Merge branch 'master' into quick_fix

environment.yml

@@ -5,7 +5,7 @@ channels:
 dependencies:
 - codecov
 # Conda packacking issue, will want to revisit later
-- fiona=1.8.3
+- fiona
 - folium
 - geopandas
 - geocoder

src/config/config_cambridge.yml

@@ -87,4 +87,8 @@ waze_features:
     jam: Existence of a jam
   continuous:
     jam_percent: Percent of time there was a jam
-
+    avg_jam_level: Jam level
+#    alert_WEATHERHAZARD: Waze weather hazard alert
+#    alert_JAM: Waze jam alert
+#    alert_ROAD_CLOSED: Waze road closed alert
+#    alert_ACCIDENT: Waze crash alert

src/config/config_losangeles.yml

@@ -0,0 +1,78 @@
+# City name
+city: Los Angeles, CA, USA
+# City centerpoint latitude & longitude (default geocoded values set)
+city_latitude: 34.0522
+city_longitude: -118.2437
+
+# City's time zone: defaults to the local time zone of computer initializing the city's config file
+timezone: America/Los_Angeles
+# Radius of city's road network from centerpoint in km, required if OSM has no polygon data (defaults to 20km)
+city_radius: 50
+
+# The folder under data where this city's data is stored
+name: losangeles
+
+# If given, limit crashes to after startdate and no later than enddate
+# Recommended to limit to just a few years for now
+startdate: 1/1/2016
+enddate: 
+
+# The type of predictions to generate, 'segment' is default, 'week' is legacy
+level: 'segment'
+
+#################################################################
+# Configuration for data standardization
+
+# crash file configurations
+crashes_files:
+  LA_TrafficData.csv:
+    required:
+      id: ID
+      latitude: Latitude 
+      longitude: Longitude
+      # If date supplied in single column:
+      date_complete: Date
+      # If date is separated into year/month/day:
+      date_year: 
+      date_month: 
+      # Leave date_day empty if not available
+      date_day: 
+      # If time is available and separate from date:
+      time: Time
+      # If time specified, time_format is one of:
+      # default (HH:MM:SS)
+      # seconds (since midnight)
+      # military (HHMM)
+      time_format: military
+    optional:
+      summary: 
+      # If the crash file doesn't have a lat/lon, you must give the address field
+      # and you will need to run the geocode_batch script - see the README
+      address: Address
+      vehicles: 
+      bikes: 
+
+# If using legacy 'week' predictions:
+# specify year & week on which to predict crashes (best practice is year & week towards the end of your crash data set
+# in format [month, year]
+time_target: [30, 2017]
+# specify how many weeks back to predict in output of train_model
+weeks_back: 1
+
+#################################################################
+# Configuration for default features
+
+# Default features from open street map. You can remove features you don't want
+# Note: we don't support adding features in the config file.
+# If there is an additional feature you want from open street map, contact the development team
+openstreetmap_features:
+  categorical:
+    width: Width
+    cycleway_type: Bike lane
+    signal: Signal
+    oneway: One Way
+    lanes: Number of lanes
+  continuous:
+    width_per_lane: Average width per lane
+
+

src/data/TMC_scraping/parse_tmc.py

@@ -110,7 +110,7 @@ def snap_inter_and_non_inter(summary):
     # Create spatial index for quick lookup
     segments_index = rtree.index.Index()
     for idx, element in enumerate(inter):
-        segments_index.insert(idx, element[0].bounds)
+        segments_index.insert(idx, element.geometry.bounds)
     print("Snapping tmcs to intersections")
 
     address_records = util.raw_to_record_list(

src/data/add_map.py

@@ -161,15 +161,15 @@ def get_int_mapping(lines, buffered, buffered_index):
     # Go through each line from the osm map
     for i, line in enumerate(lines):
         util.track(i, 1000, len(lines))
-        line_buffer = line[0].buffer(10)
+        line_buffer = line.geometry.buffer(10)
 
         best_match = {}
         best_overlap = 0
         for idx in buffered_index.intersection(line_buffer.bounds):
             buffer = buffered[idx][0]
             # If the new buffered intersection intersects the old one
             # figure out how much overlap, and take the best one
-            if buffer.intersects(line[0]):
+            if buffer.intersects(line.geometry):
                 total_area = unary_union([line_buffer, buffer]).area
                 overlap = max(
                     line_buffer.area/total_area, buffer.area/total_area)
@@ -178,7 +178,7 @@ def get_int_mapping(lines, buffered, buffered_index):
                     best_overlap = overlap
                     best_match = buffered[idx][2]
 
-        line_results.append([line[0], line[1], best_match])
+        line_results.append([line.geometry, line.properties, best_match])
 
     total = len(line_results)
     percent_matched = 100 - 100 * float(
@@ -212,19 +212,19 @@ def get_candidates(buffered, buffered_index, lines):
 
         # First, get candidates from new map that overlap the buffer
         # from the original map
-        for idx in buffered_index.intersection(line[0].bounds):
+        for idx in buffered_index.intersection(line.geometry.bounds):
             buffer = buffered[idx][0]
 
             # If the new line overlaps the old line
             # then check whether it is entirely within the old buffer
-            if buffer.intersects(line[0]):
+            if buffer.intersects(line.geometry):
 
                 # Add the linestring and the features to the overlap list
                 overlapping.append((buffered[idx][1], buffered[idx][2]))
 
         results.append({
-            'line': line[0],
-            'properties': line[1],
+            'line': line.geometry,
+            'properties': line.properties,
             'candidates': overlapping,
         })
 
@@ -316,8 +316,8 @@ def add_int_features(int_lines, dir1, dir2, featlist):
 
     # Buffer all the new lines
     for idx, new_line in enumerate(new_map_non_inter):
-        b = new_line[0].buffer(20)
-        new_buffered.append((b, new_line[0], new_line[1]))
+        b = new_line.geometry.buffer(20)
+        new_buffered.append((b, new_line.geometry, new_line.properties))
         new_index.insert(idx, b.bounds)
 
     non_ints_with_candidates = get_candidates(
@@ -348,8 +348,8 @@ def add_int_features(int_lines, dir1, dir2, featlist):
     new_buffered_inter = []
     new_index_inter = rtree.index.Index()
     for idx, new_line in enumerate(new_map_inter):
-        b = new_line[0].buffer(10)
-        new_buffered_inter.append((b, new_line[0], new_line[1]))
+        b = new_line.geometry.buffer(10)
+        new_buffered_inter.append((b, new_line.geometry, new_line.properties))
         new_index_inter.insert(idx, b.bounds)
 
     int_results = get_int_mapping(