blacken

Author: jpn--

activitysim/abm/models/trip_destination.py

@@ -30,12 +30,12 @@
 )
 from activitysim.core.configuration.base import PreprocessorSettings
 from activitysim.core.configuration.logit import LocationComponentSettings
+from activitysim.core.exceptions import DuplicateWorkflowTableError, InvalidTravelError
 from activitysim.core.interaction_sample import interaction_sample
 from activitysim.core.interaction_sample_simulate import interaction_sample_simulate
 from activitysim.core.skim_dictionary import DataFrameMatrix
 from activitysim.core.tracing import print_elapsed_time
 from activitysim.core.util import assign_in_place, reindex
-from activitysim.core.exceptions import InvalidTravelError, DuplicateWorkflowTableError
 
 logger = logging.getLogger(__name__)
 
@@ -280,7 +280,9 @@ def aggregate_size_term_matrix(maz_size_term_matrix, network_los, all_tazs=None)
     dest_taz = network_los.map_maz_to_taz(df.index)
     taz_size_term_matrix = df.groupby(dest_taz).sum()
     if all_tazs is not None:
-        taz_size_term_matrix = taz_size_term_matrix.reindex(all_tazs, fill_value=0).rename_axis(taz_size_term_matrix.index.name, axis=0)
+        taz_size_term_matrix = taz_size_term_matrix.reindex(
+            all_tazs, fill_value=0
+        ).rename_axis(taz_size_term_matrix.index.name, axis=0)
 
     taz_size_term_matrix = DataFrameMatrix(taz_size_term_matrix)
 
@@ -621,7 +623,9 @@ def destination_presample(
     else:
         all_tazs = None
 
-    TAZ_size_term_matrix = aggregate_size_term_matrix(size_term_matrix, network_los, all_tazs)
+    TAZ_size_term_matrix = aggregate_size_term_matrix(
+        size_term_matrix, network_los, all_tazs
+    )
 
     TRIP_ORIGIN = model_settings.TRIP_ORIGIN
     PRIMARY_DEST = model_settings.PRIMARY_DEST
@@ -643,7 +647,9 @@ def destination_presample(
     # as a vector which will need to align with the TAZ skims.
     if state.settings.sharrow:
         all_tazs = state.get_dataframe("land_use_taz").index
-        alternatives = alternatives.reindex(all_tazs, fill_value=0).rename_axis(alternatives.index.name, axis=0)
+        alternatives = alternatives.reindex(all_tazs, fill_value=0).rename_axis(
+            alternatives.index.name, axis=0
+        )
 
     # # i did this but after changing alt_dest_col_name to 'trip_dest' it
     # # shouldn't be needed anymore
@@ -1538,13 +1544,13 @@ def run_trip_destination(
                             """
 
                         When using the trip destination model with sharrow, it is necessary
-                        to set a value for `purpose_index_num` in the trip destination 
-                        annotate trips preprocessor.  This allows for an optimized compiled 
+                        to set a value for `purpose_index_num` in the trip destination
+                        annotate trips preprocessor.  This allows for an optimized compiled
                         lookup of the size term from the array of size terms.  The value of
-                        `purpose_index_num` should be the integer column position in the size 
-                        matrix, with usual zero-based numpy indexing semantics (i.e. the first 
+                        `purpose_index_num` should be the integer column position in the size
+                        matrix, with usual zero-based numpy indexing semantics (i.e. the first
                         column is zero).  The preprocessor expression most likely needs to be
-                        "size_terms.get_cols(df.purpose)" unless some unusual transform of 
+                        "size_terms.get_cols(df.purpose)" unless some unusual transform of
                         size terms has been employed.
 
                         """

activitysim/abm/test/trip_dest/test_trip_destination.py

@@ -1,25 +1,34 @@
-from pathlib import Path
+from __future__ import annotations
+
 import shutil
-from activitysim import abm  # noqa: F401
+from pathlib import Path
+
 import pandas as pd
 
+from activitysim import abm  # noqa: F401
 from activitysim.core import workflow as wf
 
 
 def test_trip_destination(tmp_path: Path):
-    shutil.copytree(Path(__file__).parent.joinpath("configs"), tmp_path.joinpath("configs"))
+    shutil.copytree(
+        Path(__file__).parent.joinpath("configs"), tmp_path.joinpath("configs")
+    )
     shutil.copytree(Path(__file__).parent.joinpath("data"), tmp_path.joinpath("data"))
 
     state = wf.State.make_default(working_dir=tmp_path)
 
     # init tours
-    tours = pd.read_csv(tmp_path / state.filesystem.data_dir[0] / "tours.csv").set_index("tour_id")
+    tours = pd.read_csv(
+        tmp_path / state.filesystem.data_dir[0] / "tours.csv"
+    ).set_index("tour_id")
     state.add_table("tours", tours)
     state.tracing.register_traceable_table("tours", tours)
     state.get_rn_generator().add_channel("tours", tours)
 
     # init trips
-    trips = pd.read_csv(tmp_path / state.filesystem.data_dir[0] / "trips.csv").set_index("trip_id")
+    trips = pd.read_csv(
+        tmp_path / state.filesystem.data_dir[0] / "trips.csv"
+    ).set_index("trip_id")
     state.add_table("trips", trips)
     state.tracing.register_traceable_table("trips", trips)
     state.get_rn_generator().add_channel("trips", trips)
@@ -29,4 +38,11 @@ def test_trip_destination(tmp_path: Path):
     out_trips = state.get_dataframe("trips")
 
     # logsums are generated for intermediate trips only
-    assert out_trips["destination_logsum"].isna().tolist() == [True, False, True, True, False, True]
+    assert out_trips["destination_logsum"].isna().tolist() == [
+        True,
+        False,
+        True,
+        True,
+        False,
+        True,
+    ]

activitysim/core/los.py

@@ -497,8 +497,10 @@ def load_data(self):
             else:  # SkimDataset
                 assert len(skims.dataset.indexes["otaz"]) == len(
                     self.state.get_dataframe("land_use_taz")
-                ), f"land_use_taz table length {len(self.state.get_dataframe('land_use_taz'))} does not match " \
-                f"taz skim length {len(skims.dataset.indexes['otaz'])}"
+                ), (
+                    f"land_use_taz table length {len(self.state.get_dataframe('land_use_taz'))} does not match "
+                    f"taz skim length {len(skims.dataset.indexes['otaz'])}"
+                )
 
     def create_skim_dict(self, skim_tag, _override_offset_int=None):
         """

activitysim/core/skim_dataset.py

@@ -594,7 +594,7 @@ def load_sparse_maz_skims(
     maz_to_maz_tables=(),
     max_blend_distance=None,
     data_file_resolver=None,
-    max_float_precision:int = 32,
+    max_float_precision: int = 32,
 ):
     """
     Load sparse MAZ data on top of TAZ skim data.