feat: implement VITM2 specific changes

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "vitm"]
+	path = vitm
+	url = https://github.com/VictoriaTransport/activitysim-vitm.git

activitysim/abm/models/mandatory_scheduling.py

@@ -4,6 +4,7 @@
 
 import logging
 
+import numpy as np
 import pandas as pd
 
 from activitysim.abm.models.util.tour_scheduling import run_tour_scheduling
@@ -53,6 +54,24 @@ def mandatory_tour_scheduling(
         ~is_university_tour, "univ"
     )
 
+    # split work purpose into work_white_collar and work_blue_collar which have different coefficients
+    mandatory_tours[tour_segment_col] = np.where((mandatory_tours.tour_type == 'work') & 
+        (reindex(persons_merged['work_segment'].isin([1,2,3,4]), mandatory_tours.person_id)), 
+        'work_white_collar', mandatory_tours[tour_segment_col])
+
+    mandatory_tours[tour_segment_col] = np.where((mandatory_tours.tour_type == 'work') & 
+        (reindex((persons_merged['work_segment'] == 5), mandatory_tours.person_id)), 
+        'work_blue_collar', mandatory_tours[tour_segment_col])
+
+    # split school purpose into school_primary and school_secondary which have different coefficients
+    mandatory_tours[tour_segment_col] = np.where((mandatory_tours.tour_type == 'school') & 
+        (reindex(persons_merged.is_primary_student, mandatory_tours.person_id)), 
+        'school_primary', mandatory_tours[tour_segment_col])
+
+    mandatory_tours[tour_segment_col] = np.where((mandatory_tours.tour_type == 'school') & 
+        (reindex(persons_merged.is_secondary_student, mandatory_tours.person_id)), 
+        'school_secondary', mandatory_tours[tour_segment_col])
+
     choices = run_tour_scheduling(
         state,
         model_name,

activitysim/abm/models/tour_mode_choice.py

@@ -325,6 +325,20 @@ def tour_mode_choice_simulate(
         not_university, "univ"
     )
 
+    # split work purpose into work_white_collar and work_blue_collar which have different coefficients
+    primary_tours_merged['tour_purpose'] = np.where((primary_tours_merged['tour_purpose'] == 'work') & 
+        (primary_tours_merged['work_segment'].isin([1,2,3,4])), 'work_white_collar', primary_tours_merged['tour_purpose'])
+
+    primary_tours_merged['tour_purpose'] = np.where((primary_tours_merged['tour_purpose'] == 'work') & 
+        (primary_tours_merged['work_segment'] == 5), 'work_blue_collar', primary_tours_merged['tour_purpose'])
+
+    # split school purpose into school_primary and school_secondary which have different coefficients
+    primary_tours_merged['tour_purpose'] = np.where((primary_tours_merged['tour_purpose'] == 'school') & 
+        (primary_tours_merged.is_primary_student), 'school_primary', primary_tours_merged['tour_purpose'])
+
+    primary_tours_merged['tour_purpose'] = np.where((primary_tours_merged['tour_purpose'] == 'school') & 
+        (primary_tours_merged.is_secondary_student), 'school_secondary', primary_tours_merged['tour_purpose'])
+
     # if trip logsums are used, run trip mode choice and append the logsums
     if model_settings.COMPUTE_TRIP_MODE_CHOICE_LOGSUMS:
         primary_tours_merged = get_trip_mc_logsums_for_all_modes(

activitysim/abm/models/util/canonical_ids.py

@@ -104,10 +104,13 @@ def determine_mandatory_tour_flavors(mtf_settings, model_spec, default_flavors):
         # hard code work and school tours
         "work": parse_tour_flavor_from_columns(model_spec.columns, "work"),
         "school": parse_tour_flavor_from_columns(model_spec.columns, "school"),
+        "business": parse_tour_flavor_from_columns(model_spec.columns, "business"),
     }
 
     valid_flavors = (mandatory_tour_flavors["work"] >= 1) & (
         mandatory_tour_flavors["school"] >= 1
+    ) & (
+        mandatory_tour_flavors["business"] >= 1
     )
 
     if provided_flavors is not None:
@@ -264,7 +267,7 @@ def canonical_tours(state: workflow.State):
     )
     mtf_spec = mtf_model_settings.get("SPEC", "mandatory_tour_frequency.csv")
     mtf_model_spec = read_alts_file(state, file_name=mtf_spec)
-    default_mandatory_tour_flavors = {"work": 2, "school": 2}
+    default_mandatory_tour_flavors = {"work": 2, "school": 2, "business": 2}
 
     mandatory_tour_flavors = determine_mandatory_tour_flavors(
         mtf_model_settings, mtf_model_spec, default_mandatory_tour_flavors

activitysim/abm/models/util/tour_frequency.py

@@ -222,6 +222,7 @@ def process_mandatory_tours(
         "workplace_zone_id",
         "home_zone_id",
         "household_id",
+        "business_zone_id",
     ]
     assert not persons.mandatory_tour_frequency.isnull().any()
 
@@ -249,10 +250,20 @@ def process_mandatory_tours(
     )
 
     # work tours destination is workplace_zone_id, school tours destination is school_zone_id
-    tours["destination"] = tours_merged.workplace_zone_id.where(
-        (tours_merged.tour_type == "work"), tours_merged.school_zone_id
-    )
+    conditions = [
+        tours_merged.tour_type == "work",
+        tours_merged.tour_type == "school",
+        tours_merged.tour_type == "business"
+    ]
+
+    choices = [
+        tours_merged.workplace_zone_id,
+        tours_merged.school_zone_id,
+        tours_merged.business_zone_id
+    ]
 
+    tours["destination"] = np.select(conditions, choices, default=-1)
+
     tours["origin"] = tours_merged.home_zone_id
 
     tours["household_id"] = tours_merged.household_id

activitysim/abm/tables/shadow_pricing.py

@@ -64,13 +64,7 @@
 default_segment_to_name_dict = {
     # model_selector : persons_segment_name
     "school": "school_segment",
-    "workplace": "income_segment",
-}
-
-default_segment_to_name_dict = {
-    # model_selector : persons_segment_name
-    "school": "school_segment",
-    "workplace": "income_segment",
+    "workplace": "work_segment",
 }
 
 

activitysim/core/simulate.py

@@ -418,7 +418,7 @@ def get_segment_coefficients(
         coefficients_df = filesystem.read_model_coefficients(model_settings)
         template_df = read_model_coefficient_template(filesystem, model_settings)
         coefficients_col = (
-            template_df[segment_name].map(coefficients_df.value).astype(float)
+            template_df[segment_name].replace(coefficients_df.value).astype(float)
         )
 
         if coefficients_col.isnull().any():
@@ -430,6 +430,8 @@ def get_segment_coefficients(
             assert not coefficients_col.isnull().any()
 
         coefficients_dict = coefficients_col.to_dict()
+
+    coefficients_dict['SEGMENT_NAME'] = segment_name
 
     return coefficients_dict
 

conda-environments/activitysim-dev.yml

@@ -27,7 +27,7 @@ dependencies:
 - ipykernel  # so this env will appear in jupyter as a selection
 - isort
 - jupyterlab
-- larch = 5.7.*
+# - larch = 5.7.*
 - matplotlib
 - multimethod <2.0
 - myst-parser  # allows markdown in sphinx