def get_current(self):
# generate current traces
currents = currents_given_v(self.fitter.data.v.values, self.fitter.data.t.values, self.fitter.cell.soma,
self.channel_list, self.ion_list, self.fitter.simulation_params['celsius']) # mA/cm**2
# convert units
cell_area = get_cellarea(convert_unit_prefix('u', self.fitter.cell.soma.L),
convert_unit_prefix('u', self.fitter.cell.soma.diam)) # m**2
currents = convert_unit_prefix('da', currents) * cell_area # A
return currents
def solve(candidate):
# vclamp currents
# channel_list = list(set([problem.path_variables[i][0][2] for i in range(len(problem.path_variables))]))
# only works if channel name is at 2 second position in the path!
channel_list = ["na8st", "kdr", "pas"]
ion_list = get_ionlist(channel_list)
celsius = problem.simulation_params["celsius"]
dt = problem.simulation_params["dt"]
t = problem.data.t.values
v = problem.data.v.values
i_inj = problem.data.i.values
problem.update_cell(candidate)
currents = currents_given_v(v, t, problem.cell.soma, channel_list, ion_list, celsius, plot=False)
dvdt = np.concatenate((np.array([(v[1] - v[0]) / dt]), np.diff(v) / dt))
# unit conversion
dvdt_sc, i_inj_sc, currents_sc, Cm, _ = convert_units(
problem.cell.soma.L, problem.cell.soma.diam, problem.cell.soma.cm, dvdt, i_inj, currents
)
cmdvdt_sc = dvdt_sc * Cm
i_ion_sc = np.sum(currents_sc, 0)
# hh equation
hh_eq = cmdvdt_sc - i_inj_sc + i_ion_sc
# pick points (e.g. where current traces diverge or during current injection)
current_start = np.nonzero(i_inj)[0][0]
dist = int(np.round(0.5 / dt, 0))
n_points = len(problem.path_variables)
points = np.arange(current_start, n_points * dist + dist, dist)
points = np.array(
[int(np.round(10.8 / dt)), int(np.round(11.35 / dt)), int(np.round(11.5 / dt)), int(np.round(12.0 / dt))]
) # TODO depends on data int(np.round(10.4/dt)),
hh_eq_points = hh_eq[points]
# TODO
# pl.figure()
# pl.plot(t, cmdvdt_sc-i_inj_sc, 'k')
# pl.plot(t, -i_ion_sc, 'b')
# pl.plot(t[points], (cmdvdt_sc-i_inj_sc)[points], 'yo')
# pl.plot(t[points], -i_ion_sc[points], 'ro')
# pl.show()
return hh_eq_points
currents = [problem.cell.soma.record_from(channel_list[k], 'i'+ion_list[k], pos=.5) for k in range(len(channel_list))]
v_newdt, t_newdt = run_simulation(problem.cell, **problem.simulation_params)
#pl.figure()
#pl.plot(t_newdt, v_newdt)
#pl.show()
# compute parameter
dvdt_newdt = np.concatenate((np.array([(v_newdt[1]-v_newdt[0])/dt]), np.diff(v_newdt)/dt))
i_newdt = data_newdt.i.values
celsius = problem.simulation_params['celsius']
# get currents
candidate = np.ones(len(problem.path_variables)) # gbars should be 1
problem.update_cell(candidate)
currents_newdt = currents_given_v(v_newdt, t_newdt, problem.cell.soma, channel_list, ion_list, celsius)
# convert units
dvdt_sc, i_inj_sc, currents_sc, Cm, _ = convert_units(problem.cell.soma.L, problem.cell.soma.diam,
problem.cell.soma.cm, dvdt_newdt,
i_newdt, currents_newdt)
# linear regression
weights, residual, y, X = linear_regression(dvdt_sc, i_inj_sc, currents_sc, i_pas=0, Cm=Cm)
# plots
#plot_fit(y, X, weights, t_newdt, channel_list)
# compute error
error_traces[i, j] = rms(y, np.sum(np.array(currents), 0))
for trial in range(0, n_trials):
# get current traces
v_exp = problem.data.v.values
t_exp = problem.data.t.values
i_exp = problem.data.i.values
dt = t_exp[1] - t_exp[0]
dvdt = np.concatenate((np.array([(v_exp[1]-v_exp[0])/dt]), np.diff(v_exp) / dt))
candidate = np.ones(len(problem.path_variables))
problem.update_cell(candidate)
channel_list = get_channel_list(problem.cell, 'soma')
ion_list = get_ionlist(channel_list)
celsius = problem.simulation_params['celsius']
currents = currents_given_v(v_exp, t_exp, problem.cell.soma, channel_list, ion_list, celsius)
# convert units
dvdt_sc, i_inj_sc, currents_sc, Cm, cell_area = convert_units(problem.cell.soma.L, problem.cell.soma.diam,
problem.cell.soma.cm, dvdt, i_exp,
currents)
# linear regression
weights, residual, y, X = linear_regression(dvdt_sc, i_inj_sc, currents_sc, i_pas=0, Cm=Cm)
#weights, residual, y, X = linear_regression(dvdt_sc, i_inj_sc, currents_sc, i_pas=0, Cm=None, cell_area=cell_area)
# output
print 'channels: ' + str(channel_list)
print 'weights: ' + str(weights)
# plot fit
