Joss-reviews: [PRE REVIEW]: deeplenstronomy: A dataset simulation package for strong gravitational lensing

Created on 11 Nov 2020  路  35Comments  路  Source: openjournals/joss-reviews

Submitting author: @rmorgan10 (Robert Morgan)
Repository: https://github.com/deepskies/deeplenstronomy
Version: v0.0.1.0
Editor: @pdebuyl
Reviewers: @shreyasbapat, @jiwoncpark
Managing EiC: Kristen Thyng

:warning: JOSS reduced service mode :warning:

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Author instructions

Thanks for submitting your paper to JOSS @rmorgan10. Currently, there isn't an JOSS editor assigned to your paper.

The author's suggestion for the handling editor is @harpolea.

@rmorgan10 if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). In addition, this list of people have already agreed to review for JOSS and may be suitable for this submission (please start at the bottom of the list).

Editor instructions

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Jupyter Notebook Makefile Python pre-review

Most helpful comment

Sure! I'll be glad to!

All 35 comments

Hello human, I'm @whedon, a robot that can help you with some common editorial tasks.

:warning: JOSS reduced service mode :warning:

Due to the challenges of the COVID-19 pandemic, JOSS is currently operating in a "reduced service mode". You can read more about what that means in our blog post.

For a list of things I can do to help you, just type:

@whedon commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

@whedon generate pdf

PDF failed to compile for issue #2834 with the following error:

/app/vendor/ruby-2.6.6/lib/ruby/2.6.0/psych.rb:456:in parse': (4f9319a0577a52cb76197b48/paper.md): mapping values are not allowed in this context at line 9 column 52 (Psych::SyntaxError) from /app/vendor/ruby-2.6.6/lib/ruby/2.6.0/psych.rb:456:inparse_stream'
from /app/vendor/ruby-2.6.6/lib/ruby/2.6.0/psych.rb:390:in parse' from /app/vendor/ruby-2.6.6/lib/ruby/2.6.0/psych.rb:277:inload'
from /app/vendor/ruby-2.6.6/lib/ruby/2.6.0/psych.rb:578:in block in load_file' from /app/vendor/ruby-2.6.6/lib/ruby/2.6.0/psych.rb:577:inopen'
from /app/vendor/ruby-2.6.6/lib/ruby/2.6.0/psych.rb:577:in load_file' from /app/vendor/bundle/ruby/2.6.0/bundler/gems/whedon-54ca145bf448/lib/whedon.rb:127:inload_yaml'
from /app/vendor/bundle/ruby/2.6.0/bundler/gems/whedon-54ca145bf448/lib/whedon.rb:87:in initialize' from /app/vendor/bundle/ruby/2.6.0/bundler/gems/whedon-54ca145bf448/lib/whedon/processor.rb:38:innew'
from /app/vendor/bundle/ruby/2.6.0/bundler/gems/whedon-54ca145bf448/lib/whedon/processor.rb:38:in set_paper' from /app/vendor/bundle/ruby/2.6.0/bundler/gems/whedon-54ca145bf448/bin/whedon:58:inprepare'
from /app/vendor/bundle/ruby/2.6.0/gems/thor-0.20.3/lib/thor/command.rb:27:in run' from /app/vendor/bundle/ruby/2.6.0/gems/thor-0.20.3/lib/thor/invocation.rb:126:ininvoke_command'
from /app/vendor/bundle/ruby/2.6.0/gems/thor-0.20.3/lib/thor.rb:387:in dispatch' from /app/vendor/bundle/ruby/2.6.0/gems/thor-0.20.3/lib/thor/base.rb:466:instart'
from /app/vendor/bundle/ruby/2.6.0/bundler/gems/whedon-54ca145bf448/bin/whedon:131:in <top (required)>' from /app/vendor/bundle/ruby/2.6.0/bin/whedon:23:inload'
from /app/vendor/bundle/ruby/2.6.0/bin/whedon:23:in `

'

Software report (experimental):

github.com/AlDanial/cloc v 1.84  T=0.48 s (198.9 files/s, 50289.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          39           1217           1496           3684
Jupyter Notebook                19              0          12323           1731
YAML                            19            121             27           1602
Markdown                         5            178              0            788
TeX                              1             15              0            369
DOS Batch                        1             29              1            212
make                             2             39              6            188
reStructuredText                 9             75             17            130
INI                              1              3              0             24
-------------------------------------------------------------------------------
SUM:                            96           1677          13870           8728
-------------------------------------------------------------------------------


Statistical information for the repository '3a1fc19720c38e628fb51236' was
gathered on 2020/11/11.
The following historical commit information, by author, was found:

Author                     Commits    Insertions      Deletions    % of changes
Brian Nord                      28          2767            491           22.96
Jason Poh                       10           521            192            5.03
Joao Caldeira                   13           183            307            3.45
Robert Morgan                   94          5551           1443           49.29
joshualin24                      7           194             90            2.00
sibirrer                        38          1080           1370           17.27

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
Brian Nord                 1976           71.4          8.5               19.33
Jason Poh                   132           25.3         15.6                3.79
Joao Caldeira               106           57.9         15.5               11.32
Robert Morgan              3949           71.1          4.5               12.18
joshualin24                  55           28.4         15.6               16.36
sibirrer                    182           16.9         15.9                5.49

@pdebuyl Are you able to take on this submission?

@whedon invite @pdebuyl as editor

@pdebuyl has been invited to edit this submission.

@rmorgan10 not sure about the error in your paper... can you compare your line 9 with the paper requirements and see if something is amiss?

It looks like lines 8-9 are

authors:
  - name: Robert Morgan^[Corresponding author email: [email protected]]

Though I believe I followed the same syntax as the paper requirements:

authors:
  - name: Adrian M. Price-Whelan^[Custom footnotes for e.g. denoting who the corresponding author is can be included like this.]

I'm not quite sure what the problem is either.

@whedon assign me as editor

OK, the editor is @pdebuyl

I have a feeling the compile issue is the ':' character in the footnote, or perhaps that the footnote text needs to be enclosed in single quotes. I will test this as soon as I can, but at present the online compile service seems to be down.

I have a feeling the compile issue is the ':' character in the footnote, or perhaps that the footnote text needs to be enclosed in single quotes. I will test this as soon as I can, but at present the online compile service seems to be down.

This should be fixed again now.

@rmorgan10 - is this JOSS submission associated with a paper in a AAS journal?

@rmorgan10 the AAS question should be answered before I proceed. BTW, as you have an ORCID record the email could be considered superfluous, which would solve the compilation issue :-)

@arfon this JOSS submission is not associated with a paper in a AAS journal.

@pdebuyl , @kthyng the compilation issue has been fixed and everything looks good!

@whedon generate pdf

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

@fipanther @shreyasbapat can you review the article "deeplenstronomy: A dataset simulation package for strong gravitational lensing" for JOSS ?

Sure! I'll be glad to!

At the same time, @rmorgan10 do you think this can be brought in the family of @einsteinpy ?

@kakirastern See this package!
@rmorgan10 we always planned to do something similar in @einsteinpy ! Great work!

deeplenstronomy doesn't perform any gravitational lensing calculations itself, it's a wrapper that focuses on generating and organizing data for deep learning using the package lenstronomy (which is the main gravitational lensing workhorse).

After a quick glance at the @einsteinpy family, to me it doesn't feel like deeplenstronomy fits in, but I'd be happy to discuss it more with you if you think it does!

Thank you @shreyasbapat for accepting :-)

Nice

@fipanther @shreyasbapat can you review the article "deeplenstronomy: A dataset simulation package for strong gravitational lensing" for JOSS ?

Can I help as well?

@kakirastern I pick reviewers from this list first and try to balance the reviewers' backgrounds. The best way forward, in any case, is to volunteer to review for JOSS here: https://joss.theoj.org/reviewer-signup.html Then you can be picked for a future submission.

Sure @pdebuyl, let me volunteer for JOSS now. Thanks for the heads up!

@jiwoncpark can you review the article "deeplenstronomy: A dataset simulation package for strong gravitational lensing" for JOSS?

@pdebuyl Sure, happy to.

Thank you @jiwoncpark !

@whedon assign @shreyasbapat as reviewer

OK, @shreyasbapat is now a reviewer

@whedon add @jiwoncpark as reviewer

OK, @jiwoncpark is now a reviewer

@whedon start review

OK, I've started the review over in https://github.com/openjournals/joss-reviews/issues/2854.

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