Add synthetic array (waveform) DSP support + UX improvements
Adds full array/waveform support through the synthetic DSP engine: a dsp.Sample value model (scalar or []float64), array ops (index, slice, sum, mean, min, max, length, fft) with an in-tree radix-2 FFT, and static type propagation (OpOutputType) that the editor mirrors to colour wires by data type and flag invalid wirings. Stateful filters and lua stay scalar-only. Adds a waveform plot mode (x-vs-index trace). Also: errored-node hover reasons, S/N add-signal/add-node HUD shortcuts in the synthetic editor, and view-mode widgets that blend with the canvas background (chrome kept in edit mode). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -0,0 +1,222 @@
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package synthetic
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import (
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"context"
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"log/slog"
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"math"
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"os"
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"testing"
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"time"
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"github.com/uopi/uopi/internal/broker"
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"github.com/uopi/uopi/internal/datasource"
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"github.com/uopi/uopi/internal/dsp"
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)
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// evalSampleDef compiles a SignalDef and evaluates it against per-source
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// Samples keyed by source node id, returning the output Sample.
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func evalSampleDef(t *testing.T, def SignalDef, srcVals map[string]dsp.Sample) dsp.Sample {
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t.Helper()
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rg, err := compileGraph(def)
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if err != nil {
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t.Fatalf("compileGraph: %v", err)
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}
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out, err := rg.evalSample(srcVals)
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if err != nil {
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t.Fatalf("evalSample: %v", err)
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}
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return out
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}
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// TestArrayElementwiseChain runs an array source through an elementwise op
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// (gain) and asserts the output stays an array, broadcast per element.
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func TestArrayElementwiseChain(t *testing.T) {
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def := SignalDef{
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Name: "scaled",
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Graph: &Graph{
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Output: "out",
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Nodes: []GraphNode{
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{ID: "a", Kind: "source", DS: "x", Signal: "wave"},
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{ID: "g", Kind: "op", Op: "gain", Inputs: []string{"a"}, Params: map[string]any{"gain": 2.0}},
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{ID: "out", Kind: "output", Inputs: []string{"g"}},
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},
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},
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}
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out := evalSampleDef(t, def, map[string]dsp.Sample{"a": dsp.Array([]float64{1, 2, 3})})
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if !out.IsArray {
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t.Fatalf("want array output, got %v", out)
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}
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want := []float64{2, 4, 6}
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for i, v := range want {
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if out.Arr[i] != v {
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t.Errorf("scaled[%d]: want %v, got %v", i, v, out.Arr[i])
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}
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}
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}
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// TestArrayReductionToScalar runs an array source into mean (array→scalar) and
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// asserts a scalar output and an array-output compile type for the producer.
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func TestArrayReductionToScalar(t *testing.T) {
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def := SignalDef{
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Name: "avg",
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Graph: &Graph{
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Output: "out",
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Nodes: []GraphNode{
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{ID: "a", Kind: "source", DS: "x", Signal: "wave"},
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{ID: "m", Kind: "op", Op: "mean", Inputs: []string{"a"}},
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{ID: "out", Kind: "output", Inputs: []string{"m"}},
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},
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},
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}
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out := evalSampleDef(t, def, map[string]dsp.Sample{"a": dsp.Array([]float64{2, 4, 6, 8})})
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if out.IsArray {
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t.Fatalf("want scalar output, got array %v", out.Arr)
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}
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if math.Abs(out.F-5) > 1e-9 {
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t.Errorf("mean: want 5, got %v", out.F)
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}
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}
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// TestArrayOutTypeMetadata verifies compileGraph reports an array output type
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// for a pure-elementwise array graph and scalar for a reduction graph.
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func TestArrayOutTypeMetadata(t *testing.T) {
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arrayGraph := SignalDef{
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Name: "fftout",
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Graph: &Graph{
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Output: "out",
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Nodes: []GraphNode{
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{ID: "a", Kind: "source", DS: "x", Signal: "wave"},
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{ID: "f", Kind: "op", Op: "fft", Inputs: []string{"a"}},
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{ID: "out", Kind: "output", Inputs: []string{"f"}},
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},
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},
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}
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rg, err := compileGraph(arrayGraph)
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if err != nil {
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t.Fatalf("compileGraph: %v", err)
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}
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if rg.outType != dsp.ValArray {
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t.Errorf("fft graph outType: want ValArray, got %v", rg.outType)
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}
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reduction := SignalDef{
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Name: "sumout",
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Graph: &Graph{
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Output: "out",
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Nodes: []GraphNode{
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{ID: "a", Kind: "source", DS: "x", Signal: "wave"},
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{ID: "s", Kind: "op", Op: "sum", Inputs: []string{"a"}},
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{ID: "out", Kind: "output", Inputs: []string{"s"}},
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},
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},
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}
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rg2, err := compileGraph(reduction)
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if err != nil {
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t.Fatalf("compileGraph: %v", err)
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}
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if rg2.outType != dsp.ValScalar {
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t.Errorf("sum graph outType: want ValScalar, got %v", rg2.outType)
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}
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}
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// TestStatefulRejectsArray verifies a stateful op (moving_average) errors when
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// fed an array input at runtime.
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func TestStatefulRejectsArray(t *testing.T) {
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def := SignalDef{
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Name: "ma",
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Graph: &Graph{
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Output: "out",
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Nodes: []GraphNode{
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{ID: "a", Kind: "source", DS: "x", Signal: "wave"},
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{ID: "m", Kind: "op", Op: "moving_average", Inputs: []string{"a"}, Params: map[string]any{"window": 3.0}},
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{ID: "out", Kind: "output", Inputs: []string{"m"}},
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},
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},
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}
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rg, err := compileGraph(def)
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if err != nil {
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t.Fatalf("compileGraph: %v", err)
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}
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if _, err := rg.evalSample(map[string]dsp.Sample{"a": dsp.Array([]float64{1, 2, 3})}); err == nil {
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t.Error("expected moving_average to reject an array input")
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}
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}
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// TestSubscribeArrayPassthrough is an end-to-end check that a synthetic with an
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// array-valued source and an elementwise op emits a []float64 over the broker,
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// and that GetMetadata reports the waveform type.
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func TestSubscribeArrayPassthrough(t *testing.T) {
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log := slog.New(slog.NewTextHandler(os.Stderr, nil))
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ctx, cancel := context.WithCancel(context.Background())
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defer cancel()
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base := time.Date(2026, 6, 19, 10, 0, 0, 0, time.UTC)
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src := &seqSource{name: "src", seq: []datasource.Value{
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{Timestamp: base.Add(1 * time.Second), Data: []float64{1, 2, 3}, Quality: datasource.QualityGood},
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{Timestamp: base.Add(2 * time.Second), Data: []float64{4, 5, 6}, Quality: datasource.QualityGood},
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}}
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brk := broker.New(ctx, log)
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brk.Register(src)
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syn := New(t.TempDir(), brk, log)
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if err := syn.Connect(ctx); err != nil {
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t.Fatal(err)
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}
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// gain x2 elementwise keeps the value an array.
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if err := syn.AddSignal(SignalDef{
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Name: "scaled",
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Graph: &Graph{Output: "out", Nodes: []GraphNode{
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{ID: "a", Kind: "source", DS: "src", Signal: "x"},
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{ID: "g", Kind: "op", Op: "gain", Inputs: []string{"a"}, Params: map[string]any{"gain": 2.0}},
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{ID: "out", Kind: "output", Inputs: []string{"g"}},
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}},
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}); err != nil {
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t.Fatal(err)
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}
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// An fft-based signal has a statically-known array output type (the source's
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// runtime type need not be known), so its metadata reports the waveform type.
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if err := syn.AddSignal(SignalDef{
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Name: "spectrum",
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Graph: &Graph{Output: "out", Nodes: []GraphNode{
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{ID: "a", Kind: "source", DS: "src", Signal: "x"},
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{ID: "f", Kind: "op", Op: "fft", Inputs: []string{"a"}},
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{ID: "out", Kind: "output", Inputs: []string{"f"}},
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}},
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}); err != nil {
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t.Fatal(err)
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}
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meta, err := syn.GetMetadata(ctx, "spectrum")
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if err != nil {
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t.Fatal(err)
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}
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if meta.Type != datasource.TypeFloat64Array {
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t.Errorf("metadata type: want TypeFloat64Array, got %v", meta.Type)
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}
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ch := make(chan datasource.Value, 8)
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if _, err := syn.Subscribe(ctx, "scaled", ch); err != nil {
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t.Fatal(err)
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}
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want := [][]float64{{2, 4, 6}, {8, 10, 12}}
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for i, w := range want {
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select {
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case v := <-ch:
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arr, ok := v.Data.([]float64)
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if !ok {
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t.Fatalf("emit #%d: want []float64, got %T", i, v.Data)
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}
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if len(arr) != len(w) {
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t.Fatalf("emit #%d: want len %d, got %d", i, len(w), len(arr))
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}
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for k, val := range w {
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if arr[k] != val {
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t.Errorf("emit #%d [%d]: want %v, got %v", i, k, val, arr[k])
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}
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}
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case <-time.After(2 * time.Second):
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t.Fatalf("timeout waiting for emit #%d", i)
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}
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}
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}
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@@ -126,6 +126,30 @@ func buildNode(d NodeDef) (dsp.Node, error) {
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case "lua":
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return &dsp.LuaNode{Script: stringParam(p, "script"), Vars: stringSliceParam(p, "vars")}, nil
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case "index":
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return &dsp.IndexNode{I: int(floatParam(p, "i"))}, nil
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case "slice":
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return &dsp.SliceNode{Start: int(floatParam(p, "start")), End: int(floatParam(p, "end"))}, nil
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case "sum":
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return &dsp.SumNode{}, nil
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case "mean":
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return &dsp.MeanNode{}, nil
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case "min":
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return &dsp.MinNode{}, nil
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case "max":
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return &dsp.MaxNode{}, nil
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case "length":
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return &dsp.LengthNode{}, nil
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case "fft":
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return &dsp.FFTNode{}, nil
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default:
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return nil, fmt.Errorf("unknown node type %q", d.Type)
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}
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@@ -13,9 +13,10 @@ import (
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// each node's inputs already resolved. Op-node state maps persist across
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// evaluations (for stateful nodes like moving_average / lua).
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type runtimeGraph struct {
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order []*rtNode // topological order (sources first, output last)
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sources []rtSource // source nodes, in topological order
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outputID string // id of the output node
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order []*rtNode // topological order (sources first, output last)
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sources []rtSource // source nodes, in topological order
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outputID string // id of the output node
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outType dsp.ValType // best-effort output type (scalar/array/unknown)
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}
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type rtNode struct {
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@@ -41,24 +42,30 @@ func (rg *runtimeGraph) sourceRefs() []broker.SignalRef {
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return refs
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}
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// eval computes the output value given the latest value for each source node
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// (keyed by source node id). Nodes are visited in topological order so every
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// input is already present in vals by the time a node is processed.
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func (rg *runtimeGraph) eval(sourceVals map[string]float64) (float64, error) {
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vals := make(map[string]float64, len(rg.order))
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// evalSample computes the output Sample (scalar or array) given the latest
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// value for each source node (keyed by source node id). Nodes are visited in
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// topological order so every input is present by the time a node is processed.
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//
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// Op dispatch:
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// - ArrayNode ops (reductions/producers) run natively on Samples.
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// - stateless elementwise ops broadcast over array inputs.
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// - stateful ops (filters) and lua are scalar-only; an array input errors,
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// since their per-evaluation state cannot be split across array lanes.
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func (rg *runtimeGraph) evalSample(sourceVals map[string]dsp.Sample) (dsp.Sample, error) {
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vals := make(map[string]dsp.Sample, len(rg.order))
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for id, v := range sourceVals {
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vals[id] = v
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}
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for _, n := range rg.order {
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switch n.kind {
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case "op":
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in := make([]float64, len(n.inputs))
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in := make([]dsp.Sample, len(n.inputs))
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for i, id := range n.inputs {
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in[i] = vals[id]
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}
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r, err := n.op.Process(in, n.state)
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r, err := evalOp(n, in)
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if err != nil {
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return 0, fmt.Errorf("node %s (%s): %w", n.id, n.op.Type(), err)
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return dsp.Sample{}, fmt.Errorf("node %s (%s): %w", n.id, n.op.Type(), err)
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}
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vals[n.id] = r
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case "output":
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@@ -70,6 +77,44 @@ func (rg *runtimeGraph) eval(sourceVals map[string]float64) (float64, error) {
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return vals[rg.outputID], nil
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}
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// evalOp runs a single op node over its Sample inputs, choosing the right
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// execution path for the node type.
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func evalOp(n *rtNode, in []dsp.Sample) (dsp.Sample, error) {
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if an, ok := n.op.(dsp.ArrayNode); ok {
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return an.ProcessSample(in, n.state)
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}
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if dsp.StatelessElementwise(n.op.Type()) {
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return dsp.ApplyElementwise(n.op, in, n.state)
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}
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// Stateful / lua: scalar-only.
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row := make([]float64, len(in))
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for i, s := range in {
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if s.IsArray {
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return dsp.Sample{}, fmt.Errorf("does not accept an array input")
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}
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row[i] = s.F
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}
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r, err := n.op.Process(row, n.state)
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if err != nil {
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return dsp.Sample{}, err
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}
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return dsp.Scalar(r), nil
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}
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// eval is the scalar wrapper around evalSample, kept so callers and tests that
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// deal purely in float64 (legacy linear graphs, scalar sources) are unchanged.
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func (rg *runtimeGraph) eval(sourceVals map[string]float64) (float64, error) {
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sv := make(map[string]dsp.Sample, len(sourceVals))
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for id, v := range sourceVals {
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sv[id] = dsp.Scalar(v)
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}
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out, err := rg.evalSample(sv)
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if err != nil {
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return 0, err
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}
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return out.F, nil
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}
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// compileGraph converts a SignalDef into an executable runtimeGraph. When the
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// def carries an explicit Graph it is used directly; otherwise the legacy
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// Inputs+Pipeline form is converted to an equivalent linear graph (see toGraph).
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@@ -83,23 +128,42 @@ func compileGraph(def SignalDef) (*runtimeGraph, error) {
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return nil, err
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}
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rg := &runtimeGraph{outputID: g.Output}
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// nodeType tracks each node's best-effort output type for static
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// propagation. Sources are unknown at compile time (their real type is
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// only known once data flows), so type errors here are advisory; runtime
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// Sample typing is authoritative.
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nodeType := make(map[string]dsp.ValType, len(order))
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for _, gn := range order {
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switch gn.Kind {
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case "source":
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rg.sources = append(rg.sources, rtSource{id: gn.ID, ref: broker.SignalRef{DS: gn.DS, Name: gn.Signal}})
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nodeType[gn.ID] = dsp.ValUnknown
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case "op":
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node, err := buildNode(NodeDef{Type: gn.Op, Params: gn.Params})
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if err != nil {
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return nil, fmt.Errorf("node %q: %w", gn.ID, err)
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}
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inTypes := make([]dsp.ValType, len(gn.Inputs))
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for i, id := range gn.Inputs {
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inTypes[i] = nodeType[id]
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}
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ot, terr := dsp.OpOutputType(gn.Op, inTypes)
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if terr != nil {
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return nil, fmt.Errorf("node %q: %w", gn.ID, terr)
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}
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nodeType[gn.ID] = ot
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rg.order = append(rg.order, &rtNode{id: gn.ID, kind: "op", op: node, state: map[string]any{}, inputs: gn.Inputs})
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case "output":
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rg.outputID = gn.ID
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if len(gn.Inputs) > 0 {
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nodeType[gn.ID] = nodeType[gn.Inputs[0]]
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}
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rg.order = append(rg.order, &rtNode{id: gn.ID, kind: "output", inputs: gn.Inputs})
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default:
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return nil, fmt.Errorf("node %q: unknown kind %q", gn.ID, gn.Kind)
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}
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}
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rg.outType = nodeType[rg.outputID]
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return rg, nil
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}
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@@ -13,6 +13,7 @@ import (
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"github.com/uopi/uopi/internal/broker"
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"github.com/uopi/uopi/internal/datasource"
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"github.com/uopi/uopi/internal/dsp"
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)
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const definitionsFile = "synthetic.json"
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@@ -78,7 +79,7 @@ func (s *Synthetic) ListSignals(_ context.Context) ([]datasource.Metadata, error
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out := make([]datasource.Metadata, 0, len(s.signals))
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for _, st := range s.signals {
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out = append(out, defToMetadata(st.def))
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out = append(out, defToMetadata(st.def, outTypeOf(st)))
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}
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return out, nil
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}
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@@ -93,7 +94,7 @@ func (s *Synthetic) FilteredMetadata(keep func(SignalDef) bool) []datasource.Met
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out := make([]datasource.Metadata, 0, len(s.signals))
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for _, st := range s.signals {
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if keep(st.def) {
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out = append(out, defToMetadata(st.def))
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out = append(out, defToMetadata(st.def, outTypeOf(st)))
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}
|
||||
}
|
||||
return out
|
||||
@@ -108,7 +109,7 @@ func (s *Synthetic) GetMetadata(_ context.Context, signal string) (datasource.Me
|
||||
if !ok {
|
||||
return datasource.Metadata{}, datasource.ErrNotFound
|
||||
}
|
||||
return defToMetadata(st.def), nil
|
||||
return defToMetadata(st.def, outTypeOf(st)), nil
|
||||
}
|
||||
|
||||
// Subscribe registers ch to receive computed values for the named signal.
|
||||
@@ -138,7 +139,7 @@ func (s *Synthetic) Subscribe(ctx context.Context, signal string, ch chan<- data
|
||||
defer cancel()
|
||||
|
||||
// Latest value and timestamp per source node id.
|
||||
latest := make(map[string]float64, len(refs))
|
||||
latest := make(map[string]dsp.Sample, len(refs))
|
||||
latestTs := make([]time.Time, len(refs))
|
||||
ready := make([]bool, len(refs))
|
||||
|
||||
@@ -163,7 +164,7 @@ func (s *Synthetic) Subscribe(ctx context.Context, signal string, ch chan<- data
|
||||
if !ok {
|
||||
return
|
||||
}
|
||||
val := toFloat64(u.Value.Data)
|
||||
val := toSample(u.Value.Data)
|
||||
select {
|
||||
case updateCh <- indexedUpdate{idx: idx, val: val, ts: u.Value.Timestamp}:
|
||||
default:
|
||||
@@ -224,7 +225,7 @@ func (s *Synthetic) Subscribe(ctx context.Context, signal string, ch chan<- data
|
||||
return
|
||||
}
|
||||
|
||||
result, err := cur.rg.eval(latest)
|
||||
result, err := cur.rg.evalSample(latest)
|
||||
if err != nil {
|
||||
s.log.Warn("synthetic: pipeline error", "signal", signal, "err", err)
|
||||
continue
|
||||
@@ -232,7 +233,7 @@ func (s *Synthetic) Subscribe(ctx context.Context, signal string, ch chan<- data
|
||||
|
||||
v := datasource.Value{
|
||||
Timestamp: outTs,
|
||||
Data: result,
|
||||
Data: result.AsAny(),
|
||||
Quality: datasource.QualityGood,
|
||||
}
|
||||
select {
|
||||
@@ -421,11 +422,17 @@ func (s *Synthetic) startSignal(def SignalDef) error {
|
||||
return nil
|
||||
}
|
||||
|
||||
// defToMetadata converts a SignalDef into a datasource.Metadata.
|
||||
func defToMetadata(def SignalDef) datasource.Metadata {
|
||||
// defToMetadata converts a SignalDef into a datasource.Metadata. outType is the
|
||||
// compiled graph's best-effort output type; an array output is reported as a
|
||||
// waveform (TypeFloat64Array) so widgets can pick a compatible view.
|
||||
func defToMetadata(def SignalDef, outType dsp.ValType) datasource.Metadata {
|
||||
dt := datasource.TypeFloat64
|
||||
if outType == dsp.ValArray {
|
||||
dt = datasource.TypeFloat64Array
|
||||
}
|
||||
return datasource.Metadata{
|
||||
Name: def.Name,
|
||||
Type: datasource.TypeFloat64,
|
||||
Type: dt,
|
||||
Unit: def.Meta.Unit,
|
||||
Description: def.Meta.Description,
|
||||
DisplayLow: def.Meta.DisplayLow,
|
||||
@@ -434,7 +441,38 @@ func defToMetadata(def SignalDef) datasource.Metadata {
|
||||
}
|
||||
}
|
||||
|
||||
// toFloat64 coerces any numeric value from a datasource.Value.Data to float64.
|
||||
// outTypeOf returns the compiled output type for a signal state, or unknown.
|
||||
func outTypeOf(st *signalState) dsp.ValType {
|
||||
if st == nil || st.rg == nil {
|
||||
return dsp.ValUnknown
|
||||
}
|
||||
return st.rg.outType
|
||||
}
|
||||
|
||||
// toSample coerces a datasource.Value.Data into a dsp.Sample: arrays become
|
||||
// array Samples (waveforms), everything else a scalar Sample.
|
||||
func toSample(v any) dsp.Sample {
|
||||
switch val := v.(type) {
|
||||
case []float64:
|
||||
return dsp.Array(val)
|
||||
case []float32:
|
||||
out := make([]float64, len(val))
|
||||
for i, e := range val {
|
||||
out[i] = float64(e)
|
||||
}
|
||||
return dsp.Array(out)
|
||||
case []int:
|
||||
out := make([]float64, len(val))
|
||||
for i, e := range val {
|
||||
out[i] = float64(e)
|
||||
}
|
||||
return dsp.Array(out)
|
||||
default:
|
||||
return dsp.Scalar(toFloat64(v))
|
||||
}
|
||||
}
|
||||
|
||||
// toFloat64 coerces any numeric scalar value from a datasource.Value.Data to float64.
|
||||
func toFloat64(v any) float64 {
|
||||
switch val := v.(type) {
|
||||
case float64:
|
||||
@@ -460,6 +498,6 @@ func toFloat64(v any) float64 {
|
||||
// indexedUpdate carries a value from one upstream goroutine to the pipeline runner.
|
||||
type indexedUpdate struct {
|
||||
idx int
|
||||
val float64
|
||||
val dsp.Sample
|
||||
ts time.Time
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user