# https://www.globalsino.com/ICs/
# Simple Word Cloud applications with text input from a .txt file


import collections
import numpy as np
import pandas as pd
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from matplotlib import rcParams
from wordcloud import WordCloud, STOPWORDS

# Read a text file
textFile = open(r"C:\GlobalSino2\ICs\4304ForWordCloud.txt")
myText = textFile.read()
stopwords = STOPWORDS

# ============
# Create stopword
stopwords = set(STOPWORDS)
# Generate a word cloud image
wordcloud = WordCloud(width = 3000, height = 2000, random_state=1, background_color='black', colormap='Set2', collocations=False, stopwords = STOPWORDS).generate(myText)
# Display the generated image
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.show()

# ============

filtered_words = [word for word in myText.split() if word not in stopwords]
counted_words = collections.Counter(filtered_words)
words = []
counts = []
for letter, count in counted_words.most_common(10):
    words.append(letter)
    counts.append(count)
colors = cm.rainbow(np.linspace(0, 1, 10))
rcParams['figure.figsize'] = 20, 10
plt.title('Top words in the text vs their count')
plt.xlabel('Counts')
plt.ylabel('Words')
plt.barh(words, counts, color=colors)
plt.show()