MILESpy

[isaac-aa]

Submitting Author: Isaac Alonso Asensio (@isaac-aa)
Package Name: MILESpy
One-Line Description of Package: Python wrapper for the MILES stellar library and Single Stellar Population models
Repository Link (if existing): https://github.com/miles-iac/milespy
EiC: @coatless

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Code of Conduct & Commitment to Maintain Package

• I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
• I have read and will commit to package maintenance after the review as per the pyOpenSci Policies Guidelines.

Description

• Include a brief paragraph describing what your package does:

MILESpy aims to provide users an easy interface to generate single stellar population (SSP) models, navigate the stellar library or generate a spectra given an input star formation history (SFH), among other things. We try to make this package compatible with previously existing tools, namely astropy and specutils. In addition, we provide analysis tools for the output spectra to compute basic derived quantities (e.g., magnitudes, line strength indices)

Community Partnerships

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• Astropy: My package adheres to Astropy community standards
• Pangeo: My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook

Scope

• Please indicate which category or categories this package falls under:

  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

Domain Specific

• Geospatial
• Education

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• Explain how and why the package falls under these categories (briefly, 1-2 sentences). For community partnerships, check also their specific guidelines as documented in the links above. Please note any areas you are unsure of:

The package downloads the needed repository files that contain the MILES spectra and SSP models, thus entering the "Data Retrieval" category. It then uses this downloaded data to generate spectra based, possibly modifying, interpolating,etc,... the data already present in the repository. Thus, it fits into the "Data processing/munging" category.

• Who is the target audience and what are the scientific applications of this package?

The users of this package are astrophysicists in a wide rage of fields. The generated spectra can be used to study single stars, whole stellar populations in galaxies, or to model spectra from realistic cosmological simulations. We also expect this tool to be used by other third-party packages to be included in spectral fitting routines.

• Are there other Python packages that accomplish similar things? If so, how does yours differ?

To the best of our knowledge, there is only a single python package that does something similar to ours: https://github.com/paranoya/population-synthesis-toolkit
In contrast with their package, we focused heavily on a successful and tight integration in the astropy ecosystem. This means that our output spectra are suited to be used easily on already working packages. We focused on the easy acquisition of the required dataset automatically, without manual downloads. Finally, they only provide an interface to the SSP models, not to the stellar library.

• Any other questions or issues we should be aware of:

None

P.S. Have feedback/comments about our review process? Leave a comment here

[lwasser]

hey there @isaac-aa just a quick note that I am going to share this presubmission with our astropy editors and we will get back to you!!

[lwasser]

Hi again, @isaac-aa. We'd like to invite you to submit a full package. We can evaluate astropy scope more formally at that time.

✅ Before you submit, please double-check that your package meets our core package requirements.
✅ Also please be sure to reference this issue in the new submission issue.

I am going to close this as completed. We look forward to your full submission!