The Multi-Mission Maximum Likelihood framework

These details have been verified by PyPI

Maintainers

giacomov grburgess ndilalla omodei

These details have not been verified by PyPI

Project links

Development Status
- 5 - Production/Stable
Environment
- Console
Intended Audience
- Science/Research
Operating System
- POSIX
Programming Language
- Python :: 2.7
- Python :: 3.7
Topic
- Scientific/Engineering :: Astronomy

Project description

GitHub pull requests GitHub issues

PyPi

PyPI - Downloads PyPI - Python Version

Conda

Conda Conda

The Multi-Mission Maximum Likelihood framework (3ML)

A framework for multi-wavelength/multi-messenger analysis for astronomy/astrophysics.

Installation

Please refer to the Installation instructions.

Citing

If you find this package useful in you analysis, or the code in your own custom data tools, please cite:

Vianello et al. (2015)

Acknowledgements

3ML makes use of the Spanish Virtual Observatory's Filter Profile servce (http://svo2.cab.inta-csic.es/svo/theory/fps3/index.php?mode=browse&gname=NIRT).

If you use these profiles in your research, please consider citing them by using the following suggested sentence in your paper:

"This research has made use of the SVO Filter Profile Service (http://svo2.cab.inta-csic.es/theory/fps/) supported from the Spanish MINECO through grant AyA2014-55216"

and citing the following publications:

The SVO Filter Profile Service. Rodrigo, C., Solano, E., Bayo, A. http://ivoa.net/documents/Notes/SVOFPS/index.html The Filter Profile Service Access Protocol. Rodrigo, C., Solano, E. http://ivoa.net/documents/Notes/SVOFPSDAL/index.html

Project details

These details have been verified by PyPI

Maintainers

giacomov grburgess ndilalla omodei

These details have not been verified by PyPI

Project links

Development Status
- 5 - Production/Stable
Environment
- Console
Intended Audience
- Science/Research
Operating System
- POSIX
Programming Language
- Python :: 2.7
- Python :: 3.7
Topic
- Scientific/Engineering :: Astronomy

Release history Release notifications | RSS feed

2.4.3.dev1 pre-release

Sep 12, 2024

2.4.2

May 31, 2024

2.4.2.dev2 pre-release

May 17, 2024

2.4.2.dev1 pre-release

Feb 8, 2024

2.4.1

Nov 6, 2023

2.4.1.dev2 pre-release

Nov 4, 2023

2.4.1.dev1 pre-release

Oct 6, 2022

2.4.0

Sep 29, 2022

2.4.0.dev1 pre-release

Sep 20, 2022

2.3.2

Jul 28, 2022

2.3.1

Jul 12, 2022

2.3.0

May 25, 2022

2.3.0.dev2 pre-release

Feb 3, 2022

2.2.4

Aug 30, 2021

2.2.3

Aug 20, 2021

2.2.2

May 19, 2021

2.2.1

Apr 7, 2021

2.2.0

Apr 6, 2021

2.1.3

Jan 24, 2021

2.1.2

Jan 24, 2021

2.1.1

Dec 17, 2020

2.1.0

Dec 16, 2020

This version

2.0.3

Dec 8, 2020

2.0.2

Nov 3, 2020

2.0.1

Oct 30, 2020

2.0.0

Oct 22, 2020

1.2.0

Sep 12, 2020

1.1.1

May 11, 2020

1.1.0

Apr 30, 2020

1.0.9

Apr 28, 2020

1.0.8

Apr 25, 2020

1.0.7

Apr 22, 2020

1.0.6

Apr 17, 2020

1.0.5

Apr 17, 2020

1.0.4

Apr 15, 2020

1.0.3

Apr 15, 2020

1.0.2

Apr 11, 2020

1.0.1

Apr 10, 2020

0.3.2

Jul 18, 2016

0.3.1

Jun 26, 2016

0.3.0

Jun 26, 2016

0.1.3

Apr 21, 2016

0.1.2

Apr 21, 2016

0.1.1

Apr 21, 2016

0.1.0

Apr 21, 2016

v0.0.5

Feb 6, 2015

Download files

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

Source Distribution

threeML-2.0.3.tar.gz (37.3 MB view details)

Uploaded Dec 8, 2020 Source

File details

Details for the file threeML-2.0.3.tar.gz.

File metadata

Download URL: threeML-2.0.3.tar.gz
Upload date: Dec 8, 2020
Size: 37.3 MB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/51.0.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.8.5

File hashes

Hashes for threeML-2.0.3.tar.gz
Algorithm	Hash digest
SHA256	`968e7a13f629d8d23cc8b51b205d39d9fe57ffd5be3624bc9b201424bf769974`
MD5	`fb9fcc9735ae09d1a582dac2e8476c81`
BLAKE2b-256	`a274d94dd38363065887c79cde17e4eaf1acea17b02183100cb7c5174f11b13f`