The Everest Pipeline¶
Below are the basic instructions for reproducing the
everest catalog. For
large photometric surveys like
K2, processing all light curves will take
a lot of time and a lot of computing power. It took on the order of 100,000 CPU hours
to generate the catalog for
K2 campaigns 0-8.
Users do not need to follow these instructions, unless they wish to tweak model parameters and generate catalogs of their own. Most users will simply want to interface with the existing catalog. See the user interface section.
1. Download the data¶
everest mission implements its own functionality for interfacing
with the raw data. For
K2, individual raw light curves can be downloaded
everest.missions.k2.GetData(EPIC, download_only = True)
Batch downloading for entire campaigns is implemented for individual missions.
K2, you can submit a PBS job to a cluster with
2. De-trend the data¶
Individual light curves can be de-trended by instantiating one of the
Currently, the available models are
everest.iPLD. These are all subclasses
everest.detrender.Detrender class, which accepts a bunch
of keyword arguments.
De-trending generates a
log log file, a
npz model file,
TargetDirectory() function of the mission
Batch de-trending is also implemented for individual missions.
You can check the status of the de-trending of each
K2 campaign with the
everest.k2.Status function. This is also implemented as the
everest-status command line utility in
3. Compute CBVs¶
Co-trending basis vectors (CBVs) can be computed for each of the
campaigns once they are done running. To do this, run
on each campaign. This will compile all of the de-trended light curves and
compute the top signals that are shared among all light curves using