Python-and-NumPy-II.md

Introduction to Python and NumPy, part II

Sources

This tutorial is based on a combination of a MATLAB tutorial from Prof. Todd Ehlers (Uni Tübingen) and the Software Carpentry group's lessons on Programming with Python.

Getting started

1. Since Anaconda may be installing in the background, you should open a second Terminal window by clicking on the Dash Home icon at the top left corner of the screen, typing terminal into the search box, and clicking on the Terminal icon. Alternatively, you can right click on the existing Terminal icon and select New Terminal.

2. We can start by making a folder to store files for this week's exercises.

   $ cd Desktop
   $ mkdir Lab-2
   $ cd Lab-2

Reminder: the $ symbol above represents the command prompt in the Terminal window. 3. Now you can open a new IPython window.

```bash
ipython
```

Now we are ready to start.

for loops

Loops allow parts of code to be repeated over some number of times.

1. Let's consider an example. Suppose we want to take a word and print out each letter of the word separately. We could do the following:

   >>> word = 'rock'
   >>> print(word[0])
   r
   >>> print(word[1])
   o
   >>> print(word[2])
   c
   >>> print(word[3])
   k

But this is a bad idea. Why? Well there are two reasons. First, it does not scale nicely for long strings, and will take forever to type in. Second, it won't work if the word is not 4 characters long.

```python
>>> word = 'ore'
>>> print(word[0])
o
>>> print(word[1])
r
>>> print(word[2])
e
>>> print(word[3])
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-14-e3303df6f566> in <module>()
----> 1 print(word[3])

IndexError: string index out of range
```

2. We could do a much better job by using a for loop.

   >>> word = 'rock'
   >>>
for char in word:
   ...    print(char)
   ...
   r
   o
   c
   k

Note here that the ... is displayed in the IPython window when entering code in a loop and you do not need to type in the .... Not only is this shorter, but it is also more flexible. Try out a different word such as granite. Still works, right? 3. for loops in Python have the general form below.

```python
for variable in collection:
    do things with variable
```

The variable can be any name you like, and the statement of the for loop must end with a :. The code that should be executed as part of the loop must be indented beneath the for loop, and the typical indentation is 4 spaces. There is not additional special word needed to end the loop, just change the indentation back to normal. 4. Let's consider another example.

```python
>>> length = 0
>>> for letter in 'earthquake':
...    length = length + 1
...
>>> print('There are', length, 'letters')
There are 10 letters
```

Can you follow what happens in this loop? 5. Note that the variable used in the loop, letter in the case above is just a normal variable and still exists after the loop has completed with the final value given to letter.

```python
>>> letter = 'x'
>>> for letter in 'fault':
...     print(letter)
...
f
a
u
l
t
>>> print('After the loop, letter is', letter)
```

6. A loop can be used to iterate over any list of values in Python. So far we have considered only character strings, but we could also write a loop that performs a calculation a specified number of times.

   >>> for number in range(5):
   ...     print(number)
   ...
   0
   1
   2
   3
   4

What happens here? Well, in this case, we use a special function called range() to give us a list of 5 numbers [0, 1, 2, 3, 4] and then print each number in the list to the screen. When given a integer (whole number) as an argument, range() will produce a list of numbers with a length equal to the specified number. The list starts at zero and ends with number-1. You can learn a bit more about range by typing

```python
>>> help(range)
```

7. Often when you use for loops, you are looping over the values in an array and either calculating a new value or modifying the existing values. Let's consider an example.

   >>> import numpy as np
   >>> myarray = np.zeros(10)
   >>> print(myarray)
   [ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.]
   >>> for i in range(10):
   ...     myarray[i] = myarray[i] + i
   ...
   >>> print(myarray)
   [ 0.  1.  2.  3.  4.  5.  6.  7.  8.  9.]

So, what happened? We first create and array of length 10 and fill it with zeros using np.zeros(). Then, we loop over 10 values using the range() function and add each value to the existing location in myarray. What would happen if we ran this for loop a second time?

Conditional statements

Conditional statements can change the code behaviour based on meeting certain conditions.

1. Let's take a simple example.

   >>> num = 37
   >>> if num > 100:
   ...     print('greater')
   ... else:
   ...     print('not greater')
   ...
   not greater

What did we do here? First, we used the if and else statements to determine what parts of the code to execute. Note that both lines containing if or else end with a : and the text beneath is indented. What do these tests do? The if test checks to see whether the variable value for num is greater than 100. If so, 'greater' would be written to the screen. Since 37 is smaller than 100, the code beneath the else is executed. The else statement code will run whenever the if test is false.

2. The combination of if and else is very common, but both are not strictly required.

   >>> num = 53
   >>> if num > 100:
   ...     print('53 is greater than 100')
   ...
   >>>

Note that here we use only the if statement, and because 53 is not greater than 100, nothing is printed to the screen.

3. We can also have a second test for an if statment by using the elif (else-if) statement.

   >>> num = -3
   >>> if num > 0:
   ...     print(num, 'is positive')
   ... elif num == 0:
   ...     print(num, 'is zero')
   ... else:
   ...     print(num, 'is negative')
   ...
   -3 is negative

Makes sense, right? Note here that we use the == to test if a value is equal to another. The complete list of these comparison operators is given in the table below.

| Operator | Meaning                  |
| -------- | ------------------------ |
| `<`      | Less than                |
| `<=`     | Less than or equal to    |
| `==`     | Equal to                 |
| `>=`     | Greater than or equal to |
| `>`      | Greater than             |
| `!=`     | Not equal to             |

4. We can also use and and or to have multiple conditions.

   >>> if (1 > 0) and (-1 > 0):
   ...     print('Both parts are true')
   ... else:
   ...     print('One part is not true')
   ...
   One part is not true
   >>> if (1 < 0) or (-1 < 0):
   ...     print('At least one test is true')
   ...
   At least one test is true

This can be quite handy.

Laboratory Exercise 2

For Laboratory Exercise 2 we will be using Classroom for Github, which will create a private repository containing the exercise and starter code in your personal Github space. When you are ready to do this, you can create the repository for Laboratory Exercise 2.