EMIR Reduction Recipes

author:

Sergio Pascual <sergiopr@fis.ucm.es>, Nicolás Cardiel <cardiel@fis.ucm.es>

date:

2012-03-02

version:

1

Execution environment of the Recipes

Recipes have different execution environments. Some recipes are designed to process observing modes required while observing at the telescope. These modes are related to visualization, acquisition and focusing. The corresponding Recipes are integrated in the GTC environment. We call these recipes the Data Factory Pipeline, (DFP).

Other group of recipes are devoted to scientific observing modes: imaging, spectroscopy and auxiliary calibrations. These Recipes constitute the Data Reduction Pipeline, (DRP). The software is meant to be standalone, users shall download the software and run it in their own computers, with reduction parameters and calibrations provided by the instrument team.

Users of the DRP may use the simple Numina CLI (Command Line Interface) or the higher level, database-driven Pontifex. Users of the DFP shall interact with the software through the GTC Inspector.

Recipe Parameters

EMIR Recipes based on Numina have a list of required parameters needed to properly configure the Recipe. The Recipe announces the required parameters with the following syntax (the syntax is subject to changes).

class SomeRecipeInput(RecipeInput):
    master_dark = DataProductParameter(MasterDark, 'Master dark image')
    some_numeric_value = Parameter(0.45, 'Some numeric value'),

@define_input(SomeRecipeInput)
class SomeRecipe(RecipeBase):
    ...

When the reduction is run from the command line using Numina CLI, the program checks that the required values are provided or have default values. When the reduction is automatically executed using Pontifex, the program searches the operation database looking for the most appropriated data products (in this case, a MasterDark frame).

When the Recipe is properly configured, it is executed with an observing block data structure as input. When run using Numina CLI, this data structure is created from a text file. When run with Pontifex, the observing block data structure is created from the contents of the database.

Recipe Products

Recipes based on Numina provide a list of products created by the recipe. The Recipe announces the required parameters with the following syntax (the syntax is subject to changes).

class SomeRecipeInput(RecipeInput):
    master_dark = DataProductParameter(MasterDark, 'Master dark image')
    some_numeric_value = Parameter(0.45, 'Some numeric value'),

class SomeRecipeResult(RecipeResult):
    master_flat = Product(MasterDark)

@define_input(SomeRecipeInput)
@define_result(SomeRecipeResult)
class SomeRecipe(RecipeBase):
    ...

In the following two sections, we list the Reduction Recipes for the DRP and for the DFP. The format is: name of the Python class of the recipe, name of the observing mode, required parameters and data products provided. From the fully quallified name of the recipe we have removed the initial emirdrp.recipes..

The name of the parameters are prefixed with Product if the parameter is the result provided by another Recipe. If not, the value is a Parameter, or an OptionalParameter that will be ignored if not present.

DFP Recipes Parameters

class:

focus.TelescopeRoughFocusRecipe

mode:

TS rough focus

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Parameter: objects

  • Parameter: focus_range

provides:

TelescopeFocus

class:

focus.TelescopeFineFocusRecipe

mode:

TS fine focus

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Parameter: objects

provides:

TelescopeFocus

class:

focus.DTUFocusRecipe

mode:

EMIR focus control

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Parameter: objects

  • Parameter: msm_pattern

  • Parameter: dtu_focus_range

provides:

DTUFocus

class:

acquisition.MaskCheckRecipe

mode:

Target acquisition

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

provides:

TelescopeOffset

class:

acquisition.MaskImagingRecipe

mode:

Mask image

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

provides:

MSMPositions

class:

acquisition.MaskCheckRecipe

mode:

MSM and LSM check

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

provides:

TelescopeOffset, MSMPositions

DRP Recipes Parameters

class:

auxiliary.BiasRecipe

mode:

Bias image

requires:

provides:

MasterBias

class:

auxiliary.DarkRecipe

mode:

Dark image

requires:

Product: MasterBias

provides:

MasterDark

class:

auxiliary.IntensityFlatRecipe

mode:

Intensity flat-field

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

provides:

MasterIntensityFlat

class:

auxiliary.SpectralFlatRecipe

mode:

MSM spectral flat-field

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

provides:

MasterSpectralFlat

class:

auxiliary.SlitTransmissionRecipe

mode:

Slit transmission calibration

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

provides:

SlitTransmissionCalibration

class:

auxiliary.WavelengthCalibrationRecipe

mode:

Wavelength calibration

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Product: MasterSpectralFlatField

  • Parameter: line_table (with wavelengths of arc lines)

provides:

WavelengthCalibration

class:

image.StareImageRecipe

mode:

Stare image

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • OptionalParameter: sources (list of sources coordinates)

provides:

Image, SourcesCatalog

class:

image.NBImageRecipe

mode:

Nodded/Beamswitched images

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Parameter: extinction (Mean atmospheric extinction)

  • Parameter: iterations

  • Parameter: sky_images (Images used to estimate the background before and after current image)

  • Parameter: sky_images_sep_time (Maximum separation time between consecutive sky images in minutes)

  • Parameter: check_photometry_levels (Levels to check the flux of the objects)

  • Parameter: check_photometry_actions (Actions to take on images)

  • OptionalParameter: offsets (list of integer offsets between images)

provides:

Image, SourcesCatalog

class:

image.DitheredImageRecipe

mode:

Dithered images

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Parameter: extinction (Mean atmospheric extinction)

  • Parameter: iterations

  • Parameter: sky_images (Images used to estimate the background before and after current image)

  • Parameter: sky_images_sep_time (Maximum separation time between consecutive sky images in minutes)

  • Parameter: check_photometry_levels (Levels to check the flux of the objects)

  • Parameter: check_photometry_actions (Actions to take on images)

provides:

Image, SourcesCatalog

class:

image.MicroditheredImageRecipe

mode:

Micro-dithered images

requires:

  • All the parameters of image.DitheredImageRecipe

  • Parameter: subpixelization (number of subdivisions in each pixel side)

provides:

Image, SourcesCatalog

class:

image.MosaicRecipe

mode:

Mosaiced images

requires:

provides:

Image, SourcesCatalog

class:

mos.StareSpectraRecipe

mode:

Stare spectra

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Product: MasterSpectralFlatField

  • Product: SlitTransmissionCalibration

  • Product: WavelengthCalibration

  • Parameter: lines (wavelength to measure)

provides:

Spectra, LinesCatalog

class:

mos.DNSpectraRecipe

mode:

Dithered/Nodded spectra along the slit

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Product: MasterSpectralFlatField

  • Product: SlitTransmissionCalibration

  • Product: WavelengthCalibration

  • Parameter: lines (wavelegnth to measure)

  • OptionalParameter: offsets (list of integer offsets between images)

provides:

Spectra, LinesCatalog

class:

mos.OffsetSpectraRecipe

mode:

Offset spectra beyond the slit

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Product: MasterSpectralFlatField

  • Product: SlitTransmissionCalibration

  • Product: WavelengthCalibration

  • Parameter: lines (wavelegnth to measure)

  • OptionalParameter: offsets (list of integer offsets between images)

provides:

Spectra, LinesCatalog

class:

mos.RasterSpectraRecipe

mode:

Raster spectra

requires:

  • Product: MasterBias

  • Product: MasterDark

  • Product: MasterBadPixelMask

  • Product: NonLinearityCorrection

  • Product: MasterIntensityFlatField

  • Product: MasterSpectralFlatField

  • Product: SlitTransmissionCalibration

  • Product: WavelengthCalibration

  • Parameter: lines (wavelegnth to measure)

provides:

DataCube

class:

engineering.DTU_XY_CalibrationRecipe

mode:

DTU X_Y calibration

requires:

  • Parameter: slit_pattern

  • Parameter: dtu_range

provides:

DTU_XY_Calibration

class:

engineering.DTU_Z_CalibrationRecipe

mode:

DTU Z calibration

requires:

Parameter: dtu_range

provides:

DTU_Z_Calibration

class:

engineering.DTUFlexureRecipe

mode:

DTU Flexure compensation

requires:

provides:

DTUFlexureCalibration

class:

engineering.CSU2DetectorRecipe

mode:

CSU2Detector calibration

requires:

Parameter: dtu_range

provides:

DTU_XY_Calibration

class:

engineering.FocalPlaneCalibrationRecipe

mode:

Lateral colour

requires:

provides:

PointingOriginCalibration

class:

engineering.SpectralCharacterizationRecipe

mode:

Spectral characterization

requires:

provides:

WavelengthCalibration

class:

engineering.RotationCenterRecipe

mode:

Centre of rotation

requires:

provides:

PointingOriginCalibration

class:

engineering.AstrometricCalibrationRecipe

mode:

Astrometric calibration

requires:

provides:

Image

class:

engineering.PhotometricCalibrationRecipe

mode:

Photometric calibration

requires:

Parameter: phot

provides:

PhotometricCalibration

class:

engineering.SpectroPhotometricCalibrationRecipe

mode:

Spectrophotometric calibration

requires:

Parameter: sphot

provides:

SpectroPhotometricCalibration