Package: jmotif 1.1.1

Pavel Senin

jmotif: Time Series Analysis Toolkit Based on Symbolic Aggregate Discretization, i.e. SAX

Implements time series z-normalization, SAX, HOT-SAX, VSM, SAX-VSM, RePair, and RRA algorithms facilitating time series motif (i.e., recurrent pattern), discord (i.e., anomaly), and characteristic pattern discovery along with interpretable time series classification.

Authors:Pavel Senin [aut, cre]

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jmotif.pdf |jmotif.html✨
jmotif/json (API)

# Install 'jmotif' in R:
install.packages('jmotif', repos = c('https://jmotif.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jmotif/jmotif-r/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • CBF - A standard UCR Cylinder-Bell-Funnel dataset from http://www.cs.ucr.edu/~eamonn/time_series_data
  • Gun_Point - A standard UCR Gun Point dataset from http://www.cs.ucr.edu/~eamonn/time_series_data
  • ecg0606 - A PHYSIONET dataset

On CRAN:

Conda:

anomalydiscoverydiscorddiscretizationkddsaxsax-vsmtimeseriescpp

5.12 score 55 stars 48 scripts 215 downloads 26 exports 1 dependencies

Last updated 3 years agofrom:bad4b2d4ff. Checks:1 OK, 11 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 12 2025
R-4.5-win-x86_64ERRORMar 12 2025
R-4.5-mac-x86_64ERRORMar 12 2025
R-4.5-mac-aarch64ERRORMar 12 2025
R-4.5-linux-x86_64ERRORMar 12 2025
R-4.4-win-x86_64ERRORMar 12 2025
R-4.4-mac-x86_64ERRORMar 12 2025
R-4.4-mac-aarch64ERRORMar 12 2025
R-4.4-linux-x86_64ERRORMar 12 2025
R-4.3-win-x86_64ERRORMar 12 2025
R-4.3-mac-x86_64ERRORMar 12 2025
R-4.3-mac-aarch64ERRORMar 12 2025

Exports:alphabet_to_cutsbags_to_tfidfcosine_distcosine_simearly_abandoned_disteuclidean_distfind_discords_brute_forcefind_discords_hotsaxfind_discords_rraidx_to_letteris_equal_mindistis_equal_strletter_to_idxletters_to_idxmanyseries_to_wordbagmin_distpaasax_by_chunkingsax_distance_matrixsax_via_windowseries_to_charsseries_to_stringseries_to_wordbagstr_to_repair_grammarsubseriesznorm

Dependencies:Rcpp

Readme and manuals

Help Manual

Help pageTopics
Translates an alphabet size into the array of corresponding SAX cut-lines built using the Normal distribution.alphabet_to_cuts
Computes a TF-IDF weight vectors for a set of word bags.bags_to_tfidf
A standard UCR Cylinder-Bell-Funnel dataset from http://www.cs.ucr.edu/~eamonn/time_series_dataCBF
Computes the cosine similarity between numeric vectorscosine_dist
Computes the cosine distance value between a bag of words and a set of TF-IDF weight vectors.cosine_sim
Finds the Euclidean distance between points, if distance is above the threshold, abandons the computation and returns NAN.early_abandoned_dist
A PHYSIONET datasetecg0606
Finds the Euclidean distance between points.euclidean_dist
Finds a discord using brute force algorithm.find_discords_brute_force
Finds a discord (i.e. time series anomaly) with HOT-SAX. Usually works the best with lower sizes of discretization parameters: PAA and Alphabet.find_discords_hotsax
Finds a discord with RRA (Rare Rule Anomaly) algorithm. Usually works the best with higher than that for HOT-SAX sizes of discretization parameters (i.e., PAA and Alphabet sizes).find_discords_rra
A standard UCR Gun Point dataset from http://www.cs.ucr.edu/~eamonn/time_series_dataGun_Point
Get the ASCII letter by an index.idx_to_letter
Compares two strings using mindist.is_equal_mindist
Compares two strings using natural letter ordering.is_equal_str
Get the index for an ASCII letter.letter_to_idx
Get an ASCII indexes sequence for a given character array.letters_to_idx
Converts a set of time-series into a single bag of words.manyseries_to_wordbag
Computes the mindist value for two stringsmin_dist
Computes a Piecewise Aggregate Approximation (PAA) for a time series.paa
Discretize a time series with SAX using chunking (no sliding window).sax_by_chunking
Generates a SAX MinDist distance matrix (i.e. the "lookup table") for a given alphabet size.sax_distance_matrix
Discretizes a time series with SAX via sliding window.sax_via_window
Transforms a time series into the char array using SAX and the normal alphabet.series_to_chars
Transforms a time series into the string.series_to_string
Converts a single time series into a bag of words.series_to_wordbag
Runs the repair on a string.str_to_repair_grammar
Extracts a subseries.subseries
Z-normalizes a time series by subtracting its mean and dividing by the standard deviation.znorm