API Documentation

Simulation (hnn_core):

L2Pyr([pos, override_params, gid])	Layer 2 pyramidal cell class.
L5Pyr([pos, override_params, gid])	Layer 5 Pyramidal class.
L2Basket(pos[, gid])	Class for layer 2 basket cells.
L5Basket(pos[, gid])	Class for layer 5 basket cells.
simulate_dipole(net[, n_trials, …])	Simulate a dipole given the experiment parameters.
Network(params[, add_drives_from_params, …])	The Network class.
CellResponse([spike_times, spike_gids, …])	The CellResponse class.

Dipole (hnn_core.dipole):

Dipole(times, data[, nave])	Dipole class.
simulate_dipole(net[, n_trials, …])	Simulate a dipole given the experiment parameters.
read_dipole(fname)	Read dipole values from a file and create a Dipole instance.
average_dipoles(dpls)	Compute dipole averages over a list of Dipole objects.

Params (hnn_core.params):

Params([params_input])	Params object.
read_params(params_fname)	Read param values from a file (.json or .param).

Visualization (hnn_core.viz):

plot_dipole(dpl[, tmin, tmax, ax, layer, …])	Simple layer-specific plot function.
plot_spikes_hist(cell_response[, ax, …])	Plot the histogram of spiking activity across trials.
plot_spikes_raster(cell_response[, ax, show])	Plot the aggregate spiking activity according to cell type.
plot_cells(net[, ax, show])	Plot the cells using Network.pos_dict.
plot_psd(dpl, *[, fmin, fmax, tmin, tmax, …])	Plot power spectral density (PSD) of dipole time course
plot_tfr_morlet(dpl, freqs, *[, n_cycles, …])	Plot Morlet time-frequency representation of dipole time course

Parallel backends (hnn_core.parallel_backends):

MPIBackend([n_procs, mpi_cmd])	The MPIBackend class.
JoblibBackend([n_jobs])	The JoblibBackend class.

Input and Output:

read_dipole(fname)	Read dipole values from a file and create a Dipole instance.
read_spikes(fname[, gid_ranges])	Read spiking activity from a collection of spike trial files.