Merge remote-tracking branch 'origin/feat/helmet5-parking-time' into …

…helmet5-experimental

Scripts/parameters/assignment.py

@@ -2,6 +2,11 @@
 
 from collections import namedtuple
 from typing import Dict, List, Union
+
+import numpy as np
+import pandas as pd
+
+from datahandling.zonedata import ZoneData
 RoadClass = namedtuple(
     "RoadClass",
     (
@@ -180,6 +185,11 @@
 }
 # Default distance unit cost [eur/km]
 dist_unit_cost = 0.12
+# Parking time function
+def parking_time(zone_data: ZoneData) -> pd.Series:
+    density: pd.Series = (zone_data['population'] + zone_data['workplaces']) / zone_data['zone_area']
+    return 0.05993817*np.sqrt(density) + 5.24176150
+
 # Default distance unit time for trucks and trailer trucks [min/km]
 freight_dist_unit_time = 0.2
 # Boarding penalties for different transit modes

Scripts/tests/integration/test_models.py

@@ -56,7 +56,7 @@ def test_models(self):
         self._validate_impedances(impedance["iht"])
 
         # Check that model result does not change
-        self.assertAlmostEquals(model.mode_share[0]["car"], 0.19439048477671417)
+        self.assertAlmostEquals(model.mode_share[0]["car"], 0.2115956440248976)
 
         print("Model system test done")
 

Scripts/transform/impedance_transformer.py

@@ -8,6 +8,10 @@
 from datatypes.purpose import Purpose
 import parameters.impedance_transformation as param
 from parameters.assignment import assignment_classes
+try:
+    from parameters.assignment import parking_time
+except ImportError:
+    parking_time = None
 
 import numpy as np
 import openmatrix as omx
@@ -117,18 +121,20 @@ def transform(self, purpose, impedance):
                         day_imp[mode][mtx_type] += share[1] * imp[cols, rows].T
 
         # transit cost to eur per day
-        day_imp['transit']['cost'] = transit_cost_to_per_day(day_imp['transit']['cost'], purpose)
-
-        # Process possible extra transformers (eg. P&R impedance)
-        for transformer in self._extra_transformers:
-            extra_results = transformer.transform(purpose, impedance)
-            for result_name, result in extra_results.items():
-                day_imp[result_name] = result
-
-        # Optionally export impedance data for estimation
-        if self._export_path:
-            self.export_day_impedance(purpose, day_imp)
-
+        trips_month = (param.transit_trips_per_month
+            [purpose.area][assignment_classes[purpose.name]])
+        trips_per_month = numpy.full_like(
+            day_imp["transit"]["cost"], trips_month[0])
+        for i in range(1, len(purpose.sub_bounds)):
+            trips_per_month[purpose.sub_bounds[i], :] = trips_month[i]
+        day_imp["transit"]["cost"] /= trips_per_month
+        # Add parking time to car matrices
+        if parking_time is not None:
+            ptime = parking_time(purpose.zone_data).to_numpy()[cols]
+            ptime = numpy.clip(ptime, 0, 30)
+            car_modes = [k for k in day_imp.keys() if k in ('car', 'car_work', 'car_transit')]
+            for k in car_modes:
+                day_imp[k]['time'] += ptime[None,:]
         return day_imp