Merge pull request #313 from flibbertigibbet/release/2.0.2

Release/2.0.2

Author: flibbertigibbet

taui/src/selectors/neighborhoods-sorted-with-routes.js

@@ -29,17 +29,14 @@ const MAX_DISTANCE = 130000
 const MAX_TRAVEL_TIME = 120
 const MIN_QUINTILE = 1
 const MAX_QUINTILE = 5
-// stored profile importance is offset by one from MAX_IMPORTANCE
-const PROFILE_MAX_IMPORTANCE = MAX_IMPORTANCE - 1
 
 // default to worst, if unknown
 const DEFAULT_EDUCATION_QUINTILE = 5
 const DEFAULT_CRIME_QUINTILE = 5
 
 // extra constant weighting always given to travel time over the other two factors
-const EXTRA_ACCESS_WEIGHT = 2
+const EXTRA_ACCESS_WEIGHT = 1
 
-/* eslint complexity: 0 */
 export default createSelector(
   selectNeighborhoodRoutes,
   neighborhoodTravelTimes,
@@ -67,12 +64,7 @@ export default createSelector(
       accessibilityImportance = crimeImportance = schoolsImportance = 1
     }
 
-    if (accessibilityImportance === PROFILE_MAX_IMPORTANCE) {
-      // if set to very important, add more extra weight to travel time
-      accessibilityImportance += 1
-    }
-
-    // Alwasy give accessibility (travel time) some extra weighting
+    // Give accessibility (travel time) extra weighting
     accessibilityImportance += EXTRA_ACCESS_WEIGHT
 
     const totalImportance = accessibilityImportance + crimeImportance + schoolsImportance
@@ -86,70 +78,49 @@ export default createSelector(
       const route = neighborhoodRoutes[index]
       const segments = useTransit ? route.routeSegments : []
       const time = useTransit ? travelTimes[index] : distanceTime(origin, n)
+
+      // Map weighting values to percentages
+
       // Routable neighborhoods outside the max travel time window will be filtered out.
       // Smaller travel time is better; larger timeWeight is better (reverse range).
       const timeWeight = time < MAX_TRAVEL_TIME ? scale(time, 0, MAX_TRAVEL_TIME, 1, 0) : 1
+
       // Weight schools either by percentile binned into quarters if given max importance,
       // or otherwise weight by quintile.
       let educationWeight
-      if (schoolsImportance === PROFILE_MAX_IMPORTANCE) {
-        // "very important": instead of quintiles, group percentile ranking into quarters
+      if (schoolsImportance === (MAX_IMPORTANCE - 1)) {
+        // Group percentile ranking into quarters instead of using quintiles
+        // if the importance of schools is the max importance.
         const edPercent = properties.education_percentile
           ? properties.education_percentile
           : (DEFAULT_EDUCATION_QUINTILE - 1) * 20
-        let edPercentQuarter = Math.round(scale(edPercent, 0, 100, 3, 0))
-        // Treat all schools not in the top quarter as being in the bottom quarter
-        // to strongly prioritize the top quarter
-        if (edPercentQuarter > 0) {
-          edPercentQuarter = 3
-        }
+        const edPercentQuarter = Math.round(scale(edPercent, 0, 100, 3, 0))
         educationWeight = scale(edPercentQuarter, 0, 3, 1, 0)
-      } else if (schoolsImportance > 0) {
-        // For "somewhat important", prioritize quintile 2 and below
-        // For "important", quintile 3 and below (lower is better)
-        const prioritizeQuintile = schoolsImportance === 1 ? 2 : 3
-        let educationQuintile = properties.education_percentile_quintile
+      } else {
+        // Use quintiles if the importance of schools is anything less than the max importance.
+        const educationQuintile = properties.education_percentile_quintile
           ? properties.education_percentile_quintile
           : DEFAULT_EDUCATION_QUINTILE
-        // Treat all quintiles above the maximum to prioritize as being in the worst quintile
-        if (educationQuintile > prioritizeQuintile) {
-          educationQuintile = MAX_QUINTILE
-        }
+
         // Lowest education quintile is best (reverse range).
         educationWeight = scale(educationQuintile, MIN_QUINTILE, MAX_QUINTILE, 1, 0)
-      } else {
-        educationWeight = 0 // Not important
       }
-      let crimeWeight = 0
+      let crimeQuintile = properties.violentcrime_quintile
+        ? properties.violentcrime_quintile : DEFAULT_CRIME_QUINTILE
+      // Treat lowest two (safest) violent crime quintiles equally
+      if (crimeQuintile === 2) {
+        crimeQuintile = 1
+      }
+      // Lowest crime quintile is best (reverse range).
+      const crimeWeight = scale(crimeQuintile, MIN_QUINTILE, MAX_QUINTILE, 1, 0)
+
       // Handle missing values (zero in spreadsheet) by re-assigning crime weight
-      // evenly to the other two factors. Also do so if crime set as unimportant.
-      if (properties.violentcrime_quintile === 0 || crimeImportance === 0) {
+      // evenly to the other two factors
+      if (properties.violentcrime_quintile === 0) {
         const halfCrimePercent = crimePercent / 2
         schoolPercent += halfCrimePercent
         accessibilityPercent += halfCrimePercent
         crimePercent = 0
-      } else {
-        let crimeQuintile = properties.violentcrime_quintile
-          ? properties.violentcrime_quintile : DEFAULT_CRIME_QUINTILE
-        // Treat lowest two (safest) violent crime quintiles equally
-        if (crimeQuintile === 2) {
-          crimeQuintile = 1
-        }
-        if (crimeImportance === 1 && crimeQuintile < 5) {
-          // somewhat important; treat all but worst quintile the same
-          crimeQuintile = 1
-        } else if (crimeImportance === 2 && crimeQuintile < 4) {
-          // "important"; treat all but worst two quintiles the same
-          crimeQuintile = 1
-        } else if (crimeImportance === PROFILE_MAX_IMPORTANCE && crimeQuintile > 3) {
-          // "very important"; push results for worst two quintiles to bottom
-          // by reassigning weights for those quintiles to be 90% crime
-          crimePercent = 90
-          schoolPercent /= 10
-          accessibilityPercent /= 10
-        }
-        // Lowest crime quintile is best (reverse range).
-        crimeWeight = scale(crimeQuintile, MIN_QUINTILE, MAX_QUINTILE, 1, 0)
       }
 
       // Calculate weighted overall score from the percentages. Larger score is better.