all: remove any usage of debug.Value in all packages

Using global debug value for all packages turns out is not a good
idea.

4 files changed, 0 insertions, 107 deletions

diff --git a/lib/mining/classifier/cart/cart.go b/lib/mining/classifier/cart/cart.go
index 4ee79198..99eb5b5d 100644
--- a/lib/mining/classifier/cart/cart.go
+++ b/lib/mining/classifier/cart/cart.go
@@ -17,7 +17,6 @@ package cart
 import (
 	"fmt"
 
-	"github.com/shuLhan/share/lib/debug"
 	"github.com/shuLhan/share/lib/mining/gain/gini"
 	"github.com/shuLhan/share/lib/mining/tree/binary"
 	"github.com/shuLhan/share/lib/numbers"
@@ -105,11 +104,6 @@ func (runtime *Runtime) splitTreeByGain(claset tabula.ClasetInterface) (
 	nrow := claset.GetNRow()
 
 	if nrow <= 0 {
-		if debug.Value >= 2 {
-			fmt.Printf("[cart] empty dataset (%s) : %v\n",
-				claset.MajorityClass(), claset)
-		}
-
 		node.Value = NodeValue{
 			IsLeaf: true,
 			Class:  claset.MajorityClass(),
@@ -122,11 +116,6 @@ func (runtime *Runtime) splitTreeByGain(claset tabula.ClasetInterface) (
 	// is set to that class.
 	single, name := claset.IsInSingleClass()
 	if single {
-		if debug.Value >= 2 {
-			fmt.Printf("[cart] in single class (%s): %v\n", name,
-				claset.GetColumns())
-		}
-
 		node.Value = NodeValue{
 			IsLeaf: true,
 			Class:  name,
@@ -135,10 +124,6 @@ func (runtime *Runtime) splitTreeByGain(claset tabula.ClasetInterface) (
 		return node, nil
 	}
 
-	if debug.Value >= 2 {
-		fmt.Println("[cart] claset:", claset)
-	}
-
 	// calculate the Gini gain for each attribute.
 	gains := runtime.computeGain(claset)
 
@@ -149,12 +134,6 @@ func (runtime *Runtime) splitTreeByGain(claset tabula.ClasetInterface) (
 	// if maxgain value is 0, use majority class as node and terminate
 	// the process
 	if MaxGain.GetMaxGainValue() == 0 {
-		if debug.Value >= 2 {
-			fmt.Println("[cart] max gain 0 with target",
-				claset.GetClassAsStrings(),
-				" and majority class is ", claset.MajorityClass())
-		}
-
 		node.Value = NodeValue{
 			IsLeaf: true,
 			Class:  claset.MajorityClass(),
@@ -166,10 +145,6 @@ func (runtime *Runtime) splitTreeByGain(claset tabula.ClasetInterface) (
 	// using the sorted index in MaxGain, sort all field in dataset
 	tabula.SortColumnsByIndex(claset, MaxGain.SortedIndex)
 
-	if debug.Value >= 2 {
-		fmt.Println("[cart] maxgain:", MaxGain)
-	}
-
 	// Now that we have attribute with max gain in MaxGainIdx, and their
 	// gain dan partition value in Gains[MaxGainIdx] and
 	// GetMaxPartValue(), we split the dataset based on type of max-gain
@@ -187,11 +162,6 @@ func (runtime *Runtime) splitTreeByGain(claset tabula.ClasetInterface) (
 		splitV = attrSubV[0]
 	}
 
-	if debug.Value >= 2 {
-		fmt.Println("[cart] maxgainindex:", MaxGainIdx)
-		fmt.Println("[cart] split v:", splitV)
-	}
-
 	node.Value = NodeValue{
 		SplitAttrName: claset.GetColumn(MaxGainIdx).GetName(),
 		IsLeaf:        false,
@@ -286,11 +256,6 @@ func (runtime *Runtime) SelectRandomFeature(claset tabula.ClasetInterface) {
 		col := claset.GetColumn(idx)
 		col.Flag &^= ColFlagSkip
 	}
-
-	if debug.Value >= 1 {
-		fmt.Println("[cart] selected random features:", pickedIdx)
-		fmt.Println("[cart] selected columns        :", claset.GetColumns())
-	}
 }
 
 // computeGain calculate the gini index for each value in each attribute.
@@ -345,19 +310,10 @@ func (runtime *Runtime) computeGain(claset tabula.ClasetInterface) (
 			attr := col.ToStringSlice()
 			attrV := col.ValueSpace
 
-			if debug.Value >= 2 {
-				fmt.Println("[cart] attr :", attr)
-				fmt.Println("[cart] attrV:", attrV)
-			}
-
 			target := claset.GetClassAsStrings()
 			gains[x].ComputeDiscrete(&attr, &attrV, &target,
 				&classVS)
 		}
-
-		if debug.Value >= 2 {
-			fmt.Println("[cart] gain :", gains[x])
-		}
 	}
 	return gains
 }
@@ -415,11 +371,6 @@ func (runtime *Runtime) CountOOBError(oob tabula.Claset) (
 	// save the original target to be compared later.
 	origTarget := oob.GetClassAsStrings()
 
-	if debug.Value >= 2 {
-		fmt.Println("[cart] OOB:", oob.Columns)
-		fmt.Println("[cart] TREE:", &runtime.Tree)
-	}
-
 	// reset the target.
 	oobtarget := oob.GetClassColumn()
 	oobtarget.ClearValues()
@@ -434,11 +385,6 @@ func (runtime *Runtime) CountOOBError(oob tabula.Claset) (
 
 	target := oobtarget.ToStringSlice()
 
-	if debug.Value >= 2 {
-		fmt.Println("[cart] original target:", origTarget)
-		fmt.Println("[cart] classify target:", target)
-	}
-
 	// count how many target value is miss-classified.
 	runtime.OOBErrVal, _, _ = libstrings.CountMissRate(origTarget, target)
 
diff --git a/lib/mining/classifier/crf/crf.go b/lib/mining/classifier/crf/crf.go
index 3c6f25c8..1a40e1c0 100644
--- a/lib/mining/classifier/crf/crf.go
+++ b/lib/mining/classifier/crf/crf.go
@@ -15,7 +15,6 @@ import (
 	"math"
 	"sort"
 
-	"github.com/shuLhan/share/lib/debug"
 	"github.com/shuLhan/share/lib/floats64"
 	"github.com/shuLhan/share/lib/mining/classifier"
 	"github.com/shuLhan/share/lib/mining/classifier/rf"
@@ -151,10 +150,6 @@ func (crf *Runtime) Build(samples tabula.ClasetInterface) (e error) {
 	fmt.Println(tag, "Config:", crf)
 
 	for x := 0; x < crf.NStage; x++ {
-		if debug.Value >= 1 {
-			fmt.Println(tag, "Stage #", x)
-		}
-
 		forest, e := crf.createForest(samples)
 		if e != nil {
 			return e
@@ -206,10 +201,6 @@ func (crf *Runtime) createForest(samples tabula.ClasetInterface) (
 
 	// (2)
 	for t := 0; t < crf.NTree; t++ {
-		if debug.Value >= 2 {
-			fmt.Println(tag, "Tree #", t)
-		}
-
 		// (2.1)
 		for {
 			cm, stat, e = forest.GrowTree(samples)
@@ -233,10 +224,6 @@ func (crf *Runtime) createForest(samples tabula.ClasetInterface) (
 	// (3)
 	crf.computeWeight(stat)
 
-	if debug.Value >= 1 {
-		fmt.Println(tag, "Weight:", stat.FMeasure)
-	}
-
 	// (4)
 	crf.deleteTrueNegative(samples, cm)
 
@@ -261,10 +248,6 @@ func (crf *Runtime) finalizeStage(forest *rf.Runtime) (e error) {
 	crf.AddStat(stat)
 	crf.ComputeStatTotal(stat)
 
-	if debug.Value >= 1 {
-		crf.PrintStatTotal(nil)
-	}
-
 	// (7)
 	crf.AddForest(forest)
 
@@ -309,10 +292,6 @@ func (crf *Runtime) deleteTrueNegative(samples tabula.ClasetInterface,
 			c++
 		}
 	}
-
-	if debug.Value >= 1 {
-		fmt.Println(tag, "# TN", len(tnids), "# deleted", c)
-	}
 }
 
 // refillWithFP will copy the false-positive data in training set `tnset`
@@ -338,10 +317,6 @@ func (crf *Runtime) refillWithFP(samples, tnset tabula.ClasetInterface,
 			c++
 		}
 	}
-
-	if debug.Value >= 1 {
-		fmt.Println(tag, "# FP", len(fpids), "# refilled", c)
-	}
 }
 
 // runTPSet will run true-positive set into trained stage, to get the
diff --git a/lib/mining/classifier/rf/rf.go b/lib/mining/classifier/rf/rf.go
index 38612b97..3eb08aec 100644
--- a/lib/mining/classifier/rf/rf.go
+++ b/lib/mining/classifier/rf/rf.go
@@ -15,7 +15,6 @@ import (
 	"fmt"
 	"math"
 
-	"github.com/shuLhan/share/lib/debug"
 	"github.com/shuLhan/share/lib/floats64"
 	"github.com/shuLhan/share/lib/ints"
 	"github.com/shuLhan/share/lib/mining/classifier"
@@ -147,10 +146,6 @@ func (forest *Runtime) Build(samples tabula.ClasetInterface) (e error) {
 
 	// (1)
 	for t := 0; t < forest.NTree; t++ {
-		if debug.Value >= 1 {
-			fmt.Println(tag, "tree #", t)
-		}
-
 		// (1.1)
 		for {
 			_, _, e = forest.GrowTree(samples)
@@ -191,11 +186,6 @@ func (forest *Runtime) GrowTree(samples tabula.ClasetInterface) (
 
 	bagset := bag.(tabula.ClasetInterface)
 
-	if debug.Value >= 2 {
-		bagset.RecountMajorMinor()
-		fmt.Println(tag, "Bagging:", bagset)
-	}
-
 	// (2)
 	cart, e := cart.New(bagset, cart.SplitMethodGini,
 		forest.NRandomFeature)
@@ -219,19 +209,11 @@ func (forest *Runtime) GrowTree(samples tabula.ClasetInterface) (
 
 	stat.End()
 
-	if debug.Value >= 3 && forest.RunOOB {
-		fmt.Println(tag, "Elapsed time (s):", stat.ElapsedTime)
-	}
-
 	forest.AddStat(stat)
 
 	// (6)
 	if forest.RunOOB {
 		forest.ComputeStatFromCM(stat, cm)
-
-		if debug.Value >= 2 {
-			fmt.Println(tag, "OOB stat:", stat)
-		}
 	}
 
 	forest.ComputeStatTotal(stat)
diff --git a/lib/mining/classifier/runtime.go b/lib/mining/classifier/runtime.go
index 963c54b6..2022e8c4 100644
--- a/lib/mining/classifier/runtime.go
+++ b/lib/mining/classifier/runtime.go
@@ -8,7 +8,6 @@ import (
 	"fmt"
 	"math"
 
-	"github.com/shuLhan/share/lib/debug"
 	"github.com/shuLhan/share/lib/dsv"
 	"github.com/shuLhan/share/lib/floats64"
 	"github.com/shuLhan/share/lib/ints"
@@ -110,10 +109,6 @@ func (rt *Runtime) ComputeCM(sampleIds []int,
 	cm.ComputeStrings(vs, actuals, predicts)
 	cm.GroupIndexPredictionsStrings(sampleIds, actuals, predicts)
 
-	if debug.Value >= 2 {
-		fmt.Println(tag, cm)
-	}
-
 	return cm
 }
 
@@ -170,11 +165,6 @@ func (rt *Runtime) ComputeStatFromCM(stat *Stat, cm *CM) {
 	} else {
 		stat.Accuracy = float64(stat.TP+stat.TN) / t
 	}
-
-	if debug.Value >= 1 {
-		rt.PrintOobStat(stat, cm)
-		rt.PrintStat(stat)
-	}
 }
 
 // ComputeStatTotal compute total statistic.