Ran out of ideas
It is only the third blog
This does not bode well
After meeting with Kim on Monday and discussing with Cassidy I have got both my Bias subtraction and flatfielding issues resolved. Running through the check data set was successful, yielding counts for science images of the Orion nebula ranging from ~ -10 – 250 or so. There are some negative values in the background sky for those frames, but arithmetically it makes sense for them to be there. I hope it is easily applicable to our data. I anticipate there will have to be some additional sorting routines, as the check set only had one band of observation to deal with. Other than that by class next week I’d like to have all eight nights of data bias subtracted and flatfielded.
I’ve just finished sorting and calibrating the data from night 2. There were some hiccups, in particular sorting by the RASTRNG in order to get the data in the same field in separate folders. This involved a simple (and elegant if I don’t say so myself) edit to a line in the file-sorting function to make it a little more flexible. I also had some issues with trimming, initially I was just trimming until pixel column 4100. I think that left some of the overscan behind so now I trim images to 4095 x 4095. I’d like to rethink and reorganize the pipeline a little so the sorting happens a little more hierarchal as oppose to the more sporadic ‘cross that bridge when we come to it approach.’ I wonder if there is a way to make another edit to the file-sort function that will throw the files not needed in the trash. Alas, computers cannot do everything for us.
In terms of the quality of the data products through the pipeline I’d say everything is making sense. One of the only things I had to go back and double check was what was going on with the TESS field. The bias subtracted counts were much larger than those from Praesepe. If I recall correctly, however, the TESS data was the last data taken of the night and I believe the sun was coming up. So the sky would be a good deal brighter. Python is compiling a histogram of count values for me that I will include below. I am also confident that the subtraction is working because of the overscan count histogram shown with the aforementioned total count histogram. The total count historgram is taking very long. The mean of one of the images is 1256.459, higher than that of the Praesepe image which are about 200.
The next step is to align and stack the images. How to do an elegant way of combining the image per image set seems to be a little challenging to me at the moment. The only way to do this I can think of is manually putting the data in directories based off of their groupings. I am pondering some code that sort them according to consecutive image numbers in the file name string. But the solution has not yet come to me.
After reading the shift_methods.py and the function documentations makes the shifting process make a little more sense to me. Each output of the functions feeds into the next one. The centroiding function allows you to look at a target, guess it’s center position and the function will return to you a more accurate one. The next function cross_image uses cross correlation to return to you the shift for each image, and then that result is fed into a function that actually shifts the images (and stacks them?). What is still somewhat a mystery to me is what image we should decide to shift towards. What is our ‘image prime.’ My first instinct is to shift to the image that looks the most resolved, but there may be more technical rhyme or reason to that choice.
As far as I know I’ve aligned my images properly. The counts make sense and they look good. The only discrepancy is the cycle 3 R band Praesepe images look oblong. Why this is I’m not sure. In general the images being stacked are fairly blurry. Otherwise the images look good. The gallery below shows the final product for Praesepe images. I have not yet stacked the TESS images for night two as there are only two images and they have irregularly high counts as described above. The science usefulness of them is not so certain to me. For next steps reduction wise I’d like to organize my script a little in so it runs top to bottom. And then I’ll let it loose on the rest of the data.
Next steps for the proposal will be a little more concrete after looking at the feedback, but after OOC meeting yesterday I have a better idea as to what the technical justification looks like and what it will contain. I think some inclusion of figures from other papers will be interesting, and discussion of how our data will change/update those figures. Probably will also discuss/make outlines of origional figures that we will produce.
Overall been a productive week.
Owen H. ASTRO-341 Research Blog 