complexeva
Complexity measures for 1D time series, implemented with NumPy, SciPy and Numba.
install
pip install complexeva
Requires Python 3.14 or later.
example
import numpy as np
import complexeva
x = np.random.default_rng(0).standard_normal(2000) # white noise
complexeva.hfd(x) # about 2.0
complexeva.lempel_ziv(x, normalize=True) # about 1.0
complexeva.compression_complexity(x) # about 0.96
complexeva.lyapunov_exponent(x) # largest Lyapunov exponent
measures
| function | what it returns | main parameters | reference |
|---|---|---|---|
hfd(X, k_max=10) |
Higuchi fractal dimension, 1 (smooth) to 2 (white noise) | k_max: largest time interval, 2 to len(X) // 2; report it with results |
Higuchi 1988, Physica D 31:277 |
hfd_hilbert(X, k_max=10) |
hfd of the Hilbert envelope (instantaneous amplitude) |
as hfd |
|
lempel_ziv(x, method="median", normalize=False) |
Lempel-Ziv complexity: integer count, or c·log2(n)/n (about 1 for random input) when normalize=True |
method: binarise by "median", "mean" or "diff" (rising step); a "0101..." string is used as is |
Kaspar & Schuster 1987, Phys. Rev. A 36:842 |
lempel_ziv_hilbert(x, method="median", normalize=False) |
lempel_ziv of the Hilbert envelope |
as lempel_ziv |
|
compression_complexity(data) |
zlib-compressed size / raw size of the array bytes, 0 to about 1 | depends on the array dtype | |
lyapunov_exponent(data, tau=1, m=2, dt=1.0, min_tsep=None, trajectory_len=20, fit_offset=0) |
largest Lyapunov exponent in units of 1/dt; positive suggests chaos, about 0 for periodic signals |
tau, m: delay embedding; min_tsep: Theiler window (default: mean period); trajectory_len: steps fitted |
Rosenstein et al. 1993, Physica D 65:117 |
All functions take a 1D array. Results changed in 0.3.0; see CHANGELOG.md.
licence
MIT
1 maintainer
Metadata
1 maintainer
Release files for complexeva 0.3.0
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