odynn.nsimul module

odynn.nsimul.comp_neuron_trace(neuron, trace, i_inj=array([0., 0., 0., ..., 0., 0., 0.]), scale=False, suffix='', show=True, save=False)

Compare a neuron with a given measured trace after scaling

Parameters:

• neuron (NeuronModel object) – neuron to compare
• trace – recordings to plot
• dt (float) – time step
• i_inj (ndarray) – input currents
• scale – (Default value = False)
• show (bool) – If True, show the figure (Default value = True)
• save (bool) – If True, save the figure (Default value = False)

odynn.nsimul.comp_neurons(neurons, i_inj=array([0., 0., 0., ..., 0., 0., 0.]), suffix='', show=True, save=False)

Compare different neurons on the same experiment

Parameters:

• neurons (list of object NeuronModel) – neurons to compare
• dt (float) – time step
• i_inj (ndarray) – input currents
• show (bool) – If True, show the figure (Default value = True)
• save (bool) – If True, save the figure (Default value = False)

odynn.nsimul.comp_pars(ps, t=None, dt=0.1, i_inj=array([0., 0., 0., ..., 0., 0., 0.]), suffix='', show=True, save=False)

Compare different parameter sets on the same experiment

Parameters:

• ps (list of dict) – list of parameters to compare
• dt (float) – time step
• i_inj (ndarray) – input currents
• show (bool) – If True, show the figure (Default value = True)
• save (bool) – If True, save the figure (Default value = False)

odynn.nsimul.comp_pars_targ(p, p_targ, t=None, dt=0.1, i_inj=array([0., 0., 0., ..., 0., 0., 0.]), suffix='', save=False, show=True)

Compare parameter sets with a target

Parameters:

• p (dict or list of dict) – parameter(s) to compare with the target
• p_targ (dict) – target parameters
• dt (float) – time step
• i_inj (ndarray) – input currents
• suffix (str) – suffix for the saved figure (Default value = ‘’)
• save (bool) – If True, save the figure (Default value = False)
• show (bool) – If True, show the figure (Default value = True)

odynn.nsimul.simul(p=None, neuron=None, t=None, dt=0.1, i_inj=array([0., 0., 0., ..., 0., 0., 0.]), suffix='', show=False, save=True, ca_true=None)

Main demo for the Hodgkin Huxley neuron model

Parameters:

• p (dict) – parameters of the neuron to simulate
• neuron (NeuronModel object) – neuron to simulate
• dt – time step

Returns:

records

Return type:

list