import numpy as np
np.random.seed(0)

# Creating a one dimensional array.
one = np.random.randint(10, size = 6)
print(one)

# Creating a two dimensional array.
two = np.random.randint(10, size = (2, 5))
print(two)

# Creating a three dimensional array.
three = np.random.randint(10, size = (3, 4, 5))
print(three)

# Using the attributes to determine the dimension of the arrays.
print("one ==>", one.ndim )
print("two ==>", two.ndim )
print("three ==>", three.ndim )

print("one ==>", one.shape)
print("two ==>", two.shape)
print("three ==>", three.shape)

# Using the attribute to determine the size of the arrays.
print("one ==>", one.size)
print("two ==>", two.size)
print("three ==>", three.size)

# Using the attribute to determine the datatype of the arrays.
print("one ==>", one.dtype)
print("two ==>", two.dtype)
print("three ==>", three.dtype)

# Using the attribute to determine the item size of the arrays.
print("one ==>", one.itemsize)
print("two ==>", two.itemsize)
print("three ==>", three.itemsize)

print("one ==>", one.nbytes)
print("two ==>", two.nbytes)
print("three ==>", three.nbytes)

# Array Indexing: Accessing Single Elements
oneValue = one[2]
print(oneValue)

# Accessing the elements in a multi dimensional array
print(two)
twoValue = two[0, 4]
print(twoValue)

# Changing the values of the array
print(one)
one[3] = 6
print(one)
one[4] = 4.56 # It will be silently truncated
print(one)

# Array Slicing: Accessing Subarrays
# The syntax of the slicing is ==> x[start:stop:step] ==> default value is:
# [0: size of the dimension: 1]

a = np.random.randint(10, size = (10))
print(a)
print("------------------------")

print(a[4: 9: 2])
print("------------------------")

print(a[1::2])
print("------------------------")

print(a[::2])
print("------------------------")

print(a[:9:])
print("------------------------")

# This is the best example for reversing an array
print(a[::-1])
print("------------------------")

# I tries on strings and it worked !!!
a = "University of Regina is awesome !!!"
print(a)
print("------------------------")

print(a[::-1])

print(two)
print("------------------------")

twoValue = two[:2, :3]
print(twoValue)
print("------------------------")

twoValue = two[:2, ::3]
print(twoValue)
print("------------------------")

twoValue = two[::-1, ::-1]
print(twoValue)

# Accessing array rows and columns.
print(two)
print("------------------------")

print(two[:, 0]) # first coloumn 
print("------------------------")

print(two[0, :]) # first row
print("------------------------")

print(two[0]) # Entire row

# Modifing the array without using copy() function.

print(two)
print("------------------------")

twoValue = two[:2, :2]
print(twoValue)
print("------------------------")

twoValue[0, 0] = 25
print(twoValue)
print("------------------------")

print(two)


# Modifing the array with using copy() function.

print(two)
print("------------------------")

twoValue = two[:2, :2].copy()
print(twoValue)
print("------------------------")

twoValue[0, 0] = 45
print(twoValue)
print("------------------------")

print(two)

# Reshaping of Arrays using reshape() in a more advanced way

grid = np.arange(1, 10).reshape(3, 3)
print(grid)

# Reshaping the arrays using newaxis

print(one)
print("------------------------")
print(one.reshape(3, 2))
print("------------------------")

print(one[ np.newaxis, :])
print("------------------------")

print(one[:, np.newaxis])

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
c = np.concatenate([a, b])
print(c)
print("------------------------")

d = np.array([7, 8, 9])
e = np.concatenate([c, d])
print(e)
print("------------------------")

print(two)
print("------------------------")

f = np.concatenate([two, two])
print(f)
print("------------------------")

# concatenate along the second axis (zero-indexed)
g = np.concatenate([two, two], axis = 1)
print(g)
print("------------------------")

a = np.array([1, 2, 3])
print(a)
print("------------------------")

b = np.array([[4, 5, 6], 
             [7, 8, 9]])
print(b)
print("------------------------")

print(np.vstack([a, b]))
print("------------------------")


# horizontally stack the arrays
y = np.array([[99],
              [99]])
print(np.hstack([b, y]))
print("------------------------")

# Splitting of arrays
a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])
print(a)
print("------------------------")
b, c, d = np.split(a, [2, 5])
print(b, c, d)

grid = np.arange(16).reshape(4, 4)
print(grid)

upper, lower = np.vsplit(grid, [2])
print(upper)
print("------------------------")

print(lower)

left, right = np.hsplit(grid, [2])
print(left)
print("------------------------")

print(right)