GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → dioph → periodicity

dioph / periodicity

Licence: MIT License
Useful tools for periodicity analysis in time series data.

Programming Languages

python
139335 projects - #7 most used programming language

Labels

time-seriesgaussian-processesspectral-analysiswaveletsperiodicity-analysis

Projects that are alternatives of or similar to periodicity

Exoplanet
Fast & scalable MCMC for all your exoplanet needs!
Stars: ✭ 122 (+713.33%)
Mutual labels:  time-series, gaussian-processes
models
Forecasting 🇫🇷 elections with Bayesian statistics 🥳
Stars: ✭ 24 (+60%)
Mutual labels:  time-series, gaussian-processes
Survival Analysis Using Deep Learning
This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis
Stars: ✭ 139 (+826.67%)
Mutual labels:  time-series, gaussian-processes
George
Fast and flexible Gaussian Process regression in Python
Stars: ✭ 379 (+2426.67%)
Mutual labels:  time-series, gaussian-processes
Celerite
Scalable 1D Gaussian Processes in C++, Python, and Julia
Stars: ✭ 155 (+933.33%)
Mutual labels:  time-series, gaussian-processes
Chronetic
Analyzes chronological patterns present in time-series data and provides human-readable descriptions
Stars: ✭ 23 (+53.33%)
Mutual labels:  time-series
kotori
A flexible data historian based on InfluxDB, Grafana, MQTT and more. Free, open, simple.
Stars: ✭ 73 (+386.67%)
Mutual labels:  time-series
wxee
A Python interface between Earth Engine and xarray for processing time series data
Stars: ✭ 113 (+653.33%)
Mutual labels:  time-series
COVID19
Using Kalman Filter to Predict Corona Virus Spread
Stars: ✭ 78 (+420%)
Mutual labels:  time-series
mtad-gat-pytorch
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
Stars: ✭ 85 (+466.67%)
Mutual labels:  time-series
k2sc
K2 systematics correction using Gaussian processes
Stars: ✭ 15 (+0%)
Mutual labels:  gaussian-processes
tsfile
THIS REPO HAS MOVED TO https://github.com/apache/incubator-iotdb. TsFile is a columnar file format designed for time-series data, which supports efficient compression and query. It is easy to integrate TsFile with your IOT big data processing frameworks.
Stars: ✭ 105 (+600%)
Mutual labels:  time-series
HistoricalVolatility
A framework for historical volatility estimation and analysis.
Stars: ✭ 22 (+46.67%)
Mutual labels:  time-series
pyfilter
Particle filtering and sequential parameter inference in Python
Stars: ✭ 52 (+246.67%)
Mutual labels:  time-series
BayesHMM
Full Bayesian Inference for Hidden Markov Models
Stars: ✭ 35 (+133.33%)
Mutual labels:  time-series
rbcb
R interface to Brazilian Central Bank web services
Stars: ✭ 63 (+320%)
Mutual labels:  time-series
magi
📈 high level wrapper for parallel univariate time series forecasting 📉
Stars: ✭ 17 (+13.33%)
Mutual labels:  time-series
GKT
Graph-based Knowledge Tracing: Modeling Student Proficiency Using Graph Neural Network
Stars: ✭ 43 (+186.67%)
Mutual labels:  time-series
modape
MODIS Assimilation and Processing Engine
Stars: ✭ 19 (+26.67%)
Mutual labels:  time-series
Hurst-exponent-R-S-analysis-
Calculates the Hurst exponent of a time series based on Rescaled range (R/S) analysis.
Stars: ✭ 33 (+120%)
Mutual labels:  time-series
View All Similar Projects ➔

Periodicity

Useful tools for periodicity analysis in time series data.

PyPI version Downloads

Documentation: https://periodicity.readthedocs.io

Currently includes:

  • Auto-Correlation Function (and other general timeseries utilities!)
  • Spectral methods:
    • Lomb-Scargle periodogram
    • Bayesian Lomb-Scargle with linear Trend (soon™)
  • Time-frequency methods:
    • Wavelet Transform
    • Hilbert-Huang Transform
    • Composite Spectrum
  • Phase-folding methods:
    • String Length
    • Phase Dispersion Minimization
    • Analysis of Variance (soon™)
  • Decomposition methods:
    • Empirical Mode Decomposition
    • Local Mean Decomposition
    • Variational Mode Decomposition (soon™)
  • Gaussian Processes:
    • george implementation
    • celerite2 implementation
    • celerite2.theano implementation

Installation

The latest version is available to download via PyPI: pip install periodicity.

Alternatively, you can build the current development version from source by cloning this repo (git clone https://github.com/dioph/periodicity.git) and running pip install ./periodicity.

Development

If you're interested in contributing to periodicity, install pipenv and you can setup everything you need with pipenv install --dev.

To automatically test the project (and also check formatting, coverage, etc.), simply run tox within the project's directory.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].