cabaret 0.2.0

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cabaret

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

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"

Example

Basic image

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

import cabaret

image = cabaret.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 (matplotlib required here):

import matplotlib.pyplot as plt
import numpy as np

med = np.median(science)
std = np.std(science)

fig, ax = plt.subplots()
img = ax.imshow(science, cmap="gray", vmin=med - 1 * std, vmax=med + 1 * std)
cbar = plt.colorbar(img, ax=ax)
colorbar.set_label("Intensity (ADU)")
plt.show()

Configuring an Observatory

You can customize the physical characteristics of the observatory by defining and passing Camera, Telescope, and Site objects.

import datetime
import cabaret

# Define the observatory with specific characteristics
observatory = cabaret.Observatory(
    name="MyObservatory",
    camera=cabaret.Camera(
        name="MyCamera",
        height=1024,  # Height of the camera in pixels
        width=1024,  # Width of the camera in pixels
        read_noise=10,  # Read noise in electrons
        gain=1,  # Gain in e-/ADU
        pixel_defects=dict(
            cold_pixels=dict(rate=0.005, value=300, seed=42)  # defaults to ConstantPixelDefect
        ),
    ),
    site=cabaret.Site(sky_background=21.0, seeing=1.5),
    telescope=cabaret.Telescope(diameter=1.0, focal_length=8.0),
)

# Generate an image with the configured observatory
image = observatory.generate_image(
    ra=12.33230,  # right ascension in degrees
    dec=30.4343,  # declination in degrees
    exp_time=10,  # exposure time in seconds
    dateobs=datetime.datetime.now(datetime.UTC),  # time of observation
)

You can easily save your observatory configuration to a YAML file:

observatory.save_to_yaml("path/to/config_file.yaml")

To load a previously saved configuration, you can use:

observatory.load_from_yaml("path/to/config_file.yaml")