#!/usr/bin/env python
# coding: utf-8

# # Loops
# 
# This notebook follows on in many ways from the [functions](https://hub.mybinder.org/user/bjmorgan-python_in_chemistry-ty1bfjno/notebooks/General/Functions.ipynb) notebook. The aim here is to show the utility of **loops** in Python programming. I will again endevour to use examples from *chemistry* related problems, but occasionally examples from physics or mathematics will come through. 
# 
# As is the case with many aspects of programming the propose of a loop is to allow the programmer to write less code. This leads to the idiom that *computers are really good at doing the same thing over and over*, much better than humans. 
# 
# A loop really is just that, a way to tell the computer to perform a task multiple times over. 
# 
# The Pythonic way to have a loop is:
# 
# <code>for i in array:
#     operation
# </code>
# 
# There are a few things here that need described. 
# - <code>for</code> This tells the computer that you are wanting something to be looped through
# - <code>i</code> This is the iterator, it will become more clear the utility of this in later examples
# - <code>array</code> This is some array of objects that is to be itereated through. 
# For each iteration the <code>operation</code> is performed. 
# 
# Lets have a look at some examples. 

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for i in range(0, 10):
    print('Hello World!')


# This example says <code>for i</code> in the range 0 to 10 (including zero but not ten) print the string <code>Hello World!</code>. 
# 
# The result is that the string is printed 10 times, once for each of the numbers 0, 1, 2, 3, 4, 5, 6, 7, 8, 9. Essentially, <code>i</code> is counting from 0 to 9 and printing the string each time. 
# 
# This is more clear if we include <code>i</code> in the string.

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for i in range(0, 10):
    print('Hello World {}!'.format(i))


# Of course, the array doesn't just have to be a series of continuous integers. We can have really any type of array. 

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array1 = [2.4, 6.7, 3.0, 8.2, 2.7, 7.4]
for i in array1:
    print(i)


# And the iterator need not always be called <code>i</code>. This is just a *convention* in programming.

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array2 = ['dog', 'horse', 'bear', 'lion', 'camel']
for animal in array2:
    print(animal)


# The examples above are all quite trival, lets have a look at something a bit more applicable. If you have looked at the [functions](https://hub.mybinder.org/user/bjmorgan-python_in_chemistry-ty1bfjno/notebooks/General/Functions.ipynb) notebook this example will be familiar. 
# 
# It is the calculation of the equilibrium constant for the following reaction at a series of temperatures, from 300 K to 350 K in 10 K increaments. 
# 
# $$\text{CH}_4\text{(g)} + 2\text{O}_2\text{(g)} \rightarrow \text{CO}_2\text{(g)} + 2\text{H}_2\text{O(l)} $$
# 
# | Component | $\Delta_fH$/kJmol$^{-1}$ | $_rS$/kJmol$^{-1}$ |
# |------|------|
# | CH$_4$ | -74.8 | 0.1862 |
# | O$_2$ | 0 | 0.2050 |
# | CO$_2$ | -393.5 | 0.2136 |
# | H$_2$O | -285.8 | 0.0699 |
# 
# The first thing we need it the function to calculate the equilibrium constant. 

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import numpy as np
from scipy.constants import R

def equilibrium_constant(deltaH_products, deltaH_reactants, S_products, S_reactants, T):
    deltarH = np.sum(deltaH_products) - np.sum(deltaH_reactants)
    deltarS = np.sum(S_products) - np.sum(S_reactants)
    Gibbs_free_energy = deltarH - T * deltarS
    K = np.exp(-1 * Gibbs_free_energy/(R * 1e-3 *T))
    return K


# And the range of temperatures.

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temperatures = [300., 310., 320., 330., 340., 350.]


# Then we can make use of the loop as follows.

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deltaH_products = [-393.5, -285.8 * 2]
deltaH_reactants = [-74.8, 0 * 2]
S_products = [0.2136, 0.0699, 0.0699]
S_reactants = [0.1862, 0.2050, 0.2050]

for T in temperatures:
    K = equilibrium_constant(deltaH_products, deltaH_reactants, S_products, S_reactants, T)
    print('K @ {:.0f} K = {:.3e}'.format(T, K))


# This procedure can be achieved for any range of temperatures, using the <code>np.arange</code> function. The below example also shows how the enumerate function can be utilised to count through the loops. 

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temperatures = np.arange(300, 400, 20)

deltaH_products = [-393.5, -285.8 * 2]
deltaH_reactants = [-74.8, 0 * 2]
S_products = [0.2136, 0.0699, 0.0699]
S_reactants = [0.1862, 0.2050, 0.2050]

for i, T in enumerate(temperatures):
    K = equilibrium_constant(deltaH_products, deltaH_reactants, S_products, S_reactants, T)
    print('{}. K @ {:.0f} K = {:.3e}'.format(i+1, T, K))


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