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Glossary of WSA NonSurvey attributes (UKIDSSDR11)

This Glossary alphabetically lists all attributes used in the WSA NonSurvey database(s) held in the WSA. If you would like to have more information about the schema tables please use the Schema Browser (other Browser versions).
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NameSchema TableDatabaseDescriptionTypeLengthUnitDefault ValueUnified Content Descriptor
camNum [nspid]MultiframeDetector WSA NonSurvey Number of WFCAM camera (1, 2, 3 or 4) {image extension keyword: CAMNUM} int 4     obs.field
camPower [nspid]MultiframeDetector WSA NonSurvey Camera power (On|Off) {image extension keyword: CAMPOWER} varchar 3   --- ??
camReadOut [nspid]MultiframeDetector WSA NonSurvey Camera readout (CDS|NDR|SAR|RRR) {image extension keyword: READOUT} varchar 3   --- ??
camRole [nspid]MultiframeDetector WSA NonSurvey Camera role (master|slave|unsync) {image extension keyword: CAMROLE} varchar 8   NONE ??
catalogueID [nspid]MapAverageWeights WSA NonSurvey Unique identifier for input catalogue bigint 8   -99999999 meta_id
catalogueID [nspid]MapFrameStatus, [nspid]MapRemeasAver WSA NonSurvey Unique identifier for catalogue bigint 8   -99999999 meta_id;meta_main
catalogueID [nspid]MapProvenance WSA NonSurvey the UID of the component frame bigint 8     obs.field
catalogueID [nspid]MapRemeasurement WSA NonSurvey Unique identifier for catalogue {catalogue extension keyword:  CATLGID} bigint 8   -99999999 meta_id;meta_main
catalogueSchema [nspid]Programme WSA NonSurvey Script file that describes the catalogue schema varchar 64     ??
catCreationDate [nspid]MultiframeDetector WSA NonSurvey Creation date/time of catalogue file {catalogue extension keyword:  DATE} datetime 8 MM-DD-YYYY:hh:mm:ss.sss 12-31-9999 ??
catName [nspid]MapFrameStatus WSA NonSurvey the filename of the associated catalogue MEF, eg. server:/path/filename_list.fits varchar 256   NONE ID_CATALOG
catName [nspid]Multiframe WSA NonSurvey the filename of the associated catalogue MEF, eg. server:/path/filename.fits varchar 256     meta.id;meta.dataset
ccdHeaterLevel [nspid]Multiframe WSA NonSurvey AG CCD heater level (in percent) {image primary HDU keyword: CCD_HTP} real 4   -0.9999995e9  
ccdTemp [nspid]Multiframe WSA NonSurvey AG CCD temperature {image primary HDU keyword: CCD_TEMP} real 4 degrees_Kelvin -0.9999995e9  
ccdTempSetPt [nspid]Multiframe WSA NonSurvey AG CCD temperature setpoint {image primary HDU keyword: CCDTEMPS} real 4   -0.9999995e9  
cd11 [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Element of the linear transformation matrix (with scale) {image extension keyword: CD1_1} float 8     pos.wcs.cdmatrix
cd12 [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Element of the linear transformation matrix (with scale) {image extension keyword: CD1_2} float 8     pos.wcs.cdmatrix
cd21 [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Element of the linear transformation matrix (with scale) {image extension keyword: CD2_1} float 8     pos.wcs.cdmatrix
cd22 [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Element of the linear transformation matrix (with scale) {image extension keyword: CD2_2} float 8     pos.wcs.cdmatrix
centralDec [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Dec (J2000) at device centre float 8 Degrees -0.9999995e9 pos.eq.dec;meta.main
centralRa [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey RA (J2000) at device centre float 8 Degrees -0.9999995e9 pos.eq.ra;meta.main
chi2 [nspid]ExtendedSource, [nspid]GcsPointSource, [nspid]GpsPointSource, [nspid]JHKsource, [nspid]LasPointSource, [nspid]PointSource, [nspid]Source, [nspid]YJHKsource, [nspid]ZYJHKsource WSA NonSurvey Chi-squared value of proper motion solution real 4   -0.9999995e9 FIT_CHI2
chi2 [nspid]Variability WSA NonSurvey Chi-squared value of astrometric solution real 4   -0.9999995e9 FIT_CHI2
The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.
chi2s [nspid]AstrometricInfo WSA NonSurvey Reduced chi-squared of fit float 8   -0.9999995e9 ??
chiSq [nspid]SatelliteOrbits WSA NonSurvey Chi-squared of fit real 4      
CIR_BVAR [nspid]MultiframeDetector WSA NonSurvey Latest estimate of background variance {image extension keyword: CIR_BVAR} real 4   -0.9999995e9 instr.background
CIR_SCAL [nspid]MultiframeDetector WSA NonSurvey Background scale relative to group maximum {image extension keyword: CIR_SCAL} real 4   -0.9999995e9 instr.background
CIR_ZERO [nspid]MultiframeDetector WSA NonSurvey Pedestal value relative to group average {image extension keyword: CIR_ZERO} real 4   -0.9999995e9 stat.fit.param
CIRMED [nspid]MultiframeDetector WSA NonSurvey Latest estimate of background {image extension keyword: CIRMED} real 4   -0.9999995e9 instr.background
class [nspid]Detection WSA NonSurvey Flag indicating most probable morphological classification {catalogue TType keyword: Classification}
-1 stellar, +1 non--stellar, 0 noise, -2 borderline stellar, -3 boderline galaxy, -9 saturated		 smallint 2     CLASS_MISC
Using the SE classification statistic (see the corresponding entry for classStat), a CASU-like discrete classification code is assigned for each detected object as follows:
FlagMeaning
-9Saturated
-3Probable galaxy
-2Probable star
-1Star
+1Galaxy

where rectangular regions in the magnitude-classStat plane are used to select each class.
class [nspid]Detection WSA NonSurvey Flag indicating most probable morphological classification {catalogue TType keyword: Classification}
-1 stellar, +1 non--stellar, 0 noise, -2 borderline stellar, -3 borderline galaxy, -9 saturated		 smallint 2     CLASS_MISC
A discrete classification code for each detected image, based on various cuts on morphological parameters (see the Glossary entries for classStat and ell for further details). It is primarily based on cuts on the stellar profile statistic classStat and necessarily trades-off completeness against reliability between point-like (e.g. stellar) and extended (e.g. galaxy) images. The class assignments are as follows:
FlagMeaningGenerally satisfies
-2Probable star+2.0≤classStat≤+3.0
-1Star-3.0≤classStat≤+2.0
0NoiseclassStat≤-3.0
+1GalaxyclassStat≥+3.0

but these are also moderated by ellipticity overrides (e.g. ellipticity≥0.9 is flagged as class 0) and magnitude-dependent information (e.g. near or at saturation objects are preferentially flagged as class -1). Hence class is conservative in the sense that it defines galaxy samples optimised for completeness, and conversely point-source samples optimised for reliability. For examples of the use of the various classification attributes in sample selection, especially with respect to the trade-off between completeness and reliability for point/extended samples, see the Views predefined in the WSA schema (these can be examined using the schema browser). For much more information concerning the class attribute, see the CASU standard source extraction documentation.
class [nspid]MapRemeasAver WSA NonSurvey Merged Flag indicating most probable morphological classification
-1 stellar, +1 non--stellar, 0 noise, -2 borderline stellar, -3 borderline galaxy, -9 saturated		 smallint 2     src.class
A discrete classification code for each detected image, based on various cuts on morphological parameters (see the Glossary entries for classStat and ell for further details). It is primarily based on cuts on the stellar profile statistic classStat and necessarily trades-off completeness against reliability between point-like (e.g. stellar) and extended (e.g. galaxy) images. The class assignments are as follows:
FlagMeaningGenerally satisfies
-2Probable star+2.0≤classStat≤+3.0
-1Star-3.0≤classStat≤+2.0
0NoiseclassStat≤-3.0
+1GalaxyclassStat≥+3.0

but these are also moderated by ellipticity overrides (e.g. ellipticity≥0.9 is flagged as class 0) and magnitude-dependent information (e.g. near or at saturation objects are preferentially flagged as class -1). Hence class is conservative in the sense that it defines galaxy samples optimised for completeness, and conversely point-source samples optimised for reliability. For examples of the use of the various classification attributes in sample selection, especially with respect to the trade-off between completeness and reliability for point/extended samples, see the Views predefined in the WSA schema (these can be examined using the schema browser). For much more information concerning the class attribute, see the CASU standard source extraction documentation.
class [nspid]MapRemeasurement WSA NonSurvey Flag indicating most probable morphological classification {catalogue TType keyword: Classification}
-1 stellar, +1 non--stellar, 0 noise, -2 borderline stellar, -3 borderline galaxy, -9 saturated		 smallint 2     stat
A discrete classification code for each detected image, based on various cuts on morphological parameters (see the Glossary entries for classStat and ell for further details). It is primarily based on cuts on the stellar profile statistic classStat and necessarily trades-off completeness against reliability between point-like (e.g. stellar) and extended (e.g. galaxy) images. The class assignments are as follows:
FlagMeaningGenerally satisfies
-2Probable star+2.0≤classStat≤+3.0
-1Star-3.0≤classStat≤+2.0
0NoiseclassStat≤-3.0
+1GalaxyclassStat≥+3.0

but these are also moderated by ellipticity overrides (e.g. ellipticity≥0.9 is flagged as class 0) and magnitude-dependent information (e.g. near or at saturation objects are preferentially flagged as class -1). Hence class is conservative in the sense that it defines galaxy samples optimised for completeness, and conversely point-source samples optimised for reliability. For examples of the use of the various classification attributes in sample selection, especially with respect to the trade-off between completeness and reliability for point/extended samples, see the Views predefined in the WSA schema (these can be examined using the schema browser). For much more information concerning the class attribute, see the CASU standard source extraction documentation.
class [nspid]UKIDSSDetection WSA NonSurvey Flag indicating most probable morphological classification smallint 2     CLASS_MISC
classStat [nspid]Detection WSA NonSurvey S-Extractor classification statistic CLASS_STAR (0 - galaxy, 1 - star) {catalogue TType keyword: Statistic} real 4     STAT_PROP
CLASS_STAR is SE's classification of objects on the basis of a Neural Network Output. There are several input parameters which are directly linked to the CLASS_STAR parameter:
PIXEL_SCALEPixel size in arsec.
SEEING_FWHMFWHM of stellar images in arcsec.
BACK_SIZESize, or Width, Height (in pixels) of a background mesh.
THRESH_TYPEMeaning of the DETECT_THRESH and ANALYSIS_THRESH parameters: RELATIVE (scaling factor to the background rms) or ABSOLUTE (absolute level)
ANALYSIS_THRESHThreshold (in surface brightness) at which CLASS_STAR and FWHM operate: 1argument (relative to background rms) or 2 arguments (mu[mag/arcsec²], zero-point [mag])

A perfectly point-like (stellar) object has class=1.0.
classStat [nspid]Detection WSA NonSurvey N(0,1) stellarness-of-profile statistic {catalogue TType keyword: Statistic} real 4     STAT_PROP
An equivalent N(0,1) measure of how point-like an image is, used in deriving the class attribute in a 'necessary but not sufficient' sense. Derived mainly from the curve-of-growth of flux using the well-defined stellar locus as a function of magnitude as a benchmark (see Irwin et al. 2004 SPIE 5493 411 for more details). Note that the assignment of the discrete classification flag class=-1 is based on a cut of -3.0≤classStat≤+2.0 cut on this statistic (along with ellipticity and magnitude information) and hence is conservative in the sense that it defines galaxy samples optimised for completeness, and conversely stellar samples optimised for reliability. For examples of the use of the various classification attributes in sample selection, especially with respect to the trade-off between completeness and reliability for point or extended samples, see the Views predefined in the WSA schema (these can be examined using the schema browser).
classStat [nspid]MapRemeasAver WSA NonSurvey Averaged N(0,1) stellarness-of-profile statistic (SE: classification statistic CLASS_STAR; 0 - galaxy, 1 - star) real 4     stat
An equivalent N(0,1) measure of how point-like an image is, used in deriving the class attribute in a 'necessary but not sufficient' sense. Derived mainly from the curve-of-growth of flux using the well-defined stellar locus as a function of magnitude as a benchmark (see Irwin et al. 2004 SPIE 5493 411 for more details). Note that the assignment of the discrete classification flag class=-1 is based on a cut of -3.0≤classStat≤+2.0 cut on this statistic (along with ellipticity and magnitude information) and hence is conservative in the sense that it defines galaxy samples optimised for completeness, and conversely stellar samples optimised for reliability. For examples of the use of the various classification attributes in sample selection, especially with respect to the trade-off between completeness and reliability for point or extended samples, see the Views predefined in the WSA schema (these can be examined using the schema browser).
classStat [nspid]MapRemeasurement WSA NonSurvey N(0,1) stellarness-of-profile statistic (SE: classification statistic CLASS_STAR; 0 - galaxy, 1 - star) {catalogue TType keyword: Statistic} real 4     stat
An equivalent N(0,1) measure of how point-like an image is, used in deriving the class attribute in a 'necessary but not sufficient' sense. Derived mainly from the curve-of-growth of flux using the well-defined stellar locus as a function of magnitude as a benchmark (see Irwin et al. 2004 SPIE 5493 411 for more details). Note that the assignment of the discrete classification flag class=-1 is based on a cut of -3.0≤classStat≤+2.0 cut on this statistic (along with ellipticity and magnitude information) and hence is conservative in the sense that it defines galaxy samples optimised for completeness, and conversely stellar samples optimised for reliability. For examples of the use of the various classification attributes in sample selection, especially with respect to the trade-off between completeness and reliability for point or extended samples, see the Views predefined in the WSA schema (these can be examined using the schema browser).
classStat [nspid]UKIDSSDetection WSA NonSurvey N(0,1) stellarness-of-profile statistic real 4     STAT_PROP
combicatID [nspid]MapAverageWeights WSA NonSurvey Unique identifier for combined average catalogue bigint 8   -99999999 meta_id;meta_main
combicatID [nspid]MapProvenance WSA NonSurvey the UID of the combined frame (=combiframe) bigint 8     obs.field
combiframeID [nspid]Provenance WSA NonSurvey the UID of the combined frame (=combiframe) bigint 8     obs.field
combiProdType [nspid]ProductLinks WSA NonSurvey Type (stack,tile,mosaic) of combination frame varchar 8     ??
combiProductID [nspid]ProductLinks WSA NonSurvey Product ID of combination frame int 4     ??
comment [nspid]ArchiveCurationHistory WSA NonSurvey Comment string supplied by the curator varchar 256     ??
compFile [nspid]MultiframeDetector WSA NonSurvey Filename of the compressed image of this image frame, eg. server:/path/filename.jpg varchar 256   NONE meta.id;meta.file
confID [nspid]Multiframe WSA NonSurvey UID of library calibration confidence frame {image extension keyword: CIR_CPM} bigint 8   -99999999 obs.field
configIndex [nspid]MultiframeDetector WSA NonSurvey Configuration index {image extension keyword: CNFINDEX} int 4   -99999999 spect.index
convSegm [nspid]RequiredMosaicTopLevel WSA NonSurvey Convolution segmentation software varchar 16      
coord1 [nspid]ExternalSurveyTable WSA NonSurvey The attribute name of the first (longitudinal) spherical co-ordinate, e.g. equatorial RA varchar 32     ??
coord2 [nspid]ExternalSurveyTable WSA NonSurvey The attribute name of the second (latitudinal) spherical co-ordinate, e.g. equatorial Dec varchar 32     ??
coreRadius [nspid]MultiframeDetector WSA NonSurvey Core radius for default profile fit {catalogue extension keyword:  RCORE} real 4 pixels -0.9999995e9 ??
Tunable parameter, aperture flux designed to match median seeing of survey data. It is straightforward to show that if rcore = FWHM then for typical profiles encountered the rcore flux estimate has between 80-90% of the accuracy of an idealised perfectly known PSF model method.
corPlateTemp [nspid]Multiframe WSA NonSurvey Cor plate temperature {image primary HDU keyword: CP_TEMP} real 4 degrees_Kelvin -0.9999995e9  
corrPointingDec [nspid]ProblemFrames WSA NonSurvey Corrected pointing Declination float 8 deg    
corrPointingRa [nspid]ProblemFrames WSA NonSurvey Corrected pointing Right Ascension float 8 deg    
creationDate [nspid]Multiframe WSA NonSurvey File creation date (YYYY-MM-DD HH:MM:SS) {image primary HDU keyword: DATE} datetime 8 MM-DD-YYYY 12-31-9999 time.epoch
creationDate [nspid]MultiframeDetector WSA NonSurvey Creation date/time of file {image extension keyword: DATE} datetime 8 MM-DD-YYYY:hh:mm:ss.sss 12-31-9999 ??
creator [nspid]ExternalProduct WSA NonSurvey Name of the individual that created the product varchar 32     ??
crowdedFlag [nspid]MultiframeDetector WSA NonSurvey Crowded field analysis flag (0 none, 1 active) {catalogue extension keyword:  CROWDED} tinyint 1   0 meta.code
Tunable parameter, detection algorithm tried to disentangle overlapping images or images superposed on the "slowly" varying background of other large images (default) otherwise just straightforward isophotal detection.
crPixX [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Pixel coordinate of the reference point on axis 1 {image extension keyword: CRPIX1} float 8 pixels   pos.cartesian.x;instr.det
crPixY [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Pixel coordinate of the reference point on axis 2 {image extension keyword: CRPIX2} float 8 pixels   pos.cartesian.y;instr.det
crUnit1 [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Unit of right ascension co-ordinates {image extension keyword: CRUNIT1} varchar 8   NONE  
crUnit2 [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Unit of declination co-ordinates {image extension keyword: CRUNIT2} varchar 8   NONE  
crValX [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Coordinate value at reference point on axis 1 {image extension keyword: CRVAL1} float 8   -0.9999995e9 pos.cartesian.x;instr.det
crValY [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey Coordinate value at reference point on axis 2 {image extension keyword: CRVAL2} float 8   -0.9999995e9 pos.cartesian.y;instr.det
cryostPres [nspid]Multiframe WSA NonSurvey Cryostat Pressure {image primary HDU keyword: CC_PRES} float 8 millibar -0.9999995e9  
cTypeX [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey G&C WCS type, eg 'RA---ZPN' {image extension keyword: CTYPE1} varchar 8     pos.eq.ra;meta.main
cTypeY [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey G&C WCS type, eg 'DEC--ZPN' {image extension keyword: CTYPE2} varchar 8     pos.eq.dec;meta.main
cuEventID [nspid]ArchiveCurationHistory, [nspid]AstrCalVers, [nspid]CurrentAstrometry, [nspid]EpochFrameStatus, [nspid]MapApertureIDshighzQsoMap, [nspid]MapProvenance, [nspid]MapRemeasAver, [nspid]MapRemeasurement, [nspid]Multiframe, [nspid]MultiframeDetector, [nspid]PhotCalVers, [nspid]PreviousAstrometry, [nspid]ProgrammeCurationHistory, [nspid]ProgrammeFrame, [nspid]Provenance, [nspid]QsoMapVarFrameSetInfo WSA NonSurvey UID of curation event giving rise to this record int 4     meta.bib
cuEventID [nspid]AstrometricInfo, [nspid]Detection, [nspid]DxsSource, [nspid]ExtendedSource, [nspid]GcsPointSource, [nspid]GpsPointSource, [nspid]JHKmergeLog, [nspid]JHKsource, [nspid]JKmergeLog, [nspid]JKsource, [nspid]LasPointSource, [nspid]MergeLog, [nspid]Orphan, [nspid]PointSource, [nspid]SatelliteDetection, [nspid]SatelliteOrbits, [nspid]Source, [nspid]SourceXDetectionBestMatch, [nspid]SourceXSynopticSourceBestMatch, [nspid]SynopticMergeLog, [nspid]SynopticSource, [nspid]UKIDSSDetection, [nspid]UdsSource, [nspid]VarFrameSetInfo, [nspid]Variability, [nspid]YJHKmergeLog, [nspid]YJHKsource, [nspid]ZYJHKmergeLog, [nspid]ZYJHKsource WSA NonSurvey UID of curation event giving rise to this record int 4     REFER_CODE
cuEventID [nspid]MapFrameStatus WSA NonSurvey UID of curation event giving rise to this record int 4   -99999999 REFER_CODE
cuEventID [nspid]QsoMapVariability WSA NonSurvey UID of curation event giving rise to this record int 4     meta.code
cuID [nspid]ArchiveCurationHistory, [nspid]CurationTask WSA NonSurvey the unique curation task ID smallint 2     meta.bib
curator [nspid]ArchiveCurationHistory WSA NonSurvey The archive curation scientist responsible for this event varchar 16     ??
cutOff [nspid]Filter WSA NonSurvey The 50% cut-off wavelength of the filter real 4 microns   ??
cutOn [nspid]Filter WSA NonSurvey The 50% cut-on wavelength of the filter real 4 microns   ??
cx [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey unit vector of spherical co-ordinates of device centre float 8     pos.distance;pos.cartesian.x
cx [nspid]Detection, [nspid]DxsSource, [nspid]ExtendedSource, [nspid]GcsPointSource, [nspid]GpsPointSource, [nspid]JHKmergeLog, [nspid]JHKsource, [nspid]JKmergeLog, [nspid]JKsource, [nspid]LasPointSource, [nspid]MergeLog, [nspid]PointSource, [nspid]Source, [nspid]SynopticMergeLog, [nspid]SynopticSource, [nspid]UKIDSSDetection, [nspid]UdsSource, [nspid]YJHKmergeLog, [nspid]YJHKsource, [nspid]ZYJHKmergeLog, [nspid]ZYJHKsource WSA NonSurvey unit vector of spherical co-ordinates float 8     POS_EQ_X
cx [nspid]MapRemeasAver, [nspid]MapRemeasurement WSA NonSurvey unit vector of spherical co-ordinates float 8     pos.cartesian.x
cy [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey unit vector of spherical co-ordinates of device centre float 8     pos.distance;pos.cartesian.y
cy [nspid]Detection, [nspid]DxsSource, [nspid]ExtendedSource, [nspid]GcsPointSource, [nspid]GpsPointSource, [nspid]JHKmergeLog, [nspid]JHKsource, [nspid]JKmergeLog, [nspid]JKsource, [nspid]LasPointSource, [nspid]MergeLog, [nspid]PointSource, [nspid]Source, [nspid]SynopticMergeLog, [nspid]SynopticSource, [nspid]UKIDSSDetection, [nspid]UdsSource, [nspid]YJHKmergeLog, [nspid]YJHKsource, [nspid]ZYJHKmergeLog, [nspid]ZYJHKsource WSA NonSurvey unit vector of spherical co-ordinates float 8     POS_EQ_Y
cy [nspid]MapRemeasAver, [nspid]MapRemeasurement WSA NonSurvey unit vector of spherical co-ordinates float 8     pos.cartesian.y
cz [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey unit vector of spherical co-ordinates of device centre float 8     pos.distance;pos.cartesian.z
cz [nspid]Detection, [nspid]DxsSource, [nspid]ExtendedSource, [nspid]GcsPointSource, [nspid]GpsPointSource, [nspid]JHKmergeLog, [nspid]JHKsource, [nspid]JKmergeLog, [nspid]JKsource, [nspid]LasPointSource, [nspid]MergeLog, [nspid]PointSource, [nspid]Source, [nspid]SynopticMergeLog, [nspid]SynopticSource, [nspid]UKIDSSDetection, [nspid]UdsSource, [nspid]YJHKmergeLog, [nspid]YJHKsource, [nspid]ZYJHKmergeLog, [nspid]ZYJHKsource WSA NonSurvey unit vector of spherical co-ordinates float 8     POS_EQ_Z
cz [nspid]MapRemeasAver, [nspid]MapRemeasurement WSA NonSurvey unit vector of spherical co-ordinates float 8     pos.cartesian.z


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17/01/2022