antropy

library0.2.2pypypi✓ verified 85d ago

AntroPy is a Python library for estimating entropy and complexity of time-series data, including sample entropy, approximate entropy, permutation entropy, spectral entropy, and fractal dimensions (Petrosian, Katz, Higuchi). Current version is 0.2.2, with regular releases on a roughly annual cadence. Requires Python >= 3.10.

ai-ml data

pip install antropy

github ↗package ↗

INSTALL

IMPORT

SIG · ANTROPY

antropy

ai-mlpythonv0.2.2

Install

13.1s avg

Import

16216ms

Disk

466MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.2.2 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

build_error

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 13.1s · import 16.216s · 458MB

466MB installed

● package 466MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

app_entropy

✓ from antropy import app_entropy

sample_entropy

✓ from antropy import sample_entropy

perm_entropy

✓ from antropy import perm_entropy

spectral_entropy

✓ from antropy import spectral_entropy

detrended_fluctuation

✓ from antropy import detrended_fluctuation

katz_fd

✓ from antropy import katz_fd

petrosian_fd

✓ from antropy import petrosian_fd

higuchi_fd

✓ from antropy import higuchi_fd

lz_complexity

✓ from antropy import lz_complexity

Compute sample entropy, permutation entropy, and Higuchi fractal dimension on a random 1D array.

import numpy as np from antropy import sample_entropy, perm_entropy, higuchi_fd # Generate a random time series np.random.seed(42) x = np.random.rand(100) # Sample entropy se = sample_entropy(x) print(f"Sample entropy: {se:.4f}") # Permutation entropy with order 3 pe = perm_entropy(x, order=3) print(f"Permutation entropy: {pe:.4f}") # Higuchi fractal dimension hfd = higuchi_fd(x) print(f"Higuchi fractal dimension: {hfd:.4f}")

Debug

Known issues

breakingPython 3.9 is no longer supported as of v0.2.0. Minimum required Python version is 3.10.

fix

Upgrade Python to 3.10 or newer.

affects: >=0.2.0

breakingPermutation entropy for order 3 and 4 now returns a 1-D array when input is 2-D, one value per row. Previous behavior returned a scalar or raised an error.

fix

For 2D input, access individual row entropies via indexing. For 1D input, behavior unchanged.

affects: >=0.2.2

gotchaSample entropy uses a default tolerance (r) of 0.2 * std(x). For very short or noisy signals, this may be inappropriate and lead to undefined entropy (nan).

fix

Explicitly set r parameter or check signal length is sufficient (typically > 10*(m+1) for embedding dimension m).

affects: all

deprecatedThe optional dependency 'stochastic' was removed in v0.1.9. Any code using antropy with that package is unaffected, but imports of 'stochastic' directly will fail if not installed separately.

fix

Install 'stochastic' separately if needed: pip install stochastic

affects: >=0.1.9

Errors

Common errors & fixes

ValueError: md must be an integer >=2

Passing a fractional or too small embedding dimension to sample_entropy or app_entropy.

fix

Ensure the 'dim' parameter (often 'm') is an integer >= 2, e.g., m=2.

ValueError: tolerance (r) must be positive

Passing a non-positive tolerance to sample_entropy or app_entropy.

fix

Set r to a positive float, typically 0.2 * standard deviation of the signal.

RuntimeError: Numba jit compilation failed. Falling back to pure Python.

Numba version incompatibility or missing LLVM. Antropy uses numba for acceleration, but falls back gracefully.

fix

Install compatible numba version: pip install 'numba>=0.57' or ignore if performance is acceptable.

AttributeError: module 'antropy' has no attribute 'petrosian_fd'

Older version of antropy (<0.1.5) did not include petrosian_fd, or function was renamed.

fix

Upgrade to latest version: pip install --upgrade antropy

Upgrade

Version history

0.2.2latest on PyPI · released Apr 1, 2026

Audit

Dependencies

numpyrequiredCore numerical operations

scipyrequiredSignal processing and statistical functions

scikit-learnrequiredUsed for KDTree in sample entropy

numbaoptionalOptional JIT acceleration for sample entropy and LZ complexity

Agent activity

63 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/raphaelvallat/antropy ↗

packagehttps://pypi.org/project/antropy/ ↗