soxspipe.commonutils.horne_extraction

perform optimal source extraction using the Horne method (Horne 1986)

Author

Marco Landoni & David Young

Date Created

May 17, 2023

Module Contents

Classes

horne_extraction

perform optimal source extraction using the Horne method (Horne 1986)

Functions

create_cross_dispersion_slices	This function is used to create a single, 1-pixel wide cross-dispersion slices of object data. When applied to the dataframe, a single slice is created for each discrete pixel position in the dispersion direction
extract_single_order	extract the object spectrum for a single order

API

soxspipe.commonutils.horne_extraction.create_cross_dispersion_slices(crossDispersionSlices)

This function is used to create a single, 1-pixel wide cross-dispersion slices of object data. When applied to the dataframe, a single slice is created for each discrete pixel position in the dispersion direction

Key Arguments:

• crossDispersionSlices – the seed dataframe

Return:

• crossDispersionSlices – dataframe containing metadata for each cross-dispersion slice (single data-points in extracted spectrum)

soxspipe.commonutils.horne_extraction.extract_single_order(crossDispersionSlices, funclog, ron, slitHalfLength, clippingSigma, clippingIterationLimit, globalClippingSigma, axisA, axisB, gain=1.0, hornePolyOrder=3, debug=False)

extract the object spectrum for a single order

Return:

• crossDispersionSlices – dataframe containing metadata for each cross-dispersion slice (single data-points in extracted spectrum)

class soxspipe.commonutils.horne_extraction.horne_extraction(log, settings, recipeSettings, skyModelFrame, skySubtractedFrame, unflattenedFrame, twoDMapPath, recipeName=False, qcTable=False, productsTable=False, dispersionMap=False, sofName=False, locationSetIndex=False, startNightDate='', notFlattened=False, debug=False, turnOffMP=False)

Bases: object

perform optimal source extraction using the Horne method (Horne 1986)

Key Arguments:

• log – logger

• settings – the settings dictionary

• recipeSettings – the recipe specific settings

• skyModelFrame – path to sky model frame

• skySubtractedFrame – path to sky subtracted frame

• unflattenedFrame – path to unflattened frame

• twoDMapPath – path to 2D dispersion map image path

• recipeName – name of the recipe as it appears in the settings dictionary

• qcTable – the data frame to collect measured QC metrics

• productsTable – the data frame to collect output products (if False no products are saved to file)

• dispersionMap – the FITS binary table containing dispersion map polynomial

• sofName – the set-of-files filename

• locationSetIndex – the index of the AB cycle locations (nodding mode only). Default False

• startNightDate – YYYY-MM-DD date of the observation night. Default “”

• notFlattened – flag to indicate if the frame is flattened or not. Default False

• debug – flag to indicate if debug mode is on (shows plots). Default False

• turnOffMP – turn off multiprocessing. True or False. Default False. If True, multiprocessing will be turned off and the recipe will run in serial. This is useful for debugging.

Usage:

To setup your logger, settings and database connections, please use the fundamentals package (see tutorial here https://fundamentals.readthedocs.io/en/master/initialisation.html).

To initiate a horne_extraction object, use the following:

from soxspipe.commonutils import horne_extraction
optimalExtractor = horne_extraction(
    log=log,
    skyModelFrame=skyModelFrame,
    skySubtractedFrame=skySubtractedFrame,
    unflattenedFrame=unflattenedFrame,
    twoDMapPath=twoDMap,
    settings=settings,
    recipeName="soxs-stare",
    qcTable=qc,
    productsTable=products,
    dispersionMap=dispMap,
    sofName=sofName,
    locationSetIndex=locationSetIndex,
    startNightDate=startNightDate,
    debug=debug,
    turnOffMP=turnOffMP

)
qc, products = optimalExtractor.extract()

Initialization

extract()

extract the full spectrum order-by-order and return FITS Binary table containing order-merged spectrum

Return:

• qcTable – the data frame to collect measured QC metrics

• productsTable – the data frame to collect output products

• mergedSpectumDF – path to the FITS binary table containing the merged spectrum

merge_extracted_orders(extractedOrdersDF)

merge the extracted order spectra in one continuous spectrum

Key Arguments:

• extractedOrdersDF – a data-frame containing the extracted orders

Return:

• None

plot_extracted_spectrum_qc(extractions)

plot extracted spectrum QC plot

Key Arguments:

• extractions – dataframes hosting order extractions

Usage:

optimalExtractor.plot_extracted_spectrum_qc(extractions)

residual_merge(group)

weighted_average(group)