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Merge pull request #3578 from ControlSystemStudio/LTTB
array down sampling with LTTB
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‎core/formula/doc/index.rst‎

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@@ -155,6 +155,10 @@ This includes the average, min, max, and element count
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**arrayMin(VNumberArray array)** - Returns a VDouble with the smallest value of the given array
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**arraySampleWithLTTB(VNumberArray array, VNumber threshold)** - Returns a VNumberArray which is a down-sampled version of the input array.
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The threshold parameter defines the maximum number of data points to return.
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The down-sampling is performed using the Largest-Triangle-Three-Buckets (LTTB) algorithm.
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**arraySampleWithStride(VNumberArray array, VNumber stride, VNumber offset)** - Returns a VNumberArray where each element is defined as array\[x \* stride + offset\].
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**arrayCumSum(VNumberArray array)** - Returns a VNumberArray where each element is defined as the cumulative sum of the input array.

‎core/formula/src/main/java/org/csstudio/apputil/formula/array/ArraySampleWithLTTBFunction.java‎

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package org.csstudio.apputil.formula.array;
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import org.csstudio.apputil.formula.Formula;
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import org.epics.util.array.CollectionNumbers;
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import org.epics.util.array.ListNumber;
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import org.epics.vtype.Alarm;
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import org.epics.vtype.Display;
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import org.epics.vtype.VNumberArray;
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import org.epics.vtype.VType;
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import org.phoebus.core.vtypes.VTypeHelper;
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import java.util.Arrays;
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import java.util.List;
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import java.util.logging.Level;
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/**
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* @author Kunal Shroff
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*/
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public class ArraySampleWithLTTBFunction extends BaseArrayFunction {
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@Override
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public String getName() {
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return "arraySampleWithLTTB";
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}
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@Override
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public String getDescription() {
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return "Downsample the array using LTTB";
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}
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@Override
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public List<String> getArguments() {
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return List.of("array", "buckets");
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}
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protected VType getArrayData(final VNumberArray array, final double buckets) {
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return VNumberArray.of(sampleWithLTTB(array.getData(), buckets), Alarm.none(), array.getTime(), Display.none());
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}
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// TODO at some point we might want to support non uniform x values
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private static final class Point {
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public final double x, y;
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public Point(double x, double y) { this.x = x; this.y = y; }
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}
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static ListNumber sampleWithLTTB(final ListNumber data, final double threshold) {
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final int n = data.size();
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if (threshold >= n || threshold <= 0) return data;
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if (threshold == 1) return CollectionNumbers.toListDouble(data.getDouble(0));
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if (threshold == 2) return CollectionNumbers.toListDouble(data.getDouble(0), data.getDouble(1));
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final double[] out = new double[(int) threshold];
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out[0] = data.getDouble(0); // keep first
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out[(int) (threshold-1)] = data.getDouble(n-1);
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int aIdx = 0; // index of last selected point
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double bucketSize = (double)(n - 2) / (threshold - 2);
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for (int i = 0; i < threshold - 2; i++) {
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// range of current bucket
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int cs = (int)Math.floor(i * bucketSize) + 1;
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int ce = (int)Math.floor((i + 1) * bucketSize) + 1;
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if (ce > n - 1) ce = n - 1;
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// range of next bucket
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int ns = (int)Math.floor((i + 1) * bucketSize) + 1;
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int ne = (int)Math.floor((i + 2) * bucketSize) + 1;
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if (ne > n - 1) ne = n - 1;
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// average of next bucket (x = index, y = value)
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double avgX;
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double avgY;
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if (ns == ne && ns < n) {
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avgX = ns;
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avgY = data.getDouble(ns);
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} else if (ns >= ne) {
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avgX = ns;
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avgY = data.getDouble(Math.min(ns, n - 2));
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} else {
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double sx = 0, sy = 0;
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for (int j = ns; j < ne; j++) { sx += j; sy += data.getDouble(j); }
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int cnt = ne - ns;
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avgX = sx / cnt;
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avgY = sy / cnt;
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}
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// find point in current bucket with max triangle area
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double ax = aIdx, ay = data.getDouble(aIdx);
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double bestArea = -1;
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int bestIdx = cs;
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for (int j = cs; j < ce; j++) {
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double bx = j, by = data.getDouble(j);
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double area = Math.abs(
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(bx - ax) * (avgY - ay) - (avgX - ax) * (by - ay)
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);
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if (area >= bestArea) { // prefer last index in case of tie
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bestArea = area;
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bestIdx = j;
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}
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}
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out[i+1] = data.getDouble(bestIdx);
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aIdx = bestIdx;
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}
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return CollectionNumbers.toList(out);
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}
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@Override
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public VType compute(final VType... args) throws Exception {
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if (args.length != 2) {
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throw new Exception("Function " + getName() +
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" requires 2 arguments but received " + Arrays.toString(args));
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}
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if (!VTypeHelper.isNumericArray(args[0])) {
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Formula.logger.log(Level.WARNING, "Function " + getName() +
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" takes array but received " + Arrays.toString(args));
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return DEFAULT_NAN_DOUBLE_ARRAY;
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} else {
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double buckets = VTypeHelper.toDouble(args[1]);
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return getArrayData((VNumberArray) args[0], buckets);
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}
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}
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}

‎core/formula/src/main/java/org/csstudio/apputil/formula/array/ArraySampleWithStrideFunction.java‎

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package org.csstudio.apputil.formula.array;
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import org.csstudio.apputil.formula.Formula;
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import org.epics.util.array.ListDouble;
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import org.epics.util.array.ListNumber;
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import org.epics.vtype.Alarm;
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import java.util.Arrays;
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import java.util.List;
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import java.util.logging.Level;
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/**
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* A formula function for extracting elements from the given array at regular intervals (stride),
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throw new Exception("Function " + getName() +
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" requires 2 or 3 arguments but received " + Arrays.toString(args));
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}
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if (!VTypeHelper.isNumericArray(args[0]))
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throw new Exception("Function " + getName() +
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if (!VTypeHelper.isNumericArray(args[0])) {
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Formula.logger.log(Level.WARNING, "Function " + getName() +
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" takes array but received " + Arrays.toString(args));
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return DEFAULT_NAN_DOUBLE_ARRAY;
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double stride = VTypeHelper.toDouble(args[1]);
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double offset = (args.length == 3) ? VTypeHelper.toDouble(args[2]) : 0; // Default offset to 0
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} else {
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double stride = VTypeHelper.toDouble(args[1]);
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double offset = (args.length == 3) ? VTypeHelper.toDouble(args[2]) : 0; // Default offset to 0
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return getArrayData((VNumberArray) args[0], stride, offset);
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return getArrayData((VNumberArray) args[0], stride, offset);
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}
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}
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}

‎core/formula/src/main/resources/META-INF/services/org.csstudio.apputil.formula.spi.FormulaFunction‎

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org.csstudio.apputil.formula.array.ArrayInverseScalarDivisionFunction
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org.csstudio.apputil.formula.array.ArrayOfFunction
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org.csstudio.apputil.formula.array.ArrayRangeOfFunction
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org.csstudio.apputil.formula.array.ArraySampleWithLTTBFunction
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org.csstudio.apputil.formula.array.ArraySampleWithStrideFunction
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org.csstudio.apputil.formula.array.ArrayStatsFunction
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org.csstudio.apputil.formula.array.ArrayMaxFunction

‎core/formula/src/test/java/org/csstudio/apputil/formula/array/ArraySampleWithLTTBFunctionTest.java‎

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package org.csstudio.apputil.formula.array;
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import org.epics.util.array.*;
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import org.junit.jupiter.api.Test;
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import static org.junit.jupiter.api.Assertions.*;
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class ArraySampleWithLTTBFunctionTest {
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@Test
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void testThresholdEqualsOne() {
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ListNumber data = CollectionNumbers.toListDouble(1.0, 2.0, 3.0, 4.0);
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ListNumber result = ArraySampleWithLTTBFunction.sampleWithLTTB(data, 1);
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assertEquals(1, result.size());
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assertEquals(1.0, result.getDouble(0));
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}
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@Test
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void testThresholdEqualsTwo() {
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ListNumber data = CollectionNumbers.toListDouble(1.0, 2.0, 3.0, 4.0);
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ListNumber result = ArraySampleWithLTTBFunction.sampleWithLTTB(data, 2);
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assertEquals(2, result.size());
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assertEquals(1.0, result.getDouble(0));
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assertEquals(2.0, result.getDouble(1));
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}
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@Test
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void testThresholdGreaterThanDataSize() {
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ListNumber data = CollectionNumbers.toListDouble(1.0, 2.0, 3.0);
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ListNumber result = ArraySampleWithLTTBFunction.sampleWithLTTB(data, 5);
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assertEquals(data.size(), result.size());
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for (int i = 0; i < data.size(); i++) {
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assertEquals(data.getDouble(i), result.getDouble(i));
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}
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}
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@Test
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void testMonotonicIncreasing() {
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ListNumber data = CollectionNumbers.toListDouble(1.0, 2.0, 3.0, 4.0, 5.0, 6.0);
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ListNumber result = ArraySampleWithLTTBFunction.sampleWithLTTB(data, 3);
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assertEquals(3, result.size());
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assertEquals(1.0, result.getDouble(0));
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assertEquals(5.0, result.getDouble(1));
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assertEquals(6.0, result.getDouble(2));
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}
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@Test
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void testConstantData() {
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ListNumber data = CollectionNumbers.toListDouble(5.0, 5.0, 5.0, 5.0, 5.0);
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ListNumber result = ArraySampleWithLTTBFunction.sampleWithLTTB(data, 3);
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assertEquals(3, result.size());
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assertEquals(5.0, result.getDouble(0));
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assertEquals(5.0, result.getDouble(1));
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assertEquals(5.0, result.getDouble(2));
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}
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}
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