Day 1 Tasks

bash
export PATH=/usr/local/Anaconda/bin:$PATH
source activate base
ipython

• The Python tutorial is a very useful general resource if you need a reference later regarding how to perform tasks in Python. To get started, let's work through the following examples:
  • Section 3.1.1. Numbers (but ignore the part about complex numbers)
  • Section 3.1.2. Strings
    
    
    • In addition to 3.1.2, you can convert a string to a floating-point number, or to an integer as illustrated here:

      >>> a = '1234'
      >>> b = int(a)
      >>> print a+a
      >>> print b+b
      
      >>> a = '1234.5678'
      >>> b = float(a)
      >>> print a+a
      >>> print b+b
      

      Try these examples and think about why you obtain different answers for a+a and b+b in each case (ask Adam if you are unsure).
      
      
    • You can also turn integers or floats back into strings, as follows:

      >>> a = 1234
      >>> b = str(a)
      >>> print a+a
      >>> print b+b
      

  • Section 3.1.4. Lists
  • Section 3.2. First Steps Towards Programming
  • Section 4.1. if Statements
    
    
    • In addition to 4.1, look at an online tutorial on conditional statements to see more information on what Boolean logic statements are available (if you aren't used to such statements). Try replacing the

      >>> if x < 0

      statement from the Section 4.1 tutorial with some of the other logic statements.
    
    
  • Section 4.2. for Statements
  • Section 4.3. The range() function
  • Section 4.6. Defining Functions

Day 2 Tasks

bash
export PATH=/usr/local/Anaconda/bin:$PATH
source activate base
ipython

• Two of the most common operations in astronomy are to plot quantities and to read in files in FITS format.
  • To read in a file that is called "filename" and that is in FITS format, issue the following commands at the Python prompt:

    from astropy.table import Table
    data = Table.read(filename)
    

    Note that you can also easily read in text files using numpy.loadtxt.
    
    
  • To see how to make plots in Python, try the matplotlib.pyplot tutorial at http://matplotlib.org/users/pyplot_tutorial.html (at least as far as "Controlling line properties")
    
    
  • Now, download the FITS file at http://faraday.uwyo.edu/~admyers/REU/Python/tractor-0300m160.fits and read it in.
  • Plot Right Ascension against Declination for the objects in this FITS file. You can obtain RA and Dec as follows:

    data = Table.read(filename)
    RA = data["ra"]
    Dec = data["dec"] 
    

• Now that we know a little Python, let's write a program to work through several loops in order to solve the following problem:

  A room contains 100 light switches that turn 100 lights on or off. 
  Switch 1 controls light 1. Switch 2 controls light 2 etc. 
  The switches are currently set to the "off" position. 
  Outside of the room are 100 people who enter one-by-one:
  
  Person 1 flips switches 1,2,3,4...100
  Person 2 flips switches 2,4,6,8...100
  Person 3 flips switches 3,6,9,12...99
  Person 4 flips switches 4,8,12,16...100
  .etc.
  .etc.
  Person 100 flips switch 100
  
  Use Matplotlib to plot the state of the light switches (i.e. 1 to 100 on the x-axis and either 1 for "on" or 
  0 for "off" on the y-axis) after Person 10, Person 25 and Person 50 have left the room.
  
  After all of the people have entered the room and flipped their assigned switches, which lights are ON?
  

• Once we've discussed the answer to this problem, if there's time, let's attempt it again using an array-based approach in Python. Adam will discuss how to set the problem up using numpy and, in particular, we'll walk through the following commands and points:
  • Using import numpy to use numpy modules
  • Setting up the problem with 0-100 switches, because of Python's zero-indexing choice
  • numpy.zeros to represent the 0-100 switches, e.g., switches = numpy.zeros(101)
  • numpy.arange to produce a list of the integers 0-100, e.g., a = numpy.arange(101)
  • What does the % operation do? How has the array-based approach simplified things?
  • numpy.where to test which indices are True for certain operations , e.g., w = numpy.where(a%1 == 0)
  
  

Department of Physics & Astronomy,  University of Wyoming,  1000 E. University, Dept. 3905,  Laramie, WY 82071, USA

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