brainbox.tests.test_metrics

Functions

generate_spike_train	Basic spike train generator following a poisson process for spike-times and
multiple_spike_trains
test_clusters_metrics
test_drift_estimate	From spike depths, xcorrelate drift maps to find a drift estimate
test_noise_cut_off

multiple_spike_trains(firing_rates=None, rec_len_secs=1000, cluster_ids=None, amplitude_noise=1.9999999999999998e-05)

Parameters:

• firing_rates – list or np.array of firing rates (spikes per second)

• rec_len_secs – recording length in seconds

Returns:

spike_times, spike_amps, spike_clusters

generate_spike_train(firing_rate=200, rec_len_secs=1000)

Basic spike train generator following a poisson process for spike-times and

Parameters:

• firing_rate

• rec_len_secs

Returns:

spike_times (secs) , spike_amplitudes (V)

test_clusters_metrics()

test_drift_estimate()

From spike depths, xcorrelate drift maps to find a drift estimate

test_noise_cut_off()