gomi

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 Go to latest Published: Apr 3, 2019 License: MIT Imports: 23 Imported by: 0

README

gomi is a software package for the evaluation of morphological intelligence measures on data. gomi includes all currently available morphological intelligence measures. This includes measures with continuous estimators as well as measures that use a discrete estimator.

The following sections will only provide minimal information about the measures. The goal of this post to provide information about the application of the measures, not an introduction of the measures themselves. For this purpose, please visit the other posts on these pages:

gomi is written in Go. For the installation of Go, please read the installation documentation provided here. Pre-compiled binaries of gomi for Windows, Linux, and macOS are available in the release files here.

Once Go is installed, gomi can easily be installed using the following commands:

go get github.com/kzahedi/gomi

The following two packages are required and might have to be installed manually:

go get github.com/kzahedi/goent
go get github.com/kzahedi/utils

A zip (and tarball) of stable releases can be downloaded [here].

Using the gomi binary

To calculate MI_W with the binary, use the following command line parameters:

gomi -mi MI_W -file musfib.csv -wi 1,2,3 -ai 9 -v -bins 300 -o MI_W.csv

The file musfib was used in [1] and can be downloaded here.

Explanation of the command line options used in the example above:

Option Explanation
-mi MI_W Chooses MI_W as the measure
-file musfib.csv Data is provided in the file musfib.csv
-wi 1,2,3 Columns 1,2,3 of the data provided in musfib.csv define the world state (counting starts with 0)
-ai 9 Column 9 of the data provided in musfib.csv defines the action state (counting starts with 0)
-v gomi will print useful information while it is running and it will print the result
-bins 300 Global definition of the binning. This value will be used for each of the four columns
-o MI_W.csv The result and the specified parameters will be written to MI_W.csv

Using gomi as a library

Using gomi as a library The measures implemented in gomi can also be used as a library. The following code snippet gives an example:

package main

import (
	"fmt"

	"github.com/kzahedi/goent/dh"
	goent "github.com/kzahedi/goent/discrete"
	mc "github.com/kzahedi/gomi/discrete"
)

func main() {
	// W and A are just examples for data. These would usually be read from some data file
	// For this example to work, we provide some dummy data
	w := [][]float64{{0.0, 1.0},
		{0.1, 1.1},
		{0.2, 1.2},
		{0.3, 1.3},
		{0.4, 1.4}}

	a := [][]float64{{0.0, 1.0, 2.0},
		{0.1, 1.1, 2.1},
		{0.2, 1.2, 2.2},
		{0.3, 1.3, 2.3},
		{0.4, 1.4, 2.4}}

	// discretising data. Discrestise(data, bins for each column, min values for each column, max values for each column)
	wDiscretised := dh.Discretise(w, []int{10, 10}, []float64{0.0, 0.0}, []float64{1.0, 2.0})
	aDiscretised := dh.Discretise(a, []int{10, 10, 10}, []float64{0.0, 0.0, 0.0}, []float64{1.0, 2.0, 3.0})
 
	// univariate variables
	wUnivariate := dh.MakeUnivariateRelabelled(wDiscretised, []int{10, 10})
	aUnivariate := dh.MakeUnivariateRelabelled(aDiscretised, []int{10, 10, 10})
 
	// creating w', w, a data
	w2w1a1 := make([][]int, len(w)-1, len(w)-1)
 
	for i := 0; i < len(w)-1; i++ {
		w2w1a1[i] = make([]int, 3, 3)
		w2w1a1[i][0] = wUnivariate[i+1]
		w2w1a1[i][1] = wUnivariate[i]
		w2w1a1[i][2] = aUnivariate[i]
	}
 
	// calculating p(w',w,a)
	pw2w1a1 := goent.Emperical3D(w2w1a1)
 
	// calculating MI_W
	result := mc.MorphologicalComputationW(pw2w1a1)
 
	fmt.Println(result)
}

A complete reference can be found at here.

References:

  • K. Ghazi-Zahedi, C. Langer, and N. Ay. Morphological computation: Synergy of body and brain. Entropy, 19(9), 2017.
  • K. Ghazi-Zahedi, R. Deimel, G. Montufar, V. Wall, and O. Brock. Morphological computation: The good, the bad, and the ugly. In IROS 2017, 2017.
  • K. Ghazi-Zahedi, D. F. Haeufle, G. F. Montufar, S. Schmitt, and N. Ay. Evaluating morphological computation in muscle and dc-motor driven models of hopping movements. Frontiers in Robotics and AI, 3(42), 2016.
  • K. Ghazi-Zahedi and J. Rauh. Quantifying morphological computation based on an information decomposition of the sensorimotor loop. In Proceedings of the 13th European Conference on Artificial Life (ECAL 2015), pages 70—77, July 2015.
  • K. Zahedi and N. Ay. Quantifying morphological computation. Entropy, 15(5):1887–1915, 2013.

Documentation

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func CaContinuousAvg 

func CaContinuousAvg(p Parameters, data Data) float64

CaContinuousAvg returns the result of the quantification CA. This function also writes the result to a file as specified in the parameters p This function returns -1.0, because the quantification is not implemented based on entropy estimators for continuous state spaces yet.

func CalculateABins 

func CalculateABins(p Parameters, d Data) int

CalculateABins returns the number of bins for the actuator states depending on provided data

func CalculateSBins 

func CalculateSBins(p Parameters, d Data) int

CalculateSBins returns the number of bins for the sensor states depending on provided data

func CalculateWBins 

func CalculateWBins(p Parameters, d Data) int

CalculateWBins returns the number of bins for the world states depending on provided data

func CiContinuousAvg 

func CiContinuousAvg(p Parameters, data Data) float64

CiContinuousAvg returns the result of the quantification CI. This function also writes the result to a file as specified in the parameters p This function returns -1.0, because the quantification is not implemented based on entropy estimators for continuous state spaces yet.

func ContinuousAvgCalculations 

func ContinuousAvgCalculations(p Parameters, d Data) float64

ContinuousAvgCalculations returns the averaged morphological computation based on estimators for continuous data. Note that not all measures are available on continuous state spaces.

func ContinuousSDCalculations 

func ContinuousSDCalculations(p Parameters, d Data)

ContinuousSDCalculations returns the value of the selected continuous measure state-dependent (or point-wise)

func DiscreteAvgCalculations 

func DiscreteAvgCalculations(p Parameters, d Data)

DiscreteAvgCalculations ...

func DiscreteAvgCalculationsSparse 

func DiscreteAvgCalculationsSparse(p Parameters, d Data)

DiscreteAvgCalculationsSparse ...

func DiscreteSDCalculations 

func DiscreteSDCalculations(p Parameters, d Data)

DiscreteSDCalculations ...

func DiscreteSDCalculationsSparse 

func DiscreteSDCalculationsSparse(p Parameters, d Data)

DiscreteSDCalculationsSparse ...

func MakeA1S1Discrete 

func MakeA1S1Discrete(d Data, p Parameters) [][]int

MakeA1S1Discrete returns a slice with (a,s) The retuned slice has two columns.

func MakePA1S1 

func MakePA1S1(d Data, p Parameters) [][]float64

MakePA1S1 return the joint distribution p(a,s)

func MakePA1S1Sparse 

func MakePA1S1Sparse(d Data, p Parameters) sm.SparseMatrix

MakePA1S1Sparse return the joint distribution p(a,s)

func MakePS2S1A1 

func MakePS2S1A1(d Data, p Parameters) [][][]float64

MakePS2S1A1 return the joint distribution p(s',s,a)

func MakePW2A1 

func MakePW2A1(d Data, p Parameters) [][]float64

MakePW2A1 return the joint distribution p(w',a)

func MakePW2A1W1 

func MakePW2A1W1(d Data, p Parameters) [][][]float64

MakePW2A1W1 return the joint distribution p(w',a,w)

func MakePW2A1W1Sparse 

func MakePW2A1W1Sparse(d Data, p Parameters) sm.SparseMatrix

MakePW2A1W1Sparse return the joint distribution p(w',a,w)

func MakePW2W1 

func MakePW2W1(d Data, p Parameters) [][]float64

MakePW2W1 return the joint distribution p(w',w)

func MakePW2W1A1 

func MakePW2W1A1(d Data, p Parameters) [][][]float64

MakePW2W1A1 returns the joint distribution p(w',w,a)

func MakePW2W1A1Sparse 

func MakePW2W1A1Sparse(d Data, p Parameters) sm.SparseMatrix

MakePW2W1A1Sparse returns the joint distribution p(w',w,a) as SparseMatrix

func MakePW2W1S1 

func MakePW2W1S1(d Data, p Parameters) [][][]float64

MakePW2W1S1 return the joint distribution p(w',w,s)

func MakePW2W1Sparse 

func MakePW2W1Sparse(d Data, p Parameters) sm.SparseMatrix

MakePW2W1Sparse return the joint distribution p(w',w)

func MakeS2S1A1Discrete 

func MakeS2S1A1Discrete(d Data, p Parameters) [][]int

MakeS2S1A1Discrete returns a slice with (s',s,a) The retuned slice has three columns.

func MakeW2A1Discrete 

func MakeW2A1Discrete(d Data, p Parameters) [][]int

MakeW2A1Discrete returns a slice with (w',a) The retuned slice has two columns.

func MakeW2A1W1Discrete 

func MakeW2A1W1Discrete(d Data, p Parameters) [][]int

MakeW2A1W1Discrete returns a slice with (w',a,w). The retuned slice has three columns.

func MakeW2W1A1 

func MakeW2W1A1(d Data, p Parameters) ([][]float64, []int, []int, []int)

MakeW2W1A1 returns a slice with (w',w,a) and list of indices, which indicate which columns contain which information

func MakeW2W1A1Discrete 

func MakeW2W1A1Discrete(d Data, p Parameters) [][]int

MakeW2W1A1Discrete returns a slice with (w',w,s,a). The retuned slice has four columns.

func MakeW2W1Discrete 

func MakeW2W1Discrete(d Data, p Parameters) [][]int

MakeW2W1Discrete returns a slice with (w',w). The retuned slice has two columns.

func MakeW2W1S1 

func MakeW2W1S1(d Data, p Parameters) ([][]float64, []int, []int, []int)

MakeW2W1S1 returns a slice with (w',w,s) and list of indices, which indicate which columns contain which information

func MakeW2W1S1A1 

func MakeW2W1S1A1(d Data, p Parameters) ([][]float64, []int, []int, []int, []int)

MakeW2W1S1A1 returns a slice with (w',w,s,a) and list of indices, which indicate which columns contain which information

func MakeW2W1S1Discrete 

func MakeW2W1S1Discrete(d Data, p Parameters) [][]int

MakeW2W1S1Discrete returns a slice with (w',w,s) The retuned slice has three columns.

func MiAContinuousAvg 

func MiAContinuousAvg(p Parameters, data Data) (result float64)

MiAContinuousAvg returns the result of the quantification MI_A. This function also writes the result to a file as specified in the parameters p 

MI_A = I(W';A|W)

func MiAPrimeContinuousAvg 

func MiAPrimeContinuousAvg(p Parameters, data Data) float64

MiAPrimeContinuousAvg returns the result of the quantification MI_A'. This function also writes the result to a file as specified in the parameters p 

MI_A' = 1 - I(W';A|W)/log|W|

func MiCaContinuousAvg 

func MiCaContinuousAvg(p Parameters, data Data) (result float64)

MiCaContinuousAvg returns the result of the quantification MI_CA. This function also writes the result to a file as specified in the parameters p 

MI_CA = I(W';W) - I(W';A)

func MiInContinuousAvg 

func MiInContinuousAvg(p Parameters, data Data) float64

MiInContinuousAvg returns the result of the quantification MI_IN. This function also writes the result to a file as specified in the parameters p 

MI_IN = log|A| - I(A;S)

This function returns -1.0, because the quantification is not implemented based on entropy estimators for continuous state spaces yet.

func MiMiContinuousAvg 

func MiMiContinuousAvg(p Parameters, data Data) (result float64)

MiMiContinuousAvg returns the result of the quantification MI_MI. This function also writes the result to a file as specified in the parameters p 

MI_MI = I(W';W) - I(A;S)

func MiSyContinuousAvg 

func MiSyContinuousAvg(p Parameters, data Data) float64

MiSyContinuousAvg returns the result of the quantification MI_SY. This function also writes the result to a file as specified in the parameters p This function returns -1.0, because the quantification is not implemented based on entropy estimators for continuous state spaces yet.

func MiWContinuousAvg 

func MiWContinuousAvg(p Parameters, data Data) (result float64)

MiWContinuousAvg returns the result of the quantification MI_W. This function also writes the result to a file as specified in the parameters p 

MI_W = I(W';W|A)

func MiWaContinuousAvg 

func MiWaContinuousAvg(p Parameters, data Data) (result float64)

MiWaContinuousAvg returns the result of the quantification MI_WA. This function also writes the result to a file as specified in the parameters p 

MI_WA = I(W;{W,A}) - I(W';A)

func MiWpContinuousAvg 

func MiWpContinuousAvg(p Parameters, data Data) float64

MiWpContinuousAvg returns the result of the quantification MI_Wp. This function also writes the result to a file as specified in the parameters p This function returns -1.0, because the quantification is not implemented based on entropy estimators for continuous state spaces yet.

func MiWsContinuousAvg 

func MiWsContinuousAvg(p Parameters, data Data) (result float64)

MiWsContinuousAvg returns the result of the quantification MI_WS. This function also writes the result to a file as specified in the parameters p 

MI_WS = I(W;{W,S}) - I(W';S)

func NormaliseContinuousData 

func NormaliseContinuousData(data [][]float64, minArray, maxArray [][]float64, p *Parameters) [][]float64

NormaliseContinuousData ...

func NormaliseContinuousDataByColumn 

func NormaliseContinuousDataByColumn(data [][]float64, p *Parameters) [][]float64

NormaliseContinuousDataByColumn ...

func UIContinuousAvg 

func UIContinuousAvg(p Parameters, data Data) float64

UIContinuousAvg returns the result of the quantification UI. This function also writes the result to a file as specified in the parameters p This function returns -1.0, because the quantification is not implemented based on entropy estimators for continuous state spaces yet.

Types

type CfgT 

type CfgT struct {
	Measure        string `yaml:"Measure"`
	Continuous     bool   `yaml:"Continuous"`
	ContinuousMode int    `yaml:"Continuous mode"`
	UseState       bool   `yaml:"State-dependent"`
	Verbose        bool   `yaml:"Verbose"`
	Bins           int    `yaml:"Bins"`
	Iterations     int    `yaml:"Iterations"`
	K              int    `yaml:"k"`
	Output         string `yaml:"Output file"`
	WBins          string `yaml:"W Bins"`
	ABins          string `yaml:"A Bins"`
	SBins          string `yaml:"S Bins"`
	WIndices       string `yaml:"W Indices"`
	AIndices       string `yaml:"A Indices"`
	SIndices       string `yaml:"S Indices"`
	File           string `yaml:"Full data file"`
	WFile          string `yaml:"W data file"`
	AFile          string `yaml:"A data file"`
	SFile          string `yaml:"S data file"`
	DFile          string `yaml:"Domain file"`
}

CfgT ...

type Data 

type Data struct {
	W           [][]float64
	S           [][]float64
	A           [][]float64
	Discretised DataDiscretised
}

Data contains the raw data an the discretised data (if discrete measure are used)

func (*Data) ClearContinuousData 

func (d *Data) ClearContinuousData()

ClearContinuousData ...

func (*Data) Discretise 

func (d *Data) Discretise(p Parameters)

Discretise discretises the available data and stores in the in the Discretised portion of the struct

func (*Data) Read 

func (d *Data) Read(p Parameters)

func (Data) String 

func (d Data) String() string

String returns the string representation of a Data object

type DataDiscretised 

type DataDiscretised struct {
	W [][]int
	S [][]int
	A [][]int
}

DataDiscretised is container for the discretised data

type Output 

type Output struct {
	Date    *string        `json:"date,omitempty"`
	Measure *OutputMeasure `json:"measure,omitempty"`
	Result  *OutputResult  `json:"result,omitempty"`
	Data    *OutputData    `json:"data,omitempty"`

	W2W1A1   *OutputDataRawNormalised `json:"w2w1a1,omitempty"`
	W2W1S1A1 *OutputDataRawNormalised `json:"w2w1s1a1,omitempty"`
}

Output is the JSON struct that will be exported as result of gomi

func (*Output) CreateBins 

func (o *Output) CreateBins()

CreateBins ...

func (*Output) CreateContinuous 

func (o *Output) CreateContinuous()

CreateContinuous ...

func (*Output) CreateData 

func (o *Output) CreateData()

CreateData ...

func (*Output) CreateDataFile 

func (o *Output) CreateDataFile()

CreateDataFile ...

func (*Output) CreateDataIndices 

func (o *Output) CreateDataIndices()

CreateDataIndices ...

func (*Output) CreateDomainAFile 

func (o *Output) CreateDomainAFile()

CreateDomainAFile ...

func (*Output) CreateDomainFile 

func (o *Output) CreateDomainFile()

CreateDomainFile ...

func (*Output) CreateDomainSFile 

func (o *Output) CreateDomainSFile()

CreateDomainSFile ...

func (*Output) CreateDomainWFile 

func (o *Output) CreateDomainWFile()

CreateDomainWFile ...

func (*Output) CreateMeasure 

func (o *Output) CreateMeasure()

CreateMeasure ...

func (*Output) CreateMeasureDiscrete 

func (o *Output) CreateMeasureDiscrete()

CreateMeasureDiscrete ...

func (*Output) CreateMinMax 

func (o *Output) CreateMinMax()

CreateMinMax ...

func (*Output) CreateResults 

func (o *Output) CreateResults()

CreateResults ...

func (*Output) CreateW2W1A1 

func (o *Output) CreateW2W1A1()

CreateW2W1A1 ...

func (*Output) CreateW2W1S1A1 

func (o *Output) CreateW2W1S1A1()

CreateW2W1S1A1 ...

func (Output) ExportJSON 

func (o Output) ExportJSON(filename string)

ExportJSON exports to JSON

func (*Output) SetABins 

func (o *Output) SetABins(bins []int)

SetABins ...

func (*Output) SetAFile 

func (o *Output) SetAFile(name string)

SetAFile ...

func (*Output) SetAIndices 

func (o *Output) SetAIndices(indices []int)

SetAIndices ...

func (*Output) SetAvgResult 

func (o *Output) SetAvgResult(r float64)

SetAvgResult sets the name

func (*Output) SetContinuousMode 

func (o *Output) SetContinuousMode(mode int)

SetContinuousMode ...

func (*Output) SetDate 

func (o *Output) SetDate()

SetDate ...

func (*Output) SetDomainAMinMax 

func (o *Output) SetDomainAMinMax(min, max []float64)

SetDomainAMinMax ...

func (*Output) SetDomainName 

func (o *Output) SetDomainName(name string)

SetDomainName ...

func (*Output) SetDomainSMinMax 

func (o *Output) SetDomainSMinMax(min, max []float64)

SetDomainSMinMax ...

func (*Output) SetDomainWMinMax 

func (o *Output) SetDomainWMinMax(min, max []float64)

SetDomainWMinMax ...

func (*Output) SetGlobalBins 

func (o *Output) SetGlobalBins(bins int)

SetGlobalBins ...

func (*Output) SetGlobalFile 

func (o *Output) SetGlobalFile(name string)

SetGlobalFile ...

func (*Output) SetIterations 

func (o *Output) SetIterations(iterations int)

SetIterations ...

func (*Output) SetK 

func (o *Output) SetK(k int)

SetK ...

func (*Output) SetName 

func (o *Output) SetName(name string)

SetName sets the name

func (*Output) SetNormalisation 

func (o *Output) SetNormalisation(min, max []float64)

SetNormalisation ...

func (*Output) SetParameters 

func (o *Output) SetParameters(p Parameters)

SetParameters copies from Parameters

func (*Output) SetPointWiseResult 

func (o *Output) SetPointWiseResult(r []float64)

SetPointWiseResult sets the name

func (*Output) SetSBins 

func (o *Output) SetSBins(bins []int)

SetSBins ...

func (*Output) SetSFile 

func (o *Output) SetSFile(name string)

SetSFile ...

func (*Output) SetSIndices 

func (o *Output) SetSIndices(indices []int)

SetSIndices ...

func (*Output) SetUseContinuous 

func (o *Output) SetUseContinuous(b bool)

SetUseContinuous sets the name

func (*Output) SetUseStateDependent 

func (o *Output) SetUseStateDependent(b bool)

SetUseStateDependent sets the name

func (*Output) SetW2W1A1Normalised 

func (o *Output) SetW2W1A1Normalised(data [][]float64)

SetW2W1A1Normalised ...

func (*Output) SetW2W1A1Raw 

func (o *Output) SetW2W1A1Raw(data [][]float64)

SetW2W1A1Raw ...

func (*Output) SetW2W1S1A1Normalised 

func (o *Output) SetW2W1S1A1Normalised(data [][]float64)

SetW2W1S1A1Normalised ...

func (*Output) SetW2W1S1A1Raw 

func (o *Output) SetW2W1S1A1Raw(data [][]float64)

SetW2W1S1A1Raw ...

func (*Output) SetWBins 

func (o *Output) SetWBins(bins []int)

SetWBins ...

func (*Output) SetWFile 

func (o *Output) SetWFile(name string)

SetWFile ...

func (*Output) SetWIndices 

func (o *Output) SetWIndices(indices []int)

SetWIndices ...

type OutputBins 

type OutputBins struct {
	W      *[]int `json:"w,omitempty"`
	S      *[]int `json:"s,omitempty"`
	A      *[]int `json:"a,omitempty"`
	Global *int   `json:"global,omitempty"`
}

OutputBins ...

type OutputData 

type OutputData struct {
	File    *OutputDataFile    `json:"file,omitempty"`
	Indices *OutputDataIndices `json:"indices,omitempty"`
}

OutputData ...

type OutputDataFile 

type OutputDataFile struct {
	Global *string           `json:"global,omitempty"`
	W      *string           `json:"world,omitempty"`
	S      *string           `json:"sensors,omitempty"`
	A      *string           `json:"actuators,omitempty"`
	Domain *OutputDomainFile `json:"domain,omitempty"`
}

OutputDataFile ...

type OutputDataIndices 

type OutputDataIndices struct {
	W *[]int `json:"world,omitempty"`
	S *[]int `json:"sensors,omitempty"`
	A *[]int `json:"actuators,omitempty"`
}

OutputDataIndices ...

type OutputDataRawNormalised 

type OutputDataRawNormalised struct {
	Raw        *[][]float64 `json:"raw,omitempty"`
	Normalised *[][]float64 `json:"normalised,omitempty"`
}

OutputDataRawNormalised ...

type OutputDomainFile 

type OutputDomainFile struct {
	Name     *string       `json:"name,omitempty"`
	World    *OutputMinMax `json:"world,omitempty"`
	Sensor   *OutputMinMax `json:"sensors,omitempty"`
	Actuator *OutputMinMax `json:"actuators,omitempty"`
}

OutputDomainFile ...

type OutputMeasure 

type OutputMeasure struct {
	Name              *string                  `json:"name,omitempty"`
	UseContinuous     *bool                    `json:"useContinuous,omitempty"`
	UseStateDependent *bool                    `json:"stateDependent,omitempty"`
	Continuous        *OutputMeasureContinuous `json:"continuous,omitempty"`
	Discrete          *OutputMeasureDiscrete   `json:"discrete,omitempty"`
}

OutputMeasure ...

type OutputMeasureContinuous 

type OutputMeasureContinuous struct {
	Mode          *int          `json:"mode,omitempty"`
	K             *int          `json:"k,omitempty"`
	Normalisation *OutputMinMax `json:"normalisation,omitempty"`
}

OutputMeasureContinuous ...

type OutputMeasureDiscrete 

type OutputMeasureDiscrete struct {
	Iterations *int        `json:"iterations,omitempty"`
	Bins       *OutputBins `json:"bins,omitempty"`
}

OutputMeasureDiscrete ...

type OutputMinMax 

type OutputMinMax struct {
	Min *[]float64 `json:"min,omitempty"`
	Max *[]float64 `json:"max,omitempty"`
}

OutputMinMax ...

type OutputResult 

type OutputResult struct {
	Average   *float64   `json:"averaged,omitempty"`
	PointWise *[]float64 `json:"point-wise,omitempty"`
}

OutputResult ...

type Parameters 

type Parameters struct {
	MeasureName       string
	Output            string
	ConfigFile        string
	UseContinuous     bool
	UseStateDependent bool
	Verbose           bool
	LogData           bool
	UseSparseMatrix   bool
	ContinuousMode    int
	K                 int
	GlobalBins        int
	Iterations        int
	WBins             []int
	SBins             []int
	ABins             []int
	GlobalFile        string
	WIndices          []int
	SIndices          []int
	AIndices          []int
	WFile             string
	SFile             string
	AFile             string
	DFile             string
	WorldMin          []float64
	SensorMin         []float64
	ActuatorMin       []float64
	WorldMax          []float64
	SensorMax         []float64
	ActuatorMax       []float64
	NormalisationMin  []float64
	NormalisationMax  []float64
}

Parameters ...

func CreateParametersContainer 

func CreateParametersContainer() Parameters

CreateParametersContainer ...

func (*Parameters) CheckParameters 

func (p *Parameters) CheckParameters()

CheckParameters checks for the sanity of the command line parameters

func (Parameters) GenerateString 

func (p Parameters) GenerateString(prefix string) string

GenerateString ...

func (*Parameters) SetABins 

func (p *Parameters) SetABins(aBins string)

SetABins ...

func (*Parameters) SetAFile 

func (p *Parameters) SetAFile(file string)

SetAFile ...

func (*Parameters) SetAIndices 

func (p *Parameters) SetAIndices(wIndices string)

SetAIndices ...

func (*Parameters) SetAMinMax 

func (p *Parameters) SetAMinMax(min []float64, max []float64)

SetAMinMax ...

func (*Parameters) SetConfigFile 

func (p *Parameters) SetConfigFile(file string)

SetConfigFile ..

func (*Parameters) SetContinuousMode 

func (p *Parameters) SetContinuousMode(cm int)

SetContinuousMode ...

func (*Parameters) SetDFile 

func (p *Parameters) SetDFile(file string)

SetDFile ...

func (*Parameters) SetGlobalBins 

func (p *Parameters) SetGlobalBins(bins int)

SetGlobalBins ...

func (*Parameters) SetGlobalFile 

func (p *Parameters) SetGlobalFile(file string)

SetGlobalFile ...

func (*Parameters) SetIterations 

func (p *Parameters) SetIterations(iterations int)

SetIterations ...

func (*Parameters) SetK 

func (p *Parameters) SetK(k int)

SetK ...

func (*Parameters) SetLogData 

func (p *Parameters) SetLogData(log bool)

SetLogData ...

func (*Parameters) SetMeasureName 

func (p *Parameters) SetMeasureName(name string)

SetMeasureName set the name of the measure to use, if

func (*Parameters) SetOutput 

func (p *Parameters) SetOutput(output string)

SetOutput ...

func (*Parameters) SetSBins 

func (p *Parameters) SetSBins(sBins string)

SetSBins ...

func (*Parameters) SetSFile 

func (p *Parameters) SetSFile(file string)

SetSFile ...

func (*Parameters) SetSIndices 

func (p *Parameters) SetSIndices(wIndices string)

SetSIndices ...

func (*Parameters) SetSMinMax 

func (p *Parameters) SetSMinMax(min []float64, max []float64)

SetSMinMax ...

func (*Parameters) SetUseContinuous 

func (p *Parameters) SetUseContinuous(b bool)

SetUseContinuous ...

func (*Parameters) SetUseSparseMatrix 

func (p *Parameters) SetUseSparseMatrix(b bool)

SetUseSparseMatrix ...

func (*Parameters) SetUseStateDependent 

func (p *Parameters) SetUseStateDependent(b bool)

SetUseStateDependent ...

func (*Parameters) SetVerbose 

func (p *Parameters) SetVerbose(verbose bool)

SetVerbose ...

func (*Parameters) SetWBins 

func (p *Parameters) SetWBins(wBins string)

SetWBins ...

func (*Parameters) SetWFile 

func (p *Parameters) SetWFile(file string)

SetWFile ...

func (*Parameters) SetWIndices 

func (p *Parameters) SetWIndices(wIndices string)

SetWIndices ...

func (*Parameters) SetWMinMax 

func (p *Parameters) SetWMinMax(min []float64, max []float64)

SetWMinMax ...

func (Parameters) String 

func (p Parameters) String() string

String ...

Source Files

View all Source files

Directories

Path Synopsis
apps
gomi
libgomi
state
sparse
state
state/sparse

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