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 emir.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`

EMIR Reduction Recipes¶

Execution environment of the Recipes¶

Recipe Parameters¶

Recipe Products¶

DFP Recipes Parameters¶

DRP Recipes Parameters¶

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EMIR Reduction Recipes¶

Execution environment of the Recipes¶

Recipe Parameters¶

Recipe Products¶

DFP Recipes Parameters¶

DRP Recipes Parameters¶

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