Making Bias data

Bias data is made by removing an overscan from a 0 sec integration data (Bias raw data). Each CH of one HSC’s CCD has a 16 pixels overscan region at the left or right edge of the CH (see hscccd more detail). HSC pipeline evaluates the mean value to the short, fits spline to the longest axis of the overscan region, and subtract this value from Bias raw data. Finally bias data are produced after removing some outliers from these data. It will be done by HSC pipeline command of reduceBias.py.

# making Bias data
# home = ~
reduceBias.py $home/hsc --calib=$home/hsc/CALIB --rerun=calib_dith_16h_bias --id visit=902670..902678:2 --detrendId calibVersion=all

# Usage：
#   reduceBias.py <a directory for data reduction> --calib=<a directory for detrend data> --rerun=<rerun name> --id visit=<visit ID of Bias raw data> --detrendId calibVersion=<version for making detrend>
#
# Parameters：
#   --calib    ：A directory for detrend data
#   --rerun    ：Rerun name
#   --id       ：Specifying Bias raw data to make Bias data.
#              　In example, we specify visit IDs from 902670 to 902678 with 2 increment.
#             　（i.e. visit IDs 902670, 902672, 902674, 902676, and 902678）
#   --detrendId：Specifying version for making detrend (option).

Warning

You must use the regular expression of [A-Za-z0-9_+-], when you set parameters of –calib and calibVersion. It means that ‘.’ and ‘,’ are not available.

You can use a batch process (this batch process means the one which the job is submitted to job control system) for all commands of making detrends in HSC pipeline. The pipeline provides batch process options depending on your machine environments. Note that the options are slightly different between pipeline versions.

Warning

HSC data analysis machine for open use（hanaco）does not have job control system. So please add the option in “Running a process in local machine”.

# Running a process in local machine (ex 4 threads)
# hscPipe ver 3.x
reduceBias.py --... --do-exec --mpiexec "-n 4"

# hscPipe ver 4.x
reduceBias.py --... --batch-type=smp --cores=4

# Submitting a batch script to another machine and running the script
# (ex 2 nodes 2 processes: 4 threads in total)
# hscPipe ver 3.x
reduceBias.py --... --nodes 2 --procs 2

# hscPipe ver 4.x
reduceBias.py --... --nodes 2 --cores 2

Once you perform reduceBias.py, you can find following data in your repository. Final Bias and intermediate data is produced in ~/hsc/CALIB and ~/hsc/rerun/[rerun], respectively.

  • Bias data　　　　　　　　　　　　　　　　　　　　　　　　　　　：BIAS-[ccd].fits in $home/hsc/CALIB/BIAS/[dateObs]/[filter]/[calibVersion]/
  • A result of overscan subtraction for each [visit, ccd] Bias raw data：oss-[visit]-[ccd].png in $home/hsc/rerun/[rerun]/[pointing]/[filter]/thumbs/
  • Bias data for each [visit, CCD]　　　　　　　　　　　　　　　　　：c[ccd].fits in $home/hsc/rerun/[rerun]/postISRCCD/v[visit]-f[filter]/

We shows Bias raw data (left) and Bias data produced by reduceBias.py (right) in Figure 1. Bias data is slightly smaller than Bias raw data, since overscan and prescan regions are left unattended in Bias data. You may also confirm a line in the direction of Y-axis around the center of Bias data. It is because that count values in these pixels are much higher than the rest of pixels which have nearly 0 values.

../_images/bias_raw_2.png

Fig 1: (Left) Bias raw data, and (right) Bias data produced in reduceBias.py.


After you confirm your Bias data, you must register the data to a registry. Any following data reduction will be less successful without registering the data.

# Registering Bias data to calib-registry
genCalibRegistry.py --create --root=$home/hsc/CALIB --camera=HSC --validity=1000

# Usage：
#   genCalibRegistry.py --create --root=<a directory for detrend data> --camera=HSC --validity=<days>
#
# Parameters：
#   --create   ：A statement for creating new directory for detrend data
#   --root     ：A directory for detrend data
#   --camera   ：Instruction name. It definitely HSC
#   --validity ：Usable days of Bias data（default=12）
#              　The parameter means that this Bias data is available for the on-source data sandwiched XX days including the day of Bias observation.
#              　Since you may observe Bias and sources in very different day, you need to specify appropriate days for this parameter.
#              　In the example, we set validity=1000, because obs-date of Dark data is different more than a year from the one of Bias and Flat data.