BlueBrain/eFEL

"""Neuron / DEAP optimisation example evaluation function"""
 
import neuron
neuron.h.load_file('stdrun.hoc')
 
import efel
 
# pylint: disable=W0212
 
 
Function `evaluate` has 33 lines of code (exceeds 25 allowed). Consider refactoring.
def evaluate(individual, target_voltage1=-80, target_voltage2=-60):
    """
    Evaluate a neuron model with parameters e_pas and g_pas, extracts
    features from resulting traces and returns a tuple with
    abs(voltage_base-target_voltage1) and
    abs(steady_state_voltage-target_voltage2)
    """
 
    neuron.h.v_init = target_voltage1
 
    soma = neuron.h.Section()
 
    soma.diam = 100
    soma.L = 100
 
    soma.insert('hh')
 
    soma.gnabar_hh = individual[0]
    soma.gkbar_hh = individual[1]
 
    clamp = neuron.h.IClamp(0.5, sec=soma)
 
    stim_start = 500
    stim_end = 1000
 
    clamp.amp = 5.0
    clamp.delay = stim_start
    clamp.dur = 500
 
    voltage = neuron.h.Vector()
    voltage.record(soma(0.5)._ref_v)
 
    time = neuron.h.Vector()
    time.record(neuron.h._ref_t)
 
    neuron.h.tstop = stim_end
    neuron.h.run()
 
    trace = {}
    trace['T'] = time
    trace['V'] = voltage
    trace['stim_start'] = [stim_start]
    trace['stim_end'] = [stim_end]
    traces = [trace]
 
    features = efel.get_feature_values(traces, ["voltage_base",
                                              "steady_state_voltage"])
    voltage_base = features[0]["voltage_base"][0]
    steady_state_voltage = features[0]["steady_state_voltage"][0]
 
    import pylab
    pylab.plot(time, voltage)
    pylab.show()
 
    return abs(target_voltage1 - voltage_base), \
        abs(target_voltage2 - steady_state_voltage)
 
if __name__ == '__main__':
    evaluate([0.12, 0.036])