Analyzing Supernova Data
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Import a library into a program using import libraryname .
Use the numpy library to work with arrays in Python.
Use variable = value to assign a value to a variable in order to record it in memory.
Variables are created on demand whenever a value is assigned to them.
Use print(something) to display the value of something .
The expression array.shape gives the shape of an array.
Use array[x, y] to select a single element from a 2D array.
Array indices start at 0, not 1.
Use low:high to specify a slice that includes the indices from low to high-1 .
All the indexing and slicing that works on arrays also works on strings.
Use # some kind of explanation to add comments to programs.
Use numpy.mean(array) , numpy.max(array) , and numpy.min(array) to calculate simple statistics.
Use numpy.mean(array, axis=0) or numpy.mean(array, axis=1) to calculate statistics across the specified axis.
Use the pyplot library from matplotlib for creating simple visualizations.
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Visualizing Data
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Repeating Actions with Loops
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Use for variable in sequence to process the elements of a sequence one at a time.
The body of a for loop must be indented.
Use len(thing) to determine the length of something that contains other values.
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Storing Multiple Values in Lists
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[value1, value2, value3, ...] creates a list.
Lists can contain any Python object, including lists (i.e., list of lists).
Lists are indexed and sliced with square brackets (e.g., list[0] and list[2:9]), in the same way as strings and arrays.
Lists are mutable (i.e., their values can be changed in place).
Strings are immutable (i.e., the characters in them cannot be changed).
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Analyzing Data from Multiple Files
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Use glob.glob(pattern) to create a list of files whose names match a pattern.
Use * in a pattern to match zero or more characters, and ? to match any single character.
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Making Choices
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Use if condition to start a conditional statement, elif condition to provide additional tests, and else to provide a default.
The bodies of the branches of conditional statements must be indented.
Use == to test for equality.
X and Y is only true if both X and Y are true.
X or Y is true if either X or Y , or both, are true.
Zero, the empty string, and the empty list are considered false; all other numbers, strings, and lists are considered true.
True and False represent truth values.
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Creating Functions
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Define a function using def function_name(parameter) .
The body of a function must be indented.
Call a function using function_name(value) .
Numbers are stored as integers or floating-point numbers.
Variables defined within a function can only be seen and used within the body of the function.
If a variable is not defined within the function it is used, Python looks for a definition before the function call
Use help(thing) to view help for something.
Put docstrings in functions to provide help for that function.
Specify default values for parameters when defining a function using name=value in the parameter list.
Parameters can be passed by matching based on name, by position, or by omitting them (in which case the default value is used).
Put code whose parameters change frequently in a function, then call it with different parameter values to customize its behavior.
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Errors and Exceptions
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Tracebacks can look intimidating, but they give us a lot of useful information about what went wrong in our program, including where the error occurred and what type of error it was.
An error having to do with the ‘grammar’ or syntax of the program is called a SyntaxError . If the issue has to do with how the code is indented, then it will be called an IndentationError .
A NameError will occur if you use a variable that has not been defined, either because you meant to use quotes around a string, you forgot to define the variable, or you just made a typo.
Containers like lists and strings will generate errors if you try to access items in them that do not exist. This type of error is called an IndexError .
Trying to read a file that does not exist will give you an FileNotFoundError . Trying to read a file that is open for writing, or writing to a file that is open for reading, will give you an IOError .
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Command-Line Programs
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The sys library connects a Python program to the system it is running on.
The list sys.argv contains the command-line arguments that a program was run with.
Avoid silent failures.
The pseudo-file sys.stdin connects to a program’s standard input.
The pseudo-file sys.stdout connects to a program’s standard output.
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Command-Line Programs
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The sys library connects a Python program to the system it is running on.
The list sys.argv contains the command-line arguments that a program was run with.
Avoid silent failures.
The pseudo-file sys.stdin connects to a program’s standard input.
The pseudo-file sys.stdout connects to a program’s standard output.
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Defensive Programming
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Program defensively, i.e., assume that errors are going to arise, and write code to detect them when they do.
Put assertions in programs to check their state as they run, and to help readers understand how those programs are supposed to work.
Use preconditions to check that the inputs to a function are safe to use.
Use postconditions to check that the output from a function is safe to use.
Write tests before writing code in order to help determine exactly what that code is supposed to do.
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Automating Tests for Your Code
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Pytest is a library that automates testing.
Pytest will run any function that starts with test.
Tests can be in the same file as your code, but they are better in a separate file.
Break your tests into small bits that only focus on one thing.
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Debugging
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Know what code is supposed to do before trying to debug it.
Make it fail every time.
Make it fail fast.
Change one thing at a time, and for a reason.
Keep track of what you’ve done.
Be humble.
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Astropy and Jupyter Notebooks
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To start up Jupyter Notebooks type jupyter notebook in your terminal.
Know how to execute cells and navigate around the notebook.
Understand the pitfalls of the non-linear execution of notebooks.
Astropy has several basic sub-modules.
A fits file can be read with astropy.io.fits.
An image is just a numpy array that can be plotted with matplotlib.pyplot.imshow().
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