tsmoothie

library1.0.5pypypi✓ verified 81d ago

A Python library for timeseries smoothing and outlier detection in a vectorized way. It provides multiple smoothing techniques (e.g., Convolutional, Exponential, Lowess, Kalman, Spectral) and outlier detection methods. Current version is 1.0.5. Release cadence is intermittent.

data ai-ml

pip install tsmoothie

github ↗package ↗

INSTALL

IMPORT

SIG · TSMOOTHIE

tsmoothie

datapythonv1.0.5

Install

7.4s avg

Import

—

Disk

230MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.0.5 · 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

installs and imports cleanly · install 0.0s · import 0.000s · 231MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 7.4s · import 0.000s · 222MB

230MB installed

● package 230MB

Code

Verified usage

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

ConvolutionSmoother

✓ from tsmoothie import ConvolutionSmoother

✗ from tsmoothie.smoother import ConvolutionalSmoother

ExponentialSmoother

✓ from tsmoothie import ExponentialSmoother

LowessSmoother

✓ from tsmoothie import LowessSmoother

Basic smoothing with LowessSmoother. Tsmoothie operates on 2D arrays (time series in rows). Ensure data is float and shape (n_series, n_points).

import numpy as np from tsmoothie.smoother import LowessSmoother # Generate noisy data np.random.seed(42) data = np.cumsum(np.random.randn(100)) + 10 # Set up smoother smoother = LowessSmoother(smooth_fraction=0.1, iterations=1) smoother.smooth(data) # Access smoothed and intervals smoothed = smoother.smooth_data[0] low, up = smoother.get_intervals('prediction_interval') print('Smoothed:', smoothed[:5])

Debug

Known issues

gotchaData must be 2D array-like of shape (n_series, n_points). Even a single series must be shaped (1, n_points) or a list of lists.

fix

If you have a 1D array x, use x.reshape(1, -1) or [x] before passing to smoother.

affects: all

gotchaSmoothers expect data in float dtype. Integer arrays may cause incorrect results or errors.

fix

Convert data to float: data.astype(float).

affects: all

breakingIn v1.0.2, the code was restructured: many imports moved to submodules. Previously some classes might have been importable directly from tsmoothie.

fix

Use from tsmoothie.smoother import ... instead of from tsmoothie import ...

affects: >=1.0.2

deprecatedThe method 'get_intervals' parameter 'prediction_interval' is still valid, but future versions may change the API. No official deprecation yet.

fix

Stay updated with CHANGELOG.

affects: all

Upgrade

Version history

1.0.5latest on PyPI · released Nov 23, 2023

Audit

Dependencies

numpyrequiredCore dependency for array operations

scipyrequiredRequired for some smoothing methods (e.g., Lowess, Spline)

scikit-learnoptionalUsed for KNN-based outlier detection

statsmodelsoptionalRequired for DecomposeSmoother and some statistical tests

Agent activity

16 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/cerlymarco/tsmoothie ↗

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