kevin218/wfc3

WFC3 Data Reduction Pipeline for transiting exoplanets.

WFC3

This code is intended for reducing HST/WFC3 time-series data of transiting exoplanets. It is mostly undocumented and not recommended for anyone who hasn't participated in a brief tutorial.

wfc3's Issues

Resolve missing variables/imports

I just skimmed through all the files with VS Code and was able to resolve most of the missing package errors and updated the code to use relative imports. However, there are several things I cannot fix for now which are summarized below:

1. Undefined variable k on line 153 of lib/demc.py
2. I am unable to install image_registration and pyfits packages (pyfits seems not to actually be required though). I am using python 3.9.5
3. Unknown function exp on line 218 and 372 of lib/kurucz_inten.py. I assume this is just np.exp, but didn't want to make that change without discussion.
4. Tonnes of missing arguments in lib/lsq.py
5. Missing package models_c in lib/mcmc.py
6. Missing function flatfield3 in lib/models.py
7. Variables ieclipse and ieclingress commented out in lib/models.py
8. Undefined variables midpttr and midptecl on lines 1506-1507 in lib/models.py
9. Missing file w7anal.py in LC_Fitting/run_w6.py

Current w2reduce.py code only uses first direct image for centroiding

Hey Kevin, I noticed that the current code runs the centroiding algoritm on all of the direct images but then only uses the first one for the lines shown below (the first index in ev.centroid is for which direct image you're using, and the second index is for x vs y). Moving forward, would it be best to use the most recent centroid rather than just the first direct image, or even some kind of time-based interpolation? My assumption is that the norm would be to either have one direct image per visit (in which case the current code works fine unless your folder has data from many visits) or one direct image per HST orbit (in which case it seems best to use that direct image for all observations within that orbit). My plan is to do away with the manual identification of direct images vs science spectra, and I can add some code at the same time that gives a pointer to the relevant direct image for each science spectrum unless you've previously found that doing so has a detrimental impact on the reduction.

WFC3/ir_spectroscopy/w2reduce.py

Lines 281 to 284 in 01d0345

	for m in range(ev.n_files):
	for n in range(n_reads-1):
	ev.centroids[m,n] = np.array([ev.centroid[0][0]+drift2D[m,n,0],
	ev.centroid[0][1]+drift2D[m,n,1]])