neat.CompartmentTree.computeGChanFromImpedance¶

CompartmentTree.
computeGChanFromImpedance
(channel_names, z_mat, e_eq, freqs, sv=None, weight=1.0, all_channel_names=None, other_channel_names=None, action='store')[source]¶ Fit the conductances of multiple channels from the given impedance matrices, or store the feature matrix and target vector for later use (see action).
 Parameters
channel_names (list of str) – The names of the ion channels whose conductances are to be fitted
z_mat (np.ndarray (ndim=3)) – The impedance matrix to which the ion channel is fitted. Shape is
(F, N, N)
withN
the number of compartments andF
the number of frequencies at which the matrix is evaluatede_eq (float) – The equilibirum potential at which the impedance matrix was computed
freqs (np.array) – The frequencies at which z_mat is computed (shape is
(F,)
)sv (dict {channel_name: np.ndarray} (optional)) – The state variable expansion point. If
np.ndarray
, assumes it is the expansion point of the channel that is fitted. If dict, the expansion points of multiple channels can be specified. An empty dict implies the asymptotic points derived from the equilibrium potentialweight (float) – The relative weight of the feature matrices in this part of the fit
all_channel_names (list of str or
None
) – The names of all channels whose conductances will be fitted in a single linear least squares fitother_channel_names (list of str or
None
(default)) – List of channels present in z_mat, but whose conductances are already fitted. IfNone
and ‘L’ is not in all_channel_names, sets other_channel_names to ‘L’action ('fit', 'store' or 'return') – If ‘fit’, fits the conductances for this feature matrix and target vector for directly; only based on z_mat; nothing is stored. If ‘store’, stores the feature matrix and target vector to fit later on. Relative weight in fit will be determined by weight. If ‘return’, returns the feature matrix and target vector. Nothing is stored