cabaret 0.5.4

No project description provided

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_bands=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,
)

Offline SQLite Catalogs

You can query a local SQLite catalog instead of a remote TAP endpoint.

The local table is expected to contain at least ra and dec, and optionally pmra, pmdec, plus Gaia/2MASS magnitude columns like phot_g_mean_mag, phot_bp_mean_mag, phot_rp_mean_mag, j_m, h_m, ks_m.

import cabaret
from astropy.coordinates import SkyCoord

sqlite_source = cabaret.GaiaSQLiteSource(
    database="/data/catalogs/gaia_subset.sqlite",
)

table = cabaret.GaiaQuery.query(
    center=SkyCoord(ra=323.362583, dec=-0.82325, unit="deg"),
    radius=0.1,
    filter_bands=[cabaret.Filters.G],
    tap_source=sqlite_source,
    limit=5000,
)

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