#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ENGG1811 Lecture

Numpy: Creating arrays, indexing and slicing 
"""

# Topics covered in this file
# Creating arrays
# Accessing and modifying elements
# Dimension 
# Shapes 

# %% import numpy
import numpy as np

# %% Creating arrays and array elements 

#  Creating a 1-dimensional array and print it 
array1 = np.array([1, 2, 3, -3, -5, -6, 8, 12])

# Print the array
print('array1 is', array1)

# Alternative methods to create the same array
# list1 = [1, 2, 3, -3, -5, -6, 8, 12]
# array1 = np.array(list1)

# Viewing and modifying array elements, slicing
# Same as lists 
array1[3]
array1[7] = -10
array1[3:5]
array1[:-2]
array1[0:2] = [15, 4]

#%% 
# Creating a 2-dimensional array and
array2 = np.array([ [-1.2,  2, -3.1, 4.5], 
                    [   4, -5,  3.5, 7.1],
                    [ 2.7,  9,  1.7, 3.4]])

print('array2 is', array2)

# You can access individual elements 
array2[0,3]  # 4.5
array2[1,2]  # 3.5

# Quiz: 
# What do you get for the following? Think about 
# it and type it in to verify.
# array2[2,2]
# array2[-2,-2]

# You can do slicing too 
array2[0:2,0]
array2[0:2,1:2]
array2[:,-1]
array2[:]       # returns the entire numpy array 

# Quiz: 
# What is array2[2,:]? 

# %% 
# Dimension, shape
array1.ndim     # 1
array1.shape    # (8,) 
array2.ndim     # 2 
array2.shape    # (3, 4)