//Convert a single instance over
func (as *AttributeSelection) convertInstance(inst data.Instance) data.Instance {
newVasl := make([]float64, 0, len(as.output.Attributes()))
for i, current := range as.selectedAttributes {
fmt.Println(current, i, inst.RealValues())
newVasl = append(newVasl, inst.Value(current))
//newVasl[i] = inst.Value(current)
//fmt.Println(newVasl[i], "newVasl[i]")
}
fmt.Println("----------------------------------------------")
newInst := data.NewInstance()
// newInst.SetNumAttributes(len(newVasl))
values_ := make([]float64, len(newVasl))
indices_ := make([]int, len(newVasl))
vals := 0
for i := 0; i < len(newVasl); i++ {
if newVasl[i] != 0 {
values_[vals] = newVasl[i]
indices_[vals] = i
vals++
}
}
values := make([]float64, vals)
indices := make([]int, vals)
copy(values, values_)
copy(indices, indices_)
// fmt.Println(values, "values")
// fmt.Println(indices, "indices")
for k, i := range indices {
if as.output.Attribute(i).IsNominal() {
newInst.AddValues(as.output.Attribute(i).Values()[int(values[k])])
} else {
newInst.AddValues(as.output.Attribute(i).Name())
}
}
newInst.SetIndices(indices)
newInst.SetRealValues(values)
newInst.SetWeight(inst.Weight())
return newInst
}
func (stwv *StringToWordVector) normalizeInstance(inst *data.Instance, firstCopy int) {
//fmt.Println("firstcopy ", firstCopy)
//fmt.Println("avgdoclength ", stwv.avgDocLength)
docLength := float64(0)
if stwv.avgDocLength < 0 {
panic("Average document length not set.")
}
// fmt.Println("valores: ", inst.RealValues())
// Compute length of document vector
for j := 0; j < len(inst.RealValues()); j++ {
if inst.Indices()[j] >= firstCopy {
docLength += inst.RealValues()[j] * inst.RealValues()[j]
}
}
docLength = math.Sqrt(docLength)
// Normalize document vector
for j := 0; j < len(inst.RealValues()); j++ {
if inst.Indices()[j] >= firstCopy {
val := inst.RealValues()[j] * stwv.avgDocLength / docLength
inst.AddRealValuesIndex(j, val)
if val == 0 {
fmt.Println("Setting value %d to zero", inst.Indices()[j])
j--
}
}
}
}
func (stwv *StringToWordVector) convertInstancewoDocNorm(inst data.Instance) (int, data.Instance) {
// Convert the instance into a sorted set of indexes
contained := omap.NewIntKeyed()
mapKeys := make([]float64, 0)
// Copy all non-converted attributes from input to output
firstCopy := 0
for i, _ := range stwv.inputFormat.Attributes() {
//fmt.Println("input attrs: ", i)
if !stwv.inputFormat.Attributes()[i].IsString() {
// Add simple nominal and numeric attributes directly
if inst.RealValues()[i] != 0 {
contained.Insert(firstCopy, inst.RealValues()[i])
mapKeys = append(mapKeys, float64(firstCopy))
firstCopy++
} else {
firstCopy++
}
} else if inst.IsMissingValue(i) {
//fmt.Println("print 1.2")
contained.Insert(firstCopy, inst.MissingValue)
mapKeys = append(mapKeys, float64(firstCopy))
firstCopy++
} else if stwv.inputFormat.Attributes()[i].IsString() {
//if i have to implement the range selector then code this part
}
}
//Copy the converted attributes
//fmt.Println("print 2.0" , inst.NumAttributes())
for j := 0; j < inst.NumAttributes(); j++ {
//fmt.Println("print 2.0.1" , stwv.inputFormat.Attributes()[1].IsString())
if stwv.inputFormat.Attributes()[j].IsString() && inst.IsMissingValue(j) == false {
//fmt.Println("print 2")
words := strings.Fields(inst.Values()[j])
//fmt.Println(stwv.dictionary)
//fmt.Println("------------------------------------------------")
for _, word := range words {
//fmt.Println("print 3", idx)
if index, present := stwv.dictionary.Find(word); present {
if stwv.outputsCounts {
if count, isthere := contained.Find(index); isthere {
if count, ok := count.(float64); ok { //type assertion
contained.Insert(int(index.(int)), count+1)
mapKeys = append(mapKeys, float64(index.(int)))
}
} else {
//fmt.Println(index)
contained.Insert(int(index.(int)), float64(1))
mapKeys = append(mapKeys, float64(index.(int)))
}
} else {
//fmt.Println(index)
contained.Insert(int(index.(int)), float64(1))
mapKeys = append(mapKeys, float64(index.(int)))
}
}
}
}
}
//To calculate frequencies
indexes := make([]int, contained.Len())
_values := make([]float64, contained.Len())
n := 0
contained.Do(func(key, value interface{}) {
//fmt.Println(key, " <-->", value)
index, _ := key.(int)
_value, _ := value.(float64)
indexes[n] = index
_values[n] = _value
n++
})
//------------
//TF_freq transform
if stwv.tf_transformation {
for i := 0; i < len(indexes); i++ {
index := indexes[i]
if index >= firstCopy {
val := _values[i]
val = math.Log(val + 1)
contained.Insert(index, val)
}
}
}
indexes = make([]int, contained.Len())
_values = make([]float64, contained.Len())
n = 0
contained.Do(func(key, value interface{}) {
//fmt.Println(key, " <-->", value)
index, _ := key.(int)
_value, _ := value.(float64)
indexes[n] = index
_values[n] = _value
n++
})
//IDF_freq transform
if stwv.idf_transformation {
for i := 0; i < len(indexes); i++ {
index := indexes[i]
if index >= firstCopy {
val := _values[i]
val = val * math.Log(float64(stwv.numInstances)/float64(stwv.docsCounts[index]))
contained.Insert(index, val)
}
}
// contained.Do(func(key, value interface{}) {
// k, _ := key.(int)
// val, _ := value.(float64)
// if k >= firstCopy {
// val = val * math.Log(float64(stwv.numInstances)/float64(stwv.docsCounts[k]))
// contained.Insert(k, val)
// }
// })
}
//TF_IDF_freq transform
// if stwv.transformation == TF_IDF {
// for i:= 0; i < len(indexes); i++ {
// index := indexes[i]
// if index >= firstCopy {
// val := _values[i]
// val = (val * math.Log(float64(stwv.numInstances)/float64(stwv.docsCounts[index]))) * math.Log(val+1)
// contained.Insert(index, val)
// }
// }
// contained.Do(func(key, value interface{}) {
// k, _ := key.(int)
// val, _ := value.(float64)
// if k >= firstCopy {
// val = (val * math.Log(float64(stwv.numInstances)/float64(stwv.docsCounts[k]))) * math.Log(val+1)
// contained.Insert(k, val)
// }
// })
// }
// contained.Do(func(key, value interface{}) {
// fmt.Println(key, " ", value)
// })
// Convert the set to structures needed to create a sparse instance.
values := make([]float64, contained.Len())
indices := make([]int, contained.Len())
i := 0
//fmt.Println(contained.Len())
contained.Do(func(key, value interface{}) {
index, _ := key.(int)
_value, _ := value.(float64)
values[i] = _value
indices[i] = index
i++
})
instSparse := data.NewInstance()
for k, i := range indices {
if stwv.outputFormat.Attributes()[i].IsNominal() {
instSparse.AddValues(stwv.outputFormat.Attributes()[i].Values()[int(values[k])])
} else if stwv.outputFormat.Attributes()[i].IsNominal() && !stwv.outputFormat.Attributes()[i].IsString() {
instSparse.AddValues(stwv.outputFormat.Attributes()[i].Values()[i])
} else {
instSparse.AddValues(stwv.outputFormat.Attributes()[i].Name())
}
}
instSparse.SetIndices(indices)
instSparse.SetRealValues(values)
instSparse.SetWeight(inst.Weight())
instSparse.SetNumAttributes(len(values))
return firstCopy, instSparse
}
func (ntb *NumericToBinary) convertInstance(instance data.Instance) data.Instance {
inst := data.NewInstance()
vals := make([]float64, len(instance.RealValues()))
newIndexes := make([]int, len(instance.RealValues()))
for j := range instance.RealValues() {
att := ntb.input.Attribute(instance.Index(j))
if att.Type() != data.NUMERIC || instance.Index(j) == ntb.input.ClassIndex() {
//fmt.Println(ntb.input.ClassIndex())
vals[j] = instance.ValueSparse(j)
} else {
if instance.IsMissingValue(j) {
//fmt.Println("DSAD")
vals[j] = instance.ValueSparse(j)
} else {
//fmt.Println("DSAD---")
vals[j] = 1
}
}
newIndexes[j] = instance.Index(j)
}
inst.SetWeight(instance.Weight())
inst.SetRealValues(vals)
inst.SetIndices(newIndexes)
return inst
}
