#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ENGG1811 Lecture 7 

Examples on numpy
"""
# This python file contains a number of examples on using 
# the numpy library to construct an array

# %% import numpy
import numpy as np

# %%
# This cell is similar to the file numpy_elements.py
# from Week 6's lecture 
# 
# The examples below show how you can create numpy
# arrays by specifying the elements 

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

# 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)

# %% 
#
# Sometimes you want to specify linearly spaced numbers
# E.g. an array with elements 0, 0.1, 0.2, 0.3, ..., 1.9, 2
# 
# In Week 3, you did that with range() and list comprehension
#
# range() which is a Python function but it can only 
# generate a list of integers
#
# numpy has a function called arange(), which is very 
# similar to range(), but can be used with floats

# The inputs for arange() are start, stop, step 
array3 = np.arange(0,2.01,0.1)

print('array3 is', array3)

# You can also use arange() with 1 or 2 arguments
# See its manual page at:
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html

# %% 
# 
# For arange(), you get a linearly spaced sequence of numbers
# by specifying the start value, end value and the increment 
# (= step)
#
# An alternative is to use linspace(). You need to specify 
# the start value, end value and the number of points you  
# want.  

# The inputs for arange() are start, stop, number of points 
array4 = np.linspace(0,2,21)

print('array4 is', array4)
print('The number of entries in array4 is',len(array4))

# See its manual page at:
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html#numpy.linspace

# Remark: linspace() generates arithmetic progressions.
# There is also a function called logspace() to
# generate geometric progressions.  
# 
# Manual page for logspace()
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.logspace.html#numpy.logspace

# %%
# 
# Sometimes you may want an array pre-filled with 
# either zeros or ones 

array5 = np.zeros((2,4),dtype='float')
array6 = np.ones(5,dtype='int')

print('array5 is', array5)
print('array6 is', array6)

# Manual page
# zeros()
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.zeros.html
# ones()
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html

# %% 
# 
# Sometimes you may want to have an array of zeros or ones
# which has the same shape as another array 

# array2, which we used earlier, has a shape of (3,4) 
array7 = np.zeros_like(array2, dtype='float')
# gives an array filled with zeros and has the same
# shape as array2 

print('array7 is ', array7)

# Manual page for zeros_like()
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.zeros_like.html
#
# There is also ones_like()
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones_like.html
#