ramjet.photometric_database.light_curve_collection¶

Classes¶

exception LightCurveCollectionMethodNotImplementedError[source]¶

Bases: RuntimeError

An error to raise if a collection method that is not implemented is attempted to be used. Note, the standard NotImplementedError is not supposed to be used for cases when non-implemented functions are meant to be allowed, which is why a custom class is needed.

class LightCurveCollection[source]¶

A class representing a collection of light curves. Used to define how to find, load, and label a set of light curves.

Variables:	label – The default label to be used if the load_label_from_path method is not overridden. paths – The default list of paths to be used if the get_paths method is not overridden.

__init__(self)[source]¶

Initialize self. See help(type(self)) for accurate signature.

get_paths(self)[source]¶

Gets the paths for the light curves in the collection.

Returns:	An iterable of the light curve paths.

load_times_and_fluxes_from_path(self, path: Path)[source]¶

Loads the times and fluxes from a given light curve path.

Parameters:	path – The path to the light curve file.
Returns:	The times and the fluxes of the light curve.

load_times_and_magnifications_from_path(self, path: Path)[source]¶

Loads the times and magnifications from a given path as an injectable signal.

Parameters:	path – The path to the light curve/signal file.
Returns:	The times and the magnifications of the light curve/signal.

static generate_synthetic_signal_from_real_data(fluxes: np.ndarray, times: np.ndarray)[source]¶

Takes real light curve data and converts it to a form that can be used for synthetic light curve injection.

Parameters:	fluxes – The real light curve fluxes. times – The real light curve times.
Returns:	Fake synthetic magnifications and times.

load_label_from_path(self, path: Path)[source]¶

Loads the label of an example from a corresponding path.

Parameters:	path – The path to load the label for.
Returns:	The label.

static shuffle_and_split_paths(paths: List[Path], dataset_splits: List[int], number_of_splits: int = 10)[source]¶

Repeatably shuffles a list of paths and then gets the requested dataset splits from that list of paths. Designed to allow splitting a list of paths into training, validation, and testing datasets easily.

Parameters:	paths – The original list of paths. dataset_splits – The indexes of the dataset splits to return. number_of_splits – The number of dataset splits.
Returns:	The paths of the dataset splits.

load_times_fluxes_and_flux_errors_from_path(self, path: Path)[source]¶

Loads the times, fluxes, and flux errors of a light curve from a path to the data. Unless overridden, defaults to using the method to load only the times and fluxes, and returns None for errors.

Parameters:	path – The path of the file containing the light curve data.
Returns:	The times, fluxes, and flux errors.

load_times_magnifications_and_magnification_errors_from_path(self, path: Path)[source]¶

Loads the times, magnifications, and magnification_errors of a light curve from a path to the data. Unless overridden, defaults to using the method to load only the times and magnifications, and returns None for magnification errors.

Parameters:	path – The path of the file containing the light curve data.
Returns:	The times, magnifications, and magnification errors.