Results for augurs

Python bindings for the augurs time series library.

A time-series toolkit for forecasting, outlier detection, clustering and more.

A high-level API for the augurs forecasting library.

Multiple Seasonal-Trend decomposition with LOESS (MSTL) using the augurs time series library.

Reverse engineering assistant that extracts strings and related pseudocode from a binary file.

Prophet: time-series forecasting at scale, in Rust.

Time series clustering.

ETS models for augurs

Core data structures and traits for the augurs time series library.

JavaScript bindings for the augurs time series library.

Seasonality detection using periodograms

Test framework and data for the augurs library.

Changepoint detection using Bayesian Online Change Point Detection and more.

Generate a 4 word password from words of size 3-8 characters, with frequencies in the 30th-60th percentile. This range gives a nice set of uncommon but not completely alien words. $ chbs generate --verbose -W 3..8 -P 30..60 Corpus size: 6396 candidate words of 33075 total Entropy: 48 bits (2^48 = 281474976710656) Years to guess at 1000 guesses/sec: 8926 magnate-thermal-sandbank-augur With the --verbose flag, the utility will calculate a time-to-guess based on a completely arbitrary 1000 guesses/sec. If you'd like a more secure password, either relax the various filtering rules (-W and -P), add more words to the password, or use a larger corpus. By default we use the American TV Shows & Scripts corpus taken from Wiktionary. Others provided: * Project Gutenberg 2005 corpus taken from Wiktionary. * 1 of every 7 of the top 60000 lemmas from wordfrequency.info (6900 actual lemmas after processing) See http://xkcd.com/936/ for the genesis of the idea. Data sources: http://en.wiktionary.org/wiki/Wiktionary:Frequency_lists http://wordfrequency.info/