An efficient non-recursive algorithm for transforming time series to visibility graph

In recent years, transforming a time series into visibility network has emerged as a powerful tool of data analysis, with applications in many pure and applied domains of statistical physics and non-linear dynamics. The algorithms available for this transform are either very slow or consume copious...

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Veröffentlicht in:Physica A Jg. 514; S. 189 - 202
Hauptverfasser: Ghosh, Saptorshi, Dutta, Amlan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 15.01.2019
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ISSN:0378-4371, 1873-2119
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Abstract In recent years, transforming a time series into visibility network has emerged as a powerful tool of data analysis, with applications in many pure and applied domains of statistical physics and non-linear dynamics. The algorithms available for this transform are either very slow or consume copious amount of memory resorting to recursive calls. Here we propose an efficient non-recursive algorithm for constructing natural visibility graph from time series data. In comparison to the recursive method, the new algorithm offers safer and more optimized use of memory space without sacrificing its speed. Performance of this algorithm is tested with a variety of synthetic and experimental time series data-sets. •A novel sort-and-conquer algorithm is proposed to transform a time series into visibility graph.•Being non-recursive, this algorithm does not use stack frames in memory.•Speed of execution is either comparable or better than the existing divide-and-conquer algorithm.•Memory efficiency is significantly superior to the recursive method.
AbstractList In recent years, transforming a time series into visibility network has emerged as a powerful tool of data analysis, with applications in many pure and applied domains of statistical physics and non-linear dynamics. The algorithms available for this transform are either very slow or consume copious amount of memory resorting to recursive calls. Here we propose an efficient non-recursive algorithm for constructing natural visibility graph from time series data. In comparison to the recursive method, the new algorithm offers safer and more optimized use of memory space without sacrificing its speed. Performance of this algorithm is tested with a variety of synthetic and experimental time series data-sets. •A novel sort-and-conquer algorithm is proposed to transform a time series into visibility graph.•Being non-recursive, this algorithm does not use stack frames in memory.•Speed of execution is either comparable or better than the existing divide-and-conquer algorithm.•Memory efficiency is significantly superior to the recursive method.
Author Dutta, Amlan
Ghosh, Saptorshi
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  givenname: Amlan
  surname: Dutta
  fullname: Dutta, Amlan
  email: amlan.dutta@metal.iitkgp.ac.in
  organization: Department of Metallurgical and Materials Engineering, Indian Institute of Technology Kharagpur, 721302, India
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Cites_doi 10.1016/j.physa.2007.10.055
10.1002/joc.1377
10.1016/j.physa.2017.10.015
10.1073/pnas.0709247105
10.1063/1.3332246
10.1142/S0218127411029021
10.4103/2153-3539.197191
10.1016/j.ymssp.2006.07.005
10.1103/PhysRevLett.116.033902
10.1109/LGRS.2004.828912
10.1063/1.4927835
10.1016/j.bspc.2013.10.006
10.1103/PhysRevE.97.022223
10.1016/j.physa.2006.10.089
10.1016/j.physd.2011.09.008
10.1063/1.4951681
10.1103/PhysRevE.70.036110
10.1016/j.physa.2014.07.002
10.1016/j.physa.2014.05.058
10.1103/PhysRevE.96.012318
10.1103/PhysRevE.95.062309
10.1016/j.physa.2012.07.054
10.5194/hessd-10-12793-2013
10.1016/j.physa.2017.04.091
10.1029/2009GL039129
10.1016/S0009-2541(99)00091-1
10.1002/joc.2001
10.1016/j.csbj.2016.05.002
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Keywords Visibility graph algorithm
Time series analysis
Iteration and recursion
Complex network
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References Elsner, Jagger, Fogarty (b24) 2009; 36
Lacasa, Iacovacci (b26) 2017; 96
Kugiumtzis, Kehagias, Aifantis, Neuhäuser (b7) 2004; 70
Wang (b12) 2014; 10
Leiss (b31) 2007
Mali, Manna, Mukhopadhyay, Haldar, Singh (b27) 2018; 493
Zhuang, Small, Feng (b23) 2014; 410
Rodríguez (b21) 2017; 95
Yang, Yang (b17) 2008; 387
Bhaduri, Bhaduri, Ghosh (b25) 2017; 482
Anguera, Barreiro, Lara, Lizcano (b8) 2016; 14
Onisko, Druzdzel, Austin (b9) 2016; 7
Bezsudnov, Snarskii (b34) 2014; 414
Longobardi, Villani (b5) 2010; 30
Auer (b4) 2007; 27
Ciminoa (b2) 1999; 161
Gossel, Laehne (b3) 2013; 10
Gao, Jin (b14) 2010; 20
Donner (b16) 2011; 21
(b1) 2012
Tan, Hammond (b11) 2007; 21
Ahmadlou, Adeli (b19) 2012; 241
Cormen, Leiserson, Rivest, Stein (b32) 2009
Mutua, Gu, Yang (b20) 2016; 26
Goldberger, Rigney (b33) 1991
Wang, Li, Wang (b22) 2012; 391
Ninos (b6) 2004; 1
Li, Wang (b15) 2007; 378
Aragoneses, Carpi, Tarasov, Churkin, Torrent, Masoller, Turitsyn (b28) 2016; 116
Madsen (b10) 2008
Murayama, Kinugawa, Tokuda, Gotoda (b29) 2018; 97
Lacasa, Luque, Ballesteros, Luque, Nuño (b18) 2008; 105
Lan, Mo, Chen, Liu, Deng (b30) 2015; 25
A. Darvish, K. Najarian, D.H. Jeong, W. Ribarsky, Proc. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (2005), pp. 1-6.
Ciminoa (10.1016/j.physa.2018.09.053_b2) 1999; 161
Leiss (10.1016/j.physa.2018.09.053_b31) 2007
Ninos (10.1016/j.physa.2018.09.053_b6) 2004; 1
Mutua (10.1016/j.physa.2018.09.053_b20) 2016; 26
Wang (10.1016/j.physa.2018.09.053_b12) 2014; 10
Lacasa (10.1016/j.physa.2018.09.053_b18) 2008; 105
Zhuang (10.1016/j.physa.2018.09.053_b23) 2014; 410
Longobardi (10.1016/j.physa.2018.09.053_b5) 2010; 30
(10.1016/j.physa.2018.09.053_b1) 2012
Cormen (10.1016/j.physa.2018.09.053_b32) 2009
Goldberger (10.1016/j.physa.2018.09.053_b33) 1991
Bezsudnov (10.1016/j.physa.2018.09.053_b34) 2014; 414
Auer (10.1016/j.physa.2018.09.053_b4) 2007; 27
Ahmadlou (10.1016/j.physa.2018.09.053_b19) 2012; 241
Li (10.1016/j.physa.2018.09.053_b15) 2007; 378
Aragoneses (10.1016/j.physa.2018.09.053_b28) 2016; 116
10.1016/j.physa.2018.09.053_b13
Gao (10.1016/j.physa.2018.09.053_b14) 2010; 20
Lan (10.1016/j.physa.2018.09.053_b30) 2015; 25
Gossel (10.1016/j.physa.2018.09.053_b3) 2013; 10
Anguera (10.1016/j.physa.2018.09.053_b8) 2016; 14
Yang (10.1016/j.physa.2018.09.053_b17) 2008; 387
Onisko (10.1016/j.physa.2018.09.053_b9) 2016; 7
Kugiumtzis (10.1016/j.physa.2018.09.053_b7) 2004; 70
Madsen (10.1016/j.physa.2018.09.053_b10) 2008
Bhaduri (10.1016/j.physa.2018.09.053_b25) 2017; 482
Murayama (10.1016/j.physa.2018.09.053_b29) 2018; 97
Elsner (10.1016/j.physa.2018.09.053_b24) 2009; 36
Tan (10.1016/j.physa.2018.09.053_b11) 2007; 21
Donner (10.1016/j.physa.2018.09.053_b16) 2011; 21
Lacasa (10.1016/j.physa.2018.09.053_b26) 2017; 96
Wang (10.1016/j.physa.2018.09.053_b22) 2012; 391
Mali (10.1016/j.physa.2018.09.053_b27) 2018; 493
Rodríguez (10.1016/j.physa.2018.09.053_b21) 2017; 95
References_xml – year: 2012
  ident: b1
  publication-title: Economic Time Series: Modeling and Seasonality
– reference: A. Darvish, K. Najarian, D.H. Jeong, W. Ribarsky, Proc. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (2005), pp. 1-6.
– volume: 105
  start-page: 4972
  year: 2008
  end-page: 4975
  ident: b18
  publication-title: Proc. Natl. Acad. Sci. USA
– volume: 414
  start-page: 53
  year: 2014
  end-page: 60
  ident: b34
  publication-title: Physica A
– volume: 241
  start-page: 326
  year: 2012
  end-page: 332
  ident: b19
  publication-title: Physica D
– volume: 97
  start-page: 022223
  year: 2018
  ident: b29
  publication-title: Phys. Rev. E
– volume: 36
  start-page: L16702
  year: 2009
  ident: b24
  publication-title: Geophys. Res. Lett.
– volume: 493
  start-page: 253
  year: 2018
  end-page: 266
  ident: b27
  publication-title: Physica A
– volume: 30
  start-page: 1538
  year: 2010
  end-page: 1546
  ident: b5
  publication-title: Int. J. Climatol.
– volume: 482
  start-page: 786
  year: 2017
  end-page: 795
  ident: b25
  publication-title: Physica A
– volume: 10
  start-page: 250
  year: 2014
  end-page: 259
  ident: b12
  publication-title: Biomed. Signal Process Control
– volume: 25
  start-page: 083105
  year: 2015
  ident: b30
  publication-title: Chaos
– volume: 14
  start-page: 185
  year: 2016
  end-page: 199
  ident: b8
  publication-title: Comput. Struct. Biotechnol. J.
– year: 2008
  ident: b10
  publication-title: Time Series Analysis
– year: 2007
  ident: b31
  article-title: A Programmer’s Companion to Algorithm Analysis
– volume: 70
  start-page: 036110
  year: 2004
  ident: b7
  publication-title: Phys. Rev. E
– volume: 21
  start-page: 1576
  year: 2007
  end-page: 1600
  ident: b11
  publication-title: Mech. Syst. Signal Process
– volume: 116
  start-page: 033902
  year: 2016
  ident: b28
  publication-title: Phys. Rev. Lett.
– start-page: 583
  year: 1991
  end-page: 605
  ident: b33
  publication-title: Theory of Heart: Biomechanics, Biophysics, and Nonlinear Dynamics of Cardiac Function
– volume: 96
  start-page: 012318
  year: 2017
  ident: b26
  publication-title: Phys. Rev. E
– volume: 161
  start-page: 253
  year: 1999
  end-page: 270
  ident: b2
  publication-title: Chem. Geol.
– volume: 378
  start-page: 519
  year: 2007
  end-page: 526
  ident: b15
  publication-title: Physica A
– volume: 20
  start-page: 019902
  year: 2010
  ident: b14
  publication-title: Chaos
– volume: 26
  start-page: 053107
  year: 2016
  ident: b20
  publication-title: Chaos
– volume: 1
  start-page: 162
  year: 2004
  end-page: 165
  ident: b6
  publication-title: IEEE Geosci. Remote Sens. Lett.
– volume: 7
  start-page: 50
  year: 2016
  ident: b9
  publication-title: J. Pathol. Inform.
– volume: 95
  start-page: 062309
  year: 2017
  ident: b21
  publication-title: Phys. Rev. E
– year: 2009
  ident: b32
  article-title: Introduction to Algorithms
– volume: 387
  start-page: 1381
  year: 2008
  end-page: 1386
  ident: b17
  publication-title: Physica A
– volume: 391
  start-page: 6543
  year: 2012
  end-page: 6555
  ident: b22
  publication-title: Physica A
– volume: 10
  start-page: 12793
  year: 2013
  end-page: 12827
  ident: b3
  publication-title: Hydrol. Earth Syst. Sci. Discuss.
– volume: 27
  start-page: 17
  year: 2007
  end-page: 46
  ident: b4
  publication-title: Int. J. Climatol.
– volume: 21
  start-page: 1019
  year: 2011
  end-page: 1046
  ident: b16
  publication-title: Int. J. Bifurcation Chaos
– volume: 410
  start-page: 483
  year: 2014
  end-page: 495
  ident: b23
  publication-title: Physica A
– volume: 387
  start-page: 1381
  year: 2008
  ident: 10.1016/j.physa.2018.09.053_b17
  publication-title: Physica A
  doi: 10.1016/j.physa.2007.10.055
– year: 2008
  ident: 10.1016/j.physa.2018.09.053_b10
– volume: 27
  start-page: 17
  year: 2007
  ident: 10.1016/j.physa.2018.09.053_b4
  publication-title: Int. J. Climatol.
  doi: 10.1002/joc.1377
– volume: 493
  start-page: 253
  year: 2018
  ident: 10.1016/j.physa.2018.09.053_b27
  publication-title: Physica A
  doi: 10.1016/j.physa.2017.10.015
– volume: 105
  start-page: 4972
  year: 2008
  ident: 10.1016/j.physa.2018.09.053_b18
  publication-title: Proc. Natl. Acad. Sci. USA
  doi: 10.1073/pnas.0709247105
– volume: 20
  start-page: 019902
  year: 2010
  ident: 10.1016/j.physa.2018.09.053_b14
  publication-title: Chaos
  doi: 10.1063/1.3332246
– volume: 21
  start-page: 1019
  year: 2011
  ident: 10.1016/j.physa.2018.09.053_b16
  publication-title: Int. J. Bifurcation Chaos
  doi: 10.1142/S0218127411029021
– volume: 7
  start-page: 50
  year: 2016
  ident: 10.1016/j.physa.2018.09.053_b9
  publication-title: J. Pathol. Inform.
  doi: 10.4103/2153-3539.197191
– volume: 21
  start-page: 1576
  year: 2007
  ident: 10.1016/j.physa.2018.09.053_b11
  publication-title: Mech. Syst. Signal Process
  doi: 10.1016/j.ymssp.2006.07.005
– volume: 116
  start-page: 033902
  year: 2016
  ident: 10.1016/j.physa.2018.09.053_b28
  publication-title: Phys. Rev. Lett.
  doi: 10.1103/PhysRevLett.116.033902
– volume: 1
  start-page: 162
  year: 2004
  ident: 10.1016/j.physa.2018.09.053_b6
  publication-title: IEEE Geosci. Remote Sens. Lett.
  doi: 10.1109/LGRS.2004.828912
– year: 2007
  ident: 10.1016/j.physa.2018.09.053_b31
– year: 2012
  ident: 10.1016/j.physa.2018.09.053_b1
– volume: 25
  start-page: 083105
  year: 2015
  ident: 10.1016/j.physa.2018.09.053_b30
  publication-title: Chaos
  doi: 10.1063/1.4927835
– volume: 10
  start-page: 250
  year: 2014
  ident: 10.1016/j.physa.2018.09.053_b12
  publication-title: Biomed. Signal Process Control
  doi: 10.1016/j.bspc.2013.10.006
– volume: 97
  start-page: 022223
  year: 2018
  ident: 10.1016/j.physa.2018.09.053_b29
  publication-title: Phys. Rev. E
  doi: 10.1103/PhysRevE.97.022223
– volume: 378
  start-page: 519
  year: 2007
  ident: 10.1016/j.physa.2018.09.053_b15
  publication-title: Physica A
  doi: 10.1016/j.physa.2006.10.089
– volume: 241
  start-page: 326
  year: 2012
  ident: 10.1016/j.physa.2018.09.053_b19
  publication-title: Physica D
  doi: 10.1016/j.physd.2011.09.008
– volume: 26
  start-page: 053107
  year: 2016
  ident: 10.1016/j.physa.2018.09.053_b20
  publication-title: Chaos
  doi: 10.1063/1.4951681
– volume: 70
  start-page: 036110
  year: 2004
  ident: 10.1016/j.physa.2018.09.053_b7
  publication-title: Phys. Rev. E
  doi: 10.1103/PhysRevE.70.036110
– volume: 414
  start-page: 53
  year: 2014
  ident: 10.1016/j.physa.2018.09.053_b34
  publication-title: Physica A
  doi: 10.1016/j.physa.2014.07.002
– volume: 410
  start-page: 483
  year: 2014
  ident: 10.1016/j.physa.2018.09.053_b23
  publication-title: Physica A
  doi: 10.1016/j.physa.2014.05.058
– volume: 96
  start-page: 012318
  year: 2017
  ident: 10.1016/j.physa.2018.09.053_b26
  publication-title: Phys. Rev. E
  doi: 10.1103/PhysRevE.96.012318
– volume: 95
  start-page: 062309
  year: 2017
  ident: 10.1016/j.physa.2018.09.053_b21
  publication-title: Phys. Rev. E
  doi: 10.1103/PhysRevE.95.062309
– ident: 10.1016/j.physa.2018.09.053_b13
– volume: 391
  start-page: 6543
  year: 2012
  ident: 10.1016/j.physa.2018.09.053_b22
  publication-title: Physica A
  doi: 10.1016/j.physa.2012.07.054
– start-page: 583
  year: 1991
  ident: 10.1016/j.physa.2018.09.053_b33
– volume: 10
  start-page: 12793
  year: 2013
  ident: 10.1016/j.physa.2018.09.053_b3
  publication-title: Hydrol. Earth Syst. Sci. Discuss.
  doi: 10.5194/hessd-10-12793-2013
– volume: 482
  start-page: 786
  year: 2017
  ident: 10.1016/j.physa.2018.09.053_b25
  publication-title: Physica A
  doi: 10.1016/j.physa.2017.04.091
– volume: 36
  start-page: L16702
  year: 2009
  ident: 10.1016/j.physa.2018.09.053_b24
  publication-title: Geophys. Res. Lett.
  doi: 10.1029/2009GL039129
– year: 2009
  ident: 10.1016/j.physa.2018.09.053_b32
– volume: 161
  start-page: 253
  year: 1999
  ident: 10.1016/j.physa.2018.09.053_b2
  publication-title: Chem. Geol.
  doi: 10.1016/S0009-2541(99)00091-1
– volume: 30
  start-page: 1538
  year: 2010
  ident: 10.1016/j.physa.2018.09.053_b5
  publication-title: Int. J. Climatol.
  doi: 10.1002/joc.2001
– volume: 14
  start-page: 185
  year: 2016
  ident: 10.1016/j.physa.2018.09.053_b8
  publication-title: Comput. Struct. Biotechnol. J.
  doi: 10.1016/j.csbj.2016.05.002
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Snippet In recent years, transforming a time series into visibility network has emerged as a powerful tool of data analysis, with applications in many pure and applied...
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SubjectTerms Complex network
Iteration and recursion
Time series analysis
Visibility graph algorithm
Title An efficient non-recursive algorithm for transforming time series to visibility graph
URI https://dx.doi.org/10.1016/j.physa.2018.09.053
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