Allow Formulas in Coefficients File

activitysim/abm/models/joint_tour_destination.py

@@ -326,8 +326,8 @@ def joint_tour_destination(
     person that's making the tour)
     """
 
-    trace_label = 'non_mandatory_tour_destination'
-    model_settings_file_name = 'non_mandatory_tour_destination.yaml'
+    trace_label = 'joint_tour_destination'
+    model_settings_file_name = 'joint_tour_destination.yaml'
     model_settings = config.read_model_settings(model_settings_file_name)
 
     logsum_column_name = model_settings.get('DEST_CHOICE_LOGSUM_COLUMN_NAME')

activitysim/abm/models/util/vectorize_tour_scheduling.py

@@ -76,6 +76,10 @@ def _compute_logsums(alt_tdd, tours_merged, tour_purpose, model_settings, trace_
     locals_dict.update(constants)
     locals_dict.update(skims)
 
+    # constrained coefficients can appear in expressions
+    coefficients = simulate.get_segment_coefficients(logsum_settings, tour_purpose)
+    locals_dict.update(coefficients)
+
     # - run preprocessor to annotate choosers
     # allow specification of alternate preprocessor for nontour choosers
     preprocessor = model_settings.get('LOGSUM_PREPROCESSOR', 'preprocessor')
@@ -92,17 +96,12 @@ def _compute_logsums(alt_tdd, tours_merged, tour_purpose, model_settings, trace_
             trace_label=trace_label)
 
     # - compute logsums
-
-    coefficients = simulate.get_segment_coefficients(logsum_settings, tour_purpose)
     logsum_spec = simulate.read_model_spec(file_name=logsum_settings['SPEC'])
     logsum_spec = simulate.eval_coefficients(logsum_spec, coefficients, estimator=None)
 
     nest_spec = config.get_logit_model_settings(logsum_settings)
     nest_spec = simulate.eval_nest_coefficients(nest_spec, coefficients)
 
-    # constrained coefficients can appear in expressions
-    locals_dict.update(coefficients)
-
     logsums = simulate.simple_simulate_logsums(
         choosers,
         logsum_spec,

activitysim/core/simulate.py

@@ -10,6 +10,7 @@
 import numpy as np
 import pandas as pd
 
+from .assign import evaluate_constants
 from .skim import SkimDictWrapper, SkimStackWrapper
 from . import logit
 from . import tracing
@@ -140,9 +141,23 @@ def read_model_coefficients(model_settings=None, file_name=None):
         file_name = model_settings['COEFFICIENTS']
 
     file_path = config.config_file_path(file_name)
-    coefficients = pd.read_csv(file_path, comment='#', index_col='coefficient_name')
+    print(file_path)
+    try:
+        coefficients_df = pd.read_csv(file_path, comment='#', index_col='coefficient_name')
+        assert {'constrain', 'value'}.issubset(coefficients_df.columns)
+    except ValueError:
+        logger.exception("Coefficient File Invalid: %s" % str(file_path))
+        raise
+
+    if model_settings is not None and 'CONSTANTS' in model_settings:
+        constants = model_settings['CONSTANTS']
+    else:
+        constants = None
+
+    coeffs = evaluate_constants(coefficients_df['value'], constants)
 
-    return coefficients
+    return pd.concat([pd.DataFrame(coeffs.values(), index=coeffs.keys(), columns=['value']),
+                      coefficients_df['constrain']], axis=1)
 
 
 def spec_for_segment(model_settings, spec_id, segment_name, estimator):
@@ -163,7 +178,7 @@ def spec_for_segment(model_settings, spec_id, segment_name, estimator):
     """
 
     spec = read_model_spec(file_name=model_settings[spec_id])
-    coefficients = read_model_coefficients(model_settings)
+    coefficients = read_model_coefficients(model_settings, None)
 
     if len(spec.columns) > 1:
         # if spec is segmented

activitysim/examples/example_mtc/configs/joint_tour_destination.yaml

@@ -10,9 +10,11 @@ SEGMENTS:
   - eatout
   - social
 
-
 SAMPLE_SIZE: 30
 
+# we can't use use household income_segment as this will also be set for non-workers
+CHOOSER_SEGMENT_COLUMN_NAME: tour_type
+
 SIMULATE_CHOOSER_COLUMNS:
   - tour_type
   - TAZ

activitysim/examples/example_mtc/configs/non_mandatory_tour_destination_coeffs.csv

@@ -3,7 +3,7 @@ coef_mode_logsum,0.6755,F
 coef_escort_dist_0_2,-0.1499,F
 coef_eatout_dist_0_2,-0.5609,F
 coef_eatout_social_0_2,-0.5609,F
-coef_eatout_dist_0_2,-0.7841,F
+#coef_eatout_dist_0_2,-0.7841,F
 coef_othdiscr_dist_0_2,-0.1677,F
 coef_escort_dist_2_5,-0.8671,F
 coef_shopping_dist_2_5,-0.5655,F