import numpy as np

# We create a 5 x 5 ndarray that contains integers from 0 to 24
X = np.arange(25).reshape(5, 5)

# We print X
print()
print('Original X = \n', X)
print()

# We use Boolean indexing to select elements in X:
print('The elements in X that are greater than 10:', X[X > 10])
print('The elements in X that less than or equal to 7:', X[X <= 7])
print('The elements in X that are between 10 and 17:', X[(X > 10) & (X < 17)])

# We use Boolean indexing to assign the elements that are between 10 and 17 the value of -1
X[(X > 10) & (X < 17)] = -1

# We print X
print()
print('X = \n', X)
print()

## Set Operations

# We create a rank 1 ndarray
x = np.array([1,2,3,4,5])

# We create a rank 1 ndarray
y = np.array([6,7,2,8,4])

# We print x
print()
print('x = ', x)

# We print y
print()
print('y = ', y)

# We use set operations to compare x and y:
print()
print('The elements that are both in x and y:', np.intersect1d(x,y))
print('The elements that are in x that are not in y:', np.setdiff1d(x,y))
print('All the elements of x and y:',np.union1d(x,y))

## Sorting

# We create an unsorted rank 1 ndarray
x = np.random.randint(1,11,size=(10,))

# We print x
print()
print('Original x = ', x)

# We sort x and print the sorted array using sort as a function.
print()
print('Sorted x (out of place):', np.sort(x))

# When we sort out of place the original array remains intact. To see this we print x again
print()
print('x after sorting:', x)

# We sort x but only keep the unique elements in x
print(np.sort(np.unique(x)))

## Sorting in place

# We create an unsorted rank 1 ndarray
x = np.random.randint(1,11,size=(10,))

# We print x
print()
print('Original x = ', x)

# We sort x and print the sorted array using sort as a method.
x.sort()

# When we sort in place the original array is changed to the sorted array. To see this we print x again
print()
print('x after sorting:', x)

# When sorting rank 2 ndarrays, we need to specify to the np.sort() function whether we are sorting by rows or columns. 
# This is done by using the axis keyword.

# We create an unsorted rank 2 ndarray
X = np.random.randint(1,11,size=(5,5))

# We print X
print()
print('Original X = \n', X)
print()

# We sort the columns of X and print the sorted array
print()
print('X with sorted columns :\n', np.sort(X, axis = 0))

# We sort the rows of X and print the sorted array
print()
print('X with sorted rows :\n', np.sort(X, axis = 1))

## Quiz question
X = np.arange(1, 26).reshape(5, 5)
print(X)
print(X[X%2 == 1])
