'''
This exercise contains a number of simple things to try to get familiar with 
NumPy.

Hint: Functions (probably) exist for most of these. 

Use the NumPy documentation at numpy.org - try not to be too intimidated, 
it's easier than it seems.

Google is also your friend.
'''

import numpy as np

''' 
Exercise A

Define `x_ar` so that it is an array of 124 elements ranging from 2.3 to 
1776.343, evenly spaced on a logarithmic scale.

Hint: There is a function to do this.
'''

x_ar =  # Your code here


'''
Exercise B 

Reshape `x_ar` to 2-dimensional array (pick the lengths you'd like).
'''

# Your code here


'''
Exercise C  

Add 10 to every value in the array. 

Hint: you don't need any loops to do so.
'''

# Your code here

'''
Exercise D

Reshape `x_ar` to a 1-dimensional array again.
Define a new array `y_ar` as a linear space of 10 values from 23.4 to 1006.2 
and add it to the end of `x_ar`.
'''

# Your code here

'''
Exercise E 

Print every 10th value from the new combined `x_ar`. You should be able to do 
this without loops.
'''

# Your code here


'''
Exercise F

Test out this code. Try to describe what you see and understand what is going
on before running it).
'''

test_ar = np.linspace(1, 50)
mask_ar = test_ar >= 25
new_ar = test_ar[mask_ar]
print(new_ar)


''' 
Exercise G

Now find the average for every value above 100 in the combined `x_ar`.
You should be able to do this without loops.
'''

# Your code here