Skip to main content

No project description provided

Project description

cabaret

cabaret is a Python package to simulate astronomical images using the Gaia catalog of stars.

Documentation can be found at cabaret.readthedocs.io.

Installation

You can install cabaret in a Python (>=3.11) environment with

pip install cabaret

or from a local clone

git clone https://github.com/ppp-one/cabaret
pip install -e cabaret

You can test the package has been properly installed with

python -c "import cabaret"

Quick Start

Basic image

To generate an image from RA/DEC coordinates, run:

import cabaret

image = cabaret.Observatory().generate_image(
    ra=12.33230,  # right ascension in degrees
    dec=30.4343,  # declination in degrees
    exp_time=10,  # exposure time in seconds
)

To display the image:

from cabaret.plot import plot_image

plot_image(image, contrast=0.25)

Custom Observatory Configuration

Create a fully customized observatory by defining each component:

from datetime import UTC, datetime
import cabaret

# Define observatory components
site = cabaret.Site(
    sky_background=150,  # e-/m^2/arcsec^2/s
    seeing=1.5,  # arcseconds
    elevation=2500,  # meters
)

telescope = cabaret.Telescope(
    focal_length=8,  # meters
    diameter=1.0,  # meters
)

camera = cabaret.Camera(
    name="Example Camera",
    width=2048,  # pixels
    height=2048,  # pixels
    pitch=10,  # microns
    gain=1,  # electrons per ADU
    read_noise=6.2,  # electrons
)

# Create the observatory
observatory = cabaret.Observatory(
    name="My Observatory",
    site=site,
    telescope=telescope,
    camera=camera,
)

# Generate a FITS image with metadata
hdu = observatory.generate_fits_image(
    ra=323.362583,
    dec=-0.82325,
    exp_time=0.5,
    dateobs=datetime.now(UTC),
    filter_band=cabaret.Filters.G,
    seed=42,
)

# Save as FITS file
hdu.writeto("simulated_image.fits", overwrite=True)

Custom Source Lists

You can manipulate the source catalog before generating images:

from astropy.coordinates import SkyCoord
import numpy as np

# Query Gaia catalog
center = SkyCoord(ra=323.362583, dec=-0.82325, unit="deg")
table = cabaret.GaiaQuery.query(
    center=center,
    radius=camera.get_fov_radius() * 1.5,
    filter_band=cabaret.Filters.G,
)

# Filter out bright sources
fluxes = table[cabaret.Filters.G.value].value.data
mask = fluxes < 1e4
filtered_table = table[mask]

# Create custom source list
sources = cabaret.Sources.from_arrays(
    ra=filtered_table["ra"].value.data,
    dec=filtered_table["dec"].value.data,
    fluxes=filtered_table[cabaret.Filters.G.value].value.data,
)

# Generate image with custom sources
image = observatory.generate_image(
    ra=center.ra.deg,
    dec=center.dec.deg,
    exp_time=0.5,
    sources=sources,
)

Documentation

Explore the full documentation, API reference, and advanced usage examples at cabaret.readthedocs.io.

Project details


Download files

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

Source Distribution

cabaret-0.4.4.tar.gz (502.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cabaret-0.4.4-py3-none-any.whl (28.4 kB view details)

Uploaded Python 3

File details

Details for the file cabaret-0.4.4.tar.gz.

File metadata

  • Download URL: cabaret-0.4.4.tar.gz
  • Upload date:
  • Size: 502.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for cabaret-0.4.4.tar.gz
Algorithm Hash digest
SHA256 f6208631ff3454f62441714947c0ed3ffbefb59a79ea8d522f30ddacd507cc75
MD5 8af743de25b081c9b2955816b99ac546
BLAKE2b-256 3f9b7e87a4472203885261f823e7edb0c6a636dabf65613dd3dbca4bdd1730cc

See more details on using hashes here.

Provenance

The following attestation bundles were made for cabaret-0.4.4.tar.gz:

Publisher: publish.yml on ppp-one/cabaret

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file cabaret-0.4.4-py3-none-any.whl.

File metadata

  • Download URL: cabaret-0.4.4-py3-none-any.whl
  • Upload date:
  • Size: 28.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for cabaret-0.4.4-py3-none-any.whl
Algorithm Hash digest
SHA256 eb0c854f85ef30a7441a7f59e6a22ac900b81091448b1a1592ccee259ccefd6f
MD5 43ff113a979b789b92c1ee6398a6120b
BLAKE2b-256 28d652bc6220989a9f6dabd4df0f7d2d4134f9e3940b5641fbfb6ec57fcd9790

See more details on using hashes here.

Provenance

The following attestation bundles were made for cabaret-0.4.4-py3-none-any.whl:

Publisher: publish.yml on ppp-one/cabaret

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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