v0.4.1_hotfix
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3b51f741d9067586fa06db6bc3819f3e2d0cd7387f266c93c5ffa32878df6d60 ts3monolith-linux-amd64
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84c245bc8b2534b0f3b822637cc7c7d51fa7c6918e60909025a326578d284e2a ts3monolith-linux-amd64
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+85
-16
@@ -92,7 +92,7 @@ func (m *Manager) Last(ctx context.Context) (int, error) {
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// Point is one JSON-serializable RRD sample. V is nil when the RRA has no
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// data for that timestamp (rrdtool reports it as "nan"), which the
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// front-end renders as a gap in the line rather than a drop to zero.
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// front-end renders as zero while preserving NULL as "missing" in the API.
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type Point struct {
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T int64 `json:"t"`
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V *float64 `json:"v"`
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@@ -107,6 +107,7 @@ type GraphData struct {
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Title string `json:"title"`
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Step int64 `json:"step"`
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Points []Point `json:"points"`
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PeakPoints []Point `json:"peak_points,omitempty"`
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Current *float64 `json:"current"`
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Average *float64 `json:"average"`
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Max *float64 `json:"max"`
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@@ -122,6 +123,23 @@ type GraphData struct {
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// it's returned, independent of any particular browser's viewport.
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const maxChartPoints = 450
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// chartPointTarget keeps roughly comparable visual density across ranges.
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// Long ranges get wider buckets, which suppresses one-sample needles while
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// preserving the overall trend. True peaks are returned separately from the
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// RRD MAX archive, so smoothing the average line does not hide maxima.
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func chartPointTarget(key string) int {
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switch key {
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case "week":
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return 336 // about 30 minutes per point
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case "month":
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return 372 // about 2 hours per point
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case "year":
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return 365 // about 1 day per point
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default:
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return maxChartPoints
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}
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}
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// Fetch reads the samples for one graph range directly from the RRD file
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// via `rrdtool fetch`, for the front-end to render client-side. This
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// replaces the previous approach of shelling out to `rrdtool graph` to
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@@ -137,16 +155,26 @@ func (m *Manager) Fetch(ctx context.Context, key string) (GraphData, error) {
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}
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data, err := m.fetchCF(ctx, rg, rg.CF)
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if err != nil && rg.CF != "LAST" {
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// An RRD file that predates packaging/ts3monolith-init-rrd (e.g. an
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// archived database carried over from the old PHP app, as this
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// project's README tells operators to do) may not have an
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// AVERAGE-consolidated RRA at all. LAST is the one CF every range
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// used exclusively before this JSON rewrite (see git history), so
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// it's guaranteed to exist -- fall back to it rather than leaving
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// week/month/year permanently broken against such a file.
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// Older imported RRDs may not contain AVERAGE/MAX archives. Fall
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// back to LAST so the dashboard still works with such databases.
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data, err = m.fetchCF(ctx, rg, "LAST")
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}
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if err != nil {
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return data, err
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}
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// For consolidated long ranges, fetch the matching MAX archive too.
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// The main line stays a smoothed average, while PeakPoints and Max keep
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// real peaks visible instead of deriving a fake maximum from averages.
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if rg.CF == "AVERAGE" {
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if peaks, peakErr := m.fetchCF(ctx, rg, "MAX"); peakErr == nil {
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data.PeakPoints = peaks.Points
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if peaks.Max != nil {
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data.Max = peaks.Max
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}
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}
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}
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return data, nil
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}
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func (m *Manager) fetchCF(ctx context.Context, rg *Range, cf string) (GraphData, error) {
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@@ -202,19 +230,23 @@ func (m *Manager) fetchCF(ctx context.Context, rg *Range, cf string) (GraphData,
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}
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// Current/Average/Max above are computed from the full raw series, not
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// diluted by downsampling; only the plotted points themselves shrink.
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data.Points = downsample(raw, maxChartPoints)
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target := chartPointTarget(rg.Key)
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if cf == "MAX" {
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data.Points = downsampleMax(raw, target)
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} else {
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data.Points = downsample(raw, target)
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}
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if len(data.Points) > 1 {
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data.Step = data.Points[1].T - data.Points[0].T
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}
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return data, nil
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}
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// downsample buckets points down to at most target entries. Each bucket's
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// value is the average of its non-null samples (nil if the bucket has
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// none), and its timestamp is the last raw timestamp in the bucket -- the
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// same shape as an RRD AVERAGE RRA, so long ranges read as a smooth trend
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// instead of a wall of raw per-minute noise. Points already at or under
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// the target are returned unchanged.
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// downsample buckets points down to at most target entries. Missing samples
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// inside a bucket count as zero for the plotted average, matching the UI's
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// NULL -> 0 semantics and preventing one isolated non-zero sample among many
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// NULLs from becoming a full-height needle. An all-NULL bucket remains NULL
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// so a completely empty RRD is still detected as "Brak danych".
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func downsample(points []Point, target int) []Point {
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if target <= 0 || len(points) <= target {
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return points
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@@ -244,10 +276,47 @@ func downsample(points []Point, target int) []Point {
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}
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pt := Point{T: t}
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if n > 0 {
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avg := sum / float64(n)
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avg := sum / float64(end-start)
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pt.V = &avg
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}
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out = append(out, pt)
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}
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return out
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}
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// downsampleMax keeps the highest valid value from each bucket. It is used
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// only for the secondary peak line fetched from an RRD MAX archive.
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func downsampleMax(points []Point, target int) []Point {
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if target <= 0 || len(points) <= target {
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return points
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}
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bucket := float64(len(points)) / float64(target)
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out := make([]Point, 0, target)
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for i := 0; i < target; i++ {
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start := int(float64(i) * bucket)
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end := int(float64(i+1) * bucket)
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if end <= start {
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end = start + 1
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}
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if end > len(points) {
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end = len(points)
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}
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if start >= end {
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break
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}
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pt := Point{T: points[end-1].T}
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var max *float64
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for _, p := range points[start:end] {
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if p.V == nil {
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continue
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}
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if max == nil || *p.V > *max {
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v := *p.V
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max = &v
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}
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}
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pt.V = max
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out = append(out, pt)
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}
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return out
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}
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@@ -33,14 +33,14 @@ func TestDownsampleAveragesBuckets(t *testing.T) {
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}
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}
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func TestDownsampleSkipsNulls(t *testing.T) {
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func TestDownsampleTreatsNullsAsZeroInsideNonEmptyBucket(t *testing.T) {
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in := []Point{{T: 1, V: f(2)}, {T: 2, V: nil}, {T: 3, V: f(4)}, {T: 4, V: nil}}
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out := downsample(in, 1)
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if len(out) != 1 {
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t.Fatalf("expected 1 bucket, got %d", len(out))
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}
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if out[0].V == nil || *out[0].V != 3 {
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t.Fatalf("expected average of non-null values (3), got %v", out[0].V)
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if out[0].V == nil || *out[0].V != 1.5 {
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t.Fatalf("expected NULL-as-zero bucket average (1.5), got %v", out[0].V)
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}
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}
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@@ -54,3 +54,14 @@ func TestDownsampleAllNullBucketStaysNull(t *testing.T) {
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t.Fatalf("expected nil for an all-null bucket, got %v", *out[0].V)
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}
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}
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func TestDownsampleMaxKeepsPeak(t *testing.T) {
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in := []Point{{T: 1, V: f(1)}, {T: 2, V: f(7)}, {T: 3, V: nil}, {T: 4, V: f(3)}}
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out := downsampleMax(in, 1)
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if len(out) != 1 {
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t.Fatalf("expected 1 bucket, got %d", len(out))
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}
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if out[0].V == nil || *out[0].V != 7 {
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t.Fatalf("expected bucket peak 7, got %v", out[0].V)
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}
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}
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+57
-14
@@ -99,13 +99,18 @@
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var plotW = Math.max(1, cssW - padL - padR);
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var plotH = Math.max(1, cssH - padT - padB);
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var peakPoints = (data && data.peak_points) || [];
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var values = [];
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points.forEach(function (p) { if (p.v !== null && p.v !== undefined) values.push(p.v); });
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peakPoints.forEach(function (p) { if (p.v !== null && p.v !== undefined) values.push(p.v); });
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var maxV = values.length ? Math.max.apply(null, values) : 1;
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var top = Math.max(1, Math.ceil(maxV * 1.2));
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var top = Math.max(1, Math.ceil(maxV * 1.15));
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function xAtFor(series, i) {
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return padL + (series.length > 1 ? (i / (series.length - 1)) * plotW : plotW / 2);
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}
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function xAt(i) {
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return padL + (points.length > 1 ? (i / (points.length - 1)) * plotW : plotW / 2);
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return xAtFor(points, i);
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}
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function yAt(v) {
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return padT + plotH - (v / top) * plotH;
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@@ -140,9 +145,47 @@
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});
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}
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// area + line, broken into separate segments across data gaps (nulls)
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// instead of interpolating through them
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// For week/month/year the API also returns a MAX series. Draw it first
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// as a subtle dashed line: the solid/filled line remains the smoothed
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// average trend, while real historical peaks are still visible.
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if (peakPoints.length > 1) {
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ctx.save();
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ctx.beginPath();
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peakPoints.forEach(function (p, i) {
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var v = (p.v === null || p.v === undefined) ? 0 : p.v;
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var x = xAtFor(peakPoints, i);
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var y = yAt(v);
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if (i === 0) ctx.moveTo(x, y);
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else ctx.lineTo(x, y);
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});
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ctx.lineJoin = 'round';
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ctx.lineCap = 'round';
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ctx.lineWidth = 1;
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ctx.strokeStyle = accent;
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ctx.globalAlpha = 0.42;
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ctx.setLineDash([4, 4]);
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ctx.stroke();
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ctx.restore();
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}
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// Main average/trend line; missing samples are rendered as zero so the
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// graph falls cleanly to the baseline instead of breaking into segments.
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// Short windows represent a discrete user count, so draw them as steps:
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// the value stays constant until the next sample instead of producing
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// narrow triangular needles between 0 and 1/2 users.
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var useSteps = data.key === 'hour' || data.key === 'day';
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var seg = [];
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function traceSeries(segment) {
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ctx.moveTo(segment[0][0], segment[0][1]);
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for (var i = 1; i < segment.length; i++) {
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if (useSteps) {
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ctx.lineTo(segment[i][0], segment[i - 1][1]);
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}
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ctx.lineTo(segment[i][0], segment[i][1]);
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}
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}
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function flushSegment() {
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if (seg.length < 2) {
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seg = [];
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@@ -150,17 +193,20 @@
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}
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ctx.beginPath();
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ctx.moveTo(seg[0][0], padT + plotH);
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seg.forEach(function (pt) { ctx.lineTo(pt[0], pt[1]); });
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ctx.lineTo(seg[0][0], seg[0][1]);
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for (var i = 1; i < seg.length; i++) {
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if (useSteps) {
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ctx.lineTo(seg[i][0], seg[i - 1][1]);
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}
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ctx.lineTo(seg[i][0], seg[i][1]);
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}
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ctx.lineTo(seg[seg.length - 1][0], padT + plotH);
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ctx.closePath();
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ctx.fillStyle = accent + '38';
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ctx.fill();
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ctx.beginPath();
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seg.forEach(function (pt, idx) {
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if (idx === 0) ctx.moveTo(pt[0], pt[1]);
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else ctx.lineTo(pt[0], pt[1]);
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});
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traceSeries(seg);
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ctx.lineJoin = 'round';
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ctx.lineCap = 'round';
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ctx.lineWidth = 1.6;
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@@ -169,11 +215,8 @@
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seg = [];
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}
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points.forEach(function (p, i) {
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if (p.v === null || p.v === undefined) {
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flushSegment();
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return;
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}
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seg.push([xAt(i), yAt(p.v)]);
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var v = (p.v === null || p.v === undefined) ? 0 : p.v;
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seg.push([xAt(i), yAt(v)]);
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});
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flushSegment();
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return true;
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