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All rights reserved.\n// Use of this source code is governed by a BSD-style license that can be\n// found in the LICENSE file.\n\nimport * as Core from '../core/core.js';\nimport * as Graph from '../graph/graph.js';\nimport type * as Simulation from '../simulation/simulation.js';\n\nimport {\n  type Extras,\n  Metric,\n  type MetricCoefficients,\n  type MetricComputationDataInput,\n  type MetricResult,\n} from './Metric.js';\n\nconst mobileSlow4GRtt = 150;\n\nclass SpeedIndex extends Metric {\n  static override get coefficients(): MetricCoefficients {\n    return {\n      // Note that the optimistic estimate is based on the real observed speed index rather than a\n      // real lantern graph (and the final estimate will be Math.max(FCP, Speed Index)).\n      intercept: 0,\n      optimistic: 1.4,\n      pessimistic: 0.4,\n    };\n  }\n\n  static override getScaledCoefficients(rttMs: number): MetricCoefficients {\n    // We want to scale our default coefficients based on the speed of the connection.\n    // We will linearly interpolate coefficients for the passed-in rttMs based on two pre-determined points:\n    //   1. Baseline point of 30 ms RTT where Speed Index should be a ~50/50 blend of optimistic/pessimistic.\n    //      30 ms was based on a typical home WiFi connection's actual RTT.\n    //      Coefficients here follow from the fact that the optimistic estimate should be very close\n    //      to reality at this connection speed and the pessimistic estimate compensates for minor\n    //      connection speed differences.\n    //   2. Default throttled point of 150 ms RTT where the default coefficients have been determined to be most accurate.\n    //      Coefficients here were determined through thorough analysis and linear regression on the\n    //      lantern test data set. See core/scripts/test-lantern.sh for more detail.\n    // While the coefficients haven't been analyzed at the interpolated points, it's our current best effort.\n    const defaultCoefficients = this.coefficients;\n    const defaultRttExcess = mobileSlow4GRtt - 30;\n    const multiplier = Math.max((rttMs - 30) / defaultRttExcess, 0);\n\n    return {\n      intercept: defaultCoefficients.intercept * multiplier,\n      optimistic: 0.5 + (defaultCoefficients.optimistic - 0.5) * multiplier,\n      pessimistic: 0.5 + (defaultCoefficients.pessimistic - 0.5) * multiplier,\n    };\n  }\n\n  static override getOptimisticGraph(dependencyGraph: Graph.Node): Graph.Node {\n    return dependencyGraph;\n  }\n\n  static override getPessimisticGraph(dependencyGraph: Graph.Node): Graph.Node {\n    return dependencyGraph;\n  }\n\n  static override getEstimateFromSimulation(simulationResult: Simulation.Result, extras: Extras): Simulation.Result {\n    if (!extras.fcpResult) {\n      throw new Core.LanternError('missing fcpResult');\n    }\n    if (extras.observedSpeedIndex === undefined) {\n      throw new Core.LanternError('missing observedSpeedIndex');\n    }\n\n    const fcpTimeInMs = extras.fcpResult.pessimisticEstimate.timeInMs;\n    const estimate = extras.optimistic ?\n        extras.observedSpeedIndex :\n        SpeedIndex.computeLayoutBasedSpeedIndex(simulationResult.nodeTimings, fcpTimeInMs);\n    return {\n      timeInMs: estimate,\n      nodeTimings: simulationResult.nodeTimings,\n    };\n  }\n\n  static override compute(data: MetricComputationDataInput, extras?: Omit<Extras, 'optimistic'>): MetricResult {\n    const fcpResult = extras?.fcpResult;\n    if (!fcpResult) {\n      throw new Core.LanternError('FCP is required to calculate the SpeedIndex metric');\n    }\n\n    const metricResult = super.compute(data, extras);\n    metricResult.timing = Math.max(metricResult.timing, fcpResult.timing);\n    return metricResult;\n  }\n\n  /**\n   * Approximate speed index using layout events from the simulated node timings.\n   * The layout-based speed index is the weighted average of the endTime of CPU nodes that contained\n   * a 'Layout' task. log(duration) is used as the weight to stand for \"significance\" to the page.\n   *\n   * If no layout events can be found or the endTime of a CPU task is too early, FCP is used instead.\n   *\n   * This approach was determined after evaluating the accuracy/complexity tradeoff of many\n   * different methods. Read more in the evaluation doc.\n   *\n   * @see https://docs.google.com/document/d/1qJWXwxoyVLVadezIp_Tgdk867G3tDNkkVRvUJSH3K1E/edit#\n   */\n  static computeLayoutBasedSpeedIndex(nodeTimings: Simulation.Result['nodeTimings'], fcpTimeInMs: number): number {\n    const layoutWeights: Array<{time: number, weight: number}> = [];\n    for (const [node, timing] of nodeTimings.entries()) {\n      if (node.type !== Graph.BaseNode.types.CPU) {\n        continue;\n      }\n\n      if (node.childEvents.some(x => x.name === 'Layout')) {\n        const timingWeight = Math.max(Math.log2(timing.endTime - timing.startTime), 0);\n        layoutWeights.push({time: timing.endTime, weight: timingWeight});\n      }\n    }\n\n    const totalWeightedTime =\n        layoutWeights.map(evt => evt.weight * Math.max(evt.time, fcpTimeInMs)).reduce((a, b) => a + b, 0);\n    const totalWeight = layoutWeights.map(evt => evt.weight).reduce((a, b) => a + b, 0);\n\n    if (!totalWeight) {\n      return fcpTimeInMs;\n    }\n    return totalWeightedTime / totalWeight;\n  }\n}\n\nexport {SpeedIndex};\n"]}