Python：wordcloud.wordcloud()函数的参数解析及其说明

Python：wordcloud.wordcloud()函数的参数解析及其说明

 

 

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wordcloud.wordcloud()函数的参数解析及其说明

 

 

wordcloud.wordcloud()函数的参数解析及其说明

class WordCloud Found at: wordcloud.wordcloudclass WordCloud(object):     """Word cloud object for generating and drawing.          Parameters     ----------     font_path: string     Font path to the font that will be used (OTF or TTF).     Defaults to DroidSansMono path on a Linux machine. If you are on another OS or don't have this font, you need to adjust this path.          width : int (default=400)     Width of the canvas.          height : int (default=200)     Height of the canvas.          prefer_horizontal : float (default=0.90)     The ratio of times to try horizontal fitting as opposed to vertical.  If prefer_horizontal < 1, the algorithm will try rotating the word   if it doesn't fit. (There is currently no built-in way to get only vertical words.)          mask : nd-array or None (default=None)     If not None, gives a binary mask on where to draw words. If mask  is not  None, width and height will be ignored and the shape of mask  will be used instead. All white (#FF or #FFFFFF) entries will be considerd   "masked out" while other entries will be free to draw on. [This  changed in the most recent version!]          scale : float (default=1)     Scaling between computation and drawing. For large word-cloud   images,     using scale instead of larger canvas size is significantly faster, but might lead to a coarser fit for the words.          min_font_size : int (default=4)     Smallest font size to use. Will stop when there is no more room   in this  size.          font_step : int (default=1)     Step size for the font. font_step > 1 might speed up computation  but   give a worse fit.          max_words : number (default=200)     The maximum number of words.          stopwords : set of strings or None     The words that will be eliminated. If None, the build-in  STOPWORDS  list will be used.          background_color : color value (default="black")     Background color for the word cloud image.          max_font_size : int or None (default=None)     Maximum font size for the largest word. If None, height of the    image is used.          mode : string (default="RGB")     Transparent background will be generated when mode is "RGBA"  and  background_color is None.          relative_scaling : float (default=.5)     Importance of relative word frequencies for font-size.  With  relative_scaling=0, only word-ranks are considered.  With   relative_scaling=1, a word that is twice as frequent will have twice the size.  If you want to consider the word frequencies and not  only  their rank, relative_scaling around .5 often looks good.          .. versionchanged: 2.0     Default is now 0.5.          color_func: callable, default=None     Callable with parameters word, font_size, position, orientation,  font_path, random_state that returns a PIL color for each word.     Overwrites "colormap". See colormap for specifying a matplotlib colormap instead.          regexp : string or None (optional)     Regular expression to split the input text into tokens in   process_text.     If None is specified, ``r"\w[\w']+"`` is used.          collocations : bool, default=True     Whether to include collocations (bigrams) of two words.          .. versionadded: 2.0          colormap : string or matplotlib colormap, default="viridis"     Matplotlib colormap to randomly draw colors from for each   word.     Ignored if "color_func" is specified.          .. versionadded: 2.0          normalize_plurals : bool, default=True     Whether to remove trailing 's' from words. If True and a word appears with and without a trailing 's', the one with trailing 's'  is removed and its counts are added to the version without  trailing 's' -- unless the word ends with 'ss'.     

类WordCloud在:WordCloud找到。wordcloudclass WordCloud(对象): 用于生成和绘制的Word云对象。 参数 ----------font_path:字符串 要使用的字体(OTF或TTF)的字体路径。 Linux机器上的默认DroidSansMono路径。如果你在另一个操作系统上或者没有这个字体，你需要调整这个路径。width :int(默认=400) 画布的宽度。height :int(默认=200) 画布的高度。prefer_horizontal : float(默认=0.90) 尝试水平拟合与垂直拟合的时间比。如果prefer_horizontal < 1，算法将尝试旋转不适合的单词。(目前还没有内置的方法来只获取垂直的单词。)mask : nd-array或None(默认=None) 如果没有，给出一个二进制掩码在哪里绘制单词。如果遮罩不是None，宽度和高度将被忽略，而使用遮罩的形状。所有白色(#FF或#FFFFFF)的参赛作品将被视为“屏蔽”，而其他参赛作品将可以自由提取。[这在最近的版本中有所改变!]scale :浮动(默认=1) 在计算和绘图之间缩放。对于大的字云图像， 使用scale而不是更大的画布尺寸会快得多，但可能会导致适合文字的粗化。min_font_size : int(默认=4)使用的最小字体大小。将停止时，没有更多的空间在这个大小。font_step : int(默认=1) 字体的步长。font_step > 1可能会加速计算，但是匹配效果更差。max_words :数字(默认=200)单词的最大数量。stopwords :一组字符串或没有将被删除的单词。如果没有，将使用内置的STOPWORDS列表。background_color :颜色值(默认=“黑色”)背景色为字云图像。max_font_size : int或None(默认=None) 为最大的字的最大字体大小。如果没有，则使用图像的高度。mode :string(默认="RGB") 当模式为“RGBA”，background_color为None时，将生成透明背景。relative_scaling :浮动(默认= 5) 字体大小的相对频率的重要性。对于relative_scaling=0，只考虑单词的等级。使用relative_scaling=1，出现频率两倍的单词的大小也会增加一倍。如果您想要考虑单词的频率而不仅仅是它们的排名，那么在5左右的relative_scaling通常看起来不错。 . .versionchanged: 2.0 现在默认值是0.5。color_func:可调用，默认=无 可调用参数word, font_size, position, orientation, font_path, random_state，为每个单词返回一个PIL颜色。 覆盖“colormap”。请参阅colormap以指定matplotlib的colormap。regexp :字符串或无(可选) 正则表达式，用于在process_text中将输入文本分割为令牌。 如果没有指定,“r”\ w (\ w) +”“使用。 &collocations :bool, default=True是否包含两个单词的搭配(双字母组合)。 . .versionadded: 2.0colormap : string或matplotlib colormap，默认="viridis" Matplotlib colormap为每个单词随机绘制颜色。 如果指定了“color_func”，则忽略。 . .versionadded: 2.0normalize_plurals : bool, default=True 是否删除单词后面的“s”。如果是真的，并且一个单词出现时带有或不带有结尾s，那么带有结尾s的单词将被删除，并将其计数添加到没有结尾s的版本中——除非这个单词以“ss”结尾。    Attributes     ----------     ``words_`` : dict of string to float     Word tokens with associated frequency.          .. versionchanged: 2.0     ``words_`` is now a dictionary          ``layout_ `` : list of tuples (string, int, (int, int), int, color))     Encodes the fitted word cloud. Encodes for each word the string,   font size, position, orientation and color.          Notes     -----     Larger canvases with make the code significantly slower. If you   need a  large word cloud, try a lower canvas size, and set the scale  parameter.          The algorithm might give more weight to the ranking of the words  than their actual frequencies, depending on the ``max_font_size `   and the scaling heuristic.     """属性 --------- ' ' words_ ' ':浮动字符串的dict 具有相关频率的单词标记。 . .versionchanged: 2.0 “words_”现在是一本字典 ' ' layout_ ' ':元组列表(字符串，int， (int, int)， int, color)) 编码合适的词云。为每个单词编码字符串、字体大小、位置、方向和颜色。 笔记 ----- 较大的画布使代码明显地变慢。如果你需要一个大的字云，尝试一个较低的画布大小，并设置比例参数。 根据' ' max_font_size '和缩放启发式，算法可能给予单词的排名比它们的实际频率更多的权重。 ”“”

    def __init__(self, font_path=None, width=400, height=200,       margin=2,          ranks_only=None, prefer_horizontal=.9, mask=None, scale=1,          color_func=None, max_words=200, min_font_size=4,          stopwords=None, random_state=None,           background_color='black',          max_font_size=None, font_step=1, mode="RGB",          relative_scaling=.5, regexp=None, collocations=True,          colormap=None, normalize_plurals=True):         if font_path is None:             font_path = FONT_PATH         if color_func is None and colormap is None:             # we need a color map             import matplotlib             version = matplotlib.__version__             if version[0] < "2" and version[2] < "5":                 colormap = "hsv"             else:                 colormap = "viridis"         self.colormap = colormap         self.collocations = collocations         self.font_path = font_path         self.width = width         self.height = height         self.margin = margin         self.prefer_horizontal = prefer_horizontal         self.mask = mask         self.scale = scale         self.color_func = color_func or colormap_color_func(colormap)         self.max_words = max_words         self.stopwords = stopwords if stopwords is not None else           STOPWORDS         self.min_font_size = min_font_size         self.font_step = font_step         self.regexp = regexp         if isinstance(random_state, int):             random_state = Random(random_state)         self.random_state = random_state         self.background_color = background_color         self.max_font_size = max_font_size         self.mode = mode         if relative_scaling < 0 or relative_scaling > 1:             raise ValueError(                 "relative_scaling needs to be "                 "between 0 and 1, got %f." %                  relative_scaling)         self.relative_scaling = relative_scaling         if ranks_only is not None:             warnings.warn("ranks_only is deprecated and will be               removed as"                 " it had no effect. Look into relative_scaling.",                  DeprecationWarning)         self.normalize_plurals = normalize_plurals          def fit_words(self, frequencies):         """Create a word_cloud from words and frequencies.

        Alias to generate_from_frequencies.

        Parameters         ----------         frequencies : dict from string to float             A contains words and associated frequency.

        Returns         -------         self         """         return self.generate_from_frequencies(frequencies)          def generate_from_frequencies(self, frequencies,       max_font_size=None):         """Create a word_cloud from words and frequencies. Parameters

        ----------         frequencies : dict from string to float             A contains words and associated frequency.

        max_font_size : int             Use this font-size instead of self.max_font_size

        Returns         -------         self

        """         # make sure frequencies are sorted and normalized         frequencies = sorted(frequencies.items(), key=itemgetter(1),           reverse=True)         if len(frequencies)