[REVIEW]: The Python Sky Model 3 software

[whedon]

Submitting author: @zonca (Andrea Zonca)
Repository: https://github.com/galsci/pysm
Version: v3.3.2
Editor: @christinahedges
Reviewer: @patricialarsen, @smsharma
Archive: 10.5281/zenodo.5620868

⚠️ JOSS reduced service mode ⚠️

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Review checklist for @patricialarsen

✨ Important: Please do not use the Convert to issue functionality when working through this checklist, instead, please open any new issues associated with your review in the software repository associated with the submission. ✨

Conflict of interest

• I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• Repository: Is the source code for this software available at the repository url?
• License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@zonca) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

• Installation: Does installation proceed as outlined in the documentation?
• Functionality: Have the functional claims of the software been confirmed?
• Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Does the paper have a section titled 'Statement of Need' that clearly states what problems the software is designed to solve and who the target audience is?
• State of the field: Do the authors describe how this software compares to other commonly-used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

Review checklist for @smsharma

✨ Important: Please do not use the Convert to issue functionality when working through this checklist, instead, please open any new issues associated with your review in the software repository associated with the submission. ✨

Conflict of interest

• I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• Repository: Is the source code for this software available at the repository url?
• License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@zonca) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

• Installation: Does installation proceed as outlined in the documentation?
• Functionality: Have the functional claims of the software been confirmed?
• Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Does the paper have a section titled 'Statement of Need' that clearly states what problems the software is designed to solve and who the target audience is?
• State of the field: Do the authors describe how this software compares to other commonly-used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

[whedon]

Hello human, I'm @whedon, a robot that can help you with some common editorial tasks. @patricialarsen, @smsharma it looks like you're currently assigned to review this paper 🎉.

⚠️ JOSS reduced service mode ⚠️

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[whedon]

Wordcount for paper.md is 1150

[whedon]

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

OK DOIs

- 10.1086/427976 is OK
- 10.21105/joss.01298 is OK
- 10.1093/mnras/stx949 is OK
- 10.1088/0067-0049/208/2/20 is OK
- 10.1145/2833157.2833162 is OK
- 10.1051/0004-6361/201321494 is OK
- 10.1051/0004-6361/201322068 is OK
- 10.3847/1538-3881/aabc4f is OK

MISSING DOIs

- None

INVALID DOIs

- None

[whedon]

Software report (experimental):

github.com/AlDanial/cloc v 1.88  T=0.11 s (648.0 files/s, 107392.1 lines/s)
--------------------------------------------------------------------------------
Language                      files          blank        comment           code
--------------------------------------------------------------------------------
Python                           42            820           1400           2965
Jupyter Notebook                  8              0           4416            527
reStructuredText                  7            148             28            285
TeX                               1              8              0            186
DOS Batch                         1             21              1            150
make                              1             22              5            106
INI                               1             14              0             90
YAML                              3             12             18             87
Markdown                          1             22              0             74
Bourne Shell                      2              0              0             12
Bourne Again Shell                1              1              5              5
TOML                              1              2              0              5
--------------------------------------------------------------------------------
SUM:                             69           1070           5873           4492
--------------------------------------------------------------------------------


Statistical information for the repository '7fb1e252e6e09ab7c8ccda6e' was
gathered on 2021/09/29.
The following historical commit information, by author, was found:

Author                     Commits    Insertions      Deletions    % of changes
Andrea Zonca                   218          6873           3271           79.11
Ben Thorne                      21           706            173            6.86
NicolettaK                       1            21             15            0.28
Xavier Garrido                   3            51             27            0.61
ben thorne                      11          1345            340           13.14

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
Andrea Zonca               4696           68.3         23.0               12.18
Ben Thorne                  431           61.0         26.5               15.08
NicolettaK                   17           81.0         11.5                0.00
Xavier Garrido               41           80.4         16.1                4.88

[whedon]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[christinahedges]

@zonca, @patricialarsen, @smsharma – This is the review thread for the paper. Please don't hesitate to message me here if you have questions.

Please read the "Reviewer instructions & questions" in the first comment above to get started. If you get lost, you can also see the reviewer guidelines.

Both reviewers have checklists at the top of this thread (in that first comment) with the JOSS requirements. As you go over the submission, please check any items that you feel have been satisfied. If you are concerned about a requirement, please discuss it here on this thread 🧵 . Feel free to post about questions/concerns as they come up as you go through your review.

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention #3783 so that a link is created to this thread (and I can keep an eye on what is happening).

We aim for the review process to be completed within about 4-6 weeks but please make a start well ahead of this as JOSS reviews are by their nature iterative and any early feedback you may be able to provide to the author will be very helpful in meeting this schedule. When you're finished with your checklist, leave a comment and @ me to let everyone know you're review is complete.

[patricialarsen]

Hi!

Installation is going fairly smoothly so far. The conda, pip and development installation work from the instructions on my home linux computer, with a fresh python3 installation.

A few minor issues though once I hit running the unit tests on these - firstly there's additional notes on this in the setup.py file. Those are useful but a little well-hidden and could be placed somewhere more visible. Secondly a slight issue is coming up in the config file for an install of the development version into a fresh conda environment:

I'm getting
pytest: error: unrecognized arguments: --doctest-rst

It works okay if I change the flag in line 45 of setup.cfg from
addopts = --doctest-rst
to
addopts = --doctest-glob="*.rst"

I'm having a little more trouble getting the tests running through tox, which seem to be fixed by adding dependencies to the config file as well as updating my c compilers through
conda install -c conda-forge c-compiler compilers cxx-compiler

The dependencies I had to add to the deps section of tox.ini are:
astropy
pytest
numba
healpy

I then manage to pass tests using tox with
=================================== 62 passed, 3 skipped, 585 warnings in 55.26s ===================================
And through pytest with
=================================== 60 passed, 2 skipped, 340 warnings in 52.24s ===================================

A large number of warnings, which mostly look like
UserWarning: Retrieve data for pysm_2_test_data/check_d5_100_uK_RJ_64.fits (if not cached already)

These warnings could be looked into, and suppressed if they're not important to avoid flagging as an issue.

@smsharma when you look at the installation/automated tests could you please keep an eye out for if these tests run straightforwardly on your system and if you need any adjustments to get them to run?

[zonca]

thanks @patricialarsen I started to work on your recommendations.

About tox, I cannot reproduce the problem.

I tried with a plain conda environment with only python 3.8.
I ran:

tox -e test

and it worked fine. How are you testing it?

[patricialarsen]

Hi @zonca,

I can confirm that the latest github version fixes the pytest issues on my end :)

Re the tox issues, it was failing to read the test dependencies correctly, I can't reproduce it right now oddly after re-cloning the github and restarting the computer, which means it was likely either a temporary issue in my .tox files or environment, or how I was running it at the time and probably nothing that needs changing. Assuming the other reviewer manages to run them okay it should be fine I think.

[whedon]

👋 @smsharma, please update us on how your review is going (this is an automated reminder).

[whedon]

👋 @patricialarsen, please update us on how your review is going (this is an automated reminder).

[christinahedges]

Hi @patricialarsen and @smsharma, I think the last comments were two weeks ago, just wanted to check in how your reviews are coming? It's ok if you need some more time, but maybe drop a comment if you feel you will need a lot more time. @smsharma we haven't heard from you on the thread yet so just wanted to check in.

[smsharma]

Hi @christinahedges, sincere apologies for the delay, I will need a bit more time. I will aim to complete the review by the start of next week.

[patricialarsen]

@christinahedges sorry for the delay, I'll get my next round of comments in before the weekend

[smsharma]

Hi! Congrats to the authors and contributors first of all for a very nice package that's extremely useful to the CMB community.

Installation

I tested the package on an HPC cluster (running CentOS Linux 7) starting from a clean conda environment. I was able to install it no problem through conda and pip, as well as the development version using instructions provided in the documentation.

Tests

I had to install tox and pytest separately. While this is straightforward to do, a minor suggestions would be to either specify that these need to be installed separately, or including them as requirements.

Building the docs locally required installing pandoc; this could be briefly mentioned in the repo README.rst where build instructions are provided (again minor).

Tests with pytest ran successfully. The following output was produced, and the one warning could be suppressed/ignored if it's not an issue or addressed.

=============================================================== warnings summary ================================================================
../.conda/envs/pysm/lib/python3.9/site-packages/astropy/tests/helper.py:31
  /n/home11/smsharma/.conda/envs/pysm/lib/python3.9/site-packages/astropy/tests/helper.py:31: PytestUnknownMarkWarning: Unknown pytest.mark.remote_data - is this a typo?  You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/mark.html
    remote_data = pytest.mark.remote_data

-- Docs: https://docs.pytest.org/en/stable/warnings.html
============================================= 60 passed, 2 skipped, 1 warning in 195.64s (0:03:15) ==============================================

Running tests with tox initially failed, since I did not have an active MPI environment, and hence no mpi4py installed (I'm not sure why this wasn't an issue earlier). The specific error was:

fatal error: mpi.h: No such file or directory 

It wasn't clear from the docs or README whether MPI was required or an optional enhancement to improve performance---this should be made clearer. If it's required, the fact that a working MPI installation is needed could be mentioned as well (since this seems to be the source of the error above). If not, the code and tests should be able to run without MPI.

After activating an appropriate compiler and MPI environment, the tox test completed successfully (modulo the warning from pytest above).

Functionality and API

After installation, I was able to run the examples successfully, including the Jupyter notebooks and pysm3_mpi.py with MPI. Although I wasn't able to test it out, it is clear from the examples that the functionality is easily extendable to custom use cases. The tight API integration with astropy is well done.

Just to conclude, most of the comments and suggestions above (with the exception of those re: MPI installation, testing, and usage perhaps) are very minor, and I've checked off the other items on the checklist.

[zonca]

thanks @smsharma! very good findings,
See galsci/pysm#93 for fixes on docs and test
your warning was probably due to pytest-astropy missing, it should be fixed if you follow the new docs.

Next I'll look into MPI.

[patricialarsen]

Hi @zonca

I should have my review completed fully tomorrow. Just want to confirm that I can roughly replicate the performance numbers for the parallelization, and do another pass through the paper, but I don't expect issues to come up.

Overall I'm very happy with the code. As smsharma noted the API is very nice, and I've run through the tutorial examples and confirmed they're all working as expected (the existence of those is much appreciated), and I think the documentation between the model summaries, tutorial notebooks and paper are adequate for anyone using the code. I haven't tested every variation of model options, but between the tests and the tutorials I'm convinced that this should be fine.

A few minor concerns:

a) that the mpi section of the tutorial notebooks is much lighter than the rest:

It seems like the MPI compatibility is something that was really important in the development, so even though I guess it doesn't really work with the jupyter notebook format of the tutorials as well, it would still be really nice to have the syntax of the map distribution outlined in that tutorial section. Even just to copy that linked example into the text.

Then b) when I run the pysm3_mpi example I get a lot of warnings:

Most like the below:

python3.9/site-packages/pysm3/utils/data.py:42: UserWarning: Retrieve data for pysm_2/ame2_t_new.fits (if not cached already)
warnings.warn(f"Retrieve data for {filename} (if not cached already)")

I believe that after posting this warning it does in fact retrieve the data, so can I suggest changing the warning from "retrieve data" to "retrieving data" to make that clear, and consider suppressing these since you get a little inundated?

There are other warnings like:
:228: RuntimeWarning: mpi4py.MPI.Comm size changed, may indicate binary incompatibility. Expected 32 from C header, got 40 from PyObject
which are a bit more worrying.

I think this is a compatibility issue with the default mpi4py version. These go away if I use mpi4py==3.0.3. This may just be my machine but I wonder if you could double check if a version requirement needs to be added for mpi4py? The new mpi versions were only released in August this year.

c)
do you also see in the classes list on the documentation one which looks like the below?
PackageNotFoundError | The package was not found.

(edit just noticed the CMB map class also doesn't seem to be linking to the description on the website docs properly)

d)

Finally I do find that although the run_mpi_tests.sh tests pass I get a lot of minor warnings (e.g. see below), it might be worth suppressing or fixing some of these

/pysm3/models/template.py:221: AstropyDeprecationWarning: "verbose" was deprecated in version 1.15.0 and will be removed in a future version.

[zonca]

thanks @patricialarsen

A few minor concerns:

a) that the mpi section of the tutorial notebooks is much lighter than the rest:

It seems like the MPI compatibility is something that was really important in the development, so even though I guess it doesn't really work with the jupyter notebook format of the tutorials as well, it would still be really nice to have the syntax of the map distribution outlined in that tutorial section. Even just to copy that linked example into the text.

I am actually debating if I should remove the MPI functionality, it is used very rarely and makes the code significantly more complicated.

Then b) when I run the pysm3_mpi example I get a lot of warnings:

Most like the below:

python3.9/site-packages/pysm3/utils/data.py:42: UserWarning: Retrieve data for pysm_2/ame2_t_new.fits (if not cached already) warnings.warn(f"Retrieve data for {filename} (if not cached already)")

I think this is fixed in main, see galsci/pysm#88, I will release a new version of PySM as soon as the review is finished, so all we worked on is going to be published.

I believe that after posting this warning it does in fact retrieve the data, so can I suggest changing the warning from "retrieve data" to "retrieving data" to make that clear, and consider suppressing these since you get a little inundated?

There are other warnings like: :228: RuntimeWarning: mpi4py.MPI.Comm size changed, may indicate binary incompatibility. Expected 32 from C header, got 40 from PyObject which are a bit more worrying.

I think this is a compatibility issue with the default mpi4py version. These go away if I use mpi4py==3.0.3. This may just be my machine but I wonder if you could double check if a version requirement needs to be added for mpi4py? The new mpi versions were only released in August this year.

I cannot reproduce this, I don't get warnings with mpi4py 3.1.1
Also I generally assume that people have installed also libsharp when they use MPI (I'll improve the docs explaining this) following https://pysm3.readthedocs.io/en/latest/#dependencies. Maybe that solves the issue?

c) do you also see in the classes list on the documentation one which looks like the below? PackageNotFoundError | The package was not found.

yes, I'll fix that.

(edit just noticed the CMB map class also doesn't seem to be linking to the description on the website docs properly)

do you mean from https://pysm3.readthedocs.io/en/latest/#classes?

d)

Finally I do find that although the run_mpi_tests.sh tests pass I get a lot of minor warnings (e.g. see below), it might be worth suppressing or fixing some of these

/pysm3/models/template.py:221: AstropyDeprecationWarning: "verbose" was deprecated in version 1.15.0 and will be removed in a future version.

this also should be fixed in main

[zonca]

@patricialarsen @smsharma ok, I merged galsci/pysm#93, this has fixes to the warnings and an improved documentation about MPI

[whedon]

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

OK DOIs

- 10.1086/427976 is OK
- 10.21105/joss.01298 is OK
- 10.1093/mnras/stx949 is OK
- 10.1088/0067-0049/208/2/20 is OK
- 10.1145/2833157.2833162 is OK
- 10.1051/0004-6361/201321494 is OK
- 10.1051/0004-6361/201322068 is OK
- 10.3847/1538-3881/aabc4f is OK

MISSING DOIs

- None

INVALID DOIs

- None

[whedon]

👋 @openjournals/joss-eics, this paper is ready to be accepted and published.

Check final proof 👉 openjournals/joss-papers#2720

If the paper PDF and Crossref deposit XML look good in openjournals/joss-papers#2720, then you can now move forward with accepting the submission by compiling again with the flag deposit=true e.g.

@whedon accept deposit=true

[danielskatz]

@zonca - sorry, one more thing I missed - can you protect the Ps in Python in bib entries with {P} - in Thorne et al and Zonca et al

otherwise, this is ready to publish

[zonca]

@danielskatz never noticed before that double braces {{}} preserve capitalization... ;)

[danielskatz]

@whedon recommend-accept

[whedon]

Attempting dry run of processing paper acceptance...

[whedon]

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

OK DOIs

- 10.1086/427976 is OK
- 10.21105/joss.01298 is OK
- 10.1093/mnras/stx949 is OK
- 10.1088/0067-0049/208/2/20 is OK
- 10.1145/2833157.2833162 is OK
- 10.1051/0004-6361/201321494 is OK
- 10.1051/0004-6361/201322068 is OK
- 10.3847/1538-3881/aabc4f is OK

MISSING DOIs

- None

INVALID DOIs

- None

[whedon]

👋 @openjournals/joss-eics, this paper is ready to be accepted and published.

Check final proof 👉 openjournals/joss-papers#2721

If the paper PDF and Crossref deposit XML look good in openjournals/joss-papers#2721, then you can now move forward with accepting the submission by compiling again with the flag deposit=true e.g.

@whedon accept deposit=true

[danielskatz]

@whedon accept deposit=true

[whedon]

Doing it live! Attempting automated processing of paper acceptance...

[whedon]

🐦🐦🐦 👉 Tweet for this paper 👈 🐦🐦🐦

[whedon]

🚨🚨🚨 THIS IS NOT A DRILL, YOU HAVE JUST ACCEPTED A PAPER INTO JOSS! 🚨🚨🚨

Here's what you must now do:

0. Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.03783 joss-papers#2722
1. Wait a couple of minutes, then verify that the paper DOI resolves https://doi.org/10.21105/joss.03783
2. If everything looks good, then close this review issue.
3. Party like you just published a paper! 🎉🌈🦄💃👻🤘

Any issues? Notify your editorial technical team...

[danielskatz]

Congratulations to @zonca (Andrea Zonca) and co-authors!!

And thanks to @christinahedges for editing, and @patricialarsen and @smsharma for reviewing!
We couldn't do this without you

[whedon]

🎉🎉🎉 Congratulations on your paper acceptance! 🎉🎉🎉

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[arfon]

✨✨✨ Congrats on your first paper as editor @christinahedges ✨ ✨✨