SQLAlchemy extension for indexed cone searches in astronomical catalogs
Project description
Cone Search Alchemy
The conesearch_alchemy
Python package enhances SQLAlchemy to provide fast,
indexed cone searches on astronomical catalogs using a PostgreSQL database. It
does not rely on any database extensions.
Installation
You can install conesearch_alchemy
the Python Package Index:
$ pip install conesearch-alchemy
Usage
from conesearch_alchemy.point import Point
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
# Create two tables Catalog1 and Catalog2 that both have spherical coordinates.
class Catalog1(Point, Base):
__tablename__ = 'catalog1'
id = Column(Integer, primary_key=True)
class Catalog2(Point, Base):
__tablename__ = 'catalog2'
id = Column(Integer, primary_key=True)
...
# Populate Catalog1 and Catalog2 tables with some sample data...
session.add(Catalog1(id=0, ra=320.5, dec=-23.5))
...
session.add(Catalog2(id=0, ra=18.1, dec=18.3))
...
session.commit()
# Cross-match the two tables.
separation = 1 # separation in degrees
query = session.query(
Catalog1.id, Catalog2.id
).join(
Catalog2,
Catalog1.within(point, separation)
).order_by(
Catalog1.id, Catalog2.id
)
for row in query:
... # do something with the query results
# Do a cone search around literal ra, dec values.
separation = 1 # separation in degrees
point = Point(ra=212.5, dec=-33.2)
query = session.query(
Catalog1.id
).filter(
Catalog1.within(point, separation)
).order_by(
Catalog1.id
)
for row in query:
... # do something with the query results
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