ENFv2 - Adjustments for new tech spec (EXPOSUREAPP-3853) (#1647)

* Added numberOfDaysWithHighRisk and numberOfDaysWithLowRisk

according to new tech spec

* Transformed minimumDistinctEncountersForRisk and mostRecentDateForRisk into extension fun

* typealias for ProtobufRiskLevels

Signed-off-by: Kolya Opahle <k.opahle@sap.com>

Co-authored-by: Kolya Opahle <k.opahle@sap.com>

Corona-Warn-App/src/main/java/de/rki/coronawarnapp/risk/DefaultRiskLevels.kt

@@ -28,6 +28,7 @@ import org.joda.time.Instant
 import timber.log.Timber
 import javax.inject.Inject
 import javax.inject.Singleton
+typealias ProtoRiskLevel = RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel
 
 @Singleton
 class DefaultRiskLevels @Inject constructor(
@@ -106,8 +107,7 @@ class DefaultRiskLevels @Inject constructor(
 
         val aggregatedResult = aggregateResults(riskResultsPerWindow)
 
-        return aggregatedResult.totalRiskLevel ==
-            RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel.HIGH
+        return aggregatedResult.totalRiskLevel == ProtoRiskLevel.HIGH
     }
 
     override fun isActiveTracingTimeAboveThreshold(): Boolean {
@@ -345,18 +345,14 @@ class DefaultRiskLevels @Inject constructor(
         Timber.d("totalRiskLevel: ${totalRiskLevel.name} (${totalRiskLevel.ordinal})")
 
         // 7. Determine `Date of Most Recent Date with Low Risk`
-        val mostRecentDateWithLowRisk = mostRecentDateForRisk(
-            exposureHistory,
-            RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel.LOW
-        )
+        val mostRecentDateWithLowRisk =
+            exposureHistory.mostRecentDateForRisk(ProtoRiskLevel.LOW)
 
         Timber.d("mostRecentDateWithLowRisk: $mostRecentDateWithLowRisk")
 
         // 8. Determine `Date of Most Recent Date with High Risk`
-        val mostRecentDateWithHighRisk = mostRecentDateForRisk(
-            exposureHistory,
-            RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel.HIGH
-        )
+        val mostRecentDateWithHighRisk =
+            exposureHistory.mostRecentDateForRisk(ProtoRiskLevel.HIGH)
 
         Timber.d("mostRecentDateWithHighRisk: $mostRecentDateWithHighRisk")
 
@@ -372,22 +368,37 @@ class DefaultRiskLevels @Inject constructor(
 
         Timber.d("totalMinimumDistinctEncountersWithHighRisk: $totalMinimumDistinctEncountersWithHighRisk")
 
+        // 11. Determine `Number of Days With Low Risk`
+        val numberOfDaysWithLowRisk =
+            exposureHistory.numberOfDaysForRisk(ProtoRiskLevel.LOW)
+
+        Timber.d("numberOfDaysWithLowRisk: $numberOfDaysWithLowRisk")
+
+        // 12. Determine `Number of Days With High Risk`
+        val numberOfDaysWithHighRisk =
+            exposureHistory.numberOfDaysForRisk(ProtoRiskLevel.HIGH)
+
+        Timber.d("numberOfDaysWithHighRisk: $numberOfDaysWithHighRisk")
+
         return AggregatedRiskResult(
             totalRiskLevel,
             totalMinimumDistinctEncountersWithLowRisk,
             totalMinimumDistinctEncountersWithHighRisk,
             mostRecentDateWithLowRisk,
-            mostRecentDateWithHighRisk
+            mostRecentDateWithHighRisk,
+            numberOfDaysWithLowRisk,
+            numberOfDaysWithHighRisk
         )
     }
 
-    private fun mostRecentDateForRisk(
-        exposureHistory: List<AggregatedRiskPerDateResult>,
-        riskLevel: RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel
-    ): Instant? = exposureHistory
-        .filter { it.riskLevel == riskLevel }
-        .maxOfOrNull { it.dateMillisSinceEpoch }
-        ?.let { Instant.ofEpochMilli(it) }
+    private fun List<AggregatedRiskPerDateResult>.mostRecentDateForRisk(riskLevel: ProtoRiskLevel): Instant? =
+        filter { it.riskLevel == riskLevel }
+            .maxOfOrNull { it.dateMillisSinceEpoch }
+            ?.let { Instant.ofEpochMilli(it) }
+
+    private fun List<AggregatedRiskPerDateResult>.numberOfDaysForRisk(riskLevel: ProtoRiskLevel): Int =
+        filter { it.riskLevel == riskLevel }
+            .size
 
     private fun aggregateRiskPerDate(
         dateMillisSinceEpoch: Long,
@@ -419,18 +430,14 @@ class DefaultRiskLevels @Inject constructor(
         Timber.d("riskLevel: ${riskLevel.name} (${riskLevel.ordinal})")
 
         // 4. Determine `Minimum Distinct Encounters With Low Risk per Date`
-        val minimumDistinctEncountersWithLowRisk = minimumDistinctEncountersForRisk(
-            exposureWindowsAndResultForDate,
-            RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel.LOW
-        )
+        val minimumDistinctEncountersWithLowRisk =
+            exposureWindowsAndResultForDate.minimumDistinctEncountersForRisk(ProtoRiskLevel.LOW)
 
         Timber.d("minimumDistinctEncountersWithLowRisk: $minimumDistinctEncountersWithLowRisk")
 
         // 5. Determine `Minimum Distinct Encounters With High Risk per Date`
-        val minimumDistinctEncountersWithHighRisk = minimumDistinctEncountersForRisk(
-            exposureWindowsAndResultForDate,
-            RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel.HIGH
-        )
+        val minimumDistinctEncountersWithHighRisk =
+            exposureWindowsAndResultForDate.minimumDistinctEncountersForRisk(ProtoRiskLevel.HIGH)
 
         Timber.d("minimumDistinctEncountersWithHighRisk: $minimumDistinctEncountersWithHighRisk")
 
@@ -442,12 +449,8 @@ class DefaultRiskLevels @Inject constructor(
         )
     }
 
-    private fun minimumDistinctEncountersForRisk(
-        exposureWindowsAndResultForDate: Map<ExposureWindow, RiskResult>,
-        riskLevel: RiskCalculationParametersOuterClass.NormalizedTimeToRiskLevelMapping.RiskLevel
-    ): Int =
-        exposureWindowsAndResultForDate
-            .filter { it.value.riskLevel == riskLevel }
+    private fun Map<ExposureWindow, RiskResult>.minimumDistinctEncountersForRisk(riskLevel: ProtoRiskLevel): Int =
+        filter { it.value.riskLevel == riskLevel }
             .map { "${it.value.transmissionRiskLevel}_${it.key.calibrationConfidence}" }
             .distinct()
             .size

Corona-Warn-App/src/main/java/de/rki/coronawarnapp/risk/result/AggregatedRiskResult.kt

@@ -8,5 +8,7 @@ data class AggregatedRiskResult(
     val totalMinimumDistinctEncountersWithLowRisk: Int,
     val totalMinimumDistinctEncountersWithHighRisk: Int,
     val mostRecentDateWithLowRisk: Instant?,
-    val mostRecentDateWithHighRisk: Instant?
+    val mostRecentDateWithHighRisk: Instant?,
+    val numberOfDaysWithLowRisk: Int,
+    val numberOfDaysWithHighRisk: Int
 )