Merge branch 'main' into expression-profiling

Author: jpn--

activitysim/abm/models/location_choice.py

@@ -838,19 +838,23 @@ def run_location_choice(
         )
 
         # - location_logsums
-        location_sample_df = run_location_logsums(
-            state,
-            segment_name,
-            choosers,
-            network_los,
-            location_sample_df,
-            model_settings,
-            chunk_size,
-            chunk_tag=f"{chunk_tag}.logsums",
-            trace_label=tracing.extend_trace_label(
-                trace_label, "logsums.%s" % segment_name
-            ),
-        )
+        # skip logsum calculations if LOGSUM_SETTINGS is None
+        if model_settings.LOGSUM_SETTINGS:
+            location_sample_df = run_location_logsums(
+                state,
+                segment_name,
+                choosers,
+                network_los,
+                location_sample_df,
+                model_settings,
+                chunk_size,
+                chunk_tag=f"{chunk_tag}.logsums",
+                trace_label=tracing.extend_trace_label(
+                    trace_label, "logsums.%s" % segment_name
+                ),
+            )
+        else:
+            location_sample_df[ALT_LOGSUM] = 0.0
 
         # - location_simulate
         choices_df = run_location_simulate(

activitysim/abm/models/parking_location_choice.py

@@ -203,8 +203,10 @@ def choose_parking_location(
         additional_columns=model_settings.compute_settings.protect_columns,
     )
 
+    # Passing only the index of the trips table to the interaction_dataset
+    # See ActivitySim issue #633
     destination_sample = logit.interaction_dataset(
-        state, trips, alternatives, alt_index_id=alt_dest_col_name
+        state, trips[[]], alternatives, alt_index_id=alt_dest_col_name
     )
     destination_sample.index = np.repeat(trips.index.values, len(alternatives))
     destination_sample.index.name = trips.index.name

activitysim/abm/models/trip_destination.py

@@ -1053,16 +1053,21 @@ def choose_trip_destination(
         return pd.Series(index=trips.index).to_frame("choice"), None
 
     # - compute logsums
-    destination_sample = compute_logsums(
-        state,
-        primary_purpose=primary_purpose,
-        trips=trips,
-        destination_sample=destination_sample,
-        tours_merged=tours_merged,
-        model_settings=model_settings,
-        skim_hotel=skim_hotel,
-        trace_label=trace_label,
-    )
+    # If LOGSUM_SETTINGS is set to None, we don't want to compute logsums
+    if model_settings.LOGSUM_SETTINGS:
+        destination_sample = compute_logsums(
+            state,
+            primary_purpose=primary_purpose,
+            trips=trips,
+            destination_sample=destination_sample,
+            tours_merged=tours_merged,
+            model_settings=model_settings,
+            skim_hotel=skim_hotel,
+            trace_label=trace_label,
+        )
+    else:
+        destination_sample["od_logsum"] = 0.0
+        destination_sample["dp_logsum"] = 0.0
 
     t0 = print_elapsed_time("%s.compute_logsums" % trace_label, t0)
 
@@ -1272,9 +1277,14 @@ def run_trip_destination(
             state.filesystem, model_settings_file_name
         )
     preprocessor_settings = model_settings.preprocessor
-    logsum_settings = state.filesystem.read_model_settings(
-        model_settings.LOGSUM_SETTINGS
-    )
+
+    # read in logsum settings if they exist, otherwise logsum calculations are skipped
+    if model_settings.LOGSUM_SETTINGS:
+        logsum_settings = state.filesystem.read_model_settings(
+            model_settings.LOGSUM_SETTINGS
+        )
+    else:
+        logsum_settings = None
 
     logsum_column_name = model_settings.DEST_CHOICE_LOGSUM_COLUMN_NAME
     want_logsums = logsum_column_name is not None
@@ -1342,7 +1352,9 @@ def run_trip_destination(
 
     # - filter tours_merged (AFTER copying destination and origin columns to trips)
     # tours_merged is used for logsums, we filter it here upfront to save space and time
-    tours_merged_cols = logsum_settings["TOURS_MERGED_CHOOSER_COLUMNS"]
+    tours_merged_cols = (
+        logsum_settings["TOURS_MERGED_CHOOSER_COLUMNS"] if logsum_settings else []
+    )
     redundant_cols = model_settings.REDUNDANT_TOURS_MERGED_CHOOSER_COLUMNS or []
     if redundant_cols:
         tours_merged_cols = [c for c in tours_merged_cols if c not in redundant_cols]

activitysim/abm/models/util/tour_destination.py

@@ -894,17 +894,21 @@ def run_tour_destination(
         )
 
         # - destination_logsums
-        tour_purpose = segment_name  # tour_purpose is segment_name
-        location_sample_df = run_destination_logsums(
-            state,
-            tour_purpose,
-            persons_merged,
-            location_sample_df,
-            model_settings,
-            network_los,
-            chunk_size=state.settings.chunk_size,
-            trace_label=tracing.extend_trace_label(segment_trace_label, "logsums"),
-        )
+        # if LOGSUM_SETTINGS is set to 'None', we skip this step
+        if model_settings.LOGSUM_SETTINGS:
+            tour_purpose = segment_name  # tour_purpose is segment_name
+            location_sample_df = run_destination_logsums(
+                state,
+                tour_purpose,
+                persons_merged,
+                location_sample_df,
+                model_settings,
+                network_los,
+                chunk_size=state.settings.chunk_size,
+                trace_label=tracing.extend_trace_label(segment_trace_label, "logsums"),
+            )
+        else:
+            location_sample_df["mode_choice_logsum"] = 0
 
         # - destination_simulate
         spec_segment_name = segment_name  # spec_segment_name is segment_name

activitysim/abm/models/util/tour_od.py

@@ -1132,20 +1132,24 @@ def run_tour_od(
             )
 
         # - destination_logsums
-        od_sample_df = run_od_logsums(
-            state,
-            spec_segment_name,
-            choosers,
-            od_sample_df,
-            model_settings,
-            network_los,
-            estimator,
-            chunk_size=chunk_size,
-            trace_hh_id=trace_hh_id,
-            trace_label=tracing.extend_trace_label(
-                trace_label, f"logsums.{segment_name}"
-            ),
-        )
+        # Skip logsum calculation step if LOGSUM_SETTINGS is None
+        if model_settings.LOGSUM_SETTINGS:
+            od_sample_df = run_od_logsums(
+                state,
+                spec_segment_name,
+                choosers,
+                od_sample_df,
+                model_settings,
+                network_los,
+                estimator,
+                chunk_size=chunk_size,
+                trace_hh_id=trace_hh_id,
+                trace_label=tracing.extend_trace_label(
+                    trace_label, f"logsums.{segment_name}"
+                ),
+            )
+        else:
+            od_sample_df["tour_mode_choice_logsum"] = 0.0
 
         # - od_simulate
         choices = run_od_simulate(

activitysim/cli/run.py

@@ -338,6 +338,9 @@ def run(args):
     config.filter_warnings(state)
     logging.captureWarnings(capture=True)
 
+    activitysim_version = importlib.metadata.version("activitysim")
+    logger.info(f"ActivitySim Version: {activitysim_version}")
+
     # directories
     for k in ["configs_dir", "settings_file_name", "data_dir", "output_dir"]:
         logger.info("SETTING %s: %s" % (k, getattr(state.filesystem, k, None)))

activitysim/core/configuration/logit.py

@@ -212,8 +212,11 @@ class LocationComponentSettings(BaseLogitComponentSettings):
     SAMPLE_SIZE: int
     """This many candidate alternatives will be sampled for each choice."""
 
-    LOGSUM_SETTINGS: Path
-    """Settings for the logsum computation."""
+    LOGSUM_SETTINGS: Path | None = None
+    """
+    Settings for the logsum computation.
+    If None, no logsum is computed and logsum field is populated with zeros.
+    """
 
     explicit_chunk: float = 0
     """