pypeit.spectrographs.gtc_osiris module

Module for GTC OSIRIS specific methods.

class pypeit.spectrographs.gtc_osiris.GTCMAATSpectrograph[source]

Bases: GTCOSIRISPlusSpectrograph

classmethod default_pypeit_par()[source]

Return the default parameters to use for this instrument.

Returns:

Parameters required by all of PypeIt methods.

Return type:

PypeItPar

get_datacube_bins(slitlength, minmax, num_wave)[source]

Calculate the bin edges to be used when making a datacube.

Parameters:

  • slitlength (int) – Length of the slit in pixels

  • minmax (numpy.ndarray) – An array with the minimum and maximum pixel locations on each slit relative to the reference location (usually the centre of the slit). Shape must be \((N_{\rm slits},2)\), and is typically the array returned by get_radec_image().

  • num_wave (int) –

    Number of wavelength steps. Given by::

    int(round((wavemax-wavemin)/delta_wave))

:param tuple: Three 1D numpy.ndarray providing the bins to use :param when constructing a histogram of the spec2d files. The elements: :param are \(: :type are :math:\): x,y,lambda

get_wcs(hdr, slits, platescale, wave0, dwv, spatial_scale=None)[source]

Construct/Read a World-Coordinate System for a frame.

Parameters:

  • hdr (astropy.io.fits.Header) – The header of the raw frame. The information in this header will be extracted and returned as a WCS.

  • slits (SlitTraceSet) – Slit traces.

  • platescale (float) – The platescale of an unbinned pixel in arcsec/pixel (e.g. detector.platescale).

  • wave0 (float) – The wavelength zeropoint.

  • dwv (float) – Change in wavelength per spectral pixel.

Returns:

The world-coordinate system.

Return type:

astropy.wcs.WCS

init_meta()[source]

Define how metadata are derived from the spectrograph files.

That is, this associates the PypeIt-specific metadata keywords with the instrument-specific header cards using meta.

name = 'gtc_maat'

The name of the spectrograph. See Spectrographs for the currently supported spectrographs.

pypeline = 'SlicerIFU'

String used to select the general pipeline approach for this spectrograph.

class pypeit.spectrographs.gtc_osiris.GTCOSIRISPlusSpectrograph[source]

Bases: Spectrograph

Child of Spectrograph to handle GTC/OSIRIS specific code

bpm(filename, det, shape=None, msbias=None)[source]

Generate a default bad-pixel mask.

Even though they are both optional, either the precise shape for the image (shape) or an example file that can be read to get the shape (filename using get_image_shape()) must be provided.

Parameters:

  • filename (str or None) – An example file to use to get the image shape.

  • det (int) – 1-indexed detector number to use when getting the image shape from the example file.

  • shape (tuple, optional) – Processed image shape Required if filename is None Ignored if filename is not None

  • msbias (numpy.ndarray, optional) – Processed bias frame used to identify bad pixels. This is ignored for KCWI.

Returns:

An integer array with a masked value set to 1 and an unmasked value set to 0. All values are set to 0.

Return type:

numpy.ndarray

camera = 'OSIRIS'

Name of the spectrograph camera or arm. This is used by specdb, so use that naming convention

check_frame_type(ftype, fitstbl, exprng=None)[source]

Check for frames of the provided type.

Parameters:
Returns:

Boolean array with the flags selecting the exposures in fitstbl that are ftype type frames.

Return type:

numpy.ndarray

comment = 'See :doc:`gtc_osiris`'

A brief comment or description regarding PypeIt usage with this spectrograph.

compound_meta(headarr, meta_key)[source]

Methods to generate metadata requiring interpretation of the header data, instead of simply reading the value of a header card.

Parameters:
Returns:

Metadata value read from the header(s).

Return type:

object

config_independent_frames()[source]

Define frame types that are independent of the fully defined instrument configuration.

Bias and dark frames are considered independent of a configuration. Standards are assigned to the correct configuration frame group by grism (i.e. ignoring that they are taken with a wider slit). See set_configurations().

Returns:

Dictionary where the keys are the frame types that are configuration independent and the values are the metadata keywords that can be used to assign the frames to a configuration group.

Return type:

dict

config_specific_par(scifile, inp_par=None)[source]

Modify the PypeIt parameters to hard-wired values used for specific instrument configurations.

Parameters:

  • scifile (str) – File to use when determining the configuration and how to adjust the input parameters.

  • inp_par (ParSet, optional) – Parameter set used for the full run of PypeIt. If None, use default_pypeit_par().

Returns:

The PypeIt parameter set adjusted for configuration specific parameter values.

Return type:

ParSet

configuration_keys()[source]

Return the metadata keys that define a unique instrument configuration.

This list is used by PypeItMetaData to identify the unique configurations among the list of frames read for a given reduction.

Returns:

List of keywords of data pulled from file headers and used to constuct the PypeItMetaData object.

Return type:

list

classmethod default_pypeit_par()[source]

Return the default parameters to use for this instrument.

Returns:

Parameters required by all of PypeIt methods.

Return type:

PypeItPar

get_detector_par(det, hdu=None)[source]

Return metadata for the selected detector.

Detector data from here.

Parameters:

  • det (int) – 1-indexed detector number.

  • hdu (astropy.io.fits.HDUList, optional) – The open fits file with the raw image of interest. If not provided, frame-dependent parameters are set to a default.

Returns:

Object with the detector metadata.

Return type:

DetectorContainer

header_name = 'OSIRIS'

Name of the spectrograph camera or arm from the Header. Usually the INSTRUME card.

init_meta()[source]

Define how metadata are derived from the spectrograph files.

That is, this associates the PypeIt-specific metadata keywords with the instrument-specific header cards using meta.

name = 'gtc_osiris_plus'

The name of the spectrograph. See Spectrographs for the currently supported spectrographs.

ndet = 1

Number of detectors for this instrument.

raw_header_cards()[source]

Return additional raw header cards to be propagated in downstream output files for configuration identification.

The list of raw data FITS keywords should be those used to populate the configuration_keys() or are used in config_specific_par() for a particular spectrograph, if different from the name of the PypeIt metadata keyword.

This list is used by subheader_for_spec() to include additional FITS keywords in downstream output files.

Returns:

List of keywords from the raw data files that should be propagated in output files.

Return type:

list

supported = True

Flag that PypeIt code base has been sufficiently tested with data from this spectrograph that it is officially supported by the development team.

telescope = Parameter     Value                Default  Type        Callable ---------------------------------------------------------------- name          GTC                  KECK     str         False    longitude     -17.879999999999995  None     int, float  False    latitude      28.758333333333336   None     int, float  False    elevation     2326.999999998442    None     int, float  False    fratio        None                 None     int, float  False    diameter      None                 None     int, float  False    eff_aperture  73.0                 None     int, float  False   

Instance of TelescopePar providing telescope-specific metadata.

tweak_standard(wave_in, counts_in, counts_ivar_in, gpm_in, meta_table, trim_std_pixs=None, log10_blaze_function=None, debug=False)[source]

This routine is for performing instrument/disperser specific tweaks to standard stars so that sensitivity function fits will be well behaved. For example, masking second order light. For instruments that don’t require such tweaks it will just return the inputs, but for instruments that do this function is overloaded with a method that performs the tweaks.

Parameters:

  • wave_in (numpy.ndarray) – Input standard star wavelengths (float, shape = (nspec,))

  • counts_in (numpy.ndarray) – Input standard star counts (float, shape = (nspec,))

  • counts_ivar_in (numpy.ndarray) – Input inverse variance of standard star counts (float, shape = (nspec,))

  • gpm_in (numpy.ndarray) – Input good pixel mask for standard (bool, shape = (nspec,))

  • meta_table (dict) – Table containing meta data that is slupred from the SpecObjs object. See unpack_object() for the contents of this table.

  • trim_std_pixs (list or tuple, optional) – List or tuple of two integers specifying the number of pixels to trim from the start and end of the standard star spectrum. If None, no trimming is applied. Default=None.

  • log10_blaze_function (numpy.ndarray or None) – Input blaze function to be tweaked, optional. Default=None.

Returns:

  • wave_out (numpy.ndarray) – Output standard star wavelengths (float, shape = (nspec,))

  • counts_out (numpy.ndarray) – Output standard star counts (float, shape = (nspec,))

  • counts_ivar_out (numpy.ndarray) – Output inverse variance of standard star counts (float, shape = (nspec,))

  • gpm_out (numpy.ndarray) – Output good pixel mask for standard (bool, shape = (nspec,))

  • log10_blaze_function_out (numpy.ndarray or None) – Output blaze function after being tweaked.

url = 'http://www.gtc.iac.es/instruments/osiris/'

Reference url

class pypeit.spectrographs.gtc_osiris.GTCOSIRISSpectrograph[source]

Bases: Spectrograph

Child of Spectrograph to handle GTC/OSIRIS specific code (old detector: MAT-44-82)

bpm(filename, det, shape=None, msbias=None)[source]

Generate a default bad-pixel mask.

Even though they are both optional, either the precise shape for the image (shape) or an example file that can be read to get the shape (filename using get_image_shape()) must be provided.

Parameters:

  • filename (str or None) – An example file to use to get the image shape.

  • det (int) – 1-indexed detector number to use when getting the image shape from the example file.

  • shape (tuple, optional) – Processed image shape Required if filename is None Ignored if filename is not None

  • msbias (numpy.ndarray, optional) – Processed bias frame used to identify bad pixels. This is ignored for KCWI.

Returns:

An integer array with a masked value set to 1 and an unmasked value set to 0. All values are set to 0.

Return type:

numpy.ndarray

camera = 'OSIRIS'

Name of the spectrograph camera or arm. This is used by specdb, so use that naming convention

check_frame_type(ftype, fitstbl, exprng=None)[source]

Check for frames of the provided type.

Parameters:
Returns:

Boolean array with the flags selecting the exposures in fitstbl that are ftype type frames.

Return type:

numpy.ndarray

comment = 'See :doc:`gtc_osiris`'

A brief comment or description regarding PypeIt usage with this spectrograph.

compound_meta(headarr, meta_key)[source]

Methods to generate metadata requiring interpretation of the header data, instead of simply reading the value of a header card.

Parameters:
Returns:

Metadata value read from the header(s).

Return type:

object

config_independent_frames()[source]

Define frame types that are independent of the fully defined instrument configuration.

Bias and dark frames are considered independent of a configuration. Standards are assigned to the correct configuration frame group by grism (i.e. ignoring that they are taken with a wider slit). See set_configurations().

Returns:

Dictionary where the keys are the frame types that are configuration independent and the values are the metadata keywords that can be used to assign the frames to a configuration group.

Return type:

dict

config_specific_par(scifile, inp_par=None)[source]

Modify the PypeIt parameters to hard-wired values used for specific instrument configurations.

Parameters:

  • scifile (str) – File to use when determining the configuration and how to adjust the input parameters.

  • inp_par (ParSet, optional) – Parameter set used for the full run of PypeIt. If None, use default_pypeit_par().

Returns:

The PypeIt parameter set adjusted for configuration specific parameter values.

Return type:

ParSet

configuration_keys()[source]

Return the metadata keys that define a unique instrument configuration.

This list is used by PypeItMetaData to identify the unique configurations among the list of frames read for a given reduction.

Returns:

List of keywords of data pulled from file headers and used to constuct the PypeItMetaData object.

Return type:

list

classmethod default_pypeit_par()[source]

Return the default parameters to use for this instrument.

Returns:

Parameters required by all of PypeIt methods.

Return type:

PypeItPar

get_detector_par(det, hdu=None)[source]

Return metadata for the selected detector.

Detector data from here.

Parameters:

  • det (int) – 1-indexed detector number.

  • hdu (astropy.io.fits.HDUList, optional) – The open fits file with the raw image of interest. If not provided, frame-dependent parameters are set to a default.

Returns:

Object with the detector metadata.

Return type:

DetectorContainer

header_name = 'OSIRIS'

Name of the spectrograph camera or arm from the Header. Usually the INSTRUME card.

init_meta()[source]

Define how metadata are derived from the spectrograph files.

That is, this associates the PypeIt-specific metadata keywords with the instrument-specific header cards using meta.

name = 'gtc_osiris'

The name of the spectrograph. See Spectrographs for the currently supported spectrographs.

ndet = 2

Number of detectors for this instrument.

raw_header_cards()[source]

Return additional raw header cards to be propagated in downstream output files for configuration identification.

The list of raw data FITS keywords should be those used to populate the configuration_keys() or are used in config_specific_par() for a particular spectrograph, if different from the name of the PypeIt metadata keyword.

This list is used by subheader_for_spec() to include additional FITS keywords in downstream output files.

Returns:

List of keywords from the raw data files that should be propagated in output files.

Return type:

list

supported = True

Flag that PypeIt code base has been sufficiently tested with data from this spectrograph that it is officially supported by the development team.

telescope = Parameter     Value                Default  Type        Callable ---------------------------------------------------------------- name          GTC                  KECK     str         False    longitude     -17.879999999999995  None     int, float  False    latitude      28.758333333333336   None     int, float  False    elevation     2326.999999998442    None     int, float  False    fratio        None                 None     int, float  False    diameter      None                 None     int, float  False    eff_aperture  73.0                 None     int, float  False   

Instance of TelescopePar providing telescope-specific metadata.

tweak_standard(wave_in, counts_in, counts_ivar_in, gpm_in, meta_table, trim_std_pixs=None, log10_blaze_function=None, debug=False)[source]

This routine is for performing instrument/disperser specific tweaks to standard stars so that sensitivity function fits will be well behaved. For example, masking second order light. For instruments that don’t require such tweaks it will just return the inputs, but for instruments that do this function is overloaded with a method that performs the tweaks.

Parameters:

  • wave_in (numpy.ndarray) – Input standard star wavelengths (float, shape = (nspec,))

  • counts_in (numpy.ndarray) – Input standard star counts (float, shape = (nspec,))

  • counts_ivar_in (numpy.ndarray) – Input inverse variance of standard star counts (float, shape = (nspec,))

  • gpm_in (numpy.ndarray) – Input good pixel mask for standard (bool, shape = (nspec,))

  • meta_table (dict) – Table containing meta data that is slupred from the SpecObjs object. See unpack_object() for the contents of this table.

  • trim_std_pixs (list or tuple, optional) – List or tuple of two integers specifying the number of pixels to trim from the start and end of the standard star spectrum. If None, no trimming is applied. Default=None.

  • log10_blaze_function (numpy.ndarray or None) – Input blaze function to be tweaked, optional. Default=None.

Returns:

  • wave_out (numpy.ndarray) – Output standard star wavelengths (float, shape = (nspec,))

  • counts_out (numpy.ndarray) – Output standard star counts (float, shape = (nspec,))

  • counts_ivar_out (numpy.ndarray) – Output inverse variance of standard star counts (float, shape = (nspec,))

  • gpm_out (numpy.ndarray) – Output good pixel mask for standard (bool, shape = (nspec,))

  • log10_blaze_function_out (numpy.ndarray or None) – Output blaze function after being tweaked.

url = 'http://www.gtc.iac.es/instruments/osiris/'

Reference url