Vis Analysis Results Product¶

Metadata¶

Data product name	DpdVisAnalysisResults
Data product custodian	VIS
Name of the Schema file	euc-vis-AnalysisResults.xsd
Processing Element(s) creating/using the data product	VIS_science_xml_out
Processing function using the data product	VIS

Proposed for inclusion in EAS/SAS¶

Yes

Data product elements¶

Header	object of type sys:genericHeader
Data	object of type vis:visAnalysisResults
QualityFlags	object of type dqc:sqfPlaceHolder
Parameters	object of type ppr:genericKeyValueParameters

Detailed description of the data product¶

The DpdVisAnalysisResults is a general product that can be filled by different pipelines. It is designed to store data quality control during the production of product.

VISProcessField DQC description¶

The analysis results is a .json file combining all the data quality control created during the processing of the calibrated(Quad)Frame exposure. This is very useful for determining which data is really usable for science and which not.

Name of file:

EUC_VIS_QC_PERI-[ObsId]-[Dither]-[exposure]-0000000__[YYYYMMDDThhmmss.s]Z.json

where the date is the production date.

Cosmic Rays¶

To check if the data is contaminated by X-rays, we compute the ratio of cosmic rays detection by LA Cosmicx.

For the moment, we have determined that data with a number of cosmic rays above 5.0% for a nominal exposition is data that cannot be used. To normalise to the exposure time, we also need to add the readout time (70 s) to take into account the fact that cosmics rays can also arrive during this time. In fact, this type of data can be used with caution due to the fact that the X-rays only affect some quadrants and not all the FPA. Above this threshold, a lot of cosmic rays can be missed by LA Cosmicx.

In PF-13 this DQC was saved in ratio. In PF-14 and above it was saved in percent.

We save the ratio of pixel with the flag COSMIC per detector in quadrant.cosmic_pixel_percent.

We calculate the maximum and the mean of this ratio per detector and store it in these 2 indicators :

FPA.max_cosmic_percent: This corresponds to the values quadrant.cosmic_pixel_percent of the quadrant with the maximum percentage of pixels with the COSMIC flag in the FPA. If this indicator is high it may indicate an X-Rays pattern.

FPA.cosmic_pixel_percent: This corresponds to the mean percentage of pixels with the COSMIC flag in the FPA. This may indicate a proton shower or a realy high event on one or a few quadrant.

We also used the flags CR_REGION (added in PF 14.0) to indicate if the quadrant is above a threshold defined in the config file of the VIS-PF. In PF-14 the thredsold was 3.0%. It was increased up to 5.0% in PF-15. The number of quadrants masked by CR_REGION is stored in FPA.cr_regions_count.

RA/DEC residuals¶

The requirement R-VIS-CAL-F-010 is defined as ‘astrometric residual \(< 3\) mas’.

The mean residual for each exposure is saved in vis_res_mean.

The RA/DEC mean and std is stored individualy in:

ra_res_final_mean ; ra_res_final_sdr ; dec_res_final_mean ; dec_res_final_sdr.

Spread model¶

FPA.spreadmodel_peak: It is the peak of the spread model corresponding to the star in the flux_auto vs spread_model for \(1.5 <\) log10( FLUX_AUTO/FLUXERR_AUTO) \(< 2.5\). It is a good indicator of the quality of the guidance. We have estimated that spread model peak above 0.002 corresponds to data with guiding errors.

The FPA.spreadmodel_sigma is standard deviation of the gaussian fit of the histogram of SExtractor spread model values.

Moment¶

This DQC was added in PF-14.

During the data processing we calculate the median and the standard deviation of e1, e2, r2 of the stars based on Konrad Kuijken methode. PF-14.0.4 add the calculation of t1, t2, c1, c2.

All this DQC are saved in the format FPA.moment_{r2/e1/e2/t1/t2/c1/c2}_{med/std}

From this measure, we can derive a score with :

\[\begin{split}& \frac{(e2_{med}-e2m)^2}{vare2} + (r2_{med}-r2m)^2*covinv[0,0]+ \\ & 2*(r2_{med}-r2m)*(e1_{med}-e1m)*covinv[1,0]+(e1_{med}-e1m)^2*covinv[1,1]\end{split}\]

Where:

r2m=1.9233812949640285
e1m=-0.023129496402877696
e2m=0.002733812949640288
cov00=0.0005422666041080192
cov01=-0.00011841403399019925
cov11=4.4881659889479756e-05
vare2=5.332022152062523e-06
covinv=np.linalg.inv([[cov00,cov01],[cov01,cov11]])

calculated from a reference field.

By statistical analysis, we defined that a score higher than 60 is bad.

Zero point¶

For quality control we calculate a zero point by comparing with Gaia.

FPA.zero_point: VIS zero point calculated by comparison with Gaia data.

FPA.zp_rms: Standard deviation of the VIS zero point.

A zero point for each quadrant is also available in {quadrant}.zp_mean and {quadrant}.zp_rms.