密谋返回空白图形对象
Plotly returning blank figure object
我有以下代码应该在 matplotlib 中绘制给定文本的词云并将其转换为 plotly：
from wordcloud import WordCloud, STOPWORDS
import matplotlib.pyplot as plt
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
import plotly.tools as tls
# Thanks : https://www.kaggle.com/aashita/word-clouds-of-various-shapes ##
def plot_wordcloud(text, mask=None, max_words=200, max_font_size=100, figure_size=(24.0,16.0),
title = None, title_size=40, image_color=False):
stopwords = set(STOPWORDS)
wordcloud = WordCloud(background_color='black',
stopwords = stopwords,
max_words = max_words,
max_font_size = max_font_size,
random_state = 42,
width=800,
height=400,
mask = mask)
wordcloud.generate(str(text))
fig = plt.figure()
plt.imshow(wordcloud)
return tls.mpl_to_plotly(fig)
word_list = "Wikipedia was launched on January 15, 2001, by Jimmy Wales and Larry Sanger.[10] Sanger coined its name,[11][12] as a portmanteau of wiki[notes 3] and 'encyclopedia'. Initially an English-language encyclopedia, versions in other languages were quickly developed. With 5,748,461 articles,[notes 4] the English Wikipedia is the largest of the more than 290 Wikipedia encyclopedias. Overall, Wikipedia comprises more than 40 million articles in 301 different languages[14] and by February 2014 it had reached 18 billion page views and nearly 500 million unique visitors per month.[15] In 2005, Nature published a peer review comparing 42 science articles from Encyclopædia Britannica and Wikipedia and found that Wikipedia's level of accuracy approached that of Britannica.[16] Time magazine stated that the open-door policy of allowing anyone to edit had made Wikipedia the biggest and possibly the best encyclopedia in the world and it was testament to the vision of Jimmy Wales.[17] Wikipedia has been criticized for exhibiting systemic bias, for presenting a mixture of 'truths, half truths, and some falsehoods',[18] and for being subject to manipulation and spin in controversial topics.[19] In 2017, Facebook announced that it would help readers detect fake news by suitable links to Wikipedia articles. YouTube announced a similar plan in 2018."
plot_wordcloud(word_list, title="Word Cloud")
这只是 returns 一个空白图，data 部分没有任何内容：
Figure({
'data': [],
'layout': {'autosize': False,
'height': 288,
'hovermode': 'closest',
'margin': {'b': 61, 'l': 54, 'pad': 0, 'r': 43, 't': 59},
'showlegend': False,
'width': 432,
'xaxis': {'anchor': 'y',
'domain': [0.0, 1.0],
'mirror': 'ticks',
'nticks': 10,
'range': [-0.5, 799.5],
'showgrid': False,
'showline': True,
'side': 'bottom',
'tickfont': {'size': 10.0},
'ticks': 'inside',
'type': 'linear',
'zeroline': False},
'yaxis': {'anchor': 'x',
'domain': [0.0, 1.0],
'mirror': 'ticks',
'nticks': 10,
'range': [399.5, -0.5],
'showgrid': False,
'showline': True,
'side': 'left',
'tickfont': {'size': 10.0},
'ticks': 'inside',
'type': 'linear',
'zeroline': False}}
})
这是为什么呢？我该如何解决？
如果我想绘制 matplotlib 图，它工作正常 - return fig returns wordcloud 的静态图。
我试图直接在 plotly 中绘制 wordcloud，但是对于 go.Scatter 你需要明确地提供 x 和 y 值——它不能像 plt.imshow 那样隐式地从 wordcloud 中获取它们能够。所以，我得到一个 "object is not iterable" 错误：
def plot_wordcloud(text, mask=None, max_words=200, max_font_size=100, figure_size=(24.0,16.0),
title = None, title_size=40, image_color=False):
stopwords = set(STOPWORDS)
wordcloud = WordCloud(background_color='black',
stopwords = stopwords,
max_words = max_words,
max_font_size = max_font_size,
random_state = 42,
width=800,
height=400,
mask = mask)
wordcloud.generate(str(text))
data = go.Scatter(dict(wordcloud.generate(str(text))),
mode='text',
text=words,
marker={'opacity': 0.3},
textfont={'size': weights,
'color': colors})
layout = go.Layout({'xaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False},
'yaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False}})
fig = go.Figure(data=[data], layout=layout)
return fig
word_list = "Wikipedia was launched on January 15, 2001, by Jimmy Wales and Larry Sanger.[10] Sanger coined its name,[11][12] as a portmanteau of wiki[notes 3] and 'encyclopedia'. Initially an English-language encyclopedia, versions in other languages were quickly developed. With 5,748,461 articles,[notes 4] the English Wikipedia is the largest of the more than 290 Wikipedia encyclopedias. Overall, Wikipedia comprises more than 40 million articles in 301 different languages[14] and by February 2014 it had reached 18 billion page views and nearly 500 million unique visitors per month.[15] In 2005, Nature published a peer review comparing 42 science articles from Encyclopædia Britannica and Wikipedia and found that Wikipedia's level of accuracy approached that of Britannica.[16] Time magazine stated that the open-door policy of allowing anyone to edit had made Wikipedia the biggest and possibly the best encyclopedia in the world and it was testament to the vision of Jimmy Wales.[17] Wikipedia has been criticized for exhibiting systemic bias, for presenting a mixture of 'truths, half truths, and some falsehoods',[18] and for being subject to manipulation and spin in controversial topics.[19] In 2017, Facebook announced that it would help readers detect fake news by suitable links to Wikipedia articles. YouTube announced a similar plan in 2018."
plot_wordcloud(word_list, title="Word Cloud")
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-50-0567281b72b3> in <module>()
---> 48 plot_wordcloud(word_list, title="Word Cloud")
<ipython-input-50-0567281b72b3> in plot_wordcloud(text, mask, max_words, max_font_size, figure_size, title, title_size, image_color)
18
19
---> 20 data = go.Scatter(dict(wordcloud.generate(str(text))),
21 mode='text',
22 text=words,
TypeError: 'WordCloud' object is not iterable
如果我 return wordcloud，它会显示：<wordcloud.wordcloud.WordCloud at 0x1c8faeda748>。如果有人知道如何解压缩 wordcloud 对象，以便我可以将其中的 x 和 y 参数输入到 go.Figure，那也很好（实际上更好）。
只是为了证明解包 wordcloud 对象是可行的，我可以通过在 go.Scatter 中放置 x 和 y 值的随机数来使用 plotly 本地绘制一个词云，如下所示：
import random
import plotly.graph_objs as go
def plot_wordcloud(text, mask=None, max_words=200, max_font_size=100, figure_size=(24.0,16.0),
title = None, title_size=40, image_color=False):
stopwords = set(STOPWORDS)
wordcloud = WordCloud(background_color='black',
stopwords = stopwords,
max_words = max_words,
max_font_size = max_font_size,
random_state = 42,
width=800,
height=400,
mask = mask)
wordcloud.generate(str(text))
data = go.Scatter(x=[random.random() for i in range(3000)],
y=[random.random() for i in range(3000)],
mode='text',
text=str(word_list).split(),
marker={'opacity': 0.3},
textfont={'size': weights,
'color': colors})
layout = go.Layout({'xaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False},
'yaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False}})
fig = go.Figure(data=[data], layout=layout)
return fig
它只是不正确的词云（显然，正确定义了单词的位置和大小），它应该是这样的（用matplotlib.pyplot绘制的静态词云）：
由于 wordcloud 生成图像，而 plotly 的转换功能当前无法处理图像，因此您需要以某种方式从 wordcloud.wordcloud.WordCloud 对象的位置、大小和方向重新生成词云。
这些信息存储在 .layout_ 属性中
wc = Wordcloud(...)
wc.generate(text)
print(wc.layout_)
打印
形式的元组列表
[(word, freq), fontsize, position, orientation, color]
例如在这种情况下
[(('Wikipedia', 1.0), 100, (8, 7), None, 'rgb(56, 89, 140)'),
(('articles', 0.4444444444444444), 72, (269, 310), None, 'rgb(58, 186, 118)'), ...]
所以原则上这允许将词云重新生成为文本。但是必须注意小细节。 IE。字体和字体大小需要相同。
这是一个纯 matplotlib 示例，它使用 matplotlib.text.Text 个对象重现了 wordcloud。
import numpy as np
from wordcloud import WordCloud, STOPWORDS
from wordcloud.wordcloud import FONT_PATH
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
word_list = "Wikipedia was launched on January 15, 2001, by Jimmy Wales and Larry Sanger.[10] Sanger coined its name,[11][12] as a portmanteau of wiki[notes 3] and 'encyclopedia'. Initially an English-language encyclopedia, versions in other languages were quickly developed. With 5,748,461 articles,[notes 4] the English Wikipedia is the largest of the more than 290 Wikipedia encyclopedias. Overall, Wikipedia comprises more than 40 million articles in 301 different languages[14] and by February 2014 it had reached 18 billion page views and nearly 500 million unique visitors per month.[15] In 2005, Nature published a peer review comparing 42 science articles from Encyclopædia Britannica and Wikipedia and found that Wikipedia's level of accuracy approached that of Britannica.[16] Time magazine stated that the open-door policy of allowing anyone to edit had made Wikipedia the biggest and possibly the best encyclopedia in the world and it was testament to the vision of Jimmy Wales.[17] Wikipedia has been criticized for exhibiting systemic bias, for presenting a mixture of 'truths, half truths, and some falsehoods',[18] and for being subject to manipulation and spin in controversial topics.[19] In 2017, Facebook announced that it would help readers detect fake news by suitable links to Wikipedia articles. YouTube announced a similar plan in 2018."
def get_wordcloud(width, height):
wc = WordCloud(background_color='black',
stopwords = set(STOPWORDS),
max_words = 200,
max_font_size = 100,
random_state = 42,
width=int(width),
height=int(height),
mask = None)
wc.generate(word_list)
return wc
fig, (ax, ax2) = plt.subplots(nrows=2, sharex=True, sharey=True)
fp=FontProperties(fname=FONT_PATH)
bbox = ax.get_position().transformed(fig.transFigure)
wc = get_wordcloud(bbox.width, bbox.height)
ax.imshow(wc)
ax2.set_facecolor("black")
for (word, freq), fontsize, position, orientation, color in wc.layout_:
color = np.array(color[4:-1].split(", ")).astype(float)/255.
x,y = position
rot = {None : 0, 2: 90}[orientation]
fp.set_size(fontsize*72./fig.dpi)
ax2.text(y,x, word, va="top", ha="left", color=color, rotation=rot,
fontproperties=fp)
print(wc.layout_)
plt.show()
上图是通过imshow显示的词云图像，下图是重新生成的词云。
现在你可能想在 plotly 而不是 matplotlib 中做同样的事情，但我对 plotly 不够熟练，无法直接在这里给出解决方案。
我有以下代码应该在 matplotlib 中绘制给定文本的词云并将其转换为 plotly：
from wordcloud import WordCloud, STOPWORDS
import matplotlib.pyplot as plt
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
import plotly.tools as tls
# Thanks : https://www.kaggle.com/aashita/word-clouds-of-various-shapes ##
def plot_wordcloud(text, mask=None, max_words=200, max_font_size=100, figure_size=(24.0,16.0),
title = None, title_size=40, image_color=False):
stopwords = set(STOPWORDS)
wordcloud = WordCloud(background_color='black',
stopwords = stopwords,
max_words = max_words,
max_font_size = max_font_size,
random_state = 42,
width=800,
height=400,
mask = mask)
wordcloud.generate(str(text))
fig = plt.figure()
plt.imshow(wordcloud)
return tls.mpl_to_plotly(fig)
word_list = "Wikipedia was launched on January 15, 2001, by Jimmy Wales and Larry Sanger.[10] Sanger coined its name,[11][12] as a portmanteau of wiki[notes 3] and 'encyclopedia'. Initially an English-language encyclopedia, versions in other languages were quickly developed. With 5,748,461 articles,[notes 4] the English Wikipedia is the largest of the more than 290 Wikipedia encyclopedias. Overall, Wikipedia comprises more than 40 million articles in 301 different languages[14] and by February 2014 it had reached 18 billion page views and nearly 500 million unique visitors per month.[15] In 2005, Nature published a peer review comparing 42 science articles from Encyclopædia Britannica and Wikipedia and found that Wikipedia's level of accuracy approached that of Britannica.[16] Time magazine stated that the open-door policy of allowing anyone to edit had made Wikipedia the biggest and possibly the best encyclopedia in the world and it was testament to the vision of Jimmy Wales.[17] Wikipedia has been criticized for exhibiting systemic bias, for presenting a mixture of 'truths, half truths, and some falsehoods',[18] and for being subject to manipulation and spin in controversial topics.[19] In 2017, Facebook announced that it would help readers detect fake news by suitable links to Wikipedia articles. YouTube announced a similar plan in 2018."
plot_wordcloud(word_list, title="Word Cloud")
这只是 returns 一个空白图，data 部分没有任何内容：
Figure({
'data': [],
'layout': {'autosize': False,
'height': 288,
'hovermode': 'closest',
'margin': {'b': 61, 'l': 54, 'pad': 0, 'r': 43, 't': 59},
'showlegend': False,
'width': 432,
'xaxis': {'anchor': 'y',
'domain': [0.0, 1.0],
'mirror': 'ticks',
'nticks': 10,
'range': [-0.5, 799.5],
'showgrid': False,
'showline': True,
'side': 'bottom',
'tickfont': {'size': 10.0},
'ticks': 'inside',
'type': 'linear',
'zeroline': False},
'yaxis': {'anchor': 'x',
'domain': [0.0, 1.0],
'mirror': 'ticks',
'nticks': 10,
'range': [399.5, -0.5],
'showgrid': False,
'showline': True,
'side': 'left',
'tickfont': {'size': 10.0},
'ticks': 'inside',
'type': 'linear',
'zeroline': False}}
})
这是为什么呢？我该如何解决？
如果我想绘制 matplotlib 图，它工作正常 - return fig returns wordcloud 的静态图。
我试图直接在 plotly 中绘制 wordcloud，但是对于 go.Scatter 你需要明确地提供 x 和 y 值——它不能像 plt.imshow 那样隐式地从 wordcloud 中获取它们能够。所以，我得到一个 "object is not iterable" 错误：
def plot_wordcloud(text, mask=None, max_words=200, max_font_size=100, figure_size=(24.0,16.0),
title = None, title_size=40, image_color=False):
stopwords = set(STOPWORDS)
wordcloud = WordCloud(background_color='black',
stopwords = stopwords,
max_words = max_words,
max_font_size = max_font_size,
random_state = 42,
width=800,
height=400,
mask = mask)
wordcloud.generate(str(text))
data = go.Scatter(dict(wordcloud.generate(str(text))),
mode='text',
text=words,
marker={'opacity': 0.3},
textfont={'size': weights,
'color': colors})
layout = go.Layout({'xaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False},
'yaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False}})
fig = go.Figure(data=[data], layout=layout)
return fig
word_list = "Wikipedia was launched on January 15, 2001, by Jimmy Wales and Larry Sanger.[10] Sanger coined its name,[11][12] as a portmanteau of wiki[notes 3] and 'encyclopedia'. Initially an English-language encyclopedia, versions in other languages were quickly developed. With 5,748,461 articles,[notes 4] the English Wikipedia is the largest of the more than 290 Wikipedia encyclopedias. Overall, Wikipedia comprises more than 40 million articles in 301 different languages[14] and by February 2014 it had reached 18 billion page views and nearly 500 million unique visitors per month.[15] In 2005, Nature published a peer review comparing 42 science articles from Encyclopædia Britannica and Wikipedia and found that Wikipedia's level of accuracy approached that of Britannica.[16] Time magazine stated that the open-door policy of allowing anyone to edit had made Wikipedia the biggest and possibly the best encyclopedia in the world and it was testament to the vision of Jimmy Wales.[17] Wikipedia has been criticized for exhibiting systemic bias, for presenting a mixture of 'truths, half truths, and some falsehoods',[18] and for being subject to manipulation and spin in controversial topics.[19] In 2017, Facebook announced that it would help readers detect fake news by suitable links to Wikipedia articles. YouTube announced a similar plan in 2018."
plot_wordcloud(word_list, title="Word Cloud")
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-50-0567281b72b3> in <module>()
---> 48 plot_wordcloud(word_list, title="Word Cloud")
<ipython-input-50-0567281b72b3> in plot_wordcloud(text, mask, max_words, max_font_size, figure_size, title, title_size, image_color)
18
19
---> 20 data = go.Scatter(dict(wordcloud.generate(str(text))),
21 mode='text',
22 text=words,
TypeError: 'WordCloud' object is not iterable
如果我 return wordcloud，它会显示：<wordcloud.wordcloud.WordCloud at 0x1c8faeda748>。如果有人知道如何解压缩 wordcloud 对象，以便我可以将其中的 x 和 y 参数输入到 go.Figure，那也很好（实际上更好）。
只是为了证明解包 wordcloud 对象是可行的，我可以通过在 go.Scatter 中放置 x 和 y 值的随机数来使用 plotly 本地绘制一个词云，如下所示：
import random
import plotly.graph_objs as go
def plot_wordcloud(text, mask=None, max_words=200, max_font_size=100, figure_size=(24.0,16.0),
title = None, title_size=40, image_color=False):
stopwords = set(STOPWORDS)
wordcloud = WordCloud(background_color='black',
stopwords = stopwords,
max_words = max_words,
max_font_size = max_font_size,
random_state = 42,
width=800,
height=400,
mask = mask)
wordcloud.generate(str(text))
data = go.Scatter(x=[random.random() for i in range(3000)],
y=[random.random() for i in range(3000)],
mode='text',
text=str(word_list).split(),
marker={'opacity': 0.3},
textfont={'size': weights,
'color': colors})
layout = go.Layout({'xaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False},
'yaxis': {'showgrid': False, 'showticklabels': False, 'zeroline': False}})
fig = go.Figure(data=[data], layout=layout)
return fig
它只是不正确的词云（显然，正确定义了单词的位置和大小），它应该是这样的（用matplotlib.pyplot绘制的静态词云）：
由于 wordcloud 生成图像，而 plotly 的转换功能当前无法处理图像，因此您需要以某种方式从 wordcloud.wordcloud.WordCloud 对象的位置、大小和方向重新生成词云。
这些信息存储在 .layout_ 属性中
wc = Wordcloud(...)
wc.generate(text)
print(wc.layout_)
打印
形式的元组列表[(word, freq), fontsize, position, orientation, color]
例如在这种情况下
[(('Wikipedia', 1.0), 100, (8, 7), None, 'rgb(56, 89, 140)'),
(('articles', 0.4444444444444444), 72, (269, 310), None, 'rgb(58, 186, 118)'), ...]
所以原则上这允许将词云重新生成为文本。但是必须注意小细节。 IE。字体和字体大小需要相同。
这是一个纯 matplotlib 示例，它使用 matplotlib.text.Text 个对象重现了 wordcloud。
import numpy as np
from wordcloud import WordCloud, STOPWORDS
from wordcloud.wordcloud import FONT_PATH
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
word_list = "Wikipedia was launched on January 15, 2001, by Jimmy Wales and Larry Sanger.[10] Sanger coined its name,[11][12] as a portmanteau of wiki[notes 3] and 'encyclopedia'. Initially an English-language encyclopedia, versions in other languages were quickly developed. With 5,748,461 articles,[notes 4] the English Wikipedia is the largest of the more than 290 Wikipedia encyclopedias. Overall, Wikipedia comprises more than 40 million articles in 301 different languages[14] and by February 2014 it had reached 18 billion page views and nearly 500 million unique visitors per month.[15] In 2005, Nature published a peer review comparing 42 science articles from Encyclopædia Britannica and Wikipedia and found that Wikipedia's level of accuracy approached that of Britannica.[16] Time magazine stated that the open-door policy of allowing anyone to edit had made Wikipedia the biggest and possibly the best encyclopedia in the world and it was testament to the vision of Jimmy Wales.[17] Wikipedia has been criticized for exhibiting systemic bias, for presenting a mixture of 'truths, half truths, and some falsehoods',[18] and for being subject to manipulation and spin in controversial topics.[19] In 2017, Facebook announced that it would help readers detect fake news by suitable links to Wikipedia articles. YouTube announced a similar plan in 2018."
def get_wordcloud(width, height):
wc = WordCloud(background_color='black',
stopwords = set(STOPWORDS),
max_words = 200,
max_font_size = 100,
random_state = 42,
width=int(width),
height=int(height),
mask = None)
wc.generate(word_list)
return wc
fig, (ax, ax2) = plt.subplots(nrows=2, sharex=True, sharey=True)
fp=FontProperties(fname=FONT_PATH)
bbox = ax.get_position().transformed(fig.transFigure)
wc = get_wordcloud(bbox.width, bbox.height)
ax.imshow(wc)
ax2.set_facecolor("black")
for (word, freq), fontsize, position, orientation, color in wc.layout_:
color = np.array(color[4:-1].split(", ")).astype(float)/255.
x,y = position
rot = {None : 0, 2: 90}[orientation]
fp.set_size(fontsize*72./fig.dpi)
ax2.text(y,x, word, va="top", ha="left", color=color, rotation=rot,
fontproperties=fp)
print(wc.layout_)
plt.show()
上图是通过imshow显示的词云图像，下图是重新生成的词云。
现在你可能想在 plotly 而不是 matplotlib 中做同样的事情，但我对 plotly 不够熟练，无法直接在这里给出解决方案。