Set of Jupyter Notebooks, along with datafiles, to get started with Scientific Computing in Astronomy
- Basic syntax, and syntax for loops, conditional statements, and opening simple files, (lists, tuples and dictionaries)
- Parse a file and make a list containing the number of moons for each planet.
- Numpy arrays, indexing, slicing.
- Parse file as above using numpy (np.where, for example).
- Beehive Cluster.
- Defining functions.
- Hubble Law, Number density of galaxies.
- Simple Plotting. Labels, colors, title, grid
- GW astronomy
- Using Astropy.io to import datafiles, astropy.table.
- Take the data from a harder to parse data file.
- Introduction to fits files.
- Scrape web for some data (try to do this for constellations)
- Make an image of the constellation using RA, Dec or Mars in retrograde (simple scatter plot)
- Curve fitting
- Scrape data from Cepheids, and plot Period-Luminosity relation
- Frequency vs time inspiral
- Using Bias and Flats.
- Reducing an image of a popular target. (And further processing)
- Subplots, and Using Object Oriented approach
- Make several HR diagrams, say, with different filters.
- Compare features, and observe that UV filters are good at filtering multiple stellar populations.
- Using astropy quantities, make a black body spectra.
- Using filters (SDSS), find the instrumental magnitude of a star in different bands.
- Have a function which returns these values, given the temperature of a star.
- Make a class for a star and a filter.
- Rewrite the previous codes to make it more adaptable to changes.
- Time Series analysis.
- Find a peak/Periodicity search.
- Coordinate Systems and Time.
- Convert coordinates. Plot an analemma of the Sun. See how it changes with latitude.
- Differential Equation solving. Scipy.integrate.solve_ivp.
- Solve differential equations for some system numerically.
