MUSE Python Data Analysis Framework is a python framework in view of the analysis of MUSE data in the context of the GTO.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for bacon from gravatar.com bacon Avatar for laure.piqueras from gravatar.com laure.piqueras Avatar for saimon from gravatar.com saimon

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License (BSD)
  • Maintainer: Laure Piqueras
  • Tags astronomy, astrophysics, science, muse, vlt, cube, image, spectrum
  • Requires: Python >=3.9
  • Provides-Extra: all, docs
Classifiers

Project description

https://github.com/musevlt/mpdaf/workflows/Run%20unit%20tests/badge.svg https://codecov.io/gh/musevlt/mpdaf/branch/master/graph/badge.svg

MPDAF, the MUSE Python Data Analysis Framework, is an open-source (BSD licensed) Python package, developed and maintained by CRAL and partially funded by the ERC advanced grant 339659-MUSICOS (see Authors and Credits for more details). It has been developed and used in the MUSE Consortium for several years, and is available freely for the community.

It provides tools to work with MUSE-specific data (raw data, pixel tables, etc.), and with more general data like spectra, images and data cubes. Although its main use is to work with MUSE data, it is also possible to use it with other data, for example HST images.

MPDAF also provides MUSELET, a SExtractor-based tool to detect emission lines in a datacube, and a format to gather all the information on a source in one FITS file.

Bug reports, comments, and help with development are very welcome.

MPDAF 3.0 requires Python 3.5 or later. It is the first version that supports only Python 3. Older versions can be installed for users that still need Python 2.

Reporting Issues

If you have found a bug in MPDAF please create an issue on Github.

Citing

MPDAF can be cited with the ASCL reference (ADS, BibTeX), and was also presented at ADASS XXVI, for which the proceedings is on the arXiv (ADS, BibTeX).

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for bacon from gravatar.com bacon Avatar for laure.piqueras from gravatar.com laure.piqueras Avatar for saimon from gravatar.com saimon

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License (BSD)
  • Maintainer: Laure Piqueras
  • Tags astronomy, astrophysics, science, muse, vlt, cube, image, spectrum
  • Requires: Python >=3.9
  • Provides-Extra: all, docs
Classifiers

Release history Release notifications | RSS feed

This version

3.6

3.5

3.4

3.2

3.1

3.0

2.5.1

2.5

2.4

2.3

2.2

2.1

2.0

2.0rc1 pre-release

Download files

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

Source Distribution

mpdaf-3.6.tar.gz (61.0 MB view details)

Uploaded Source

Built Distributions

mpdaf-3.6-cp312-cp312-musllinux_1_2_x86_64.whl (59.9 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.2+ x86-64

mpdaf-3.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (59.8 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

mpdaf-3.6-cp312-cp312-macosx_10_9_x86_64.whl (58.9 MB view details)

Uploaded CPython 3.12 macOS 10.9+ x86-64

mpdaf-3.6-cp311-cp311-musllinux_1_2_x86_64.whl (59.9 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.2+ x86-64

mpdaf-3.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (59.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

mpdaf-3.6-cp311-cp311-macosx_10_9_x86_64.whl (58.9 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

mpdaf-3.6-cp310-cp310-musllinux_1_2_x86_64.whl (59.8 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.2+ x86-64

mpdaf-3.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (59.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

mpdaf-3.6-cp310-cp310-macosx_10_9_x86_64.whl (58.9 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

mpdaf-3.6-cp39-cp39-musllinux_1_2_x86_64.whl (59.8 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ x86-64

mpdaf-3.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (59.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

mpdaf-3.6-cp39-cp39-macosx_10_9_x86_64.whl (58.9 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

File details

Details for the file mpdaf-3.6.tar.gz.

File metadata

  • Download URL: mpdaf-3.6.tar.gz
  • Upload date:
  • Size: 61.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.2

File hashes

Hashes for mpdaf-3.6.tar.gz
Algorithm Hash digest
SHA256 836cd0b3b2941900f1257c640449cca931d33dcf914419ceeb661a7607557208
MD5 c8c25067549ffca1f558684aa47ae12e
BLAKE2b-256 4f5cc1a7c67d9b8246da2b754da8655510dd053d377f30ffce13b23385efc003

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 5b5784adf32ee89a0f06d6404705ca0b5c24bcb8475518f8048ce4aedb7fa2df
MD5 d4da2b4915974dc37f99fd5ad196304e
BLAKE2b-256 492f4d8e9f1e3b04d856808c8c5d17dc41d23223f29825a003973299f9dbbd7a

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 aab07f57e856abbb04697c1d44732f1434f3c3150ac29ddbca1775b51fcab1f4
MD5 afacf296efbc9bf38293f635d6cf2517
BLAKE2b-256 3aab7963672c13c4cfeedc2a2b11514c953ee84d41b1ba084f4b657d8d463408

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cfbcefe299b36913cff1891989f24134d707f86bb1bc69505072ccb0e8218bf3
MD5 1bad86052b1b1d8909b701fe3df392c9
BLAKE2b-256 4d2ee80de572bf2eb3f8cdf5ffb7305daf419d3b7797b558d66e65d458a7c3e7

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 88f53c2c17282ef2cfcbc46f4a03434e1d7883614cae992470774899b2363f47
MD5 9250065bcc3688f5a38b290d3d7be295
BLAKE2b-256 75d24587f810b63c49ad8b69fab567001bccb918576746d4bc474ddec864ee73

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c76e20ae254012669ed966c35f2acd31ced81acc31946d9a04587cce3578ee17
MD5 7437266a31d9c8f919bd8b6535d4bd67
BLAKE2b-256 98d82d2d0bbc4718fc296144b0799795dfb2d40db76219b6ac3c66e602133898

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4a10690c8f9326276004c45f34b400b0ba32bc489d15ca34e9922c7e54ae4a65
MD5 043d65f5810cd36e49d3ad9ed57b4c4b
BLAKE2b-256 46a53f296fc9d7b32549b653c16e0b1e265b9cde063dd9b68bd74a24131ae0e9

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 9e0504c37e070cd7aeadca13101c916e1feecd11d006565f7bcf1e847ac25bb2
MD5 b8ba51cf2788386c13572df676cfdaac
BLAKE2b-256 c72d834bd96196db4256f7f8a6bdf946c366632655b3a4ca9e41d34842fb19fb

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1d930446dd8eba37f506d5a7b413916bc561742ca5c9e6e52e16c6839fa71c57
MD5 c98c7b7a3692dc3ebc0e0740b097b2b1
BLAKE2b-256 701001acb201c54eaa591e49660755bdb8c92dc5bbfa94c2d817123a0ebf3637

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 7b0216184e98c23b9be50d33d0dc7879b93585cebd7064d24f0bef822a885c2d
MD5 8141d33469ab03928f79d0c7ce91804a
BLAKE2b-256 d6eeb007cd8e66291f3d69b52666ea0f765726cff2b8fe2f66f975995ca42632

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 18bff07734d35b78da548da8d04c4c1a129b20c18674a00a93d5e016562a22c6
MD5 7dac1b3d41a0b991f621cf834eff8055
BLAKE2b-256 8c2e8794cb4ed84f1ee2ec75d4663a20fa304678027251cd1846e4436daf410e

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6d9ad6ed19612cebb6842f5d6364cbfc09dcdda9c9425674f4bdf70acd1cf872
MD5 ffa92b7240d26c528a11707c252fb464
BLAKE2b-256 fc989be82c85c8c6e32c3119d3a57c05d90a39df15763c0758923e7707d687f2

See more details on using hashes here.

Provenance

File details

Details for the file mpdaf-3.6-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for mpdaf-3.6-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ed6dd2b68196d961d9aca43a328f9de1f356c01abaff7398102ab372c72b2815
MD5 408ba18bd74b2331381bc205adc59528
BLAKE2b-256 8d0db78181ce2183071fe553fa5d3034a80a4345ac3097d43db1befd00c2b5f6

See more details on using hashes here.

Provenance

Supported by

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