Oslo, July 9th, 2009

Notes about eis_prep
Alessandro Gardini
University of Oslo
http://folk.uio.no/gardini/EIS_PREP.ppt

1tirsdag 28. juli 2009

What is eis_prep?
Eis_prep is the standard tool to convert raw level-0 dataof Hinode/EIS into calibrated level-1 data.
It is written in IDL and is part of the Solarsoft package.

2
tirsdag 28. juli 2009

Level-0 data.
Level-0 data consist of EIS CCD intensities arranged
in arrays of 3D windows, called datacubes.
Datacubes coordinates are the wavelenght (λ), theCCD’s spatial Y coordinate, and the time.
Intensities are expressed in data numbers (DN).

3
tirsdag 28. juli 2009

Level-1 data.
Level-1 data consist of datacubes containing thecalibrated intensities and datacubes containing thecorresponding errors.
Both intensities and errors are given (by user’s choice) in:• erg/cm2/s/sr/Å (physical units), or• DN (data numbers), or• photon counts.
Bad pixels are marked as “missing” by setting theirerror value to -100.
4
tirsdag 28. juli 2009Calling eis_prep on a level-0 file.
IDL> eis_prep, filename,/savewhere filename is the name of the file:• eis_l0_YYYYMMDD_HHMMSS.fits
The /save keyword tells eis_prep to create• eis_l1_YYYYMMDD_HHMMSS.fits• eis_er_YYYYMMDD_HHMMSS.fits
5tirsdag 28. juli 2009Calling eis_prep on an eis_data object.
IDL> data=obj_new(‘eis_data’, filename)
IDL> eis_prep, data
Calibrated intensities remain stored in the computer
memory in the same input object, while errors are
stored in an eis_cal object pointed by it.
Level-1 data can be then saved in a file through theeis_data “save” method.

6
tirsdag 28. juli 2009

What does eis_prep do?
1. Flagging saturated data.
2. Subtracting dark current (/retain).
3. Cosmic ray removal (/nocr).
4. Flagging hot and warm pixels (/nohp, /nowp).
5. Flagging pixels affected by dust (/nodp).
6. Radiometric calibration (/noabs,/photons).
This sequence of steps is performed rigidly. To change
the steps’ order, execute eis_prep with the proper
keywords on the same eis_data object twice or more.
7
tirsdag 28. juli 2009

Step 1: Flagging saturated data.
As EIS CCDs have a 14 bit dynamic range,
saturation occurs at 16,383 DN.
All these pixels are marked as missing.

8tirsdag 28. juli 2009

Step 2: Dark current subtraction.
Dark current is usually modeled as a polynomial,and coefficients are stored in specific calibration files.
A particular file can be selected by the dc_file keyword,or the default file can be selected by /default.
Otherwise, a window pops up asking to select one.
If no file is available the following procedures apply.

9tirsdag 28. juli 2009

Step 2: Dark current subtraction (2).
In the raw data, intensities are found to sit on abackground of about 500 DN (from bias and DC).
For each 3D data window, 2% of the detector pixels
are isolated that have the lowest DN values.
Their median value is assumed as the background leveland subtracted from the DN value of each pixel.

10tirsdag 28. juli 2009

Step 2: Dark current subtraction (3).
Alternatively, for full CCD spectra, regions are identified
where no lines are present.
Their median value is assumed as the background leveland subtracted from the DN value of each pixel.
Some pixels end up with negative values: they are set to 0
and marked as missing, unless the /retain keyword is set.
In this case, they maintain their own negative value,
and the corresponding error is set to the DC error estimate.
11
tirsdag 28. juli 2009

Step 3: Cosmic rays removal.
It is performed by eis_despike which wraps new_spike,originally written for SOHO/CDS.
The nearest-neighbor removal option is switched off.
Removed pixels are marked as missing and their values
replaced by the mean value of the valid pixels in the
5x5 square (in λ and Y) surrounding them.

12tirsdag 28. juli 2009

Step 4: Flagging hot and warm pixels.
Hot and warm pixels have anomalously high DN values:
either above and below 25,000 electrons/pixel/s at room
temperature.
Separate maps of hot and warm pixel are generated
every 2-4 weeks by the EIS team, following inspectionof 100s dark exposures.
The maps closest in time to observations are used by
eis_prep to mark hot and warm pixels as missing.
Their values are filled recursively by median values ofvalid neighbors (now, along Y only).
13
tirsdag 28. juli 2009

Step 5: Flagging dusty pixels.
Several small pieces of dust are found to completely
block the CCD signal at their location.
They are fixed in position an occupy less than 0.1%of the CCDs, but affect some strong lines.
Dusty pixels are marked as missing but not refilled.

14
tirsdag 28. juli 2009

Step 6: Radiometric calibration.
Finally, DN values are converted to intensities inphysical units: erg/cm2/s/sr/Å.
Errors are computed assuming photon statistics together
with an error estimate for the DC: 2.24 to 2.37 DN.
The /noabs keyword allows to retain DN data.
The /photon keyword allows to get photon counts.

15
tirsdag 28. juli 2009

Additional keywords.
The /refill keyword allows eis_prep to refill all thepixels marked as missing according to the prescriptions
recommended in the Warm Pixel Study, to better
preserve scientific information.
The /quiet keyword sets eis_prep to run without popping
up information widgets.

16
tirsdag 28. juli 2009

Additional information.
Additional information can be found in•••

the header of the eis_prep routine
EISWiki
http://folk.uio.no/gardini/Eis_prep.doc

17
tirsdag 28. juli 2009