| Name | pyxmip JSON |
| Version |
1.0.3
JSON |
| download |
| home_page | None |
| Summary | Cross-matching and cross-identification toolkit for astronomical surveys. |
| upload_time | 2024-06-12 16:41:46 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | MIT License Copyright (c) 2024 Eliza Diggins Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
astronomy
cross-matching
cross-identification
survey
statistics
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
alabaster
blockdiag
docutils
ipykernel
ipython
ipython-genutils
ipywidgets
isort
jupyter
matplotlib
myst-parser
nbclient
nbconvert
nbformat
nbsphinx
notebook
numpy
pre-commit
pydata-sphinx-theme
Pygments
PyGObject
PyJWT
PyNaCl
pytest
ruamel.yaml
scipy
Sphinx
sphinx-copybutton
sphinx-hoverxref
sphinx_design
sphinxcontrib-applehelp
sphinxcontrib-blockdiag
sphinxcontrib-devhelp
sphinxcontrib-htmlhelp
sphinxcontrib-jquery
sphinxcontrib-jsmath
sphinxcontrib-mermaid
sphinxcontrib-qthelp
sphinxcontrib-serializinghtml
tqdm
virtualenv
pandas
SQLAlchemy
healpy
pydantic
astropy
astroquery
scikit-learn
typing-extensions
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
.. image:: docs/source/images/logos_icons/logo_main.png
:width: 400
|precom| |linting| |docs| |isort Status| |black| |astropy| |pydantic| |sklearn|
pyXMIP (the **p**\ ython **X**\ -**M**\ atching and **I**\ dentification **P**\ ackage) is an astronomical software package for cross referencing source catalogs
against known databases. The package provides a variety of statistical tools for quantifying the confidence of a given match and automates
queries against many of the most common astronomical databases.
Features
========
- Cross match catalogs of sources from survey missions against a wide array of known source databases.
- Use statistical methodologies to model the distribution of sources and produce match probabilities.
Documentation
=============
|docs|
The documentation for ``pyXMIP`` is hosted `here <https://eliza-diggins.github.io/pyXMIP>`_. It includes various example
notebooks, a complete API documentation and further information. It also includes guides on custom code implementations to
meet your science goals.
Installation
============
``pyXMIP`` may be installed from PyPI (stable versions) as follows:
.. code-block:: shell
>>> pip install pyxmip
To install ``pyXMIP`` from source, you need only clone the git repository
.. code-block:: shell
>>> git clone https://www.github.com/eliza-diggins/pyXMIP
and then install using
.. code-block:: shell
>>> cd pyXMIP
>>> pip install .
You can also achieve this in one line using
.. code-block:: shell
>>> pip install git+https://www.github.com/eliza-diggins/pyXMIP.git
.. |docs| image:: https://img.shields.io/badge/docs-latest-brightgreen.svg
:target: https://eliza-diggins.github.io/pyXMIP
.. |precom| image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit
:target: https://github.com/pre-commit/pre-commit
.. |linting| image:: https://img.shields.io/badge/linting-Flake8-brightgreen.svg?style=flat
.. |Github Page| image:: https://github.com/eliza-diggins/pyXMIP/actions/workflows/build_docs.yml/badge.svg
.. |isort Status| image:: https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336
:target: https://pycqa.github.io/isort/
:alt: isort Status
.. |black| image:: https://img.shields.io/badge/code%20style-black-000000.svg
:target: https://github.com/psf/black
.. |astropy| image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat
:target: https://www.astropy.org
.. |pydantic| image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/pydantic/pydantic/main/docs/badge/v2.json
:target: https://docs.pydantic.dev/latest/
.. |sklearn| image:: http://img.shields.io/badge/powered%20by-sklearn-cyan.svg?style=flat
:target: https://scikit-learn.org/stable/index.html
Raw data
{
"_id": null,
"home_page": null,
"name": "pyxmip",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": null,
"keywords": "astronomy, cross-matching, cross-identification, survey, statistics",
"author": null,
"author_email": "\"Eliza C. Diggins\" <eliza.diggins@utah.edu>",
"download_url": "https://files.pythonhosted.org/packages/5f/29/7cd7829726d17286d9bfc99960ef473108aaccc1683acb0114a8802cae6e/pyxmip-1.0.3.tar.gz",
"platform": null,
"description": ".. image:: docs/source/images/logos_icons/logo_main.png\n :width: 400\n\n|precom| |linting| |docs| |isort Status| |black| |astropy| |pydantic| |sklearn|\n\npyXMIP (the **p**\\ ython **X**\\ -**M**\\ atching and **I**\\ dentification **P**\\ ackage) is an astronomical software package for cross referencing source catalogs\nagainst known databases. The package provides a variety of statistical tools for quantifying the confidence of a given match and automates\nqueries against many of the most common astronomical databases.\n\n\nFeatures\n========\n\n- Cross match catalogs of sources from survey missions against a wide array of known source databases.\n- Use statistical methodologies to model the distribution of sources and produce match probabilities.\n\nDocumentation\n=============\n\n|docs|\n\nThe documentation for ``pyXMIP`` is hosted `here <https://eliza-diggins.github.io/pyXMIP>`_. It includes various example\nnotebooks, a complete API documentation and further information. It also includes guides on custom code implementations to\nmeet your science goals.\n\nInstallation\n============\n\n``pyXMIP`` may be installed from PyPI (stable versions) as follows:\n\n.. code-block:: shell\n\n >>> pip install pyxmip\n\nTo install ``pyXMIP`` from source, you need only clone the git repository\n\n.. code-block:: shell\n\n >>> git clone https://www.github.com/eliza-diggins/pyXMIP\n\nand then install using\n\n.. code-block:: shell\n\n >>> cd pyXMIP\n >>> pip install .\n\nYou can also achieve this in one line using\n\n.. code-block:: shell\n\n >>> pip install git+https://www.github.com/eliza-diggins/pyXMIP.git\n\n\n\n.. |docs| image:: https://img.shields.io/badge/docs-latest-brightgreen.svg\n :target: https://eliza-diggins.github.io/pyXMIP\n.. |precom| image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit\n :target: https://github.com/pre-commit/pre-commit\n.. |linting| image:: https://img.shields.io/badge/linting-Flake8-brightgreen.svg?style=flat\n.. |Github Page| image:: https://github.com/eliza-diggins/pyXMIP/actions/workflows/build_docs.yml/badge.svg\n.. |isort Status| image:: https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336\n :target: https://pycqa.github.io/isort/\n :alt: isort Status\n.. |black| image:: https://img.shields.io/badge/code%20style-black-000000.svg\n :target: https://github.com/psf/black\n.. |astropy| image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat\n :target: https://www.astropy.org\n.. |pydantic| image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/pydantic/pydantic/main/docs/badge/v2.json\n :target: https://docs.pydantic.dev/latest/\n.. |sklearn| image:: http://img.shields.io/badge/powered%20by-sklearn-cyan.svg?style=flat\n :target: https://scikit-learn.org/stable/index.html\n",
"bugtrack_url": null,
"license": "MIT License Copyright (c) 2024 Eliza Diggins Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ",
"summary": "Cross-matching and cross-identification toolkit for astronomical surveys.",
"version": "1.0.3",
"project_urls": {
"Homepage": "https://github.com/eliza-diggins/pyXMIP"
},
"split_keywords": [
"astronomy",
" cross-matching",
" cross-identification",
" survey",
" statistics"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "e9ec291eca9845d59b7ca6cde6709f54ad8516afbfef3b92c9f1de908e5d6569",
"md5": "3c3fc2092a33a3ea900881f5c81f73a9",
"sha256": "23092f1d4a5a98686ad520f12e8589617b2a0a0fa9241603b8179e3c0d969a09"
},
"downloads": -1,
"filename": "pyxmip-1.0.3-py3-none-any.whl",
"has_sig": false,
"md5_digest": "3c3fc2092a33a3ea900881f5c81f73a9",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9",
"size": 333412,
"upload_time": "2024-06-12T16:41:44",
"upload_time_iso_8601": "2024-06-12T16:41:44.986455Z",
"url": "https://files.pythonhosted.org/packages/e9/ec/291eca9845d59b7ca6cde6709f54ad8516afbfef3b92c9f1de908e5d6569/pyxmip-1.0.3-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "5f297cd7829726d17286d9bfc99960ef473108aaccc1683acb0114a8802cae6e",
"md5": "85cc24e0d84b0e08cdbfc36d01aaa660",
"sha256": "eda2fc459ba9530233e8b0d53df0c3534af8fdf47c73873ee8fbda221f39e064"
},
"downloads": -1,
"filename": "pyxmip-1.0.3.tar.gz",
"has_sig": false,
"md5_digest": "85cc24e0d84b0e08cdbfc36d01aaa660",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9",
"size": 2357451,
"upload_time": "2024-06-12T16:41:46",
"upload_time_iso_8601": "2024-06-12T16:41:46.750017Z",
"url": "https://files.pythonhosted.org/packages/5f/29/7cd7829726d17286d9bfc99960ef473108aaccc1683acb0114a8802cae6e/pyxmip-1.0.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-06-12 16:41:46",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "eliza-diggins",
"github_project": "pyXMIP",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "alabaster",
"specs": [
[
"==",
"0.7.13"
]
]
},
{
"name": "blockdiag",
"specs": [
[
"==",
"3.0.0"
]
]
},
{
"name": "docutils",
"specs": [
[
"==",
"0.20.1"
]
]
},
{
"name": "ipykernel",
"specs": [
[
"==",
"6.26.0"
]
]
},
{
"name": "ipython",
"specs": [
[
"==",
"8.16.1"
]
]
},
{
"name": "ipython-genutils",
"specs": [
[
"==",
"0.2.0"
]
]
},
{
"name": "ipywidgets",
"specs": [
[
"==",
"8.1.1"
]
]
},
{
"name": "isort",
"specs": [
[
"==",
"4.3.4"
]
]
},
{
"name": "jupyter",
"specs": [
[
"==",
"1.0.0"
]
]
},
{
"name": "matplotlib",
"specs": [
[
"==",
"3.8.0"
]
]
},
{
"name": "myst-parser",
"specs": [
[
"==",
"2.0.0"
]
]
},
{
"name": "nbclient",
"specs": [
[
"==",
"0.8.0"
]
]
},
{
"name": "nbconvert",
"specs": [
[
"==",
"7.9.2"
]
]
},
{
"name": "nbformat",
"specs": [
[
"==",
"5.9.2"
]
]
},
{
"name": "nbsphinx",
"specs": [
[
"==",
"0.9.3"
]
]
},
{
"name": "notebook",
"specs": [
[
"==",
"7.0.6"
]
]
},
{
"name": "numpy",
"specs": [
[
"==",
"1.26.1"
]
]
},
{
"name": "pre-commit",
"specs": [
[
"==",
"3.5.0"
]
]
},
{
"name": "pydata-sphinx-theme",
"specs": [
[
"==",
"0.14.2"
]
]
},
{
"name": "Pygments",
"specs": [
[
"==",
"2.16.1"
]
]
},
{
"name": "PyGObject",
"specs": [
[
"==",
"3.36.0"
]
]
},
{
"name": "PyJWT",
"specs": [
[
"==",
"1.7.1"
]
]
},
{
"name": "PyNaCl",
"specs": [
[
"==",
"1.3.0"
]
]
},
{
"name": "pytest",
"specs": [
[
"==",
"7.4.3"
]
]
},
{
"name": "ruamel.yaml",
"specs": [
[
"==",
"0.18.2"
]
]
},
{
"name": "scipy",
"specs": [
[
"==",
"1.11.3"
]
]
},
{
"name": "Sphinx",
"specs": [
[
"==",
"7.2.6"
]
]
},
{
"name": "sphinx-copybutton",
"specs": [
[
"==",
"0.5.2"
]
]
},
{
"name": "sphinx-hoverxref",
"specs": [
[
"==",
"1.3.0"
]
]
},
{
"name": "sphinx_design",
"specs": [
[
"==",
"0.5.0"
]
]
},
{
"name": "sphinxcontrib-applehelp",
"specs": [
[
"==",
"1.0.7"
]
]
},
{
"name": "sphinxcontrib-blockdiag",
"specs": [
[
"==",
"3.0.0"
]
]
},
{
"name": "sphinxcontrib-devhelp",
"specs": [
[
"==",
"1.0.5"
]
]
},
{
"name": "sphinxcontrib-htmlhelp",
"specs": [
[
"==",
"2.0.4"
]
]
},
{
"name": "sphinxcontrib-jquery",
"specs": [
[
"==",
"4.1"
]
]
},
{
"name": "sphinxcontrib-jsmath",
"specs": [
[
"==",
"1.0.1"
]
]
},
{
"name": "sphinxcontrib-mermaid",
"specs": [
[
"==",
"0.9.2"
]
]
},
{
"name": "sphinxcontrib-qthelp",
"specs": [
[
"==",
"1.0.6"
]
]
},
{
"name": "sphinxcontrib-serializinghtml",
"specs": [
[
"==",
"1.1.9"
]
]
},
{
"name": "tqdm",
"specs": [
[
"==",
"4.66.1"
]
]
},
{
"name": "virtualenv",
"specs": [
[
"==",
"20.24.6"
]
]
},
{
"name": "pandas",
"specs": []
},
{
"name": "SQLAlchemy",
"specs": []
},
{
"name": "healpy",
"specs": []
},
{
"name": "pydantic",
"specs": []
},
{
"name": "astropy",
"specs": []
},
{
"name": "astroquery",
"specs": []
},
{
"name": "scikit-learn",
"specs": []
},
{
"name": "typing-extensions",
"specs": []
}
],
"lcname": "pyxmip"
}
