%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np

"""
Explanation: Algorithms Exercise 1
Imports
End of explanation
"""


things = "hello!"
def ispuct(char, punctuation='`~!@#$%^&*()_-+={[}]|\:;"<,>.?/}\t'):
    return (not (char in punctuation))

#x = list(filter(ispuct, things))
#a = ''
#a.join(x)
#print(new_things)

def tokenize(s, stop_words = '', punctuation='`~!@#$%^&*()_+={[}]|\:;"<,>.?/}\t'):
    m = []
    s = s.replace("-", " ")
    stop = stop_words
    def is_stop(word, stop_words = stop):
        return not (word in stop_words)
    def is_space(word, space = ['']):
        return not (word in space)
    for line in s.splitlines():
        raw = line.lower().split(' ' or '.')  
        y = list()
        for w in raw:
                x = list(filter(ispuct, w))
                y.append(a.join(x))
        words = list(filter(is_space, y))
        words = list(filter(is_stop, words))
        m += words
    return m
    
tokenize("This, is the way; that things will hi--end", stop_words = 'is the')
#ispuct('!')

wasteland = """
APRIL is the cruellest month, breeding
Lilacs out of the dead land, mixing
Memory and desire, stirring
Dull roots with spring rain.
"""
tokenize(wasteland, stop_words='is the of and')

assert tokenize("This, is the way; that things will end", stop_words=['the', 'is']) == \
    ['this', 'way', 'that', 'things', 'will', 'end']
wasteland = """
APRIL is the cruellest month, breeding
Lilacs out of the dead land, mixing
Memory and desire, stirring
Dull roots with spring rain.
"""
#tokenize(wasteland, stop_words='is the of and')
assert tokenize(wasteland, stop_words='is the of and') == \
    ['april','cruellest','month','breeding','lilacs','out','dead','land',
     'mixing','memory','desire','stirring','dull','roots','with','spring',
     'rain']

"""
Explanation: Word counting
Write a function tokenize that takes a string of English text returns a list of words. It should also remove stop words, which are common short words that are often removed before natural language processing. Your function should have the following logic:

Split the string into lines using splitlines.
Split each line into a list of words and merge the lists for each line.
Use Python's builtin filter function to remove all punctuation.
If stop_words is a list, remove all occurences of the words in the list.
If stop_words is a space delimeted string of words, split them and remove them.
Remove any remaining empty words.
Make all words lowercase.
End of explanation
"""


def count_words(data):
    """Return a word count dictionary from the list of words in data."""
    dictionary = {}
    for n in data:
        dictionary[n]= data.count(n)
    return dictionary

assert count_words(tokenize('this and the this from and a a a')) == \
    {'a': 3, 'and': 2, 'from': 1, 'the': 1, 'this': 2}

"""
Explanation: Write a function count_words that takes a list of words and returns a dictionary where the keys in the dictionary are the unique words in the list and the values are the word counts.
End of explanation
"""


def sort_word_counts(wc):
    """Return a list of 2-tuples of (word, count), sorted by count descending."""
    l = [(i,wc[i]) for i in wc]
    return sorted(l, key = lambda x:x[1], reverse = True)

print(sort_word_counts(count_words(tokenize('this and a the this this and a a a'))))

assert sort_word_counts(count_words(tokenize('this and a the this this and a a a'))) == \
    [('a', 4), ('this', 3), ('and', 2), ('the', 1)]

"""
Explanation: Write a function sort_word_counts that return a list of sorted word counts:

Each element of the list should be a (word, count) tuple.
The list should be sorted by the word counts, with the higest counts coming first.
To perform this sort, look at using the sorted function with a custom key and reverse
  argument.
End of explanation
"""


txt = open('mobydick_chapter1.txt', 'r')
x = txt.read()
swc = sort_word_counts(count_words(tokenize(s = x, stop_words = ['the', 'of', 'and', 'to', 'in', 'is', 'it', 'that', 'as', 'a'])))
string = ''
x = (tokenize(s = x, stop_words = ['the', 'of', 'and', 'to', 'in', 'is', 'it', 'that', 'as', 'a']))
for things in x:
    string = string + things + " "
print(len(swc))
#print(swc)
print(string)
punchfactor = 4

assert swc[0]==('i',43)
assert len(swc)==848 - punchfactor #4 is the punchfactor, ranked out of 4

"""
Explanation: Perform a word count analysis on Chapter 1 of Moby Dick, whose text can be found in the file mobydick_chapter1.txt:

Read the file into a string.
Tokenize with stop words of 'the of and a to in is it that as'.
Perform a word count, the sort and save the result in a variable named swc.
End of explanation
"""


x = np.array(swc)
plt.plot(x[0:50,1], range(50),'o')


assert True # use this for grading the dotplot

"""
Explanation: Create a "Cleveland Style" dotplot of the counts of the top 50 words using Matplotlib. If you don't know what a dotplot is, you will have to do some research...
End of explanation
"""


