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Time Series Analysis Tool TSAT

This software is for time series analysis with GUI and CLI interfaces. It is a highly modified version of GrammarViz with additional functionality. The GUI enables interactive time series exploration workflow that allows for variable length recurrent and anomalous patterns discovery [4] along with time series classification using Representative Pattern Mining (RPM) using either Euclidean or Dynamic Time Warping (DTW) distance functions [6].

From grammarviz:

It is implemented in Java and is based on continuous signal discretization with SAX, Grammatical Inference with Sequitur and Re-Pair, and algorithmic (Kolmogorov) complexity.

TSAT takes from GrammarViz which also implements the "Rule Density Curve" and "Rare Rule Anomaly (RRA)" algorithms for time series anomaly discovery [5], that significantly outperform HOT-SAX algorithm for time series discord discovery which is current state of the art. In the table below, the algorithms performance is measured in the amount of calls to the distance function (less is better). The last column shows the RRA performance improvement over HOT-SAX :

Dataset and SAX parameters Dataset size Brute Force HOT-SAX RRA Reduction
Daily commute (350,15,4) 17,175 271,442,101 879,067 112,405 87.2%
Dutch power demand (750,6,3) 35,040 1.13 * 10^9 6,196,356 327,950 95.7%
ECG 0606 (120,4,4) 2,300 4,241,541 72,390 16,717 76.9%
ECG 308 (300,4,4) 5,400 23,044,801 327,454 14,655 95.5%
ECG 15 (300,4,4) 15,000 207,374,401 1,434,665 111,348 92.2%
ECG 108 (300,4,4) 21,600 441,021,001 6,041,145 150,184 97.5%
ECG 300 (300,4,4) 536,976 288 * 10^9 101,427,254 17,712,845 82.6%
ECG 318 (300,4,4) 586,086 343 * 10^9 45,513,790 10,000,632 78.0%
Respiration, NPRS 43 (128,5,4) 4,000 14,021,281 89,570 45,352 49.3%
Respiration, NPRS 44 (128,5,4) 24,125 569,753,031 1,146,145 257,529 77.5%
Video dataset (150,5,3) 11,251 119,935,353 758,456 69,910 90.8%
Shuttle telemetry, TEK14 (128,4,4) 5,000 22,510,281 691,194 48,226 93.0%
Shuttle telemetry, TEK16 (128,4,4) 5,000 22,491,306 61,682 15,573 74.8%
Shuttle telemetry, TEK17 (128,4,4) 5,000 22,491,306 164,225 78,211 52.4%


[1] Lin, J., Keogh, E., Wei, L. and Lonardi, S., Experiencing SAX: a Novel Symbolic Representation of Time Series. DMKD Journal, 2007.

[2] Nevill-Manning, C.G., Witten, I.H., Identifying Hierarchical Structure in Sequences: A linear-time algorithm. arXiv:cs/9709102, 1997.

[3] Larsson, N. J., Moffat, A., Offline Dictionary-Based Compression, IEEE 88 (11): 1722–1732, doi:10.1109/5.892708, 2000.

Citing this work:

[4] Senin, P., Lin, J., Wang, X., Oates, T., Gandhi, S., Boedihardjo, A.P., Chen, C., Frankenstein, S., Lerner, M., GrammarViz 2.0: a tool for grammar-based pattern discovery in time series, ECML/PKDD Conference, 2014.

[5] Senin, P., Lin, J., Wang, X., Oates, T., Gandhi, S., Boedihardjo, A.P., Chen, C., Frankenstein, S., Lerner, M., Time series anomaly discovery with grammar-based compression, The International Conference on Extending Database Technology, EDBT 15.

[6] Wang, X., Lin, J., Senin, P., Oates, T., Gandhi, S., Boedihardjo, A., Chen, C., Frankenstein, S. (2016). RPM: Representative Pattern Mining for Efficient Time Series Classification. In EDBT (pp. 185-196).

1.0 Building

We use Maven and Java 7 to build an executable.

$ java -version
java version "1.7.0_80"
Java(TM) SE Runtime Environment (build 1.7.0_80-b15)
Java HotSpot(TM) 64-Bit Server VM (build 24.80-b11, mixed mode)

$ mvn -version
Apache Maven 2.2.1 (rdebian-8)
Java version: 1.7.0_80
Java home: /usr/lib/jvm/java-7-oracle/jre
Default locale: fr_FR, platform encoding: UTF-8
OS name: "linux" version: "3.2.0-86-generic" arch: "amd64" Family: "unix"

$ mvn package -Psingle
[INFO] Scanning for projects...

[INFO] Building jar: /media/Stock/git/TSAT/target/tsat-0.0.1-SNAPSHOT-jar-with-dependencies.jar
[INFO] ------------------------------------------------------------------------
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 5 seconds
[INFO] Finished at: Wed Jun 17 15:43:01 CEST 2015
[INFO] Final Memory: 47M/238M
[INFO] ------------------------------------------------------------------------

2.0 Running

To run the GUI use GrammarVizGUI class, or run the jar from the command line: $ java -Xmx2g -jar target/tsat-0.0.1-SNAPSHOT-jar-with-dependencies.jar (here I have allocated max of 2Gb of memory for the software).

3.0 CLI interface

By using CLI as discussed in these tutorials, it is possible to save the inferred grammar, motifs, and discords.

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