avocado.AstronomicalObject¶
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class
avocado.
AstronomicalObject
(metadata, observations)¶ An astronomical object, with metadata and a lightcurve.
An astronomical object has both metadata describing its global properties, and observations of its light curve.
Parameters: - metadata (dict-like) –
Metadata for this object. This is represented using a dict internally, and must be able to be cast to a dict. Any keys and information are allowed. Various functions assume that the following keys exist in the metadata:
- object_id: A unique ID for the object. This will be stored as a string internally.
- galactic: Whether or not the object is in the Milky Way galaxy or not.
- host_photoz: The photometric redshift of the object’s host galaxy.
- host_photoz_error: The error on the photometric redshift of the object’s host galaxy.
- host_specz: The spectroscopic redshift of the object’s host galaxy.
For training data objects, the following keys are assumed to exist in the metadata: - redshift: The true redshift of the object. - class: The true class label of the object.
- observations (pandas.DataFrame) –
Observations of the object’s light curve. This should be a pandas DataFrame with at least the following columns:
- time: The time of each observation.
- band: The band used for the observation.
- flux: The measured flux value of the observation.
- flux_error: The flux measurement uncertainty of the observation.
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__init__
(metadata, observations)¶ Create a new AstronomicalObject
Methods
__init__
(metadata, observations)Create a new AstronomicalObject fit_gaussian_process
([fix_scale, verbose, …])Fit a Gaussian Process model to the light curve. get_default_gaussian_process
()Get the default Gaussian Process. plot_light_curve
([show_gp, verbose, axis])Plot the object’s light curve predict_gaussian_process
(bands, times[, …])Predict the Gaussian process in a given set of bands and at a given set of times. preprocess_observations
([subtract_background])Apply preprocessing to the observations. print_metadata
()Print out the object’s metadata in a nice format. subtract_background
()Subtract the background levels from each band. Attributes
bands
Return a list of bands that this object has observations in - metadata (dict-like) –