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https://github.com/htm-community/htm

Hierarchical Temporal Memory implementation in Golang
https://github.com/htm-community/htm

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Hierarchical Temporal Memory implementation in Golang

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htm

===



Hierarchical Temporal Memory Implementation in Golang



[![GoDoc](https://godoc.org/github.com/nupic-community/htm?status.png)](https://godoc.org/github.com/nupic-community/htm)

[![Build Status](https://travis-ci.org/nupic-community/htm.svg?branch=master)](https://travis-ci.org/nupic-community/htm)



This is a direct port of the spatial & temporal poolers, temporal memory, and encoders as they currently exist in Numenta's Nupic Project. This project was done as a learning exercise, no effort has been made to optimize this implementation and it was not designed for production use.



The Nupic project basically demonstrates the CLA, a single stage of the cortical hierarchy. Eventually this same code can be extended to form a full HTM hierarchy. https://github.com/numenta/nupic



##Changes From Numentas Implementation

 * Temporal pooler ephemeral state is stored in strongly typed struct rather than a hashmap. t-1 vars have "last" appended to their names.

 * Temporal pooler params stored in "params" sub struct

 * Binary data structures are used rather than ints

 * No C++ dependency everything is written in Go



##Current State of Project

 * Temporal and Spatial poolers pass basic tests

 * Temporal memory passes basic unit tests

 * Basic scaler encoder implemented



##Todo

 ~~* Finish temporal unit tests~~

 * Implement a better sparse binary matrix structure with versions optimized for col or row heavy access.

 * Implement better binary datastructure

 * Refactor to be more idiomatic Go. It is basically a line for line port of the python implementation, it could be refactored to make better use of Go's type system.

 * Implement some of the common encoders



##Examples



###Temporal Pooler

```go

package main



import (

	"fmt"

	"github.com/zacg/htm"

	"github.com/nupic-community/htmutils"

)



func main() {

	tps := htm.NewTemporalPoolerParams()

	tps.Verbosity = 0

	tps.NumberOfCols = 50

	tps.CellsPerColumn = 2

	tps.ActivationThreshold = 8

	tps.MinThreshold = 10

	tps.InitialPerm = 0.5

	tps.ConnectedPerm = 0.5

	tps.NewSynapseCount = 10

	tps.PermanenceDec = 0.0

	tps.PermanenceInc = 0.1

	tps.GlobalDecay = 0

	tps.BurnIn = 1

	tps.PamLength = 10

	tps.CollectStats = true

	tp := htm.NewTemporalPooler(*tps)



	//Mock encoding of ABCDE

	inputs := make([][]bool, 5)

	inputs[0] = boolRange(0, 9, 50)   //bits 0-9 are "on"

	inputs[1] = boolRange(10, 19, 50) //bits 10-19 are "on"

	inputs[2] = boolRange(20, 29, 50) //bits 20-29 are "on"

	inputs[3] = boolRange(30, 39, 50) //bits 30-39 are "on"

	inputs[4] = boolRange(40, 49, 50) //bits 40-49 are "on"



	//Learn 5 sequences above

	for i := 0; i < 10; i++ {

		for p := 0; p < 5; p++ {

			tp.Compute(inputs[p], true, false)

		}

		tp.Reset()

	}



	//Predict sequences

	for i := 0; i < 4; i++ {

		tp.Compute(inputs[i], false, true)

		p := tp.DynamicState.InfPredictedState



		fmt.Printf("Predicted: %v From input: %v \n", p.NonZeroRows(), utils.OnIndices(inputs[i]))



	}



}



//helper method for creating boolean sequences

func boolRange(start int, end int, length int) []bool {

	result := make([]bool, length)

	for i := start; i <= end; i++ {

		result[i] = true

	}

	return result

}



```



###Spatial Pooler

```go

package main



import (

	"fmt"

	"github.com/davecheney/profile"

	"github.com/zacg/htm"

	"github.com/nupic-community/htmutils"

	"math/rand"

)



func main() {

	

	ssp := htm.NewSpParams()

	ssp.ColumnDimensions = []int{64, 64}

	ssp.InputDimensions = []int{32, 32}

	ssp.PotentialRadius = ssp.NumInputs()

	ssp.NumActiveColumnsPerInhArea = int(0.02 * float64(ssp.NumColumns()))

	ssp.GlobalInhibition = true

	ssp.SynPermActiveInc = 0.01

	ssp.SpVerbosity = 10

	sp := htm.NewSpatialPooler(ssp)

	



	activeArray := make([]bool, sp.NumColumns())

	inputVector := make([]bool, sp.NumInputs())



	for idx, _ := range inputVector {

		inputVector[idx] = rand.Intn(5) >= 2

	}



	sp.Compute(inputVector, true, activeArray, sp.InhibitColumns)



	fmt.Println("Active Indices:", utils.OnIndices(activeArray))



}



```



###Temporal Memory

```go



	tmp := NewTemporalMemoryParams()

	tmp.MaxNewSynapseCount = 1000



	tm := NewTemporalMemory(tmp)



```



###Encoding

```go



	//Create new scaler encoder

	p := NewScalerEncoderParams(3, 1, 8)

	p.Radius = 1.5

	p.Periodic = true

	p.Verbosity = 5

	e := NewScalerEncoder(p)



	//Encode "1"

	encoded := e.Encode(1, false)



	//Print results

	fmt.Printfn("1 Encoded as: %v", utils.Bool2Int(encoded))



```



```go



	//Create new date encoder

	p := NewDateEncoderParams()

	p.SeasonWidth = 3

	p.DayOfWeekWidth = 1

	p.WeekendWidth = 3

	p.TimeOfDayWidth = 5

	p.Verbosity = 5

	de := NewDateEncoder(p)

	

	d := time.Date(2010, 11, 4, 14, 55, 0, 0, time.UTC)

	encoded := de.Encode(d)



	//Print results

	fmt.Printfn("%v Encoded as: %v", d, utils.Bool2Int(encoded))



```