Functions§
- count_
values 🔒 - digamma 🔒
- Digamma function approximation (Stirling series, accurate to ~1e-10 for x > 6).
- entropy_
from_ 🔒counts - kozachenko_
leonenko_ mi - Kozachenko-Leonenko k-NN mutual information estimator (Kraskov et al. 2004). Returns MI in nats.
- mutual_
information - Mutual information between two binned spike trains (bits).
- noise_
entropy - Noise entropy via pseudo-trials (de Ruyter van Steveninck et al. 1997). Returns bits.
- spike_
train_ entropy - Spike train entropy via binary word analysis (Strong et al. 1998). Returns bits.
- stimulus_
specific_ information - Stimulus-specific information (Butts 2003). Returns bits.
- time_
rescaling_ ks_ test - Time-rescaling KS test for point process goodness-of-fit (Brown et al. 2002). rate_func(t) -> conditional intensity. Returns (ks_statistic, passes_at_95pct).
- transfer_
entropy - Transfer entropy from source to target spike train (bits).