This repo contains course materials for the Fall 2017 ASTR 337 (“Observational Techniques“) course at Amherst College. Please contact Kate Follette at [email protected] or Kim Ward-Duong ([email protected]) with any questions.
These materials may be reproduced for educational purposes only.
Contents of the Labs are as follows (also in labcontents.txt in Lab folder):
- Jupyter introduction
- Reading in tabular data with pandas
- Working with pandas series
- Making scatterplots
- Discussion of the HR diagram
- Working with data from VizieR
- Python functions and pandas dataframes
- More on scatterplots
- Discussion of color-magnitude diagrams
- Using iObserve
- Working with the Simbad database
- Writing an observing proposal
- Reading in .fits with the astropy package
- Displaying images with imshow
- Working with images in DS9
- Sorting data based on header information
- Creating N-dimensional image arrays
- Arithmetic operations on arrays
- Bias frames, darks, and flatfielding
(to be added)
- Using imexam in pyraf to analyze images
- Padding numpy arrays
- Shifting numpy arrays
- Interactive photometry exercise