Day 1-2 (07/11-12)
- Day 1: Reviewed papers Chris sent, met with Chris and Eske on Zoom to discuss expectations, project outline on wiki page
- Day 2: Set up FASRC account. Followed the "User Quick Start Guide" on FASRC page
- set up 2FA, FASRC VPN, terminal access, and watched a few data transfer videos
- Used rsync to load Eske's target directory /n/holystore01/LABS/stubbs_lab/Lab/Auxtel_data/spectrum_data onto computer
- Went into lab and met Eske, Ali, and Mark in person. Very cool people.
- Opened Jupyter notebook; looked up astropy documentation to open fits files
- Successfully opened fits file to view contents inside, retrieved and displayed table data, displayed file header information, and plotted data
Day 3 (07/13)
- In Jupyter notebook, filtered all the fits files in '/spectrum_data' to print out star name and date/time of observation
- Stored names of files in record type that are all associated with one star; looks like there are 4 observed stars in the dataset Eske gave me.
Day 4 (07/14)
- Found data files missing the table of equivalent widths that Eske gave me
spec_data_2022062800336.fits HD205905 2022-06-29
- Plotted H2O and O2 equivalent widths against air masses for each star on each night (four stars on four nights based on data Eske gave me)
- Noticed that some files do not have O2 data (may have variants like O2(Z) or O2(B), though)
First Impressions of Data:
- The equivalent widths of H20 seem to have much more variability than those of O2
- May be some outliers in the data (particularly for the first two plots with the negative equivalent widths, may need to check on those data points
Findings
Links to Notebook:
Github repo of project code: https://github.com/ariscjj/stubbs
In notebook: https://github.com/ariscjj/stubbs/blob/master/Extract_H20.ipynb (added Chris as a collaborator on the github)
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- Noted that I only have 187 files, I think Eske mentioned I should have access to a number of files in the 700 range. Will need to check with him on that.
- Exported the data table as "faulty_files.csv" file that can be found herebelow. I might not pursue any further the conversion of pandas data frame to image.
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