def run_short_squares(cell_id,
model_type,
neuron_config,
pulses,
total_time=1000.0,
dt=0.005):
"""Generates a series of square injection currents
Parameters
----------
cell_id : ID of cell speciment
model_type : LIF, LIF-R, LIF-R-ASC, LIF-ASC, LIF-R-ASC-A
pulse_time : A list of tuples (start_time (ms), end_time (ms), amplitude (Amps))
"""
ret = {}
amp_times = [0.0]
amp_values = [0.0]
for p in pulses:
amp_times += [p[0], p[0] + p[1]]
amp_values += [p[2], 0.0]
output = runNestModel(model_type, neuron_config, amp_times, amp_values, dt,
total_time)
ret['times'] = output[0]
ret['voltages'] = output[1]
ret['spike_times'] = output[2]
I = plotter.get_step_trace(amp_times, amp_values, dt, total_time)
ret['I'] = I
ret['dt'] = dt
return ret
def run_long_square(cell_id,
model_type,
neuron_config,
pulse_time,
amplitude,
total_time=1000.0,
dt=0.005):
"""Generates a single long constant injection current
Parameters
----------
cell_id : ID of cell speciment
model_type : LIF, LIF-R, LIF-R-ASC, LIF-ASC, LIF-R-ASC-A
pulse_time : A tuple 0 <= (start_time, end_time) <= total_time, in ms
ampltiude : Amps of input current
"""
ret = {}
amp_times = [0.0, pulse_time[0], pulse_time[1]]
amp_values = [0.0, amplitude, 0.0]
output = runNestModel(model_type, neuron_config, amp_times, amp_values, dt,
total_time)
ret['times'] = output[0]
ret['voltages'] = output[1]
ret['spike_times'] = output[2]
I = plotter.get_step_trace(amp_times, amp_values, dt, total_time)
ret['I'] = I
ret['dt'] = dt
return ret