Index

Modules: nimkov, nimkov/constants, nimkov/generator, nimkov/typedefs, nimkov/utils, nimkov/validators.

API symbols

add:

• generator: proc add(generator: MarkovGenerator; samples: seq[string])
• generator: proc add(generator: MarkovGenerator; sample: string)

clear:

• generator: proc clear(generator: MarkovGenerator)

defaultValidator:

• validators: proc defaultValidator(): MarkovValidator

generate:

• generator: proc generate(generator: MarkovGenerator; attempts: Positive = 1; begin = none string; validator: MarkovValidator = defaultValidator()): string

MarkovEmptyModelError:

• typedefs: object MarkovEmptyModelError

MarkovError:

• typedefs: object MarkovError

MarkovGenerateOptions:

• typedefs: object MarkovGenerateOptions

MarkovGenerator:

• generator: type MarkovGenerator

MarkovGeneratorModelType:

• typedefs: enum MarkovGeneratorModelType

MarkovNotEnoughSamplesError:

• typedefs: object MarkovNotEnoughSamplesError

MarkovOutOfAttemptsError:

• typedefs: object MarkovOutOfAttemptsError

MarkovProcessWordProc:

• typedefs: type MarkovProcessWordProc

MarkovValidator:

• typedefs: type MarkovValidator

mgtSimple:

• typedefs: MarkovGeneratorModelType.mgtSimple

mgtWeighted:

• typedefs: MarkovGeneratorModelType.mgtWeighted

model:

• generator: proc model(generator: MarkovGenerator): Table[string, CountTable[string]]

mrkvEnd:

• constants: const mrkvEnd

mrkvStart:

• constants: const mrkvStart

newMarkov:

• generator: proc newMarkov(samples = newSeq(); wordProc: MarkovProcessWordProc = (proc ( word: string): Option[string] = result = some unicodeStringToLower(word)); kind: MarkovGeneratorModelType = mgtSimple): MarkovGenerator

symbolsCount:

• validators: proc symbolsCount(min = 0; max = int.high): MarkovValidator

unicodeStringToLower:

• utils: proc unicodeStringToLower(str: string): string

weightedRandom:

• utils: proc weightedRandom[T](weights: openArray[tuple[key: T, weight: int]]): T

wordsCount:

• validators: proc wordsCount(min = 0; max = int.high): MarkovValidator