Merge branch 'cfg-doc-2' into cfg-documentation-vy

activitysim/abm/models/auto_ownership.py

@@ -14,7 +14,7 @@
 logger = logging.getLogger(__name__)
 
 
-class AutoOwnershipSettings(PydanticReadable):
+class AutoOwnershipSettings(LogitComponentSettings):
     """
     Settings for the `auto_ownership` component.
     """

activitysim/abm/models/location_choice.py

@@ -139,9 +139,6 @@ def _location_sample(
 
     sample_size = model_settings.SAMPLE_SIZE
 
-    if "sched" in trace_label:
-        print()
-
     if state.settings.disable_destination_sampling or (
         estimator and estimator.want_unsampled_alternatives
     ):

activitysim/abm/models/parking_location_choice.py

@@ -310,7 +310,7 @@ def parking_location(
     proposed_trip_departure_period = model_settings["TRIP_DEPARTURE_PERIOD"]
     # TODO: the number of skim time periods should be more readily available than this
     n_skim_time_periods = np.unique(
-        network_los.los_settings.skim_time_periods["labels"]
+        network_los.los_settings.skim_time_periods.labels
     ).size
     if trips_merged_df[proposed_trip_departure_period].max() > n_skim_time_periods:
         # max proposed_trip_departure_period is out of range,

activitysim/abm/models/tour_od_choice.py

@@ -35,17 +35,15 @@ def tour_od_choice(
 
     Parameters
     ----------
-    tours : orca.DataFrameWrapper
+    tours : pd.DataFrame
         lazy-loaded tours table
-    persons : orca.DataFrameWrapper
+    persons : pd.DataFrame
         lazy-loaded persons table
-    households : orca.DataFrameWrapper
+    households : pd.DataFrame
         lazy-loaded households table
-    land_use : orca.DataFrameWrapper
+    land_use : pd.DataFrame
         lazy-loaded land use data table
-    stop_frequency_alts : orca.DataFrameWrapper
-        lazy-loaded table of stop frequency alternatives, e.g. "1out2in"
-    network_los : orca._InjectableFuncWrapper
+    network_los : los.Network_LOS
         lazy-loaded activitysim.los.Network_LOS object
     """
     if model_settings is None:

activitysim/abm/models/trip_destination.py

@@ -129,6 +129,7 @@ def DESTINATION_SPEC(self) -> Path:
         return self.SPEC
 
 
+@workflow.func
 def _destination_sample(
     state: workflow.State,
     primary_purpose,
@@ -218,6 +219,7 @@ def _destination_sample(
     return choices
 
 
+@workflow.func
 def destination_sample(
     state: workflow.State,
     primary_purpose,
@@ -521,6 +523,7 @@ def choose_MAZ_for_TAZ(
     return taz_choices
 
 
+@workflow.func
 def destination_presample(
     state: workflow.State,
     primary_purpose,
@@ -669,6 +672,7 @@ def trip_destination_sample(
     return choices
 
 
+@workflow.func
 def compute_ood_logsums(
     state: workflow.State,
     choosers,
@@ -960,6 +964,7 @@ def trip_destination_simulate(
     return destinations
 
 
+@workflow.func
 def choose_trip_destination(
     state: workflow.State,
     primary_purpose,
@@ -1184,6 +1189,7 @@ def logsum_skims(self):
         return skims
 
 
+@workflow.func
 def run_trip_destination(
     state: workflow.State,
     trips: pd.DataFrame,

activitysim/abm/models/trip_mode_choice.py

@@ -80,7 +80,7 @@ def trip_mode_choice(
 
     orig_col = "origin"
     dest_col = "destination"
-    min_per_period = network_los.skim_time_periods["period_minutes"]
+    min_per_period = network_los.skim_time_periods.period_minutes
     periods_per_hour = 60 / min_per_period
 
     constants = {}

activitysim/abm/models/util/annotate.py

@@ -1,10 +1,11 @@
 # ActivitySim
 # See full license in LICENSE.txt.
-
 from __future__ import annotations
 
 import logging
 
+import pandas as pd
+
 from activitysim.core import expressions, tracing, workflow
 from activitysim.core.configuration import PydanticBase
 

activitysim/abm/models/util/tour_od.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import logging
+from typing import Optional
 
 import numpy as np
 import pandas as pd

activitysim/abm/models/vehicle_allocation.py

@@ -105,13 +105,12 @@ def vehicle_allocation(
     Parameters
     ----------
     state : workflow.State
-    persons : orca.DataFrameWrapper
-    households : orca.DataFrameWrapper
-    vehicles : orca.DataFrameWrapper
-    vehicles_merged : orca.DataFrameWrapper
-    tours : orca.DataFrameWrapper
-    tours_merged : orca.DataFrameWrapper
-    chunk_size : orca.injectable
+    persons : pd.DataFrame
+    households : pd.DataFrame
+    vehicles : pd.DataFrame
+    tours : pd.DataFrame
+    tours_merged : pd.DataFrame
+    network_los : los.Network_LOS
     """
     trace_label = "vehicle_allocation"
     model_settings_file_name = "vehicle_allocation.yaml"

activitysim/abm/models/vehicle_type_choice.py

@@ -316,7 +316,7 @@ def iterate_vehicle_type_choice(
     locals_dict : dict
         additional variables available when writing expressions
     estimator : Estimator object
-    chunk_size : orca.injectable
+    chunk_size : int
     trace_label : str
 
     Returns
@@ -516,9 +516,9 @@ def vehicle_type_choice(
 
     Parameters
     ----------
-    persons : orca.DataFrameWrapper
-    households : orca.DataFrameWrapper
-    vehicles : orca.DataFrameWrapper
+    persons : pd.DataFrame
+    households : pd.DataFrame
+    vehicles : pd.DataFrame
     vehicles_merged : DataFrame
     """
     trace_label = "vehicle_type_choice"

activitysim/abm/tables/landuse.py

@@ -11,6 +11,8 @@
 from activitysim.core import workflow
 from activitysim.core.exceptions import MissingInputTableDefinition
 from activitysim.core.input import read_input_table
+from activitysim.core.los import Network_LOS
+from activitysim.core.skim_dictionary import SkimDict
 
 logger = logging.getLogger(__name__)
 

activitysim/abm/tables/shadow_pricing.py

@@ -334,7 +334,7 @@ def __init__(
                     self.target[segment] = land_use[target]
 
     def read_saved_shadow_prices(
-        self, state, model_settings: TourLocationComponentSettings
+        self, state: workflow.State, model_settings: TourLocationComponentSettings
     ):
         """
         Read saved shadow_prices from csv file in data_dir (so-called warm start)

activitysim/benchmarking/componentwise.py

@@ -181,7 +181,7 @@ def run_component(state, component_name):
 def teardown_component(state, component_name):
     logger.info("teardown_component: %s", component_name)
 
-    # use the pipeline module to clear out all the orca tables, so
+    # use the pipeline module to clear out all the tables, so
     # the next benchmark run has a clean slate.
     # anything needed should be reloaded from the pipeline checkpoint file
     pipeline_tables = state.registered_tables()

activitysim/cli/benchmark.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import json
 import os
 import shutil
@@ -43,7 +45,6 @@
         "pyyaml": [],
         "pytables": [],
         "toolz": [],
-        "orca": [],
         "psutil": [],
         "requests": [],
         "numba": ["0.54"],

activitysim/core/config.py

@@ -1,6 +1,3 @@
-# ActivitySim
-# See full license in LICENSE.txt.
-
 from __future__ import annotations
 
 import logging
@@ -11,6 +8,10 @@
 from activitysim.core.configuration.base import PydanticBase
 from activitysim.core.configuration.logit import LogitComponentSettings
 
+# ActivitySim
+# See full license in LICENSE.txt.
+
+
 logger = logging.getLogger(__name__)
 
 
@@ -177,10 +178,11 @@ def filter_warnings(state=None):
 
     # beginning pandas version 1.3, various places emit a PerformanceWarning that is
     # caught in the "strict" filter above, but which are currently unavoidable for complex models.
-    # These warning are left as warnings as an invitation for future enhancement.
+    # Turning this filter back to "default" could be a good helper for finding places to
+    # look for future performance enhancements.
     from pandas.errors import PerformanceWarning
 
-    warnings.filterwarnings("default", category=PerformanceWarning)
+    warnings.filterwarnings("ignore", category=PerformanceWarning)
 
     # pandas 1.5
     # beginning in pandas version 1.5, a new warning is emitted when a column is set via iloc

activitysim/core/configuration/network.py

@@ -1,8 +1,11 @@
 from __future__ import annotations
 
+import warnings
 from pathlib import Path
 from typing import Literal
 
+from pydantic import PositiveInt, root_validator
+
 from activitysim.core.configuration.base import (
     Any,
     PydanticBase,
@@ -156,6 +159,44 @@ class MazToMazSettings(PydanticBase, extra="forbid"):
     """The name of the skim table used to blend distances for MAZs."""
 
 
+class TimeSettings(PydanticReadable, extra="forbid"):
+    """
+    Settings to describe discrete time.
+    """
+
+    time_window: PositiveInt = 1440
+    """total duration (in minutes) of the modeled time span."""
+
+    period_minutes: PositiveInt = 60
+    """length of time (in minutes) each model time period represents.
+
+    Must be whole factor of ``time_window``."""
+
+    periods: list[int]
+    """Breakpoints that define the aggregate periods for skims and assignment.
+
+    The first value should be zero and the last value should equal `time_window`
+    divided by `period_minutes`.  The intervals between these various values
+    represent the skimmed time periods, so this list should be one longer than
+    that of `labels`.
+    """
+
+    labels: list[str]
+    """Labels to define names for aggregate periods for skims and assignment"""
+
+    @root_validator(pre=True)
+    def hours_deprecated(cls, data):
+        if "hours" in data:
+            data["periods"] = data.pop("hours")
+            warnings.warn(
+                "support for `skim_time_periods` key `hours` will be removed in "
+                "future verions. Use `periods` instead",
+                FutureWarning,
+                stacklevel=2,
+            )
+        return data
+
+
 class NetworkSettings(PydanticReadable, extra="forbid"):
     """
     Network level of service and skims settings
@@ -188,14 +229,8 @@ class NetworkSettings(PydanticReadable, extra="forbid"):
     TAZ_Settings class, which allows for ZARR transformation and pre-processing.
     """
 
-    skim_time_periods: dict
-    """time period upper bound values and labels
-
-    * ``time_window`` - total duration (in minutes) of the modeled time span (Default: 1440 minutes (24 hours))
-    * ``period_minutes`` - length of time (in minutes) each model time period represents. Must be whole factor of ``time_window``. (Default: 60 minutes)
-    * ``periods`` - Breakpoints that define the aggregate periods for skims and assignment
-    * ``labels`` - Labels to define names for aggregate periods for skims and assignment
-    """
+    skim_time_periods: TimeSettings
+    """How to discretize time in this model."""
 
     read_skim_cache: bool = False
     """Read cached skims (using numpy memmap) from output directory.

activitysim/core/configuration/top.py

@@ -620,21 +620,16 @@ class Settings(PydanticBase, extra="allow", validate_assignment=True):
     rng_base_seed: Union[int, None] = 0
     """Base seed for pseudo-random number generator."""
 
-    duplicate_step_execution: Literal["raise", "warn", "allow"] = "raise"
+    duplicate_step_execution: Literal["error", "allow"] = "error"
     """
     How activitysim should handle attempts to re-run a step with the same name.
 
     .. versionadded:: 1.3
 
-    * "raise"
+    * "error"
         Attempts to re-run a step that has already been run and
         checkpointed will raise a `RuntimeError`, halting model execution.
         This is the default if no value is given.
-    * "warn"
-        Attempts to re-run a step that has already been run and
-        checkpointed will be trigger a warning message and that particular step
-        will not be (re)executed, but overall model execution will be allowed to
-        continue.
     * "allow"
         Attempts to re-run a step are allowed, potentially overwriting
         the results from the previous time that step was run.