P |
Name | Schema Table | Database | Description | Type | Length | Unit | Default Value | Unified Content Descriptor |
pa |
[nspid]Detection |
WSA NonSurvey |
ellipse fit orientation to x axis {catalogue TType keyword: Position_angle} Angle of ellipse major axis wrt x axis. |
real |
4 |
degrees |
|
POS_POS-ANG |
pairingCriterion |
[nspid]Programme |
WSA NonSurvey |
The pairing criterion for associating detections into merged sources |
real |
4 |
Degrees |
|
?? |
pcSysID |
[nspid]MultiframeDetector |
WSA NonSurvey |
PC system identifier {image extension keyword: PCSYSID} |
varchar |
32 |
|
NONE |
?? |
petroFlux |
[nspid]Detection |
WSA NonSurvey |
flux within circular aperture to k × r_p ; k = 2 {catalogue TType keyword: Petr_flux} |
real |
4 |
ADU |
|
PHOT_INTENSITY_ADU |
petroFluxErr |
[nspid]Detection |
WSA NonSurvey |
error on Petrosian flux {catalogue TType keyword: Petr_flux_err} |
real |
4 |
ADU |
|
ERROR |
petroMag |
[nspid]Detection |
WSA NonSurvey |
Calibrated Petrosian magnitude within circular aperture r_p |
real |
4 |
mag |
|
PHOT_INT-MAG |
petroMagErr |
[nspid]Detection |
WSA NonSurvey |
error on calibrated Petrosian magnitude |
real |
4 |
mag |
|
ERROR |
petroRad |
[nspid]Detection |
WSA NonSurvey |
r_p as defined in Yasuda et al. 2001 AJ 112 1104 {catalogue TType keyword: Petr_radius} |
real |
4 |
pixels |
|
EXTENSION_RAD |
pGalaxy |
[nspid]Source |
WSA NonSurvey |
Probability that the source is a galaxy |
real |
4 |
|
|
STAT_PROP |
Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag | Meaning | Probability (%) | | | Star | Galaxy | Noise | Saturated | -9 | Saturated | 0.0 | 0.0 | 5.0 | 95.0 | -3 | Probable galaxy | 25.0 | 70.0 | 5.0 | 0.0 | -2 | Probable star | 70.0 | 25.0 | 5.0 | 0.0 | -1 | Star | 90.0 | 5.0 | 5.0 | 0.0 | 0 | Noise | 5.0 | 5.0 | 90.0 | 0.0 | +1 | Galaxy | 5.0 | 90.0 | 5.0 | 0.0 | Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation. |
pHeight |
[nspid]Detection |
WSA NonSurvey |
Highest pixel value above sky {catalogue TType keyword: Peak_height} In counts relative to local value of sky - also zeroth order aperture flux. |
real |
4 |
ADU |
|
PHOT_COUNTS_MISC |
pHeightErr |
[nspid]Detection |
WSA NonSurvey |
Error in peak height {catalogue TType keyword: Peak_height_err} |
real |
4 |
ADU |
|
ERROR |
photZP |
[nspid]Multiframe |
WSA NonSurvey |
Photometric zeropoint for default extinction: this will be DEPRECATED soon; use MultiframeDetector.photZPCat {image primary HDU keyword: MAGZPT} |
real |
4 |
mag |
-0.9999995e9 |
|
photZPCat |
[nspid]MultiframeDetector |
WSA NonSurvey |
Photometric zero point for default extinction for the catalogue data {catalogue extension keyword: MAGZPT} |
real |
4 |
mags |
-0.9999995e9 |
?? |
Derived detector zero-point in the sense of what magnitude object gives a total (corrected) flux of 1 count/s. These ZPs are appropriate for generating magnitudes in the natural detector+filter system based on Vega, see CASU reports for more details on colour equations etc. The ZPs have been derived from a robust average of all photometric standards observed on any particular set of frames, corrected for airmass but assuming the default extinction values listed later. For other airmass or other values of the extinction use ZP → ZP - [sec(z)-1]×extinct + extinct default - extinct You can then make use of any of the assorted flux estimators to produce magnitudes via Mag = ZP - 2.5*log10(flux/exptime) - aperCor - skyCorr Note that for the so-called total and isophotal flux options it is not possible to have a single-valued aperture correction. |
photZPCat |
[nspid]PreviousMFDZP |
WSA NonSurvey |
Photometric zeropoint for default extinction in catalogue header |
real |
4 |
mag |
-0.9999995e9 |
|
photZPErr |
[nspid]Multiframe |
WSA NonSurvey |
Photometric zeropoint error: this will be DEPRECATED soon; use MultiframeDetector.photZPErrCat {image primary HDU keyword: MAGZRR} |
real |
4 |
mag |
-0.9999995e9 |
|
photZPErrCat |
[nspid]MultiframeDetector |
WSA NonSurvey |
Photometric zero point error for the catalogue data {catalogue extension keyword: MAGZRR} [Currently set to -1 for WFCAM data.] |
real |
4 |
mags |
-0.9999995e9 |
?? |
Error in the zero point. If good photometric night this error will be at the level of a few percent. Values of 0.05 and above indicate correspondingly non-photometric night and worse. |
photZPErrCat |
[nspid]PreviousMFDZP |
WSA NonSurvey |
Photometric zeropoint error in catalogue header |
real |
4 |
mag |
-0.9999995e9 |
|
photZPErrExt |
[nspid]MultiframeDetector |
WSA NonSurvey |
Photometric zero point error of the detector {image extension keyword: MAGZRR} [Currently set to -1 for WFCAM data.] |
real |
4 |
mags |
-0.9999995e9 |
?? |
Error in the zero point. If good photometric night this error will be at the level of a few percent. Values of 0.05 and above indicate correspondingly non-photometric night and worse. |
photZPErrExt |
[nspid]PreviousMFDZP |
WSA NonSurvey |
Photometric zeropoint error in image extension {image primary HDU keyword: MAGZRR} |
real |
4 |
mag |
-0.9999995e9 |
|
photZPExt |
[nspid]MultiframeDetector |
WSA NonSurvey |
Photometric zero point for default extinction of the detector {image extension keyword: MAGZPT} |
real |
4 |
mags |
-0.9999995e9 |
?? |
Derived detector zero-point in the sense of what magnitude object gives a total (corrected) flux of 1 count/s. These ZPs are appropriate for generating magnitudes in the natural detector+filter system based on Vega, see CASU reports for more details on colour equations etc. The ZPs have been derived from a robust average of all photometric standards observed on any particular set of frames, corrected for airmass but assuming the default extinction values listed later. For other airmass or other values of the extinction use ZP → ZP - [sec(z)-1]×extinct + extinct default - extinct You can then make use of any of the assorted flux estimators to produce magnitudes via Mag = ZP - 2.5*log10(flux/exptime) - aperCor - skyCorr Note that for the so-called total and isophotal flux options it is not possible to have a single-valued aperture correction. |
photZPExt |
[nspid]PreviousMFDZP |
WSA NonSurvey |
Photometric zeropoint for default extinction in image extension |
real |
4 |
mag |
-0.9999995e9 |
|
pixelScale |
[nspid]MultiframeDetector |
WSA NonSurvey |
Warning - Original detector pixel size, the actual angular pixel size is written to xPixSize and yPixSize in the CurrentAstrometry table {image extension keyword: PIXLSIZE} |
real |
4 |
arcsec per pixel |
-0.9999995e9 |
INST_PIXSIZE |
pmDec |
[nspid]FSstars |
WSA NonSurvey |
Proper motion in Dec |
real |
4 |
arcsec per year |
0.0 |
|
pmRA |
[nspid]FSstars |
WSA NonSurvey |
Proper motion in RA |
real |
4 |
arcsec per year |
0.0 |
|
pNoise |
[nspid]Source |
WSA NonSurvey |
Probability that the source is noise |
real |
4 |
|
|
STAT_PROP |
Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag | Meaning | Probability (%) | | | Star | Galaxy | Noise | Saturated | -9 | Saturated | 0.0 | 0.0 | 5.0 | 95.0 | -3 | Probable galaxy | 25.0 | 70.0 | 5.0 | 0.0 | -2 | Probable star | 70.0 | 25.0 | 5.0 | 0.0 | -1 | Star | 90.0 | 5.0 | 5.0 | 0.0 | 0 | Noise | 5.0 | 5.0 | 90.0 | 0.0 | +1 | Galaxy | 5.0 | 90.0 | 5.0 | 0.0 | Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation. |
pointingID |
[nspid]Multiframe |
WSA NonSurvey |
Pointing ID within survey {image primary HDU keyword: SURVEY_I} |
varchar |
64 |
|
NONE |
?? |
posAngle |
[nspid]CurrentAstrometry, [nspid]PreviousAstrometry |
WSA NonSurvey |
orientation of image x-axis to N-S |
float |
8 |
Degrees |
-0.9999995e9 |
POS_POS-ANG |
ppErrBits |
[nspid]Detection |
WSA NonSurvey |
additional WFAU post-processing error bits (place holder for now) |
int |
4 |
|
-99999999 |
CODE_MISC |
ppErrBits |
[nspid]Detection |
WSA NonSurvey |
additional WFAU post-processing error bits (place holder for now) |
int |
4 |
|
0 |
CODE_MISC |
ppErrBitsStatus |
[nspid]ProgrammeFrame |
WSA NonSurvey |
Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme. |
int |
4 |
|
0 |
|
priOrSec |
[nspid]Source |
WSA NonSurvey |
Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates). |
bigint |
8 |
|
-99999999 |
CODE_MISC |
Because of the spacing of the detectors in WFCAM, and the restrictions on guide star brightness, there will always be overlap regions between adjacent frame sets. Source merging is done on a set-by-set basis; hence after source merging there are usually a small number of duplicate sources in the table. A process known as seaming takes place after source merging is complete, whereby duplicates are identified and flagged. The flagging attribute is priOrSec, and the meaning of the flag is quite simple: if a source is not found to be duplicated in overlap regions, then priOrSec=0; if a source is duplicated, then priOrSec will be set to the frameSetID of the source that should be considered the best one to use out of the set of duplicates. Presently, the choice of which is best is made on the basis of proximity to the optical axis of the camera, the assumption being that this will give the best quality image in general. So, if a particular source has a non-zero priOrSec that is set to it's own value of frameSetID, then this indicates that there is a duplicate elsewhere in the table, but this is the one that should be selected as the best (i.e. this is the primary source). On the other hand, if a source has a non-zero value of priOrSec that is set a different frameSetID than that of the source in question, then this indicates that this source should be considered as a secondary duplicate of a source who's primary is actually to be found in the frame set pointed to by that value of frameSetID. Hence, the WHERE clause for selecting out a seamless, best catalogue is of the form WHERE ... AND (priOrSec=0 OR priOrSec=frameSetID). |
productID |
[nspid]RequiredDiffImage |
WSA NonSurvey |
A unique identifier assigned to each required difference image product entry |
int |
4 |
|
|
?? |
productID |
[nspid]RequiredMosaic |
WSA NonSurvey |
A unique identifier assigned to each required mosaic product entry |
int |
4 |
|
|
?? |
productID |
[nspid]RequiredStack |
WSA NonSurvey |
A unique identifier assigned to each required stack product entry |
int |
4 |
|
|
?? |
programmeID |
[nspid]Programme |
WSA NonSurvey |
UID of the archived programme coded as above |
int |
4 |
|
|
ID_SURVEY |
programmeID |
[nspid]ProgrammeCurationHistory, [nspid]ProgrammeTable, [nspid]RequiredCurationTask, [nspid]RequiredDiffImage, [nspid]RequiredFilters, [nspid]RequiredListDrivenProduct, [nspid]RequiredMosaic, [nspid]RequiredNeighbours, [nspid]RequiredStack, [nspid]RequiredSynoptic |
WSA NonSurvey |
the unique programme ID |
int |
4 |
|
|
ID_SURVEY |
programmeID |
[nspid]ProgrammeFrame, [nspid]SurveyProgrammes |
WSA NonSurvey |
WSA assigned programme UID {image primary HDU keyword: PROJECT} |
int |
4 |
|
-99999999 |
ID_SURVEY |
project |
[nspid]Multiframe |
WSA NonSurvey |
Time-allocation code {image primary HDU keyword: PROJECT} |
varchar |
64 |
|
NONE |
REFER_CODE |
projection |
[nspid]RequiredMosaic |
WSA NonSurvey |
CASU mosaic tool option to specify output WCS projection type (TAN for gnomonic, ZPN for zenithal polynomial) |
varchar |
3 |
|
|
?? |
propPeriod |
[nspid]Programme |
WSA NonSurvey |
the proprietory period for any data taken for this programme in months, e.g. 12 for open time. |
int |
4 |
months |
|
TIME_PERIOD |
proprietary |
[nspid]Survey |
WSA NonSurvey |
Logical flag indicating whether a survey is proprietary or not (1=yes; 0=no) |
tinyint |
1 |
|
|
?? |
pSaturated |
[nspid]Source |
WSA NonSurvey |
Probability that the source is saturated |
real |
4 |
|
|
STAT_PROP |
Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag | Meaning | Probability (%) | | | Star | Galaxy | Noise | Saturated | -9 | Saturated | 0.0 | 0.0 | 5.0 | 95.0 | -3 | Probable galaxy | 25.0 | 70.0 | 5.0 | 0.0 | -2 | Probable star | 70.0 | 25.0 | 5.0 | 0.0 | -1 | Star | 90.0 | 5.0 | 5.0 | 0.0 | 0 | Noise | 5.0 | 5.0 | 90.0 | 0.0 | +1 | Galaxy | 5.0 | 90.0 | 5.0 | 0.0 | Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation. |
psfFitChi2 |
[nspid]Detection |
WSA NonSurvey |
standard normalised variance of PSF fit {catalogue TType keyword: PSF_fit_chi2} |
real |
4 |
|
-0.9999995e9 |
FIT_STDEV |
psfFitDof |
[nspid]Detection |
WSA NonSurvey |
no. of degrees of freedom of PSF fit {catalogue TType keyword: PSF_fit_dof} |
smallint |
2 |
|
-9999 |
STAT_N-DOF |
psfFitX |
[nspid]Detection |
WSA NonSurvey |
PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X} |
real |
4 |
pixels |
-0.9999995e9 |
POS_PLATE_X |
psfFitXerr |
[nspid]Detection |
WSA NonSurvey |
Error on PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X_error} |
real |
4 |
pixels |
-0.9999995e9 |
ERROR |
psfFitXerr |
[nspid]Detection |
WSA NonSurvey |
Error on PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X_err} |
real |
4 |
pixels |
-0.9999995e9 |
ERROR |
psfFitY |
[nspid]Detection |
WSA NonSurvey |
PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_Y} |
real |
4 |
pixels |
-0.9999995e9 |
POS_PLATE_Y |
psfFitYerr |
[nspid]Detection |
WSA NonSurvey |
Error on PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_y_error} |
real |
4 |
pixels |
-0.9999995e9 |
ERROR |
psfFitYerr |
[nspid]Detection |
WSA NonSurvey |
Error on PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_y_err} |
real |
4 |
pixels |
-0.9999995e9 |
ERROR |
psfFlux |
[nspid]Detection |
WSA NonSurvey |
PSF-fitted flux {catalogue TType keyword: PSF_flux} |
real |
4 |
ADU |
-0.9999995e9 |
PHOT_INTENSITY_ADU |
psfFluxErr |
[nspid]Detection |
WSA NonSurvey |
Error on PSF-fitted flux {catalogue TType keyword: PSF_flux_error} |
real |
4 |
ADU |
-0.9999995e9 |
ERROR |
psfFluxErr |
[nspid]Detection |
WSA NonSurvey |
Error on PSF-fitted flux {catalogue TType keyword: PSF_flux_err} |
real |
4 |
ADU |
-0.9999995e9 |
ERROR |
psfMag |
[nspid]Detection |
WSA NonSurvey |
PSF-fitted calibrated magnitude |
real |
4 |
mag |
-0.9999995e9 |
PHOT_PROFILE |
psfMagErr |
[nspid]Detection |
WSA NonSurvey |
Error on PSF-fitted calibrated magnitude |
real |
4 |
mag |
-0.9999995e9 |
ERROR |
pStar |
[nspid]Source |
WSA NonSurvey |
Probability that the source is a star |
real |
4 |
|
|
STAT_PROP |
Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code: Flag | Meaning | Probability (%) | | | Star | Galaxy | Noise | Saturated | -9 | Saturated | 0.0 | 0.0 | 5.0 | 95.0 | -3 | Probable galaxy | 25.0 | 70.0 | 5.0 | 0.0 | -2 | Probable star | 70.0 | 25.0 | 5.0 | 0.0 | -1 | Star | 90.0 | 5.0 | 5.0 | 0.0 | 0 | Noise | 5.0 | 5.0 | 90.0 | 0.0 | +1 | Galaxy | 5.0 | 90.0 | 5.0 | 0.0 | Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent: P(classk)=ΠiP(classk)i / ΣkΠiP(classk)i where classk is one of star|galaxy|noise|saturated, and i denotes the ith single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation. |
pv21 |
[nspid]CurrentAstrometry, [nspid]PreviousAstrometry |
WSA NonSurvey |
Coefficient for r term (use only with ZPN projection) {image extension keyword: PV2_1} transformation from pixel to celestial co-ordinates |
float |
8 |
|
-0.9999995e9 |
POS_TRANSF_PARAM |
pv22 |
[nspid]CurrentAstrometry, [nspid]PreviousAstrometry |
WSA NonSurvey |
Coefficient for r**2 term (use only with ZPN projection) {image extension keyword: PV2_2} transformation from pixel to celestial co-ordinates |
float |
8 |
|
-0.9999995e9 |
POS_TRANSF_PARAM |
pv23 |
[nspid]CurrentAstrometry, [nspid]PreviousAstrometry |
WSA NonSurvey |
Coefficient for r**3 term (use only with ZPN projection) {image extension keyword: PV2_3} transformation from pixel to celestial co-ordinates |
float |
8 |
|
-0.9999995e9 |
POS_TRANSF_PARAM |