tdr 0.0.1

TriCCS Data Reduction

TriCCS Data Reduction (TDR)

developer mail

Overview

Data reduction of data taken with Seimei/TriCCS could be done in this repository.
Though optimized for Seimei/TriCCS, you can apply it for imaging data taken with other high-speed cameras (Tomo-e Gozen etc.).

Procedures

1. Calibration (dark subtraction, flat-field correction)

2. Stacking fits by mean, median, etc.

3. Splitting fits (only for photometry using Moving Object Photometry (movphot) (bitbucket) )

4. Common ID search

Installing

# Install from PyPI
pip install tdr

or

# Install with `setup.py`
git clone https://[e-mail]/jin_beniyama/triccs-data-reduction.git
python setup.py install

Usage

Here g-band data taken with Seimei/TriCCS is considered. All band data could be analyzed in the same way.

Fits data taken with TriCCS have a format like TRCS00005180.fits.

First 4 characters TRCS means the instrument TriCCS, the next 7 characters are the exposure ID

and the last 1 character is band identical number (0 for g-band, 1 for r-band and 2 for i/z-band).

After each reduction stage, a prefix is added to the filename. History can be checked in fits header as well.

1. Calibration

Here, consider the situation: exposure time for an object frame is 10 s, for a flat frame is 1 s, and for dark frames are 1s and 10s (all in g-band) like below.

1. object TRCS00000010.fits (10 s)
2. dark for flat TRCS00000020.fits (1s)
3. dark for object TRCS00000030.fits (10s)
4. flat TRCS00000040.fits (1s)

Dark subtraction and flat-field correction are done as follows.

First, create master dark frame, which has prefix d like dTRCS00000020.fits.

The maximum count frame is not used for stacking, which leads to avoiding cosmic rays or fast-moving object contamination.

[usage]
# Create master dark
makedark (3-d dark)

[example]
# Create master dark for flat
makedark TRCS00000020.fits
# Create master dark for object
makedark TRCS00000030.fits

Next, create a master normalized flat frame using master dark for a flat frame. , which has prefix f like fTRCS00000040.fits.

The maximum count frame is not used for stacking as well.

[usage]
# Create master flat
makeflat --flat (3-d flat) --dark (2-d master dark)

[example]
# Create master flat
makeflat --flat TRCS00000040.fits --dark dTRCS00000020.fits

Finally, reduce an object frame using both master dark and flat frames.

The reduced object frame has prefix r like rTRCS00000010.fits.

[usage]
# Do dark subtraction and flat-field correction
reduce --obj (3-d object) --dark (2-d master dark) --flat (2-d master flat)

[example]
# Do dark subtraction and flat-field correction
reduce --obj TRCS00000010.fits --dark dTRCS00000020.fits --flat fTRCS00000040.fits

2. Stacking

Output fits have format like maxrTRCS00000010.fits (max), minrTRCS00000010.fits (min), meanrTRCS00000010.fits (mean) and medianrTRCS00000010.fits (median).

[usage]
# Maximum stacking
stackfits (3-d reduced fits) max
# Minimum stacking
stackfits (3-d reduced fits) min
# Mean stacking
stackfits (3-d reduced fits) mean
# Median stacking
stackfits (3-d reduced fits) median

[example]
# Maximum stacking
stackfits rTRCS00000010.fits  max
# Minimum stacking
stackfits rTRCS00000010.fits  min
# Mean stacking
stackfits rTRCS00000010.fits  mean
# Median stacking
stackfits rTRCS00000010.fits  median

3. Splitting [in preparation]

If you are going to use Moving Object Photometry (movphot)(bitbucket) for photometry, 3-d fits cube should be split into multiple 2-d fits.

[usage]
# Mask pixels and split fits into multiple 2-d fits
mask_split (3-d fits)

[example]
# Mask pixels and split fits to multiple 2-d fits
mask_split rTRCS00000010.fits

Output fits are as follows (when the number of frames is 3). The masked and splitted frames hav suffix ms like rTRCS00000010ms0001.fits.

4. Common ID search

If the wcs pasting failed for some fits, it is necessary to extract common ID fits.

[example]
# Extract common fits ID from g,r,i bands list (glist.txt, rlist.txt, ilist.txt)
cat glist.txt | awk '{print substr($0,17,3)}' > gID.txt
cat rlist.txt | awk '{print substr($0,17,3)}' > rID.txt
cat ilist.txt | awk '{print substr($0,17,3)}' > iID.txt
# Create common ID list 
commonIDsearch gID.txt rID.txt iID.txt --pre rTRCS00001260ce0 
--post w.fits > glist_common.txt

Dependencies

This library is depending on NumPy. Scripts are developed on Python 3.7.10 and NumPy 1.19.2.

LICENCE

This software is released under the MIT License.