Skip to main content Module decoding Copy item path Source bayesian_decode Bayesian MAP decoder (Dayan & Abbott 2001).
spike_counts: (n_neurons,). tuning_rates: (n_stimuli × n_neurons, row-major flat).
prior: (n_stimuli,) or empty for uniform. Returns MAP stimulus index. linear_discriminant_decode Fisher linear discriminant decoder (Fisher 1936).
train_data: (n_samples × n_features, row-major flat). labels: (n_samples,).
test_point: (n_features,). Returns predicted class label. maximum_likelihood_decode Maximum likelihood stimulus decoder (Dayan & Abbott 2001). Uniform prior. naive_bayes_decode Gaussian naive Bayes decoder (Mitchell 1997).
train_data: (n_samples × n_features, row-major flat). labels: (n_samples,).
test_point: (n_features,). Returns predicted class label. population_vector_decode Georgopoulos population vector decoding.
trains: slice of binary spike trains (i32). preferred_directions: angle per neuron (radians).
Returns decoded angle per time bin. solve_linear 🔒 Solve A x = b via Gaussian elimination with partial pivoting.