whedon commented 3 years ago

Submitting author: !--author-handle-->@piotrbartman@dhhagan<!--end-editor-- Reviewers: @darothen, @josephhardinee Archive: 10.5281/zenodo.6321270

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Review checklist for @josephhardinee

Conflict of interest

[x] 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

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

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

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] 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

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

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] 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?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] 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 @darothen

Conflict of interest

[x] 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

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

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

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] 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

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

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] 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?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] 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 commented 3 years ago

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

: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.

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If you haven't already, you should seriously consider unsubscribing from GitHub notifications for this (https://github.com/openjournals/joss-reviews) repository. As a reviewer, you're probably currently watching this repository which means for GitHub's default behaviour you will receive notifications (emails) for all reviews 😿

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whedon commented 3 years ago

PDF failed to compile for issue #3219 with the following error:

 Can't find any papers to compile :-(

whedon commented 3 years ago

Software report (experimental):

github.com/AlDanial/cloc v 1.88  T=0.41 s (534.1 files/s, 31905.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                         212           2053           1184           7548
SVG                              1              0             19           1402
Jupyter Notebook                 3              0            207            336
Markdown                         1             38              0            280
YAML                             4             20              4            112
-------------------------------------------------------------------------------
SUM:                           221           2111           1414           9678
-------------------------------------------------------------------------------

Statistical information for the repository 'ee5fa7f3802655beaf36d792' was
gathered on 2021/04/26.
The following historical commit information, by author, was found:

Author                     Commits    Insertions      Deletions    % of changes
Anna Jaruga                      1             3              1            0.01
Bartosz Piasecki                 1            42             23            0.08
Michael                         18           443            170            0.80
Michaeldz36                     37          2661           2424            6.64
Piotr Bartman                   10            14             19            0.04
Sylwester Arabas               417         11939           7609           25.54
piotrbartman                    61          2072           2853            6.44
prbartman                      438         26379          19740           60.27
tehAgitto                        4            84             51            0.18

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
Bartosz Piasecki             30           71.4          5.1                0.00
Michael                     289           65.2         15.1               10.03
Sylwester Arabas           4438           37.2          3.2                4.35
piotrbartman               6011          290.1          9.3                7.97
tehAgitto                    42           50.0          4.5                2.38

slayoo commented 3 years ago

@whedon generate pdf from branch JOSS

whedon commented 3 years ago

Attempting PDF compilation from custom branch JOSS. Reticulating splines etc...

whedon commented 3 years ago

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

darothen commented 3 years ago

Review - @darothen

PySDM is a new open-source package for particle-resolved modeling of the physics and chemistry of cloud and aerosol microphysics. It provides high-performance reference implementations of state-of-the-science process models in a flexible, highly-configurable package that is relatively easy to manipulate and modify to suit a wide variety of cloud and aerosol modeling tasks. It also ships with a back-end for running certain processes on GPUs, although this functionality does not seem to be fully implemented for all configurations which a user may seek to leverage.

Overall this is a high quality and valuable contribution to the field. Many researchers leverage simple box and parcel models for critical work into fundamental aerosol/cloud microphysics, and PySDM provides extremely useful tooling for exploring this domain and for replicating the results of other researchers. However, the library is lacking in documentation, both formally (in clearly defining the complex structure of the objects which comprise the code and how they interact) and informally (through docstrings and other comments/annotations in the code which may allow users to better understand arguments to key functions and how to manipulate and extend them). At present, the authors provide a nice "Hello world" example with some prose on how to configure it, as well as a basic section on package structure and API. But a more comprehensive listing of the arguments, attributes, and parameters that the user should know about in order to configure or extend this example would go a very long way to promote practical usability.

I would encourage the authors to improve or augment this documentation before the final publication of this software paper. However, in all other aspects I find this to be a comprehensive and uniquely valuable software contribution to the cloud and aerosol microphysical modeling community and an ideal candidate for publication in JOSS.

Please note the handful of detailed comments below on specific changes necessary to meet JOSS standards.

General Checks

Two authors on the paper (Grzegorz Lazarski and Aleksandra Talar) do not seem to appear as contributors to the repo and aren't listed in "Author Contributions." I don't really believe there is any issue here - for long-incubated software projects like this with lots of research interfaces there have to be many contributors over time! But I do want to note this for the editors.

Functionality

A simple install recipe using PyPI is provided, but given the capability to run on the GPU a conda-forge recipe or something which can help readers understand requirements - or provide a turnkey installation with necessary dependencies - would be very helpful! (Issue 494)
Installation using the documented instructions misses out on installing pystrict, a required dependency (Issue/PR 495)

Documentation

The automated tests seem to work out of the box, but the smoke tests seem to take a very long time to run. Even one of the unit tests (namely attributes/chemistry/test_pH.py) took a disproportionate amount of time compared to the others. Please note that I was not able to run the GPU tests as I did not have immediate access to a GPU-powered machine.
While there is extensive, excellent demonstration and example code available from the authors in related, clearly-linked repositories, the API documentation leaves much to be desired. There is a high degree of customizability and configuration exposed to the user, but very little in the way of curated documentation for the APIs and data structures in the software, or docstrings and annotations. As a motivating example, consider the spectra module; in this module, a nice base class for building probability distributions is exposed, but there are no docstrings describing the required and optional arguments for either the base class or any of the sub-classes which implement it. An effort to improve the documentation with basic docstrings for all the core methods and functionality would greatly improve the quality of the software and the user experience when adapting it for a specialized research task. Ideally, a simple Sphinx-based documentation for the key API and configurations exposed to users would follow very plainly from such an effort, greatly improving the ease of access of the software.
Community / contribution guidelines are not provided with the repo; the JOSS reviewer guidelines suggest that such documentattion should clearly indicate how third-parties may contribute to the software, report issues, and seek support should they need to do so.

Software Paper

The software paper does not include a section which explicitly explains a "Statement of Need." However, I do believe that the prose in the paper covers this topic with the necessary detail. I will defer to the editors whether a stand-alone "Statement of Need" section is required to meet JOSS guidelines.
It's much appreciated that the authors include links to open source software which attempts to tackle subsets of the broad functionality that PySDM provides. I would strongly encourage the author to include a brief discussion of each package (particularly pyrcel and PyBox) and compare/contrast the unique or improved functionalities of PySDM relative to each. My take (as the author of one of those libraries, pyrcel!) is that PySDM offers a substantial improvement over each in terms of the breadth of calculations and science/research that can be performed with it as well as the cleanliness of its interface and design for future improvements and extensions. These are all very positive things for PySDM and I would strongly encourage the authors to lean into the fantastic work here to promote the capabilities and utility of their library relative to the competition!

slayoo commented 3 years ago

@darothen, on behalf of all authors, let me thank for the feedback!

Let me just address one comment right away:

Two authors on the paper (Grzegorz Lazarski and Aleksandra Talar) do not seem to appear as contributors to the repo and aren't listed in "Author Contributions." I don't really believe there is any issue here - for long-incubated software projects like this with lots of research interfaces there have to be many contributors over time! But I do want to note this for the editors.

GŁ's (@golui) and AT's (@aleksandratal) contributions were subject to refactors during which we've not preserved commit authorship, yet these can be traced back, e.g., here: https://github.com/atmos-cloud-sim-uj/PySDM/pull/157 & https://github.com/atmos-cloud-sim-uj/PySDM/pull/142 Both are mentioned in the "Author Contributions" section:

Thanks!

slayoo commented 3 years ago

@whedon generate pdf from branch JOSS

whedon commented 3 years ago

Attempting PDF compilation from custom branch JOSS. Reticulating splines etc...

slayoo commented 3 years ago

@whedon generate pdf from branch JOSS

This was just to reflect an API change within one of the code snippets presented in the text: https://github.com/atmos-cloud-sim-uj/PySDM/commit/ca4d8214ce49abeb6b6b08892428eb04b794bc1f

whedon commented 3 years ago

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

whedon commented 3 years ago

:wave: @jwuttke, please update us on how your review is going (this is an automated reminder).

whedon commented 3 years ago

:wave: @darothen, please update us on how your review is going (this is an automated reminder).

darothen commented 3 years ago

@dhhagan Just checking in here - anything immediately needed from me here?

@slayoo please let me know if there are any PRs or other updates I've missed.

slayoo commented 3 years ago

We are almost done with preparing a release and will soon after post here a point-by-point reply to the review detailing how the points were addressed in the release. Thanks, S.

dhhagan commented 3 years ago

@darothen Thanks for checking in -> you should be good for now. Just waiting on the other reviewer and updated/patches from the authors before any next steps are needed. Thanks for checking in!

dhhagan commented 3 years ago

@jwuttke Can you please update us on the status of your review? Thanks!

piotrbartman commented 3 years ago

@whedon generate pdf from branch JOSS

whedon commented 3 years ago

Attempting PDF compilation from custom branch JOSS. Reticulating splines etc...

dhhagan commented 3 years ago

@whedon reming @jwuttke in 1 day

whedon commented 3 years ago

I'm sorry human, I don't understand that. You can see what commands I support by typing:

@whedon commands

dhhagan commented 3 years ago

@whedon remind @jwuttke in 1 day

whedon commented 3 years ago

Reminder set for @jwuttke in 1 day

whedon commented 3 years ago

:wave: @jwuttke, please update us on how your review is going (this is an automated reminder).

dhhagan commented 3 years ago

Hey @piotrbartman sorry about the long delays here. I am going to start looking for a new reviewer so we can finish this up. Hope to be back with some good news later this week or next.

piotrbartman commented 3 years ago

@dhhagan Thanks for the update!

slayoo commented 3 years ago

Let me provide a point-by-point reply to @darothen's review.

First of all, on behalf of all authors, let me express again our appreciation for the feedback. We have been working on addressing the points raised in the review, and a lot is already reflected in the recent 1.4 release of PySDM (https://github.com/atmos-cloud-sim-uj/PySDM/releases/tag/v1.4).

Review - @darothen

PySDM is a new open-source package for particle-resolved modeling of the physics and chemistry of cloud and aerosol microphysics. It provides high-performance reference implementations of state-of-the-science process models in a flexible, highly-configurable package that is relatively easy to manipulate and modify to suit a wide variety of cloud and aerosol modeling tasks. It also ships with a back-end for running certain processes on GPUs, although this functionality does not seem to be fully implemented for all configurations which a user may seek to leverage.

As correctly pointed out by the reviewer, at the time of the initial submission, the GPU support has been limited to the coalescence process. As of version 1.4, this is extended to all but aqueous chemistry processes, in particular supporting condensational growth/evaporation of particles (yet without adaptive timestepping which features logic less applicable in the GPU SIMT context). Parcel and single-column examples work OK on the GPU, and testing of the GPU code (through the FakeUnits mocking layer) is part of the Continuous Integration workflow.

Overall this is a high quality and valuable contribution to the field. Many researchers leverage simple box and parcel models for critical work into fundamental aerosol/cloud microphysics, and PySDM provides extremely useful tooling for exploring this domain and for replicating the results of other researchers. However, the library is lacking in documentation, both formally (in clearly defining the complex structure of the objects which comprise the code and how they interact) and informally (through docstrings and other comments/annotations in the code which may allow users to better understand arguments to key functions and how to manipulate and extend them). At present, the authors provide a nice "Hello world" example with some prose on how to configure it, as well as a basic section on package structure and API. But a more comprehensive listing of the arguments, attributes, and parameters that the user should know about in order to configure or extend this example would go a very long way to promote practical usability.

The steps taken so far to improve the documentation include:

deployment of pdoc-generated API manual to GitHub pages at https://atmos-cloud-sim-uj.github.io/PySDM/;
addition of a parcel-framework condensation-only example to the README file (with code snippets in Matlab, Julia and Python, as for the earlier available coalescence-only example);
cleanup in docstrings in numerous files in the project.

I would encourage the authors to improve or augment this documentation before the final publication of this software paper. However, in all other aspects I find this to be a comprehensive and uniquely valuable software contribution to the cloud and aerosol microphysical modeling community and an ideal candidate for publication in JOSS.

Extending the documentation is going to be a priority for the upcoming releases and the growing user-base will help us to fulfill this commitment.

Please note the handful of detailed comments below on specific changes necessary to meet JOSS standards. General Checks

Two authors on the paper (Grzegorz Lazarski and Aleksandra Talar) do not seem to appear as contributors to the repo and aren't listed in "Author Contributions." I don't really believe there is any issue here - for long-incubated software projects like this with lots of research interfaces there have to be many contributors over time! But I do want to note this for the editors.

As pointed out above (https://github.com/openjournals/joss-reviews/issues/3219#issuecomment-827915407), contributions of both Grzegorz Łazarski and Aleksandra Talar can be traced back on github, yet the commit authorship was partly lost as a part of refactors when handling their contributions.

Functionality

A simple install recipe using PyPI is provided, but given the capability to run on the GPU a conda-forge recipe or something which can help readers understand requirements - or provide a turnkey installation with necessary dependencies - would be very helpful! (Issue 494)

We are actively working on addressing it:

following our request, the conda ThrustRTC package has been updated: https://github.com/fynv/ThrustRTC/issues/13
following our request, a conda CURandRTC package has been created: https://github.com/fynv/CURandRTC/issues/3
a draft of conda meta file is already being worked on in a PySDM PR by @Golui (Grzegorz Łazarski): https://github.com/atmos-cloud-sim-uj/PySDM/pull/575

Installation using the documented instructions misses out on installing pystrict, a required dependency (Issue/PR 495)

As elaborated on in the issue (https://github.com/atmos-cloud-sim-uj/PySDM/pull/495):

the single use of pystrict was removed;
in order to more clearly distinguish between run-time and test-time requirements (listed in setup.py and requirements.txt file, respectively), the requirements.txt file was renamed to test-time-requirements.txt;
package installation via pip on a fresh system was added to the CI workflow to detect such issues automatically. Thank you for pointing this out!

Documentation

The automated tests seem to work out of the box, but the smoke tests seem to take a very long time to run. Even one of the unit tests (namely attributes/chemistry/test_pH.py) took a disproportionate amount of time compared to the others. Please note that I was not able to run the GPU tests as I did not have immediate access to a GPU-powered machine.

The aqueous chemistry code has received a major refactor and cleanup as a part of developments leading to v1.4. The timing of test_pH.py has improved. Part of resource usage in test_pH.py is taken by chempy - an external package used from within the test to compare PySDM results with an independent code.

While there is extensive, excellent demonstration and example code available from the authors in related, clearly-linked repositories, the API documentation leaves much to be desired. There is a high degree of customizability and configuration exposed to the user, but very little in the way of curated documentation for the APIs and data structures in the software, or docstrings and annotations. As a motivating example, consider the spectra module; in this module, a nice base class for building probability distributions is exposed, but there are no docstrings describing the required and optional arguments for either the base class or any of the sub-classes which implement it. An effort to improve the documentation with basic docstrings for all the core methods and functionality would greatly improve the quality of the software and the user experience when adapting it for a specialized research task. Ideally, a simple Sphinx-based documentation for the key API and configurations exposed to users would follow very plainly from such an effort, greatly improving the ease of access of the software.

Besides following the suggestion of using a Sphinx-like tool (pdoc3 in this case) and setting up automatic deployment of up-to-date API docs on Github pages as pointed above, we have also reorganised the physics-related code (which is likely to be the first a user would intend to study and extend) and grouped it in the physics directory/subpackage with the following structure:

    PySDM.physics.aqueous_chemistry
    PySDM.physics.coalescence_kernels
    PySDM.physics.condensation_coordinate
    PySDM.physics.constants
    PySDM.physics.diffusion_kinetics
    PySDM.physics.diffusion_thermics
    PySDM.physics.dimensional_analysis
    PySDM.physics.drop_growth
    PySDM.physics.formulae
    PySDM.physics.hydrostatics
    PySDM.physics.hygroscopicity
    PySDM.physics.impl
    PySDM.physics.latent_heat
    PySDM.physics.particle_advection
    PySDM.physics.saturation_vapour_pressure
    PySDM.physics.spectra
    PySDM.physics.state_variable_triplet
    PySDM.physics.surface_tension
    PySDM.physics.terminal_velocity
    PySDM.physics.trivia
    PySDM.physics.ventilation

All of the above subpackages have at least top-level docstrings included.

Community / contribution guidelines are not provided with the repo; the JOSS reviewer guidelines suggest that such documentattion should clearly indicate how third-parties may contribute to the software, report issues, and seek support should they need to do so.

A "Contributing, reporting issues, seeking support" section has been added to the README file: https://github.com/atmos-cloud-sim-uj/PySDM/pull/579

Software Paper

The software paper does not include a section which explicitly explains a "Statement of Need." However, I do believe that the prose in the paper covers this topic with the necessary detail. I will defer to the editors whether a stand-alone "Statement of Need" section is required to meet JOSS guidelines.

While the "Statement of Need" section title is not used, the Introduction section was meant to cover it.

It's much appreciated that the authors include links to open source software which attempts to tackle subsets of the broad functionality that PySDM provides. I would strongly encourage the author to include a brief discussion of each package (particularly pyrcel and PyBox) and compare/contrast the unique or improved functionalities of PySDM relative to each. My take (as the author of one of those libraries, pyrcel!) is that PySDM offers a substantial improvement over each in terms of the breadth of calculations and science/research that can be performed with it as well as the cleanliness of its interface and design for future improvements and extensions. These are all very positive things for PySDM and I would strongly encourage the authors to lean into the fantastic work here to promote the capabilities and utility of their library relative to the competition!

While wholeheartedly agreeing that a comparison of features of different parcel models available in the Python ecosystem would be of great value for the community, we argue that it falls out of scope of the PySDM JOSS paper for three reasons:

none of the authors on the paper has enough experience with pyrcel or PyBox,
PySDM focus, as the name suggests, is on the Monte-Carlo representation of coalescence (condensation/evaporation are of course of equal importance for using it for modelling clouds, yet focusing on parcel frameworks/condensation only would not match project scope),
the paper already exceeds JOSS suggested length of 250-1000 words. We thus suggest to follow up together with the other package developers and carry out such comparison elsewhere.

Last but not least, let me note and ask for confirmation that we have added Oleksii Bulenok @abulenok to the paper author list. Oleksii has worked on the export mechanisms in PySDM and his VTK exporter PR has been merged before the v1.4 release offering the PySDM users to smoothly save and view multi-dimensional simulation state in such tools as Paraview (now mentioned in the text).

slayoo commented 3 years ago

For the record, PySDM v1.4 is now available on PyPI as well: https://pypi.org/project/PySDM/

dhhagan commented 3 years ago

👋 @andreas-h, @josephhardinee, @ashwinvis : are you available and interested in reviewing this paper for JOSS?

josephhardinee commented 3 years ago

I could probably help generically on the python and modeling side, but let me check if a colleague with more domain knowledge, especially around chemistry, would be interested in reviewing for JOSS first.

josephhardinee commented 3 years ago

@dhhagan One is overbooked right now and the other has a COI so I can act as a second reviewer for this.

dhhagan commented 3 years ago

@josephhardinee Thanks! I will edit the checklist above and invite you.

dhhagan commented 3 years ago

@whedon add @josephhardinee as reviewer

whedon commented 3 years ago

OK, @josephhardinee is now a reviewer

darothen commented 2 years ago

Hi @dhhagan, can you advise on next steps here? I want to keep this on my radar.

dhhagan commented 2 years ago

Hey @darothen thanks for checking in! As of now, we're just waiting on the review from @josephhardinee. I believe the authors made changes in response to your initial comments, so you can either review and update your checklist now or wait until the final revision comes in. Everything is a bit slow right now during the pandemic, but thanks for being on top of it!

darothen commented 2 years ago

Thanks @dhhagan, I'll wait until the final revision.

dhhagan commented 2 years ago

Hi @josephhardinee - just wanted to ping you one more time to see if you still have this on your radar before moving on. Please let me know if this review is not within your scope? Thanks!

josephhardinee commented 2 years ago

Sorry, I accepted this then changed jobs and this fell off radar. I will get this done this week.

dhhagan commented 2 years ago

No problem, @josephhardinee - thanks so much for the quick reply!

slayoo commented 2 years ago

@whedon generate pdf from branch JOSS

whedon commented 2 years ago

Attempting PDF compilation from custom branch JOSS. Reticulating splines etc...

slayoo commented 2 years ago

(API and affiliation updates)

whedon commented 2 years ago

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

slayoo commented 2 years ago

@whedon generate pdf from branch JOSS

whedon commented 2 years ago

Attempting PDF compilation from custom branch JOSS. Reticulating splines etc...

whedon commented 2 years ago

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

slayoo commented 2 years ago

(added mention of one additional example based on Lowe et al. 2019 and added Clare Singer, who contributed the example, to the author list)

slayoo commented 2 years ago

Hi @josephhardinee - let us ping one more time, please update us on the review, thank you for your help!

openjournals / joss-reviews

[REVIEW]: PySDM v1: particle-based cloud modelling package for warm-rain microphysics and aqueous chemistry #3219

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Reviewer instructions & questions

Review checklist for @josephhardinee

Conflict of interest

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Software paper

Review checklist for @darothen

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

Review - @darothen

General Checks

Functionality

Documentation

Software Paper