDensity:Na_all/mS_per_cm2', 100),
('cell:RS/channelDensity:Kd_all/mS_per_cm2', 20),
('cell:RS/channelDensity:LeakConductance_all/mS_per_cm2', 1e-5)
])
t, v = cont.run_individual(sim_vars, show=(not nogui))
else:
run_one_optimisation(prefix,
123456,
population_size=30,
max_evaluations=200,
'cell:Granule_98/channelDensity:Gran_NaF_98_all/mS_per_cm2':
55.74495636439219,
'cell:Granule_98/specificCapacitance:all/uF_per_cm2':
1.0808061342038033
}
sim_vars = OrderedDict(vars)
#sim_vars = OrderedDict([])
if '-one' in sys.argv:
simulator = 'jNeuroML_NEURON'
#simulator = 'jNeuroML'
cont = NeuroMLController('TestGran', 'models/GranuleCell.net.nml',
'network_GranuleCell', sim_time, dt,
simulator)
t, v = cont.run_individual(sim_vars, show=False)
analysis = utils.simple_iclamp_analysis(v['Gran/0/Granule_98/v'],
t,
plot=True)
elif '-mone' in sys.argv:
simulator = 'jNeuroML_NEURON'
#simulator = 'jNeuroML'
sim_time = 700
cont = NeuroMLController('TestGranNet',
'cell:Granule_98/channelDensity:Gran_H_98_all/mS_per_cm2': 0.03559929171361169,
'cell:Granule_98/channelDensity:Gran_KDr_98_all/mS_per_cm2': 7.016013314649269,
'cell:Granule_98/channelDensity:Gran_NaF_98_all/mS_per_cm2': 55.74495636439219,
'cell:Granule_98/specificCapacitance:all/uF_per_cm2': 1.0808061342038033}
sim_vars = OrderedDict(vars)
#sim_vars = OrderedDict([])
if '-one' in sys.argv:
simulator = 'jNeuroML_NEURON'
#simulator = 'jNeuroML'
cont = NeuroMLController('TestGran',
'models/GranuleCell.net.nml',
'network_GranuleCell',
sim_time,
dt,
simulator)
t, v = cont.run_individual(sim_vars, show=False)
analysis = utils.simple_iclamp_analysis(v['Gran/0/Granule_98/v'], t, plot=True)
elif '-mone' in sys.argv:
simulator = 'jNeuroML_NEURON'
#simulator = 'jNeuroML'
sim_time = 700
cont = NeuroMLController('TestGranNet',
'models/GranuleCellMulti.net.nml',
