processing

tessvectors processing

The tessvectors.processing classes makevectors and diagnostics containg the functionality that created the tessvectors products.
- The makevectors class contains the processing workflow that creates each CSV - The diagnostics class contains the plotting & visualisation routines

basic tessvectors processing

tessvectors was developed to use web-based TESS data hosted on MAST. Basic creation of vectors for a sector can be created by running:

from tessvectors.processing import makevectors
makevectors().create_vectors_sector(1, check_exists=True)

This will create all tessvectors files for a given sector (020/120/FFI Cadences & Cameras 1/2/3/4). If check_exists = True (default), it will prevent TESSVectors from overwriting files

Diagnostic plots for a given sector can be created similarily

from tessvectors.processing import diagnostics
diagnostics.create_diagnostics_sector(1):

There also exist a few convenience functions in tessvectors - process_sector, run_bulk_vectors and run_bulk_diagnostics.

- process sector will create vectors and diagnostic plots for a given sector
- run_bulk_vectors & run_bulk_diagnostics will use multiprocessing.Pool multiprocessing to run a large number of sectors at a time

tessvectors processing usage

We expect that the most common usage for this code will be to create data products and diagnostics for a future sector. This can be done simply by using the TESSVectors_process_sector function, e.g. :

    import tessvectors
    tessvectors.process_sector(Sector_Number)

Which calls the tessvectors.processing.makevectors.create_vectors_sector function that creates the TESSVectors CSV files for a given sector and the create_diagnostics_sector function that creates the diagnostic plots for a given sector.

There are also some convenient multiprocessing functions if you wish to create a bulk reprocessing of the TESSVectors data - run_bulk_vectors, run_bulk_processing, andrun_bulk_diagnostics which create all products, data files, and diagnostic plots respectively.

TESSVectors has been optimized to minimize its reliance and repeated calls to external data. From a high level perspective, this means that the default processing has been designed around creating TESSVectors for a given sector and accross all Cameras and Cadences at once.

Local vs Remote Usage

TESSVectors requires access to certain files to create its end products for a given sector. These files are:

- Sector Quaternion Files: *-quat.fits
- Sector Earth-Moon Information Files: *-emi.fits
- 1 tpf for each TESS observing cadence for each camera: (20s where available, 120s, FFI)

By default this information is retrieved from remote sources using API calls to mast holdings, and through the lightkurve package.

TESSVectors was initially designed and the initial products were made using remote data accessed from the MAST web holdings. We reccomend this. However, TESSVectors also has a somewhat experimental 'local' mode in the event that one is running these files where a sufficient archive of local data exists.

The local access functions broadly assumes that all of your tpfs for a given TESS observing cadence are in a single folder. If they are not (which is a sensible choice), you may need to modify the local access functions to account for your local data directory structure. For the FFI files, TESSVectors will attempt to use the list of FFI files as a TESSCut stand-in and create the nescessary products from these files. That means that if any FFI files are missing from this list, TESSVectors will exclude those FFI times from the end products.

This method is experimental and may require development/tweaking if you wish to use purely local files.

TESSVectors Code Workflow

flowchart LR
    subgraph For Each Sector
    TESSVectors_process_sector --> create_vectors_sector
    get_eng_data --> |Quaternion Data| create_vectors_sector
    get_eng_data --> |Earth-Moon Info| create_vectors_sector
    subgraph For Each Camera
    get_camera_sector_cadences --> create_vectors_sector
    
    subgraph For Each Cadence
    get_ccd_centers --> get_camera_sector_cadences
    get_timing_midpoints_tpf --> get_camera_sector_cadences
    gettimes[get_times_from_mast
            or get_times_local] --> get_timing_midpoints_tpf
    get_break_times --> get_timing_midpoints_tpf
    get_segment_label --> get_timing_midpoints_tpf
    end
    
    Bin_Quat_Camera --> create_vectors_sector

    subgraph For Each Cadence
    Bin_Quat_Cadence --> Bin_Quat_Camera
    end

    Bin_EMI_Camera --> create_vectors_sector
    subgraph For Each Cadence
    Bin_EMI_Cadence --> Bin_EMI_Camera
    EMI_Extension_Dict --> Bin_EMI_Cadence
    end


    create_vectors_sector --> write_vector_sector_camera
    
    subgraph For Each Cadence
    write_vector_sector_camera --> Output((TESSVectors File))
    end

    end

    create_vectors_sector --> create_diagnostics_sector

    subgraph For Each Camera
    subgraph For Each Cadence 
    create_diagnostics_sector --> create_diagnostic_timeseries --> OT((Quaternion 
    Timeseries Plot))
    create_diagnostics_sector --> create_diagnostic_emi --> OE((Earth-Moon 
    Information Plot))
    end
    create_diagnostics_sector --> create_diagnostic_periodogram --> OP((Periodogram Plot))
    end

    end

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