from wordcloud import WordCloud
f = open(u'txt/AliceEN.txt','r').read()
wordcloud = WordCloud(background_color="white",width=1000, height=860, margin=2).generate(f)
# width,height,margin可以設置圖片屬性
# generate 可以對全部文本進行自動分詞,但是他對中文支持不好,對中文的分詞處理請看我的下一篇文章
#wordcloud = WordCloud(font_path = r'D:Fontssimkai.ttf').generate(f)
# 你可以通過font_path參數來設置字體集
#background_color參數為設置背景顏色,默認顏色為黑色
import matplotlib.pyplot as plt
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
wordcloud.to_file('test.png')

#!/usr/bin/env python
"""
Colored by Group Example
========================
Generating a word cloud that assigns colors to words based on
a predefined mapping from colors to words
"""
from wordcloud import (WordCloud, get_single_color_func)
import matplotlib.pyplot as plt
class SimpleGroupedColorFunc(object):
 """Create a color function object which assigns EXACT colors
 to certain words based on the color to words mapping
 Parameters
 ----------
 color_to_words : dict(str -> list(str))
 A dictionary that maps a color to the list of words.
 default_color : str
 Color that will be assigned to a word that's not a member
 of any value from color_to_words.
 """
 def __init__(self, color_to_words, default_color):
 self.word_to_color = {word: color
 for (color, words) in color_to_words.items()
 for word in words}
 self.default_color = default_color
 def __call__(self, word, **kwargs):
 return self.word_to_color.get(word, self.default_color)
class GroupedColorFunc(object):
 """Create a color function object which assigns DIFFERENT SHADES of
 specified colors to certain words based on the color to words mapping.
 Uses wordcloud.get_single_color_func
 Parameters
 ----------
 color_to_words : dict(str -> list(str))
 A dictionary that maps a color to the list of words.
 default_color : str
 Color that will be assigned to a word that's not a member
 of any value from color_to_words.
 """
 def __init__(self, color_to_words, default_color):
 self.color_func_to_words = [
 (get_single_color_func(color), set(words))
 for (color, words) in color_to_words.items()]
 self.default_color_func = get_single_color_func(default_color)
 def get_color_func(self, word):
 """Returns a single_color_func associated with the word"""
 try:
 color_func = next(
 color_func for (color_func, words) in self.color_func_to_words
 if word in words)
 except StopIteration:
 color_func = self.default_color_func
 return color_func
 def __call__(self, word, **kwargs):
 return self.get_color_func(word)(word, **kwargs)
text = """The Zen of Python, by Tim Peters
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!"""
# Since the text is small collocations are turned off and text is lower-cased
wc = WordCloud(collocations=False).generate(text.lower())
# 自定義所有單詞的顏色
color_to_words = {
 # words below will be colored with a green single color function
 '#00ff00': ['beautiful', 'explicit', 'simple', 'sparse',
 'readability', 'rules', 'practicality',
 'explicitly', 'one', 'now', 'easy', 'obvious', 'better'],
 # will be colored with a red single color function
 'red': ['ugly', 'implicit', 'complex', 'complicated', 'nested',
 'dense', 'special', 'errors', 'silently', 'ambiguity',
 'guess', 'hard']
}
# Words that are not in any of the color_to_words values
# will be colored with a grey single color function
default_color = 'grey'
# Create a color function with single tone
# grouped_color_func = SimpleGroupedColorFunc(color_to_words, default_color)
# Create a color function with multiple tones
grouped_color_func = GroupedColorFunc(color_to_words, default_color)
# Apply our color function
# 如果你也可以將color_func的參數設置為圖片,詳細的說明請看 下一部分
wc.recolor(color_func=grouped_color_func)
# Plot
plt.figure()
plt.imshow(wc, interpolation="bilinear")
plt.axis("off")
plt.show()

#!/usr/bin/env python
"""
Image-colored wordcloud
=======================
You can color a word-cloud by using an image-based coloring strategy
implemented in ImageColorGenerator. It uses the average color of the region
occupied by the word in a source image. You can combine this with masking -
pure-white will be interpreted as 'don't occupy' by the WordCloud object when
passed as mask.
If you want white as a legal color, you can just pass a different image to
"mask", but make sure the image shapes line up.
"""
from os import path
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator
d = path.dirname(__file__)
# Read the whole text.
text = open(path.join(d, 'alice.txt')).read()
# read the mask / color image taken from
# http://jirkavinse.deviantart.com/art/quot-Real-Life-quot-Alice-282261010
alice_coloring = np.array(Image.open(path.join(d, "alice_color.png")))
# 設置停用詞
stopwords = set(STOPWORDS)
stopwords.add("said")
# 你可以通過 mask 參數 來設置詞云形狀
wc = WordCloud(background_color="white", max_words=2000, mask=alice_coloring,
 stopwords=stopwords, max_font_size=40, random_state=42)
# generate word cloud
wc.generate(text)
# create coloring from image
image_colors = ImageColorGenerator(alice_coloring)
# show
# 在只設置mask的情況下,你將會得到一個擁有圖片形狀的詞云
plt.imshow(wc, interpolation="bilinear")
plt.axis("off")
plt.figure()
# recolor wordcloud and show
# we could also give color_func=image_colors directly in the constructor
# 我們還可以直接在構造函數中直接給顏色
# 通過這種方式詞云將會按照給定的圖片顏色布局生成字體顏色策略
plt.imshow(wc.recolor(color_func=image_colors), interpolation="bilinear")
plt.axis("off")
plt.figure()
plt.imshow(alice_coloring, cmap=plt.cm.gray, interpolation="bilinear")
plt.axis("off")
plt.show()