Observatory

class cabaret.Observatory(name: str = 'Observatory', camera: Camera | dict = Camera(name='gaia-camera-simulated', width=1024, height=1024, bin_x=1, bin_y=1, pitch=13.5, plate_scale=None, max_adu=65535, well_depth=65535, bias=300, gain=1.0, read_noise=6.2, dark_current=0.2, average_quantum_efficiency=0.8, rotation=0.0, pixel_defects={}), focuser: Focuser | dict = Focuser(position=10000, best_position=10000, scale=100, max_seeing_multiplier=5.0), telescope: Telescope | dict = Telescope(focal_length=8.0, diameter=1.0, collecting_area=0.7853981633974483), site: Site | dict = Site(sky_background=150, seeing=1.3, latitude=None, longitude=None, elevation=None, sun_altitude=None))

Observatory configuration.

Examples

>>> from datetime import datetime, UTC
>>> dateobs = datetime.now(UTC)
>>> from cabaret.observatory import Observatory
>>> observatory = Observatory()

Query Gaia for sources and generate an image:

>>> image = observatory.generate_image(
...     ra=12.3323, dec=30.4343, exp_time=10, dateobs=dateobs, seed=0
... )

Or using a set of predefined sources:

>>> from cabaret.sources import Sources
>>> sources = Sources.from_arrays(
...     ra=[10.64, 10.68], dec=[10.68, 41.22], fluxes=[169435.6, 52203.9]
... )
>>> img = observatory.generate_image(
...     ra=sources.ra.deg.mean(),
...     dec=sources.dec.deg.mean(),
...     exp_time=10,
...     seed=0,
...     sources=sources,
... )

If you have matplotlib installed, you can visualize the image using cabaret’s plot utility:

>>> import matplotlib.pyplot as plt
>>> from cabaret.plot import plot_image
>>> _ = plot_image(image, title="Simulated Image")
>>> plt.show()

Methods

__init__([name, camera, focuser, telescope, ...])
copy()	Create a deep copy of the Observatory instance.
from_dict(config)	Create an Observatory instance from a configuration dictionary.
generate_fits_image(ra, dec, exp_time, ...)	Generate a simulated FITS image of the sky.
generate_image(ra, dec, exp_time, dateobs, ...)	Generate a simulated image of the sky.
generate_image_stack(ra, dec, exp_time, ...)	Generate a stack of images from different stages in the image simulation pipeline.
load_from_yaml(file_path)	Load Observatory configuration from a YAML file.
save_to_yaml(file_path)	Save Observatory configuration to a YAML file.
to_dict()	Convert the Observatory configuration to a dictionary.

Attributes

name	Observatory name.
camera	Camera configuration.
focuser	Focuser configuration.
telescope	Telescope configuration.
site	Site configuration.