Skip to main content

Multi-Mission Multi-Messenger Observation Planning Toolkit

Project description

Multi-Mission Multi-Messenger Observation Planning Toolkit

Python Package Index status Powered by Astropy Badge Code coverage status Documentation Status Visualization of an example observing plan for UVEX generated M4OPT

M4OPT is an open-source toolkit for multi-facility scheduling of astrophysics observing campaigns. It focuses on extremely rapid follow-up of gravitational wave (GW) and neutrino events with heterogeneous networks of space and ground-based observatories.

M4OPT uses the versatile mathematical framework of mixed integer programming to model and solve complex observation scheduling problems. Although M4OPT is open source, for the largest problems it can leverage two industrial-strength commercial MIP solvers: CPLEX or Gurobi. Both solvers are available for free for academic users.

M4OPT is designed from the Astropy affiliated package template, and is meant to follow those standards, including interoperability with the Astropy ecosystem. It also complies with NASA Procedural Requirements (NPR) 7150 for Class C software and is suitable for non-safety-critical ground software applications for Class D NASA payloads.

Features

  • Global: jointly and globally solves the problems of tiling (the set of telescope boresight orientations and roll angles) and the scheduling (which tile is observed at what time), rather than solving each sub-problem one at a time

  • Optimal: generally solves all the way to optimality, rather than finding merely a “good enough” solution

  • Fast: solve an entire orbit in about 5 minutes

  • General: does not depend on heuristics of any kind

  • Flexible: problem is formulated in the versatile framework of mixed integer programming

License

This project is Copyright (c) M4OPT Developers and licensed under the terms of the BSD 3-Clause license. This package is based upon the Astropy package template which is licensed under the BSD 3-clause license. See the licenses folder for more information.

How to Cite

If you use M4OPT in your research, then please cite the following paper:

Singer, L. P., Criswell, A. W., Leggio, S. C., et al. (2025). Optimal Follow-Up of Gravitational-Wave Events with the UltraViolet EXplorer (UVEX) (Version 1). https://doi.org/10.48550/ARXIV.2502.17560

Contributing

We love contributions! m4opt is open source, built on open source, and we’d love to have you hang out in our community.

Imposter syndrome disclaimer: We want your help. No, really.

There may be a little voice inside your head that is telling you that you’re not ready to be an open source contributor; that your skills aren’t nearly good enough to contribute. What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong. If you can write code at all, you can contribute code to open source. Contributing to open source projects is a fantastic way to advance one’s coding skills. Writing perfect code isn’t the measure of a good developer (that would disqualify all of us!); it’s trying to create something, making mistakes, and learning from those mistakes. That’s how we all improve, and we are happy to help others learn.

Being an open source contributor doesn’t just mean writing code, either. You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process). Some of these contributions may be the most valuable to the project as a whole, because you’re coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.

Note: This disclaimer was originally written by Adrienne Lowe for a PyCon talk, and was adapted by m4opt based on its use in the README file for the MetPy project.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

m4opt-2.3.1.tar.gz (1.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

m4opt-2.3.1-py3-none-any.whl (1.3 MB view details)

Uploaded Python 3

File details

Details for the file m4opt-2.3.1.tar.gz.

File metadata

  • Download URL: m4opt-2.3.1.tar.gz
  • Upload date:
  • Size: 1.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for m4opt-2.3.1.tar.gz
Algorithm Hash digest
SHA256 93fcfc00e32fef53827506d5c98377abb3514d062e38c82c03af24b90b3f6d7b
MD5 722771d3b14cc758ae368163cab4ddd9
BLAKE2b-256 1341d4a11b6380e5a3368c9250ed3b447bd4f2568d9c8b13aeb079a5c6d4ec3a

See more details on using hashes here.

File details

Details for the file m4opt-2.3.1-py3-none-any.whl.

File metadata

  • Download URL: m4opt-2.3.1-py3-none-any.whl
  • Upload date:
  • Size: 1.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for m4opt-2.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9a3d715099dab1ead894a562360ba8cc87f6a7f68ac175f6cbf3a3b09c5ac49a
MD5 aadff95adc3ad3ebd7d09a0db8e08a1b
BLAKE2b-256 eb96970b00225abfadca3247cab26e25e85a6726d0b8bddedac22d5e50f2ab05

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page