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'.
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. """
