Home

Class goog.text.LoremIpsum

Generates random strings of "lorem ipsum" text, based on the word distribution of a sample text, using the words in a dictionary.

Instance Method Summary
chooseRandomStart_() ⇒ ?Array

Picks a random starting chain.

generateChains_(string sample)

Generates the chains and starts values required for sentence generation.

generateParagraph(boolean opt_startWithLorem) ⇒ string

Generates a single lorem ipsum paragraph, of random length.

generateParagraphStatistics_(string sample)

Calculates the mean and standard deviation of the lengths of paragraphs (in sentences) in a sample text.

generateSentence(boolean opt_startWithLorem) ⇒ string

Generates a single sentence, of random length.

generateSentenceStatistics_(string sample)

Calculates the mean and standard deviation of the lengths of sentences (in words) in a sample text.

generateStatistics_(string sample)

Calculates the mean and standard deviation of sentence and paragraph lengths.

initializeDictionary_(string dictionary)

Sets the generator to use a given selection of words for generating sentences with.

Static Method Summary
arrayLength_(?Array array) ⇒ number

Returns the length of an array. Written as a function so it can be used as a function parameter.

chooseClosest(?Array values, number target) ⇒ number

Find the number in the list of values that is closest to the target.

getWordInfo_(string word) ⇒ ?Array

Gets info about a word used as part of the lorem ipsum algorithm.

isNotEmptyOrWhitepace_(string text) ⇒ boolean

Returns the text is not empty or just whitespace.

randomChoice_(?Array array) ⇒ <Any Type>

Picks a random element of the array.

randomNormal_(number mu, number sigma)

Generates a random number for a normal distribution with the specified mean and sigma.

splitParagraphs_(string text) ⇒ ?Array

Splits a piece of text into paragraphs.

splitSentences_(string text) ⇒ ?Array

Splits a piece of text into sentences.

splitWords_(string text) ⇒ ?Array

Splits a piece of text into words..