change default condense_parameters to False

activitysim/estimation/larch/nonmand_tour_freq.py

@@ -1,14 +1,10 @@
-import itertools
 import logging
 import os
-import re
 from pathlib import Path
-from typing import Mapping
 
-import numpy as np
 import pandas as pd
 import yaml
-from larch import DataFrames, Model, P, X
+from larch import DataFrames, Model
 from larch.log import logger_name
 from larch.util import Dict
 
@@ -125,7 +121,7 @@ def unavail(model, x_ca):
 def nonmand_tour_freq_model(
     edb_directory="output/estimation_data_bundle/{name}/",
     return_data=False,
-    condense_parameters=True,
+    condense_parameters=False,
 ):
     """
     Prepare nonmandatory tour frequency models for estimation.
@@ -137,7 +133,7 @@ def nonmand_tour_freq_model(
     return_data : bool, default False
         Whether to return the data used in preparing this function.
         If returned, data is a dict in the second return value.
-    condense_parameters : bool, default True
+    condense_parameters : bool, default False
         Apply a transformation whereby all parameters in each model that
         have the same initial value are converted to have the same name
         (and thus to be the same parameter, used in various places).

activitysim/estimation/test/test_larch_estimation.py

@@ -279,7 +279,7 @@ def test_tour_and_subtour_mode_choice(est_data, num_regression, dataframe_regres
 def test_nonmand_tour_freq(est_data, num_regression, dataframe_regression):
     from activitysim.estimation.larch.nonmand_tour_freq import nonmand_tour_freq_model
 
-    m = nonmand_tour_freq_model()
+    m = nonmand_tour_freq_model(condense_parameters=True)
     loglike_prior = {}
     expected_n_params = {
         "PTYPE_FULL": 72,