Use pandas 2 for docbuild environment (#928)

* fix link

* allow failure to import larch

* workflow

* blacken

* try some pins

* speed up docbuild

* use pandas 2 for docs

* oops wrong file

* restore foundation

Author: jpn--

.github/workflows/core_tests.yml

@@ -8,7 +8,7 @@ on:
   pull_request:
     branches:
       - '*'
-  
+
   workflow_dispatch:
 
 env:
@@ -455,7 +455,7 @@ jobs:
 
   develop-docbuild:
     needs: foundation
-    if: github.ref_name == 'main'
+    if: github.ref_name == 'main' || github.ref_name == 'docs-fix'
     name: develop-docbuild
     runs-on: ubuntu-latest
     permissions:

activitysim/abm/misc.py

@@ -18,7 +18,6 @@
 
 @workflow.cached_object
 def households_sample_size(state: workflow.State, override_hh_ids) -> int:
-
     if override_hh_ids is None:
         return state.settings.households_sample_size
     else:
@@ -27,7 +26,6 @@ def households_sample_size(state: workflow.State, override_hh_ids) -> int:
 
 @workflow.cached_object
 def override_hh_ids(state: workflow.State) -> np.ndarray | None:
-
     hh_ids_filename = state.settings.hh_ids
     if hh_ids_filename is None:
         return None
@@ -65,7 +63,6 @@ def override_hh_ids(state: workflow.State) -> np.ndarray | None:
 
 @workflow.cached_object
 def trace_od(state: workflow.State) -> tuple[int, int] | None:
-
     od = state.settings.trace_od
 
     if od and not (

activitysim/abm/models/auto_ownership.py

@@ -72,7 +72,6 @@ def auto_ownership_simulate(
     # - preprocessor
     preprocessor_settings = model_settings.preprocessor
     if preprocessor_settings:
-
         locals_d = {}
         if constants is not None:
             locals_d.update(constants)

activitysim/abm/models/initialize.py

@@ -148,7 +148,6 @@ def initialize_households(
     model_settings_file_name: str = "initialize_households.yaml",
     trace_label: str = "initialize_households",
 ) -> None:
-
     with chunk.chunk_log(state, trace_label, base=True) as chunk_sizer:
         chunk_sizer.log_rss(f"{trace_label}.inside-yield")
 

activitysim/abm/models/input_checker.py

@@ -209,7 +209,6 @@ class HouseholdValidator(pydantic.BaseModel) list_of_households...
 
 
 def report_errors(state, input_checker_settings, v_warnings, v_errors):
-
     # logging overall statistics first before printing details
     for table_settings in input_checker_settings["table_list"]:
         table_name = table_settings["name"]

activitysim/abm/models/non_mandatory_tour_frequency.py

@@ -236,7 +236,6 @@ def non_mandatory_tour_frequency(
     # - preprocessor
     preprocessor_settings = model_settings.preprocessor
     if preprocessor_settings:
-
         locals_dict = {
             "person_max_window": lambda x: person_max_window(state, x),
             "person_available_periods": lambda persons, start_bin, end_bin, continuous: person_available_periods(

activitysim/abm/models/trip_purpose_and_destination.py

@@ -69,7 +69,6 @@ def trip_purpose_and_destination(
     model_settings_file_name: str = "trip_purpose_and_destination.yaml",
     trace_label: str = "trip_purpose_and_destination",
 ) -> None:
-
     if model_settings is None:
         model_settings = TripPurposeAndDestinationSettings.read_settings_file(
             state.filesystem,

activitysim/abm/models/trip_scheduling_choice.py

@@ -358,7 +358,6 @@ def trip_scheduling_choice(
     model_settings_file_name: str = "trip_scheduling_choice.yaml",
     trace_label: str = "trip_scheduling_choice",
 ) -> None:
-
     if model_settings is None:
         model_settings = TripSchedulingChoiceSettings.read_settings_file(
             state.filesystem,
@@ -416,7 +415,6 @@ def trip_scheduling_choice(
     }
 
     if preprocessor_settings:
-
         simulate.set_skim_wrapper_targets(tours_df, skims)
 
         expressions.assign_columns(

activitysim/abm/models/util/cdap.py

@@ -297,7 +297,6 @@ def cached_joint_spec_name(hhsize):
 
 
 def get_cached_spec(state: workflow.State, hhsize):
-
     spec_name = cached_spec_name(hhsize)
 
     spec = state.get_injectable(spec_name, None)
@@ -319,7 +318,6 @@ def get_cached_spec(state: workflow.State, hhsize):
 
 
 def get_cached_joint_spec(state: workflow.State, hhsize):
-
     spec_name = cached_joint_spec_name(hhsize)
 
     spec = state.get_injectable(spec_name, None)
@@ -625,7 +623,6 @@ def build_cdap_joint_spec(
     #         N_p1  0.0  0.0  0.0  1.0  1.0  1.0  0.0  0.0  0.0
     for pnum in range(1, hhsize + 1):
         for activity in ["M", "N", "H"]:
-
             new_row_index = len(spec)
             spec.loc[new_row_index, expression_name] = add_pn(activity, pnum)
 
@@ -638,7 +635,6 @@ def build_cdap_joint_spec(
 
     # for each row in the joint util table
     for row in joint_tour_coefficients.itertuples():
-
         # if there is no dependencies
         if row.dependency is np.nan:
             expression = row.Expression

activitysim/abm/models/util/overlap.py

@@ -138,7 +138,6 @@ def p2p_time_window_overlap(state: workflow.State, p1_ids, p2_ids):
 
 
 def person_pairs(persons):
-
     p = persons[["household_id", "adult"]].reset_index()
     p2p = pd.merge(p, p, left_on="household_id", right_on="household_id", how="outer")
 
@@ -166,7 +165,6 @@ def person_pairs(persons):
 
 
 def hh_time_window_overlap(state: workflow.State, households, persons):
-
     p2p = person_pairs(persons)
 
     p2p["max_overlap"] = p2p_time_window_overlap(state, p2p.person1, p2p.person2)
@@ -189,7 +187,6 @@ def hh_time_window_overlap(state: workflow.State, households, persons):
 
 
 def person_time_window_overlap(state: workflow.State, persons):
-
     p2p = person_pairs(persons)
 
     p2p["max_overlap"] = p2p_time_window_overlap(state, p2p.person1, p2p.person2)
@@ -224,7 +221,6 @@ def person_time_window_overlap(state: workflow.State, persons):
 
 
 def person_max_window(state: workflow.State, persons):
-
     timetable = state.get_injectable("timetable")
 
     # ndarray with one row per person and one column per time period