// === predict_linear(node model.ValMatrix, k model.ValScalar) Vector ===
func funcPredictLinear(ev *evaluator, args Expressions) model.Value {
	vec := funcDeriv(ev, args[0:1]).(vector)
	duration := model.SampleValue(model.SampleValue(ev.evalFloat(args[1])))

	excludedLabels := map[model.LabelName]struct{}{
		model.MetricNameLabel: {},
	}

	// Calculate predicted delta over the duration.
	signatureToDelta := map[uint64]model.SampleValue{}
	for _, el := range vec {
		signature := model.SignatureWithoutLabels(el.Metric.Metric, excludedLabels)
		signatureToDelta[signature] = el.Value * duration
	}

	// add predicted delta to last value.
	matrixBounds := ev.evalMatrixBounds(args[0])
	outVec := make(vector, 0, len(signatureToDelta))
	for _, samples := range matrixBounds {
		if len(samples.Values) < 2 {
			continue
		}
		signature := model.SignatureWithoutLabels(samples.Metric.Metric, excludedLabels)
		delta, ok := signatureToDelta[signature]
		if ok {
			samples.Metric.Del(model.MetricNameLabel)
			outVec = append(outVec, &sample{
				Metric:    samples.Metric,
				Value:     delta + samples.Values[1].Value,
				Timestamp: ev.Timestamp,
			})
		}
	}
	return outVec
}

// === histogram_quantile(k model.ValScalar, vector model.ValVector) Vector ===
func funcHistogramQuantile(ev *evaluator, args Expressions) model.Value {
	q := model.SampleValue(ev.evalFloat(args[0]))
	inVec := ev.evalVector(args[1])

	outVec := vector{}
	signatureToMetricWithBuckets := map[uint64]*metricWithBuckets{}
	for _, el := range inVec {
		upperBound, err := strconv.ParseFloat(
			string(el.Metric.Metric[model.BucketLabel]), 64,
		)
		if err != nil {
			// Oops, no bucket label or malformed label value. Skip.
			// TODO(beorn7): Issue a warning somehow.
			continue
		}
		signature := model.SignatureWithoutLabels(el.Metric.Metric, excludedLabels)
		mb, ok := signatureToMetricWithBuckets[signature]
		if !ok {
			el.Metric.Del(model.BucketLabel)
			el.Metric.Del(model.MetricNameLabel)
			mb = &metricWithBuckets{el.Metric, nil}
			signatureToMetricWithBuckets[signature] = mb
		}
		mb.buckets = append(mb.buckets, bucket{upperBound, el.Value})
	}

	for _, mb := range signatureToMetricWithBuckets {
		outVec = append(outVec, &sample{
			Metric:    mb.metric,
			Value:     model.SampleValue(bucketQuantile(q, mb.buckets)),
			Timestamp: ev.Timestamp,
		})
	}

	return outVec
}