nested now with alternative numbers, not names, change structure to b…

…e more consistent with current impl

activitysim/core/logit.py

@@ -228,9 +228,8 @@ def choose_from_tree(nest_utils, all_alternatives, logit_nest_groups, nest_alter
 # alternatives and set the corresponding entry to 1 for each row, set all other alternatives at this level to zero.
 # Once the tree is walked (all alternatives have been processed), take the product of the alternatives in each
 # leaf's alternative list. Then pick the only alternative with entry 1, all others must be 0.
-def make_choices_ru_frozen(nested_utilities, nest_spec, trace_label=None, trace_choosers=None):
+def make_choices_ru_frozen_nl(nested_utilities, nest_spec):
     """ walk down the nesting tree and make choice at each level, which is the root of the next level choice."""
-    trace_label = tracing.extend_trace_label(trace_label, 'make_choices_ru_frozen')
     nest_utils_for_choice = add_ev1_random(nested_utilities)
 
     all_alternatives = set(nest.name for nest in each_nest(nest_spec, type='leaf'))
@@ -243,22 +242,34 @@ def make_choices_ru_frozen(nested_utilities, nest_spec, trace_label=None, trace_
     )
     assert not choices.isnull().any(), "No choice for XXX - implement reporting"
     choices = pd.Series(choices, index=nest_utils_for_choice.index)
+
+    # TODO [janzill Jun2022]: REMOVE HACK, make this numpy and positional indexes from the beginning
+    choices = choices.map({v: k for k,v in enumerate(nest_utils_for_choice.columns)})
+
     return choices
 
 
-# TODO: integrate with nested impl above
-# TODO: make everything in nested and here numpy from beginning to make choices consistent with previous impl (
-#  want column index and not alternative name)
-def make_choices_ru_frozen_mnl(utilities, trace_label=None):
-    trace_label = tracing.extend_trace_label(trace_label, 'make_choices_ru_frozen_mnl')
+# TODO [janzill Jun2022]: integrate with nested impl above
+# TODO [janzill Jun2022]: make everything in nested and here numpy from beginning to make choices consistent with
+#  previous impl (want column index and not alternative name)
+def make_choices_ru_frozen_mnl(utilities):
     utilities_incl_unobs = add_ev1_random(utilities)
     choices = np.argmax(utilities_incl_unobs.to_numpy(), axis=1)
     assert not np.isnan(choices).any(), "No choice for XXX - implement reporting"
     choices = pd.Series(choices, index=utilities_incl_unobs.index)
     return choices
 
+def make_choices_ru_frozen(utilities, nest_spec=None, trace_label=None):
+    trace_label = tracing.extend_trace_label(trace_label, 'make_choices_ru_frozen_mnl')
+    if nest_spec is None:
+        choices = make_choices_ru_frozen_mnl(utilities)
+    else:
+        choices = make_choices_ru_frozen_nl(utilities, nest_spec)
+    return choices
+
 
-def make_choices(probs, trace_label=None, trace_choosers=None, allow_bad_probs=False):
+def make_choices(probs, utilities=None, nest_spec=None, trace_label=None, trace_choosers=None, allow_bad_probs=False,
+                 choose_individual_max_utility=False):
     """
     Make choices for each chooser from among a set of alternatives.
 
@@ -286,8 +297,14 @@ def make_choices(probs, trace_label=None, trace_choosers=None, allow_bad_probs=F
     """
     trace_label = tracing.extend_trace_label(trace_label, 'make_choices')
 
-    # probs should sum to 1 across each row
+    if choose_individual_max_utility:
+        choices = make_choices_ru_frozen(utilities, nest_spec, trace_label)
+        # TODO: rands
+        rands = pd.Series(np.zeros_like(utilities.index.values), index=utilities.index)
+        return choices, rands
 
+
+    # probs should sum to 1 across each row
     BAD_PROB_THRESHOLD = 0.001
     bad_probs = \
         probs.sum(axis=1).sub(np.ones(len(probs.index))).abs() \