Merge branch 'sample_resolution_select' into dev

This commit is contained in:
Christoph Kluge
2024-09-24 17:43:15 +02:00
42 changed files with 826 additions and 242 deletions

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@@ -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) {

123
pkg/resampler/resampler.go Normal file
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@@ -0,0 +1,123 @@
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
flag_ := 0
for ; currBucketStart < currBucketEnd; currBucketStart++ {
area := calculateTriangleArea(schema.Float(pointX), pointY, avgPointX, avgPointY, schema.Float(currBucketStart), data[currBucketStart])
if area > maxArea {
maxArea = area
maxAreaPoint = currBucketStart
}
if math.IsNaN(float64(avgPointY)) {
flag_ = 1
}
}
if flag_ == 1 {
new_data = append(new_data, schema.NaN) // Pick this point from the bucket
} else {
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
}

35
pkg/resampler/util.go Normal file
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@@ -0,0 +1,35 @@
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) {
flag := 0
for _, point := range points {
avgX += schema.Float(xStart)
avgY += point
xStart++
if math.IsNaN(float64(point)) {
flag = 1
}
}
l := schema.Float(len(points))
avgX /= l
avgY /= l
if flag == 1 {
return avgX, schema.NaN
} else {
return avgX, avgY
}
}

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@@ -76,6 +76,13 @@ type Retention struct {
IncludeDB bool `json:"includeDB"`
}
type ResampleConfig struct {
// Trigger next zoom level at less than this many visible datapoints
Trigger int `json:"trigger"`
// Array of resampling target resolutions, in seconds; Example: [600,300,60]
Resolutions []int `json:"resolutions"`
}
// Format of the configuration (file). See below for the defaults.
type ProgramConfig struct {
// Address where the http (or https) server will listen on (for example: 'localhost:80').
@@ -133,6 +140,9 @@ type ProgramConfig struct {
// be provided! Most options here can be overwritten by the user.
UiDefaults map[string]interface{} `json:"ui-defaults"`
// If exists, will enable dynamic zoom in frontend metric plots using the configured values
EnableResampling *ResampleConfig `json:"enable-resampling"`
// Where to store MachineState files
MachineStateDir string `json:"machine-state-dir"`

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@@ -424,6 +424,27 @@
"plot_general_colorscheme",
"plot_list_selectedMetrics"
]
},
"enable-resampling": {
"description": "Enable dynamic zoom in frontend metric plots.",
"type": "object",
"properties": {
"trigger": {
"description": "Trigger next zoom level at less than this many visible datapoints.",
"type": "integer"
},
"resolutions": {
"description": "Array of resampling target resolutions, in seconds.",
"type": "array",
"items": {
"type": "integer"
}
}
},
"required": [
"trigger",
"resolutions"
]
}
},
"required": [