avocado.Augmentor._simulate_detection

Augmentor._simulate_detection(observations, augmented_metadata)

Simulate the detection process for a light curve.

This method needs to be implemented in survey-specific subclasses of this class. It should simulate whether each observation is detected as a point-source by the survey and set the “detected” flag in the observations DataFrame. It should also return whether or not the light curve passes a base set of criterion to be included in the sample that this classifier will be applied to.

Parameters:

• observations (pandas.DataFrame) – The augmented observations that have been sampled from a Gaussian Process.
• augmented_metadata (dict) – The augmented metadata

Returns:

• observations (pandas.DataFrame) – The observations with the detected flag set.
• pass_detection (bool) – Whether or not the full light curve passes the detection thresholds used for the full sample.