معرفی شرکت ها

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

Tools to organize and query astronomical catalogs

ویژگی	مقدار
سیستم عامل	-
نام فایل	extcats-2.4.3
نام	extcats
نسخه کتابخانه	2.4.3
نگهدارنده	['Jakob van Santen']
ایمیل نگهدارنده	['jakob.van.santen@desy.de']
نویسنده	Matteo Giomi
ایمیل نویسنده	matteo.giomi@desy.de
آدرس صفحه اصلی	https://github.com/AmpelProject/extcats
آدرس اینترنتی	https://pypi.org/project/extcats/
مجوز	MIT

******* extcats ******* .. image:: https://coveralls.io/repos/github/AmpelProject/extcats/badge.svg?branch=master :target: https://coveralls.io/github/AmpelProject/extcats?branch=master tools to organize and query astronomical catalogs ################################################# This modules provides classes to import astronomical catalogs into a **mongodb** database, and to efficiently query this database for positional matches. Description: ############ The two main classes of this module are: - **CatalogPusher**: will process the raw files with the catalog sources and creates a database. See *insert_example* notebook for more details and usage instruction. - **CatalogQuery**: will perform queries on the catalogs. See *query_example* for examples and benchmarking. Supported queries includes: - all the sources with a certain distance. - closest source at a given position. - binary search: return yes/no if anything is around the positon. - user defined queries. The first item on the above list (cone search around target) provides the basic block for the other two types of positional-based queries. The code supports tree types of basic cone-search queries, depending on the indexing strategy of the database. - using **HEALPix**: if the catalog sources have been assigned an HEALPix index (using `healpy <https://healpy.readthedocs.io/en/latest/#>`_). - using **GeoJSON** (or 'legacy coordinates'): if the catalog documents have the position arranged in one of these two formats (`example <https://docs.mongodb.com/manual/geospatial-queries/>`_), the query is based on the ``$geoWithin`` and ``$centerSphere`` mongo operators. - **raw**: this method uses the ``$where`` keyword to evaluate on each document a ``javascript`` function computing the angular distance between each source and the target. This method does not require any additional field to be added to the catalog but has, in general, poorer performances with respect to the methods above. All the core functions are defined in the ``catquery_utils`` module. In all cases the results of the queries will be return an ``astropy.table.Table`` objects. Notes on indexing and query performances: ----------------------------------------- The recommended method to index and query catalogs is based on the GeoJSON coorinate type. See the *example_insert* notebook for how this can be implemented. Performant queries requires the database indexes to reside in the RAM. The indexes are efficiently compressed by mongodb default engine (WiredTiger), however there is little redundant (and hence compressible) information in accurately measured coordinate pairs. As a consequence, GeoJSON type indexes tends to require fair amount of free memory (of the order 40 MB for 2M entries). For large catalogs (and / or small RAM) indexing on coordinates might not be feasible. In this case, the HEALPix based indexing should be used. As (possibly) many sources shares the same HEALPix index, compression is more efficient into moderating RAM usage. Installation: ^^^^^^^^^^^^^ The easiest way to install the Python library is with pip: :: pip install extcats If you want do modify `extcats` itself, you'll need an editable installation. After cloning this Git repository: :: poetry install Usefull links: -------------- - `mongodb installation <https://docs.mongodb.com/manual/administration/install-community/>`_ - `healpy <https://healpy.readthedocs.io/en/latest/#>`_ - `astropy <http://www.astropy.org/>`_

نیازمندی

مقدار	نام
>=3.7,<5.0	pymongo
>=1.14.0,<2.0.0	healpy
>=4.2,<6	astropy
>=1.2,<2.0)	pandas
>=4.58.0,<5.0.0)	tqdm

زبان مورد نیاز

مقدار	نام
>=3.8,<4.0	Python

نحوه نصب

نصب پکیج whl extcats-2.4.3:

pip install extcats-2.4.3.whl

نصب پکیج tar.gz extcats-2.4.3:

pip install extcats-2.4.3.tar.gz