Fixing all tests

base/serialize.go

@@ -3,7 +3,6 @@ package base
 import (
 	"archive/tar"
 	"compress/gzip"
-	"encoding/csv"
 	"encoding/json"
 	"fmt"
 	"io"
@@ -285,14 +284,6 @@ func (c *ClassifierSerializer) Close() error {
 		return fmt.Errorf("Could not close file writer: %s", err)
 	}
 
-	log.Printf("Closed ClassifierSerializerStub at %s", c.f.Name())
-
-	//if err := c.f.Close(); err != nil {
-	//	return fmt.Errorf("Could not close file: %s", err)
-	//}
-
-	os.Rename(c.f.Name(), c.filePath)
-
 	return nil
 }
 
@@ -433,115 +424,3 @@ func CreateSerializedClassifierStub(filePath string, metadata ClassifierMetadata
 	return &ret, nil
 
 }
-
-func SerializeInstances(inst FixedDataGrid, f io.Writer) error {
-	var hdr *tar.Header
-
-	gzWriter := gzip.NewWriter(f)
-	tw := tar.NewWriter(gzWriter)
-
-	// Write the MANIFEST entry
-	hdr = &tar.Header{
-		Name: "MANIFEST",
-		Size: int64(len(SerializationFormatVersion)),
-	}
-	if err := tw.WriteHeader(hdr); err != nil {
-		return fmt.Errorf("Could not write MANIFEST header: %s", err)
-	}
-
-	if _, err := tw.Write([]byte(SerializationFormatVersion)); err != nil {
-		return fmt.Errorf("Could not write MANIFEST contents: %s", err)
-	}
-
-	// Now write the dimensions of the dataset
-	attrCount, rowCount := inst.Size()
-	hdr = &tar.Header{
-		Name: "DIMS",
-		Size: 16,
-	}
-	if err := tw.WriteHeader(hdr); err != nil {
-		return fmt.Errorf("Could not write DIMS header: %s", err)
-	}
-
-	if _, err := tw.Write(PackU64ToBytes(uint64(attrCount))); err != nil {
-		return fmt.Errorf("Could not write DIMS (attrCount): %s", err)
-	}
-	if _, err := tw.Write(PackU64ToBytes(uint64(rowCount))); err != nil {
-		return fmt.Errorf("Could not write DIMS (rowCount): %s", err)
-	}
-
-	// Write the ATTRIBUTES files
-	classAttrs := inst.AllClassAttributes()
-	normalAttrs := NonClassAttributes(inst)
-	if err := writeAttributesToFilePart(classAttrs, tw, "CATTRS"); err != nil {
-		return fmt.Errorf("Could not write CATTRS: %s", err)
-	}
-	if err := writeAttributesToFilePart(normalAttrs, tw, "ATTRS"); err != nil {
-		return fmt.Errorf("Could not write ATTRS: %s", err)
-	}
-
-	// Data must be written out in the same order as the Attributes
-	allAttrs := make([]Attribute, attrCount)
-	normCount := copy(allAttrs, normalAttrs)
-	for i, v := range classAttrs {
-		allAttrs[normCount+i] = v
-	}
-
-	allSpecs := ResolveAttributes(inst, allAttrs)
-
-	// First, estimate the amount of data we'll need...
-	dataLength := int64(0)
-	inst.MapOverRows(allSpecs, func(val [][]byte, row int) (bool, error) {
-		for _, v := range val {
-			dataLength += int64(len(v))
-		}
-		return true, nil
-	})
-
-	// Then write the header
-	hdr = &tar.Header{
-		Name: "DATA",
-		Size: dataLength,
-	}
-	if err := tw.WriteHeader(hdr); err != nil {
-		return fmt.Errorf("Could not write DATA: %s", err)
-	}
-
-	// Then write the actual data
-	writtenLength := int64(0)
-	if err := inst.MapOverRows(allSpecs, func(val [][]byte, row int) (bool, error) {
-		for _, v := range val {
-			wl, err := tw.Write(v)
-			writtenLength += int64(wl)
-			if err != nil {
-				return false, err
-			}
-		}
-		return true, nil
-	}); err != nil {
-		return err
-	}
-
-	if writtenLength != dataLength {
-		return fmt.Errorf("Could not write DATA: changed size from %v to %v", dataLength, writtenLength)
-	}
-
-	// Finally, close and flush the various levels
-	if err := tw.Flush(); err != nil {
-		return fmt.Errorf("Could not flush tar: %s", err)
-	}
-
-	if err := tw.Close(); err != nil {
-		return fmt.Errorf("Could not close tar: %s", err)
-	}
-
-	if err := gzWriter.Flush(); err != nil {
-		return fmt.Errorf("Could not flush gz: %s", err)
-	}
-
-	if err := gzWriter.Close(); err != nil {
-		return fmt.Errorf("Could not close gz: %s", err)
-	}
-
-	return nil
-}

knn/knn.go

@@ -356,7 +356,6 @@ func (KNN *KNNClassifier) Save(filePath string) error {
 
 // SaveWithPrefix outputs KNN as part of another file.
 func (KNN *KNNClassifier) SaveWithPrefix(writer *base.ClassifierSerializer, prefix string) error {
-	fmt.Printf("writer: %v", writer)
 	err := writer.WriteInstancesForKey(writer.Prefix(prefix, "TrainingInstances"), KNN.TrainingData, true)
 	if err != nil {
 		return err

trees/id3.go

@@ -67,7 +67,6 @@ func (d *DecisionTreeRule) unmarshalJSON(data []byte) error {
 	if err != nil {
 		panic(err)
 	}
-	fmt.Printf("%s\n", splitBytes)
 	if string(splitBytes) != "\"unknown\"" {
 		d.SplitAttr, err = base.DeserializeAttribute(splitBytes)
 		if err != nil {
@@ -107,7 +106,7 @@ type DecisionTreeNode struct {
 	Children  map[string]*DecisionTreeNode `json:"children"`
 	ClassDist map[string]int               `json:"class_dist"`
 	Class     string                       `json:"class_string"`
-	ClassAttr base.Attribute 				`json:"-"`
+	ClassAttr base.Attribute               `json:"-"`
 	SplitRule *DecisionTreeRule            `json:"decision_tree_rule"`
 }
 

trees/tree_test.go

@@ -7,7 +7,6 @@ import (
 	. "github.com/smartystreets/goconvey/convey"
 	"io/ioutil"
 	"math/rand"
-	"fmt"
 	"os"
 	"testing"
 )
@@ -145,8 +144,6 @@ func verifyTreeClassification(trainData, testData base.FixedDataGrid) {
 					f.Close()
 				}()
 
-				fmt.Printf("%s", root)
-
 				err = root.Save(f.Name())
 				So(err, ShouldBeNil)