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

Illustrating the numpy functions all and any 
"""
import numpy as np 

# Problem parameters
array1 = np.array([ [-3.2,  0,  0.5, 5.8], 
                    [   6, -4,  6.2, 7.1],
                    [ 3.8,  5,  2.7, 3.7]])


# Using all and any 
print(np.all(array1 > 0, axis = 1))

print(np.any(array1 > 6, axis = 0))

# %% Quiz 
# The temperature data  
temp_array = np.array(
             [[ 0.3,  0.4,  0.5,  0.5,  0.1,  0.8,  0.8,  0.5,  0.0,  0.7],
              [ 0.2,  0.4,  0.8,  0.4,  0.8,  1.8,  0.9,  0.1,  1.4,  1.7],
              [ 1.1,  0.1,  0.8,  0.9,  0.5,  0.3,  0.2,  0.2,  1.1,  0.4],
              [ 0.4,  0.7,  0.6,  0.6,  0.4,  0.4,  0.5,  0.0,  0.1,  0.2],
              [ 0.2,  0.1,  0.9,  0.9,  0.3,  0.5,  0.4,  0.7,  0.2,  0.7]]
             )

# Each row contains data from a thermometer 
# 
# Each column contains the daily readings from the five 
# thermometers 
# 
# For normal operation, the temperature readings for 
# all thermometers in a day must be 
# strictly smaller 1.2 

# Question: How many normal operation days were there?
days_normal = np.all(temp_array < 1.2, axis = 0)
np.sum(days_normal)

# Can merge into one line
np.sum(np.all(temp_array < 1.2, axis = 0))

# %% Forum question 
# After learning about where()
# If column 0 is day 0, column 1 is day 1, 
# determine the indices of the days where the operation
# was not normal