[PRE REVIEW]: Traja: A Python toolbox for animal trajectory analysis

[whedon]

Submitting author: @justinshenk (Justin Shenk) Repository: https://github.com/traja-team/traja Version: v0.2.5 Editor: @jni Reviewers: @a-paxton, @abigailmcgovern Managing EiC: Arfon Smith

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Software report (experimental):

github.com/AlDanial/cloc v 1.88  T=0.24 s (318.4 files/s, 62843.0 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          47           1819           2000           6420
TeX                              1            148              0           1893
reStructuredText                18            537            417            513
Markdown                         1            148              0            404
YAML                             6             18              0            115
TOML                             1              1              0             20
Jupyter Notebook                 1              0            511             18
make                             1              4              6              9
-------------------------------------------------------------------------------
SUM:                            76           2675           2934           9392
-------------------------------------------------------------------------------

Statistical information for the repository 'a3ada5064c96b198323881bd' was
gathered on 2021/03/14.
The following historical commit information, by author, was found:

Author                     Commits    Insertions      Deletions    % of changes
Alex Liberzon                    1             4              3            0.01
JarnoRFB                         2           463            319            1.56
Justin Shenk                   263         17100           9899           53.87
Madhav                           2            17             15            0.06
Madhav Thakker                   6            61           1779            3.67
Saran-nns                      161          8173           4142           24.57
Saranraj Nambusubram             1             2             27            0.06
Wolf Byttner                   134          3520           4596           16.19

Below are the number of rows from each author that have survived and are still
intact in the current revision:

Author                     Rows      Stability          Age       % in comments
Alex Liberzon                 2           50.0          6.8                0.00
JarnoRFB                    232           50.1         24.4                3.02
Justin Shenk               6129           35.8         19.3                8.68
Madhav                       45          264.7          0.2                0.00
Madhav Thakker               20           32.8          0.4                5.00
Saran-nns                  1658           20.3          2.2                8.38
Wolf Byttner               2153           61.2          1.3                8.04

[whedon]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[whedon]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.3389/fnsys.2019.00020 is OK
- 10.1111/eth.12739 is OK
- 10.4103/0976-500X.72351 is OK
- 10.1161/01.str.30.12.2752 is OK
- 10.1161/STROKEAHA.108.541128 is OK
- 10.1021/ac60214a047 is OK
- 10.3390/s19153274 is OK
- 10.1038/jcbfm.2015.149 is OK
- 10.2147/DDDT.S56071 is OK
- 10.1186/s40462-017-0097-x is OK
- 10.1155/2016/6846721 is OK
- 10.1038/jcbfm.2012.185 is OK
- 10.1016/j.neurobiolaging.2013.09.038 is OK
- 10.1098/rsif.2017.0885 is OK
- 10.1038/s41598-018-32949-3 is OK
- 10.1007/s10182-017-0302-7 is OK
- 10.1038/s41598-018-32949-3 is OK
- 10.1109/ISM.2008.115 is OK
- 10.1109/EMBC.2016.7591745 is OK
- 10.1007/BF00379695 is OK
- 10.1007/978-3-540-74553-2_44 is OK
- 10.1007/s10462-018-9619-1 is OK
- 10.1553/giscience2019_01_s54 is OK
- 10.1214/aoms/1177703732 is OK
- 10.1016/j.ecolmodel.2003.06.004 is OK
- 10.1007/s10651-006-0015-7 is OK
- 10.1016/j.applanim.2014.11.018 is OK
- 10.1145/3159652.3159671 is OK
- 10.1371/journal.pone.0220751 is OK
- 10.1145/2743025 is OK
- 10.3390/nu11102430 is OK
- 10.1016/j.heliyon.2019.e01454 is OK
- 10.1371/journal.pone.0211063 is OK
- 10.1016/S0149-7634(02)00103-3 is OK
- 10.1016/j.anbehav.2016.12.005 is OK
- 10.1111/eth.12739 is OK
- 10.1101/345132 is OK
- 10.1016/j.jneumeth.2012.02.001 is OK
- 10.1016/j.jneumeth.2011.01.010 is OK
- 10.5607/en.2014.23.1.104 is OK
- 10.1016/j.jneumeth.2010.01.035 is OK
- 10.1016/S0031-9384(01)00530-3 is OK
- 10.1016/j.pnpbp.2007.06.023 is OK
- 10.1016/S0165-0270(99)00156-9 is OK
- 10.1016/j.jneumeth.2010.12.016 is OK
- 10.1016/j.neubiorev.2010.04.004 is OK
-  10.25080/Majora-92bf1922-00a  is OK
- 10.1037/0096-1523.16.4.755 is OK
- 10.5281/zenodo.3509134 is OK
- 10.1186/s40462-019-0177-1 is OK
- 10.1371/journal.pbio.1000412 is OK
- 10.1161/STROKEAHA.108.541128 is OK
- 10.3791/2423 is OK
- 10.1007/978-1-4615-0123-7_17 is OK
- 10.1523/JNEUROSCI.1206-09.2009 is OK
- 10.1111/j.1601-183x.2004.00064.x is OK
- 10.1016/j.lfs.2009.07.015 is OK
- 10.1016/j.physbeh.2004.04.006 is OK
- 10.1186/1743-0003-2-20 is OK
- 10.1007/s10182-017-0302-7 is OK
- 10.1093/brain/119.2.551 is OK
- 10.1016/0006-8993(75)90545-4 is OK
- 10.1523/JNEUROSCI.5692-07.2008 is OK
- 10.1371/journal.pone.0202505 is OK
- 10.7150/thno.17559 is OK
- 10.1016/j.neubiorev.2010.04.004 is OK
- 10.1016/j.coisb.2017.07.012 is OK
- 10.1111/jnc.14213 is OK
- 10.1145/2743025 is OK
- 10.1016/j.anbehav.2016.12.005 is OK
- 10.12688/wellcomeopenres.9892.2 is OK
- 10.1038/nature19356 is OK
- 10.1152/physiolgenomics.00139.2006 is OK
- 10.1002/9780470942390.mo140229 is OK
- 10.1038/ncb437 is OK
- 10.3758/BF03195394 is OK
- 10.1073/pnas.0809053106 is OK
- 10.1038/ncomms1064 is OK
- 10.1016/j.neuron.2008.03.001 is OK
- 10.1016/j.gaitpost.2012.01.004 is OK
- 10.1038/sc.2010.128 is OK
- 10.1016/j.lfs.2009.07.015 is OK
- 10.3389/fnins.2016.00042 is OK
- 10.1016/j.jneumeth.2010.12.016 is OK
- 10.5607/en.2014.23.1.104 is OK
- 10.1016/j.jneumeth.2010.01.035 is OK
- 10.1038/srep16171 is OK
- 10.4018/978-1-7998-5101-1.ch001 is OK
- 10.3389/fnins.2020.00518 is OK

MISSING DOIs

- 10.1109/cvprw.2019.00359 may be a valid DOI for title: Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs
- 10.1109/cvprw.2019.00358 may be a valid DOI for title: Peeking into the Future: Predicting Future Person Activities and Locations in Videos
- 10.1109/cvpr.2019.00868 may be a valid DOI for title: TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions
- 10.25080/majora-92bf1922-00a may be a valid DOI for title: Data structures for statistical computing in python
- 10.1109/cvpr.2019.00868 may be a valid DOI for title: TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions
- 10.1007/s10182-017-0302-7 may be a valid DOI for title: Statistical modelling of individual animal movement: an overview of key methods and a discussion of practical challenges
- 10.1371/journal.pcbi.1005115 may be a valid DOI for title: M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice
- 10.1109/cvpr.2019.00868 may be a valid DOI for title: TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions
- 10.1109/cvprw.2019.00358 may be a valid DOI for title: Peeking into the Future: Predicting Future Person Activities and Locations in Videos
- 10.1109/cvprw.2019.00359 may be a valid DOI for title: Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs
- 10.1109/seaa.2018.00018 may be a valid DOI for title: Software Engineering Challenges of Deep Learning
- 10.1007/978-3-540-74553-2_44 may be a valid DOI for title: Mining Trajectory Patterns Using Hidden Markov Models
- 10.1016/s0047-6374(01)00324-4 may be a valid DOI for title: Automated measurement of age-related changes in the locomotor response to environmental novelty and home-cage activity.
- 10.1109/seaa.2018.00018 may be a valid DOI for title: Software Engineering Challenges of Deep Learning
- 10.1109/cvpr.2019.00868 may be a valid DOI for title: TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions

INVALID DOIs

- https://doi.org/10.1046/j.1365-2656.1999.00279.x is INVALID because of 'https://doi.org/' prefix
- https://doi.org/10.1111/j.2041-210X.2012.00197.x is INVALID because of 'https://doi.org/' prefix

[arfon]

@whedon invite @jni as editor

👋 @jni would you be willing to edit this submission for JOSS? I realized that #3103 might be a better fit for @cMadan.

[whedon]

@jni has been invited to edit this submission.

[jni]

@whedon assign me as editor

[whedon]

OK, the editor is @jni

[jni]

Hi @justinshenk,

Thanks for your submission. While I look for reviewers (feel free to suggest any here, without @-mentioning them), could you please:

a) fix the references in the paper as suggested by this comment from our bot, b) make sure you cite appropriate papers for any software you use. For example, I don't see citations for matplotlib, seaborn, or NumPy, all of which I think your software uses directly? And, c) re-work the paper to move most of the content, which discusses the API in details, to the documentation? The paper should contain a succinct, high-level description of the software's functionality, not details of the API. For more, please read the "What should my paper contain section of our documentation.

Thank you!

[JustinShenk]

@whedon generate pdf

[whedon]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[JustinShenk]

@whedon check references

[whedon]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.3389/fnsys.2019.00020 is OK
- 10.25080/majora-92bf1922-00a is OK
- 10.1111/eth.12739 is OK
- 10.4103/0976-500X.72351 is OK
- 10.1161/01.str.30.12.2752 is OK
- 10.1161/STROKEAHA.108.541128 is OK
- 10.1021/ac60214a047 is OK
- 10.3390/s19153274 is OK
- 10.1038/jcbfm.2015.149 is OK
- 10.2147/DDDT.S56071 is OK
- 10.1186/s40462-017-0097-x is OK
- 10.1155/2016/6846721 is OK
- 10.1038/jcbfm.2012.185 is OK
- 10.1016/j.neurobiolaging.2013.09.038 is OK
- 10.1098/rsif.2017.0885 is OK
- 10.1038/s41598-018-32949-3 is OK
- 10.1007/s10182-017-0302-7 is OK
- 10.1038/s41598-018-32949-3 is OK
- 10.1109/ISM.2008.115 is OK
- 10.1109/EMBC.2016.7591745 is OK
- 10.1007/BF00379695 is OK
- 10.1007/s10462-018-9619-1 is OK
- 10.1553/giscience2019_01_s54 is OK
- 10.1214/aoms/1177703732 is OK
- 10.1016/j.ecolmodel.2003.06.004 is OK
- 10.1007/s10651-006-0015-7 is OK
- 10.1016/j.applanim.2014.11.018 is OK
- 10.1145/3159652.3159671 is OK
- 10.1371/journal.pone.0220751 is OK
- 10.1371/journal.pcbi.1005115 is OK
- 10.1145/2743025 is OK
- 10.3390/nu11102430 is OK
- 10.1016/j.heliyon.2019.e01454 is OK
- 10.1371/journal.pone.0211063 is OK
- 10.1109/cvprw.2019.00359 is OK
- 10.1016/S0149-7634(02)00103-3 is OK
- 10.1016/j.anbehav.2016.12.005 is OK
- 10.1111/eth.12739 is OK
- 10.1101/345132 is OK
- 10.1016/j.jneumeth.2012.02.001 is OK
- 10.1016/j.jneumeth.2011.01.010 is OK
- 10.5607/en.2014.23.1.104 is OK
- 10.1016/j.jneumeth.2010.01.035 is OK
- 10.1016/S0031-9384(01)00530-3 is OK
- 10.1016/j.pnpbp.2007.06.023 is OK
- 10.1016/S0165-0270(99)00156-9 is OK
- 10.1016/j.jneumeth.2010.12.016 is OK
- 10.1016/j.neubiorev.2010.04.004 is OK
- 10.1109/seaa.2018.00018 is OK
-  10.25080/Majora-92bf1922-00a  is OK
- 10.1037/0096-1523.16.4.755 is OK
- 10.5281/zenodo.3509134 is OK
- 10.1186/s40462-019-0177-1 is OK
- 10.1371/journal.pbio.1000412 is OK
- 10.1161/STROKEAHA.108.541128 is OK
- 10.3791/2423 is OK
- 10.1007/978-1-4615-0123-7_17 is OK
- 10.1523/JNEUROSCI.1206-09.2009 is OK
- 10.1046/j.1365-2656.1999.00279.x is OK
- 10.1111/j.1601-183x.2004.00064.x is OK
- 10.1016/j.lfs.2009.07.015 is OK
- 10.1016/j.physbeh.2004.04.006 is OK
- 10.1186/1743-0003-2-20 is OK
- 10.1007/978-3-540-74553-2_44 is OK
- 10.1038/s41586-020-2649-2 is OK
- 10.5281/zenodo.592845 is OK
- 10.1109/MCSE.2007.55 is OK
- 10.1111/j.2041-210X.2012.00197.x is OK
- 10.1007/s10182-017-0302-7 is OK
- 10.1093/brain/119.2.551 is OK
- 10.1016/0006-8993(75)90545-4 is OK
- 10.1523/JNEUROSCI.5692-07.2008 is OK
- 10.1371/journal.pone.0202505 is OK
- 10.7150/thno.17559 is OK
- 10.1016/j.neubiorev.2010.04.004 is OK
- 10.1016/j.coisb.2017.07.012 is OK
- 10.1111/jnc.14213 is OK
- 10.1145/2743025 is OK
- 10.1016/j.anbehav.2016.12.005 is OK
- 10.12688/wellcomeopenres.9892.2 is OK
- 10.1038/nature19356 is OK
- 10.1152/physiolgenomics.00139.2006 is OK
- 10.1002/9780470942390.mo140229 is OK
- 10.1038/ncb437 is OK
- 10.3758/BF03195394 is OK
- 10.1073/pnas.0809053106 is OK
- 10.1038/ncomms1064 is OK
- 10.1016/s0047-6374(01)00324-4  is OK
- 10.1016/j.neuron.2008.03.001 is OK
- 10.1016/j.gaitpost.2012.01.004 is OK
- 10.1038/sc.2010.128 is OK
- 10.1016/j.lfs.2009.07.015 is OK
- 10.3389/fnins.2016.00042 is OK
- 10.1016/j.jneumeth.2010.12.016 is OK
- 10.5607/en.2014.23.1.104 is OK
- 10.1016/j.jneumeth.2010.01.035 is OK
- 10.1038/srep16171 is OK
- 10.4018/978-1-7998-5101-1.ch001 is OK
- 10.3389/fnins.2020.00518 is OK
- 10.1109/cvpr.2019.00868 is OK

MISSING DOIs

- 10.1109/cvprw.2019.00358 may be a valid DOI for title: Peeking into the Future: Predicting Future Person Activities and Locations in Videos

INVALID DOIs

- None

[JustinShenk]

@whedon generate pdf

[whedon]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[JustinShenk]

Hi @justinshenk,

Thanks for your submission. While I look for reviewers (feel free to suggest any here, without @-mentioning them), could you please:

a) fix the references in the paper as suggested by this comment from our bot, b) make sure you cite appropriate papers for any software you use. For example, I don't see citations for matplotlib, seaborn, or NumPy, all of which I think your software uses directly? And, c) re-work the paper to move most of the content, which discusses the API in details, to the documentation? The paper should contain a succinct, high-level description of the software's functionality, not details of the API. For more, please read the "What should my paper contain section of our documentation.

Thank you!

Hi @jni, Thanks for your helpful comments! The paper has been updated as requested, with API documentation removed and links fixed.

Looking forward to your further review.

[jni]

Great, thank you! Still looking for reviewers but I have one promising and one open lead. 🤞

[jni]

Thanks everyone for your patience — almost there...! 😬

[jni]

@whedon assign @a-paxton as reviewer

[whedon]

OK, @a-paxton is now a reviewer

[jni]

@whedon add @abigailmcgovern as reviewer

[whedon]

OK, @abigailmcgovern is now a reviewer

[jni]

@whedon start review

[whedon]

OK, I've started the review over in https://github.com/openjournals/joss-reviews/issues/3202.

[JustinShenk]

@whedon generate pdf

[whedon]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[jni]

Did you mean to do this here instead of on #3202, @justinshenk?

[JustinShenk]

Good catch. Thank you for reminding me of the new location!