Sampling Feature for archived and fresh data

pkg/archive/json.go

@@ -9,8 +9,8 @@ import (
 	"io"
 	"time"
 
-	"github.com/ClusterCockpit/cc-backend/pkg/schema"
 	"github.com/ClusterCockpit/cc-backend/pkg/log"
+	"github.com/ClusterCockpit/cc-backend/pkg/schema"
 )
 
 func DecodeJobData(r io.Reader, k string) (schema.JobData, error) {

pkg/resampler/resampler.go

@@ -0,0 +1,113 @@
+package resampler
+
+import (
+	"errors"
+	"fmt"
+	"math"
+
+	"github.com/ClusterCockpit/cc-backend/pkg/schema"
+)
+
+func SimpleResampler(data []schema.Float, old_frequency int64, new_frequency int64) ([]schema.Float, error) {
+	if old_frequency == 0 || new_frequency == 0 {
+		return nil, errors.New("either old or new frequency is set to 0")
+	}
+
+	if new_frequency%old_frequency != 0 {
+		return nil, errors.New("new sampling frequency should be multiple of the old frequency")
+	}
+
+	var step int = int(new_frequency / old_frequency)
+	var new_data_length = len(data) / step
+
+	if new_data_length == 0 || len(data) < 100 || new_data_length >= len(data) {
+		return data, nil
+	}
+
+	new_data := make([]schema.Float, new_data_length)
+
+	for i := 0; i < new_data_length; i++ {
+		new_data[i] = data[i*step]
+	}
+
+	return new_data, nil
+}
+
+// Inspired by one of the algorithms from https://skemman.is/bitstream/1946/15343/3/SS_MSthesis.pdf
+// Adapted from https://github.com/haoel/downsampling/blob/master/core/lttb.go
+func LargestTriangleThreeBucket(data []schema.Float, old_frequency int, new_frequency int) ([]schema.Float, int, error) {
+
+	if old_frequency == 0 || new_frequency == 0 {
+		return data, old_frequency, nil
+	}
+
+	if new_frequency%old_frequency != 0 {
+		return nil, 0, errors.New(fmt.Sprintf("new sampling frequency : %d should be multiple of the old frequency : %d", new_frequency, old_frequency))
+	}
+
+	var step int = int(new_frequency / old_frequency)
+	var new_data_length = len(data) / step
+
+	if new_data_length == 0 || len(data) < 100 || new_data_length >= len(data) {
+		return data, old_frequency, nil
+	}
+
+	new_data := make([]schema.Float, 0, new_data_length)
+
+	// Bucket size. Leave room for start and end data points
+	bucketSize := float64(len(data)-2) / float64(new_data_length-2)
+
+	new_data = append(new_data, data[0]) // Always add the first point
+
+	// We have 3 pointers represent for
+	// > bucketLow - the current bucket's beginning location
+	// > bucketMiddle - the current bucket's ending location,
+	//                  also the beginning location of next bucket
+	// > bucketHight - the next bucket's ending location.
+	bucketLow := 1
+	bucketMiddle := int(math.Floor(bucketSize)) + 1
+
+	var prevMaxAreaPoint int
+
+	for i := 0; i < new_data_length-2; i++ {
+
+		bucketHigh := int(math.Floor(float64(i+2)*bucketSize)) + 1
+		if bucketHigh >= len(data)-1 {
+			bucketHigh = len(data) - 2
+		}
+
+		// Calculate point average for next bucket (containing c)
+		avgPointX, avgPointY := calculateAverageDataPoint(data[bucketMiddle:bucketHigh+1], int64(bucketMiddle))
+
+		// Get the range for current bucket
+		currBucketStart := bucketLow
+		currBucketEnd := bucketMiddle
+
+		// Point a
+		pointX := prevMaxAreaPoint
+		pointY := data[prevMaxAreaPoint]
+
+		maxArea := -1.0
+
+		var maxAreaPoint int
+		for ; currBucketStart < currBucketEnd; currBucketStart++ {
+
+			area := calculateTriangleArea(schema.Float(pointX), pointY, avgPointX, avgPointY, schema.Float(currBucketStart), data[currBucketStart])
+			if area > maxArea {
+				maxArea = area
+				maxAreaPoint = currBucketStart
+			}
+		}
+
+		new_data = append(new_data, data[maxAreaPoint]) // Pick this point from the bucket
+		prevMaxAreaPoint = maxAreaPoint                 // This MaxArea point is the next's prevMAxAreaPoint
+
+		//move to the next window
+		bucketLow = bucketMiddle
+		bucketMiddle = bucketHigh
+	}
+
+	new_data = append(new_data, data[len(data)-1]) // Always add last
+
+	return new_data, new_frequency, nil
+}

pkg/resampler/util.go

@@ -0,0 +1,25 @@
+package resampler
+
+import (
+	"math"
+
+	"github.com/ClusterCockpit/cc-backend/pkg/schema"
+)
+
+func calculateTriangleArea(paX, paY, pbX, pbY, pcX, pcY schema.Float) float64 {
+	area := ((paX-pcX)*(pbY-paY) - (paX-pbX)*(pcY-paY)) * 0.5
+	return math.Abs(float64(area))
+}
+
+func calculateAverageDataPoint(points []schema.Float, xStart int64) (avgX schema.Float, avgY schema.Float) {
+
+	for _, point := range points {
+		avgX += schema.Float(xStart)
+		avgY += point
+		xStart++
+	}
+	l := schema.Float(len(points))
+	avgX /= l
+	avgY /= l
+	return avgX, avgY
+}