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Commit 521dc6be authored by Aldo Eduardo Niebla Cruz's avatar Aldo Eduardo Niebla Cruz
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examen resuelto

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08-Test2.ipynb
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...@@ -880,314 +880,6 @@ ...@@ -880,314 +880,6 @@
"palab_al, frecuenc_al = list(zip(*dict_ale))\n" "palab_al, frecuenc_al = list(zip(*dict_ale))\n"
] ]
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{
"cell_type": "code",
"execution_count": 264,
"metadata": {},
"outputs": [
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"name": "stdout",
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"text": [
"Help on class WordCloud in module wordcloud.wordcloud:\n",
"\n",
"class WordCloud(builtins.object)\n",
" | Word cloud object for generating and drawing.\n",
" | \n",
" | Parameters\n",
" | ----------\n",
" | font_path : string\n",
" | Font path to the font that will be used (OTF or TTF).\n",
" | Defaults to DroidSansMono path on a Linux machine. If you are on\n",
" | another OS or don't have this font, you need to adjust this path.\n",
" | \n",
" | width : int (default=400)\n",
" | Width of the canvas.\n",
" | \n",
" | height : int (default=200)\n",
" | Height of the canvas.\n",
" | \n",
" | prefer_horizontal : float (default=0.90)\n",
" | The ratio of times to try horizontal fitting as opposed to vertical.\n",
" | If prefer_horizontal < 1, the algorithm will try rotating the word\n",
" | if it doesn't fit. (There is currently no built-in way to get only\n",
" | vertical words.)\n",
" | \n",
" | mask : nd-array or None (default=None)\n",
" | If not None, gives a binary mask on where to draw words. If mask is not\n",
" | None, width and height will be ignored and the shape of mask will be\n",
" | used instead. All white (#FF or #FFFFFF) entries will be considerd\n",
" | \"masked out\" while other entries will be free to draw on. [This\n",
" | changed in the most recent version!]\n",
" | \n",
" | contour_width: float (default=0)\n",
" | If mask is not None and contour_width > 0, draw the mask contour.\n",
" | \n",
" | contour_color: color value (default=\"black\")\n",
" | Mask contour color.\n",
" | \n",
" | scale : float (default=1)\n",
" | Scaling between computation and drawing. For large word-cloud images,\n",
" | using scale instead of larger canvas size is significantly faster, but\n",
" | might lead to a coarser fit for the words.\n",
" | \n",
" | min_font_size : int (default=4)\n",
" | Smallest font size to use. Will stop when there is no more room in this\n",
" | size.\n",
" | \n",
" | font_step : int (default=1)\n",
" | Step size for the font. font_step > 1 might speed up computation but\n",
" | give a worse fit.\n",
" | \n",
" | max_words : number (default=200)\n",
" | The maximum number of words.\n",
" | \n",
" | stopwords : set of strings or None\n",
" | The words that will be eliminated. If None, the build-in STOPWORDS\n",
" | list will be used. Ignored if using generate_from_frequencies.\n",
" | \n",
" | background_color : color value (default=\"black\")\n",
" | Background color for the word cloud image.\n",
" | \n",
" | max_font_size : int or None (default=None)\n",
" | Maximum font size for the largest word. If None, height of the image is\n",
" | used.\n",
" | \n",
" | mode : string (default=\"RGB\")\n",
" | Transparent background will be generated when mode is \"RGBA\" and\n",
" | background_color is None.\n",
" | \n",
" | relative_scaling : float (default='auto')\n",
" | Importance of relative word frequencies for font-size. With\n",
" | relative_scaling=0, only word-ranks are considered. With\n",
" | relative_scaling=1, a word that is twice as frequent will have twice\n",
" | the size. If you want to consider the word frequencies and not only\n",
" | their rank, relative_scaling around .5 often looks good.\n",
" | If 'auto' it will be set to 0.5 unless repeat is true, in which\n",
" | case it will be set to 0.\n",
" | \n",
" | .. versionchanged: 2.0\n",
" | Default is now 'auto'.\n",
" | \n",
" | color_func : callable, default=None\n",
" | Callable with parameters word, font_size, position, orientation,\n",
" | font_path, random_state that returns a PIL color for each word.\n",
" | Overwrites \"colormap\".\n",
" | See colormap for specifying a matplotlib colormap instead.\n",
" | To create a word cloud with a single color, use\n",
" | ``color_func=lambda *args, **kwargs: \"white\"``.\n",
" | The single color can also be specified using RGB code. For example\n",
" | ``color_func=lambda *args, **kwargs: (255,0,0)`` sets color to red.\n",
" | \n",
" | regexp : string or None (optional)\n",
" | Regular expression to split the input text into tokens in process_text.\n",
" | If None is specified, ``r\"\\w[\\w']+\"`` is used. Ignored if using\n",
" | generate_from_frequencies.\n",
" | \n",
" | collocations : bool, default=True\n",
" | Whether to include collocations (bigrams) of two words. Ignored if using\n",
" | generate_from_frequencies.\n",
" | \n",
" | \n",
" | .. versionadded: 2.0\n",
" | \n",
" | colormap : string or matplotlib colormap, default=\"viridis\"\n",
" | Matplotlib colormap to randomly draw colors from for each word.\n",
" | Ignored if \"color_func\" is specified.\n",
" | \n",
" | .. versionadded: 2.0\n",
" | \n",
" | normalize_plurals : bool, default=True\n",
" | Whether to remove trailing 's' from words. If True and a word\n",
" | appears with and without a trailing 's', the one with trailing 's'\n",
" | is removed and its counts are added to the version without\n",
" | trailing 's' -- unless the word ends with 'ss'. Ignored if using\n",
" | generate_from_frequencies.\n",
" | \n",
" | repeat : bool, default=False\n",
" | Whether to repeat words and phrases until max_words or min_font_size\n",
" | is reached.\n",
" | \n",
" | Attributes\n",
" | ----------\n",
" | ``words_`` : dict of string to float\n",
" | Word tokens with associated frequency.\n",
" | \n",
" | .. versionchanged: 2.0\n",
" | ``words_`` is now a dictionary\n",
" | \n",
" | ``layout_`` : list of tuples (string, int, (int, int), int, color))\n",
" | Encodes the fitted word cloud. Encodes for each word the string, font\n",
" | size, position, orientation and color.\n",
" | \n",
" | Notes\n",
" | -----\n",
" | Larger canvases with make the code significantly slower. If you need a\n",
" | large word cloud, try a lower canvas size, and set the scale parameter.\n",
" | \n",
" | The algorithm might give more weight to the ranking of the words\n",
" | than their actual frequencies, depending on the ``max_font_size`` and the\n",
" | scaling heuristic.\n",
" | \n",
" | Methods defined here:\n",
" | \n",
" | __array__(self)\n",
" | Convert to numpy array.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | image : nd-array size (width, height, 3)\n",
" | Word cloud image as numpy matrix.\n",
" | \n",
" | __init__(self, font_path=None, width=400, height=200, margin=2, ranks_only=None, prefer_horizontal=0.9, 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='auto', regexp=None, collocations=True, colormap=None, normalize_plurals=True, contour_width=0, contour_color='black', repeat=False)\n",
" | Initialize self. See help(type(self)) for accurate signature.\n",
" | \n",
" | fit_words(self, frequencies)\n",
" | Create a word_cloud from words and frequencies.\n",
" | \n",
" | Alias to generate_from_frequencies.\n",
" | \n",
" | Parameters\n",
" | ----------\n",
" | frequencies : dict from string to float\n",
" | A contains words and associated frequency.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | self\n",
" | \n",
" | generate(self, text)\n",
" | Generate wordcloud from text.\n",
" | \n",
" | The input \"text\" is expected to be a natural text. If you pass a sorted\n",
" | list of words, words will appear in your output twice. To remove this\n",
" | duplication, set ``collocations=False``.\n",
" | \n",
" | Alias to generate_from_text.\n",
" | \n",
" | Calls process_text and generate_from_frequencies.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | self\n",
" | \n",
" | generate_from_frequencies(self, frequencies, max_font_size=None)\n",
" | Create a word_cloud from words and frequencies.\n",
" | \n",
" | Parameters\n",
" | ----------\n",
" | frequencies : dict from string to float\n",
" | A contains words and associated frequency.\n",
" | \n",
" | max_font_size : int\n",
" | Use this font-size instead of self.max_font_size\n",
" | \n",
" | Returns\n",
" | -------\n",
" | self\n",
" | \n",
" | generate_from_text(self, text)\n",
" | Generate wordcloud from text.\n",
" | \n",
" | The input \"text\" is expected to be a natural text. If you pass a sorted\n",
" | list of words, words will appear in your output twice. To remove this\n",
" | duplication, set ``collocations=False``.\n",
" | \n",
" | Calls process_text and generate_from_frequencies.\n",
" | \n",
" | ..versionchanged:: 1.2.2\n",
" | Argument of generate_from_frequencies() is not return of\n",
" | process_text() any more.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | self\n",
" | \n",
" | process_text(self, text)\n",
" | Splits a long text into words, eliminates the stopwords.\n",
" | \n",
" | Parameters\n",
" | ----------\n",
" | text : string\n",
" | The text to be processed.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | words : dict (string, int)\n",
" | Word tokens with associated frequency.\n",
" | \n",
" | ..versionchanged:: 1.2.2\n",
" | Changed return type from list of tuples to dict.\n",
" | \n",
" | Notes\n",
" | -----\n",
" | There are better ways to do word tokenization, but I don't want to\n",
" | include all those things.\n",
" | \n",
" | recolor(self, random_state=None, color_func=None, colormap=None)\n",
" | Recolor existing layout.\n",
" | \n",
" | Applying a new coloring is much faster than generating the whole\n",
" | wordcloud.\n",
" | \n",
" | Parameters\n",
" | ----------\n",
" | random_state : RandomState, int, or None, default=None\n",
" | If not None, a fixed random state is used. If an int is given, this\n",
" | is used as seed for a random.Random state.\n",
" | \n",
" | color_func : function or None, default=None\n",
" | Function to generate new color from word count, font size, position\n",
" | and orientation. If None, self.color_func is used.\n",
" | \n",
" | colormap : string or matplotlib colormap, default=None\n",
" | Use this colormap to generate new colors. Ignored if color_func\n",
" | is specified. If None, self.color_func (or self.color_map) is used.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | self\n",
" | \n",
" | to_array(self)\n",
" | Convert to numpy array.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | image : nd-array size (width, height, 3)\n",
" | Word cloud image as numpy matrix.\n",
" | \n",
" | to_file(self, filename)\n",
" | Export to image file.\n",
" | \n",
" | Parameters\n",
" | ----------\n",
" | filename : string\n",
" | Location to write to.\n",
" | \n",
" | Returns\n",
" | -------\n",
" | self\n",
" | \n",
" | to_html(self)\n",
" | \n",
" | to_image(self)\n",
" | \n",
" | ----------------------------------------------------------------------\n",
" | Data descriptors defined here:\n",
" | \n",
" | __dict__\n",
" | dictionary for instance variables (if defined)\n",
" | \n",
" | __weakref__\n",
" | list of weak references to the object (if defined)\n",
"\n"
]
}
],
"source": [
"help(WordCloud)"
]
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
......
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