If you don't know what a Markov Chain is I recommend reading up on it and checking out this visual explanation. To put it simply, Markov Chain represent probabilistic state changes inside a Finite-State-Machine. The state transition probabilities can be easily represented as a matrix but in practice (software) that leaves lots of entries being 0 and taking up memory, so a more elegant solution is a nested hash map.
In the code above the following are used:
// represents a grouping of individual words
// eg: []string{"I", "am", "Alex"}, this can be extracted
// from an original string of any form or shape:
// "I am Alex", "I am Alex", "I:am:Alex"
// and it's all up to the caller to split their strings into sequences
type Sequence []string// a pairs represents a possible transition between a sequence of n words
// and the next (single) word
// the Current sequence must be of an equal lenght to the chain pair size
// meaning you can't have some transitions for 2-grouped words and 1-grouped words
type Pair struct {
Current Sequence
Next string
}// by having a
type transitionMap map[string]int
// and then nested inside
frequencyMatrix map[string]transitionMap
// we generate our mapping of all encountered
// sequences to their respective next word
// and the number of times this occursOnce your wrap your head around these structures, the rest of the functions are easy to understand.
The text below was generated on a 2-paired sequence chain with a student movie script as input.
You know I can't KEN I understand. KEN opens the door to
a soaking wet KEN, who stands on the pink scissors and
picks them up, toying with them. KEN glances around for
his wallet. DEBRA (Comforting) There's nothing to be
embarrassed about you know. Lots of people it happens.
KEN grunts. KEN Yeah. The bird chirps from its cage in
the corner. KEN tries to scream but is unable to pull in
oxygen. The pressure in his ears begins to burst as the
bathtub overflows. 29. A figure appears above him,
blurry through the water.
If you have Go installed, you can simply run:
go get cpl.li/go/markov/markov-cliI provided an example main function with stdin input and basic flag parsing for generating n words from the input data.
package main
import (
"flag"
"fmt"
"io/ioutil"
"log"
"os"
"strings"
"cpl.li/go/markov"
)
func main() {
// handle flags
maxWords := flag.Int("words", 100, "max words to generate (default 100)")
pairSize := flag.Int("pairs", 2, "size of a word pair (default 2)")
flag.Parse()
c := NewChain(*pairSize) // create markov chain
// read stdin
data, err := ioutil.ReadAll(os.Stdin)
if err != nil {
log.Fatal(err)
}
// give data as sequence to chain model
c.Add(strings.Fields(string(data)))
b := c.NewBuilder(nil) // create builder on top of chain
b.Generate(*maxWords - c.PairSize) // generate new words
fmt.Println(b.String()) // print end product
}