Core Python package for astronomy: coordinate transforms, units/quantities, FITS I/O, WCS, cosmology, precise time handling, and table operations. USE WHEN a research task involves astronomical data, celestial coordinates, FITS files, unit conversions, or cosmological calculations.
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Core Python package for astronomy: coordinate transforms, units/quantities, FITS I/O, WCS, cosmology, precise time handling, and table operations. USE WHEN a research task involves astronomical data, celestial coordinates, FITS files, unit conversions, or cosmological calculations.
cluster
research-knowledge
version
1.0.0
origin
antigravity-awesome-skills (MIT)
license
BSD-3-Clause license
metadata
{"skill-author":"K-Dense Inc."}
risk
unknown
source
https://github.com/astropy/astropy
Astropy
Overview
Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis. Use astropy for coordinate transformations, unit and quantity calculations, FITS file operations, cosmological calculations, precise time handling, tabular data manipulation, and astronomical image processing.
When to Use This Skill
Use astropy when tasks involve:
Converting between celestial coordinate systems (ICRS, Galactic, FK5, AltAz, etc.)
Working with physical units and quantities (converting Jy to mJy, parsecs to km, etc.)
Reading, writing, or manipulating FITS files (images or tables)
Cosmological calculations (luminosity distance, lookback time, Hubble parameter)
Precise time handling with different time scales (UTC, TAI, TT, TDB) and formats (JD, MJD, ISO)
See:references/wcs_and_other_modules.md for WCS operations and transformations.
Additional Capabilities
The references/wcs_and_other_modules.md file also covers:
NDData and CCDData
Containers for n-dimensional datasets with metadata, uncertainty, masking, and WCS information.
Modeling
Framework for creating and fitting mathematical models to astronomical data.
Visualization
Tools for astronomical image display with appropriate stretching and scaling.
Constants
Physical and astronomical constants with proper units (speed of light, solar mass, Planck constant, etc.).
Convolution
Image processing kernels for smoothing and filtering.
Statistics
Robust statistical functions including sigma clipping and outlier rejection.
Installation
# Install astropy
uv pip install astropy
# With optional dependencies for full functionality
uv pip install astropy[all]
Common Workflows
Converting Coordinates Between Systems
from astropy.coordinates import SkyCoord
import astropy.units as u
# Create coordinate
c = SkyCoord(ra='05h23m34.5s', dec='-69d45m22s', frame='icrs')
# Transform to galactic
c_gal = c.galactic
print(f"l={c_gal.l.deg}, b={c_gal.b.deg}")
# Transform to alt-az (requires time and location)from astropy.time import Time
from astropy.coordinates import EarthLocation, AltAz
observing_time = Time('2023-06-15 23:00:00')
observing_location = EarthLocation(lat=40*u.deg, lon=-120*u.deg)
aa_frame = AltAz(obstime=observing_time, location=observing_location)
c_altaz = c.transform_to(aa_frame)
print(f"Alt={c_altaz.alt.deg}, Az={c_altaz.az.deg}")
Reading and Analyzing FITS Files
from astropy.io import fits
import numpy as np
# Open FITS filewith fits.open('observation.fits') as hdul:
# Display structure
hdul.info()
# Get image data and header
data = hdul[1].data
header = hdul[1].header
# Access header values
exptime = header['EXPTIME']
filter_name = header['FILTER']
# Analyze data
mean = np.mean(data)
median = np.median(data)
print(f"Mean: {mean}, Median: {median}")
Cosmological Distance Calculations
from astropy.cosmology import Planck18
import astropy.units as u
import numpy as np
# Calculate distances at z=1.5
z = 1.5
d_L = Planck18.luminosity_distance(z)
d_A = Planck18.angular_diameter_distance(z)
print(f"Luminosity distance: {d_L}")
print(f"Angular diameter distance: {d_A}")
# Age of universe at that redshift
age = Planck18.age(z)
print(f"Age at z={z}: {age.to(u.Gyr)}")
# Lookback time
t_lookback = Planck18.lookback_time(z)
print(f"Lookback time: {t_lookback.to(u.Gyr)}")
