Vehicle Type Alts Filtering Bug Fix

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None:

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None:

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None:

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None:

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None:

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None:

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None:

activitysim/abm/models/util/test/test_vehicle_type_alts.py

@@ -0,0 +1,59 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.vehicle_type_choice import (
+ get_combinatorial_vehicle_alternatives,
+ construct_model_alternatives,
+ VehicleTypeChoiceSettings,
+)
+from activitysim.core import workflow
+
+
+def test_vehicle_type_alts():
+ state = workflow.State.make_default(__file__)
+
+ alts_cats_dict = {
+ "body_type": ["Car", "SUV"],
+ "fuel_type": ["Gas", "BEV"],
+ "age": [1, 2, 3],
+ }
+
+ alts_wide, alts_long = get_combinatorial_vehicle_alternatives(alts_cats_dict)
+
+ # alts are initially constructed combinatorially
+ assert len(alts_long) == 12, "alts_long should have 12 rows"
+ assert len(alts_wide) == 12, "alts_wide should have 12 rows"
+
+ model_settings = VehicleTypeChoiceSettings.model_construct()
+ model_settings.combinatorial_alts = alts_cats_dict
+ model_settings.PROBS_SPEC = None
+ model_settings.WRITE_OUT_ALTS_FILE = False
+
+ # constructing veh type data with missing alts
+ vehicle_type_data = pd.DataFrame(
+ data={
+ "body_type": ["Car", "Car", "Car", "SUV", "SUV"],
+ "fuel_type": ["Gas", "Gas", "BEV", "Gas", "BEV"],
+ "age": ["1", "2", "3", "1", "2"],
+ "dummy_data": [1, 2, 3, 4, 5],
+ },
+ index=[0, 1, 2, 3, 4],
+ )
+
+ alts_wide, alts_long = construct_model_alternatives(
+ state, model_settings, alts_cats_dict, vehicle_type_data
+ )
+
+ # should only have alts left that are in the file
+ assert len(alts_long) == 5, "alts_long should have 5 rows"
+
+ # indexes need to be the same to choices match alts
+ pdt.assert_index_equal(alts_long.index, alts_wide.index)
+
+ # columns need to be in correct order for downstream configs
+ pdt.assert_index_equal(
+ alts_long.columns, pd.Index(["body_type", "age", "fuel_type"])
+ )

activitysim/abm/models/vehicle_type_choice.py

@@ -244,7 +244,19 @@ def construct_model_alternatives(
  ), f"missing vehicle data for alternatives:\n {missing_alts}"
  else:
  # eliminate alternatives if no vehicle type data
+ num_alts_before_filer = len(alts_wide)
  alts_wide = alts_wide[alts_wide._merge != "left_only"]
+ logger.warning(
+ f"Removed {num_alts_before_filer - len(alts_wide)} alternatives not included in input vehicle type data."
+ )
+ # need to also remove any alts from alts_long
+ alts_long.set_index(["body_type", "age", "fuel_type"], inplace=True)
+ alts_long = alts_long[
+ alts_long.index.isin(
+ alts_wide.set_index(["body_type", "age", "fuel_type"]).index
+ )
+ ].reset_index()
+ alts_long.index = alts_wide.index
  alts_wide.drop(columns="_merge", inplace=True)
 
  # converting age to integer to allow interactions in utilities
@@ -455,11 +467,11 @@ def iterate_vehicle_type_choice(
  alts = (
  alts_long[alts_long.columns]
  .apply(lambda row: "_".join(row.values.astype(str)), axis=1)
- .values
+ .to_dict()
  )
  else:
- alts = model_spec.columns
- choices["vehicle_type"] = choices["vehicle_type"].map(dict(enumerate(alts)))
+ alts = enumerate(dict(model_spec.columns))
+ choices["vehicle_type"] = choices["vehicle_type"].map(alts)
 
  # STEP II: append probabilistic vehicle type attributes
  if probs_spec_file is not None: