kumo

Include `kumo-tokenizers` if you want Chinese serialization. More languages to come.
```xml

    com.kennycason
    kumo-tokenizers
    1.28

final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
frequencyAnalyzer.setWordFrequenciesToReturn(300);
frequencyAnalyzer.setMinWordLength(4);
frequencyAnalyzer.setStopWords(loadStopWords());

final List wordFrequencies = frequencyAnalyzer.load("text/datarank.txt");
final Dimension dimension = new Dimension(500, 312);
final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.PIXEL_PERFECT);
wordCloud.setPadding(2);
wordCloud.setBackground(new PixelBoundryBackground("backgrounds/whale_small.png"));
wordCloud.setColorPalette(new ColorPalette(new Color(0x4055F1), new Color(0x408DF1), new Color(0x40AAF1), new Color(0x40C5F1), new Color(0x40D3F1), new Color(0xFFFFFF)));
wordCloud.setFontScalar(new LinearFontScalar(10, 40));
wordCloud.build(wordFrequencies);
wordCloud.writeToFile("kumo-core/output/whale_wordcloud_small.png");

final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
final List wordFrequencies = frequencyAnalyzer.load("text/my_text_file.txt");
final Dimension dimension = new Dimension(600, 600);
final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.PIXEL_PERFECT);
wordCloud.setPadding(2);
wordCloud.setBackground(new CircleBackground(300));
wordCloud.setColorPalette(new ColorPalette(new Color(0x4055F1), new Color(0x408DF1), new Color(0x40AAF1), new Color(0x40C5F1), new Color(0x40D3F1), new Color(0xFFFFFF)));
wordCloud.setFontScalar(new SqrtFontScalar(10, 40));
wordCloud.build(wordFrequencies);
wordCloud.writeToFile("kumo-core/output/datarank_wordcloud_circle_sqrt_font.png");

final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
final List wordFrequencies = frequencyAnalyzer.load("text/my_text_file.txt");
final Dimension dimension = new Dimension(600, 600);
final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.RECTANGLE);
wordCloud.setPadding(0);
wordCloud.setBackground(new RectangleBackground(dimension));
wordCloud.setColorPalette(new ColorPalette(Color.RED, Color.GREEN, Color.YELLOW, Color.BLUE));
wordCloud.setFontScalar(new LinearFontScalar(10, 40));
wordCloud.build(wordFrequencies);
wordCloud.writeToFile("kumo-core/output/wordcloud_rectangle.png");

final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
frequencyAnalyzer.setWordFrequenciesToReturn(500);
frequencyAnalyzer.setMinWordLength(4); 
final List wordFrequencies = frequencyAnalyzer.load("text/my_text_file.txt");
final Dimension dimension = new Dimension(600, 600);
final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.PIXEL_PERFECT);
wordCloud.setPadding(2);
wordCloud.setBackground(new CircleBackground(300));
// colors followed by and steps between
wordCloud.setColorPalette(new LinearGradientColorPalette(Color.RED, Color.BLUE, Color.GREEN, 30, 30));
wordCloud.setFontScalar( new SqrtFontScalar(10, 40));
wordCloud.build(wordFrequencies);
wordCloud.writeToFile("kumo-core/output/wordcloud_gradient_redbluegreen.png");

final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
frequencyAnalyzer.setWordFrequenciesToReturn(600);
frequencyAnalyzer.setMinWordLength(2);
frequencyAnalyzer.setWordTokenizer(new ChineseWordTokenizer());

final List wordFrequencies = frequencyAnalyzer.load("text/chinese_language.txt");
final Dimension dimension = new Dimension(600, 600);
final WordCloud wordCloud = new WordCloud(dimension, CollisionMode.PIXEL_PERFECT);
wordCloud.setPadding(2);
wordCloud.setBackground(new CircleBackground(300));
wordCloud.setColorPalette(new ColorPalette(new Color(0xD5CFFA), new Color(0xBBB1FA), new Color(0x9A8CF5), new Color(0x806EF5)));
wordCloud.setFontScalar(new SqrtFontScalar(12, 45));
wordCloud.build(wordFrequencies);
wordCloud.writeToFile("kumo-core/output/chinese_language_circle.png");

final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
frequencyAnalyzer.setWordFrequenciesToReturn(750);
frequencyAnalyzer.setMinWordLength(4);
frequencyAnalyzer.setStopWords(loadStopWords());

final List wordFrequencies = frequencyAnalyzer.load("text/new_york_positive.txt");
final List wordFrequencies2 = frequencyAnalyzer.load("text/new_york_negative.txt");
final Dimension dimension = new Dimension(600, 600);
final PolarWordCloud wordCloud = new PolarWordCloud(dimension, CollisionMode.PIXEL_PERFECT, PolarBlendMode.BLUR);
wordCloud.setPadding(2);
wordCloud.setBackground(new CircleBackground(300));
wordCloud.setFontScalar(new SqrtFontScalar(10, 40));
wordCloud.build(wordFrequencies, wordFrequencies2);
wordCloud.writeToFile("kumo-core/output/polar_newyork_circle_blur_sqrt_font.png");

final FrequencyAnalyzer frequencyAnalyzer = new FrequencyAnalyzer();
frequencyAnalyzer.setWordFrequenciesToReturn(300);
frequencyAnalyzer.setMinWordLength(5);
frequencyAnalyzer.setStopWords(loadStopWords());

final List wordFrequencies = frequencyAnalyzer.load("text/new_york_positive.txt");
final List wordFrequencies2 = frequencyAnalyzer.load("text/new_york_negative.txt");
final Dimension dimension = new Dimension(600, 386);
final LayeredWordCloud layeredWordCloud = new LayeredWordCloud(2, dimension, CollisionMode.PIXEL_PERFECT);

layeredWordCloud.setPadding(0, 1);
layeredWordCloud.setPadding(1, 1);

layeredWordCloud.setFontOptions(0, new KumoFont("LICENSE PLATE", FontWeight.BOLD));
layeredWordCloud.setFontOptions(1, new KumoFont("Comic Sans MS", FontWeight.BOLD));

layeredWordCloud.setBackground(0, new PixelBoundryBackground("backgrounds/cloud_bg.bmp"));
layeredWordCloud.setBackground(1, new PixelBoundryBackground("backgrounds/cloud_fg.bmp"));

layeredWordCloud.setColorPalette(0, new ColorPalette(new Color(0xABEDFF), new Color(0x82E4FF), new Color(0x55D6FA)));
layeredWordCloud.setColorPalette(1, new ColorPalette(new Color(0xFFFFFF), new Color(0xDCDDDE), new Color(0xCCCCCC)));

layeredWordCloud.setFontScalar(0, new SqrtFontScalar(10, 40));
layeredWordCloud.setFontScalar(1, new SqrtFontScalar(10, 40));

layeredWordCloud.build(0, wordFrequencies);
layeredWordCloud.build(1, wordFrequencies2);
layeredWordCloud.writeToFile("kumo-core/output/layered_word_cloud.png");

final Dimension dimension = new Dimension(2000, 2000);
ParallelLayeredWordCloud parallelLayeredWordCloud = new ParallelLayeredWordCloud(4, dimension, CollisionMode.PIXEL_PERFECT);

// Setup parts for word clouds
final Normalizer[] NORMALIZERS = new Normalizer[] { 
    new UpperCaseNormalizer(), 
    new LowerCaseNormalizer(),
    new BubbleTextNormalizer(),
    new StringToHexNormalizer() 
};
final Font[] FONTS = new Font[] { 
            new Font("Lucida Sans", Font.PLAIN, 10), 
            new Font("Comic Sans", Font.PLAIN, 10),
            new Font("Yu Gothic Light", Font.PLAIN, 10), 
            new Font("Meiryo", Font.PLAIN, 10) 
};
final List> listOfWordFrequencies = new ArrayList<>();
final Point[] positions = new Point][] { new Point(0, 0), new Point(0, 1000), new Point(1000, 0), new Point(1000, 1000) };
final Color[] colors = new Color[] { Color.RED, Color.WHITE, new Color(0x008080)/* TEAL */, Color.GREEN };

// set up word clouds
for (int i = 0; i ` yourself, or you can load in a text file containing the word frequency and word pairs.
The `FrequencyFileLoader` can be used to load such files. The required format is:

Order does not matter as the `FrequencyFileLoader` will automatically sort the pairs.

### Tokenizers

Tokenizers are the code that splits a sentence/text into a list of words. Currently only two tokenizers are built into Kumo.
To add your own just create a class that override the `Tokenizer` interface and call the `FrequencyAnalyzer.setTokenizer()` or `FrequencyAnalyzer.addTokenizer()`.

| Tokenizer   |
|-------------|
| WhiteSpaceWordTokenizer |
| ChineseWordTokenizer |

### Filters

After tokenization, filters are applied to each word to determine whether or not should be omitted from the word list. 

To add set the filter, call `FrequencyAnalyzer.setFilter()` or `FrequencyAnalyzer.addFilter()`

| Tokenizer   | Description |
|-------------|-------------|
| UrlFilter | A filter to remove words that are urls. |
| CompositeFilter | A wrapper of a collection of filters. |
| StopWordFilter | Internally used, the FrequencyAnalyzer makes this filter easy to use via `FrequencyAnalyzer.setStopWords()`. |
| WordSizeFilter | Internally used, the FrequencyAnalyzer makes this filter easy to use via `FrequencyAnalyzer.setMinWordLength()` and `FrequencyAnalyzer.setMaxWordLength()`. |

### Normalizers

After word tokenization and filtering has occurred you can further transform each word via a normalizer.
The default normalizer ia `lowerCase•characterStripping*trimToEmpty(word)`, the normalizer is even named `DefaultNormalizer`

To add set the normalizer, call `FrequencyAnalyzer.setNormalizer()` or `FrequencyAnalyzer.addNormalizer()`

| Normalizers | Description |
|-------------|-------------|
| CharacterStrippingNormalizer | Constructed with a Pattern, it will replace all matched occurrences with a configurable 'replaceWith' string. The default pattern is `\\.|:|;|\\(|\\)|\"|,|\\?|,|!||/`|
| LowerCaseNormalizer | Converts all text to lowercase. |
| UpperCaseNormalizer | Converts all text to uppercase. |
| TrimToEmptyNormalizer | Trims the text down to an empty string, even if null. |
| UpsideDownNormalizer | Converts A-Z,a-z,0-9 character to an upside-down variant. |
| StringToHexNormalizer | Converts each character to it's hex value and concatenates them. |
| DefaultNormalizer | Combines the TrimToEmptyNormalizer, CharacterStrippingNormalizer, and LowerCaseNormalizer. |
| BubbleTextNormalizer | Replaces A-Z,a-z with characters enclosed in Bubbles ⓐ-ⓩⒶ-Ⓩ (requires a supporting font) |

### Command Line Interface (CLI)

Kumo can now be accessed via CLI. It is not quite as flexible as the programmatic interface yet but should support most of the common needs.

The CLI Documentation can be found [here](https://github.com/kennycason/kumo/blob/master/CLI.md).

The below examples assume you have the jar installed under the name of "kumo". To install via Brew run the following command.

`brew install https://raw.githubusercontent.com/kennycason/kumo/master/script/kumo.rb`

Examples:

Create a standard word cloud.

Create a standard word cloud excluding stop words.

Create a standard word cloud with a limited word count.

Create a sta