词云在这两年一直都热门话题，假如你耐下性质花个10分钟看看这篇文章，也许你就再也不必艳羡那些会词云的人了。这不是一项高深莫测的手艺，你也能够学会。快来尝尝吧！
本篇我们解说的是怎样制造英文词云，下一期我们将给人人带来怎样制造中文词云，敬请期待！
疾速生成词云
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能够设置图片属性
# generate 能够对悉数文本举行自动分词,然则他对中文支撑不好,对中文的分词处置惩罚请看我的下一篇文章
#wordcloud = WordCloud(font_path = r'D:\Fonts\simkai.ttf').generate(f)
# 你能够经由过程font_path参数来设置字体集
#background_color参数为设置背景色彩,默许色彩为黑色
import matplotlib.pyplot as plt
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
wordcloud.to_file('test.png')
# 保留图片,然则在第三模块的例子中 图片大小将会根据 mask 保留
自定义字体色彩
这段代码重要来自wordcloud的github,你能够在github下载该例子
#!/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())
# 自定义一切单词的色彩
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
# 假如你也能够将color_func的参数设置为图片,细致的申明请看 下一部份
wc.recolor(color_func=grouped_color_func)
# Plot
plt.figure()
plt.imshow(wc, interpolation="bilinear")
plt.axis("off")
plt.show()
应用背景图片生成词云，设置停用词词集
该段代码重要来自于wordcloud的github,你一样能够在github下载该例子以及原图片与结果图
#!/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")))
# 设置停用词
stopwords = set(STOPWORDS)
stopwords.add("said")
# 你能够经由过程 mask 参数 来设置词云外形
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
# 在只设置mask的情况下,你将会获得一个具有图片外形的词云
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
# 我们还能够直接在组织函数中直接给色彩
# 经由过程这类体式格局词云将会根据给定的图片色彩规划生成字体色彩战略
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()
展现结果以下:
以上就是Python + wordcloud 十分钟学会生成英文词云的细致内容，更多请关注ki4网别的相干文章！
