Merge e4eaa0a into 367cbac

.gitignore

@@ -72,4 +72,5 @@ _test_est
 *_local/
 *_local.*
 
+**/__sharrowcache__
 **/output/

.travis.yml

@@ -5,6 +5,10 @@ env:
   global:
   - TEST_ENV=activitysim-test
 
+cache:
+  directories:
+    - activitysim/examples/example_mtc/test/output/cache
+
 jobs:
   include:
     # Add new TEST_SUITE jobs as needed via Travis build matrix expansion
@@ -18,10 +22,12 @@ jobs:
     - env: TEST_SUITE=activitysim/cli
     - env: TEST_SUITE=activitysim/core
 
-    - stage: Examples
+    - stage: Primary Example
       name: "MTC Example"
       env: TEST_SUITE=activitysim/examples/example_mtc/test
-    - name: "MTC Extended Example"
+
+    - stage: Other Examples
+      name: "MTC Extended Example"
       env: TEST_SUITE=activitysim/examples/example_mtc_extended/test
     - name: "Multizone Example"
       env: TEST_SUITE=activitysim/examples/example_multiple_zone/test

activitysim/__init__.py

@@ -2,5 +2,5 @@
 # See full license in LICENSE.txt.
 
 
-__version__ = '1.0.4'
-__doc__ = 'Activity-Based Travel Modeling'
+__version__ = "1.0.4"
+__doc__ = "Activity-Based Travel Modeling"

activitysim/__main__.py

@@ -0,0 +1,25 @@
+import os
+import sys
+
+
+def main():
+    # clean up message formatting
+    if sys.argv and sys.argv[0].endswith("__main__.py"):
+        sys.argv[0] = "activitysim"
+
+    # threadstopper
+    if "--fast" not in sys.argv:
+        os.environ["MKL_NUM_THREADS"] = "1"
+        os.environ["OMP_NUM_THREADS"] = "1"
+        os.environ["OPENBLAS_NUM_THREADS"] = "1"
+        os.environ["NUMBA_NUM_THREADS"] = "1"
+        os.environ["VECLIB_MAXIMUM_THREADS"] = "1"
+        os.environ["NUMEXPR_NUM_THREADS"] = "1"
+
+    from .cli.main import main
+
+    main()
+
+
+if __name__ == "__main__":
+    main()

activitysim/abm/misc.py

@@ -18,26 +18,28 @@
 def households_sample_size(settings, override_hh_ids):
 
     if override_hh_ids is None:
-        return settings.get('households_sample_size', 0)
+        return settings.get("households_sample_size", 0)
     else:
         return 0 if override_hh_ids is None else len(override_hh_ids)
 
 
 @inject.injectable(cache=True)
 def override_hh_ids(settings):
 
-    hh_ids_filename = settings.get('hh_ids', None)
+    hh_ids_filename = settings.get("hh_ids", None)
     if hh_ids_filename is None:
         return None
 
     file_path = config.data_file_path(hh_ids_filename, mandatory=False)
     if not file_path:
-        logger.error("hh_ids file name '%s' specified in settings not found" % hh_ids_filename)
+        logger.error(
+            "hh_ids file name '%s' specified in settings not found" % hh_ids_filename
+        )
         return None
 
-    df = pd.read_csv(file_path, comment='#')
+    df = pd.read_csv(file_path, comment="#")
 
-    if 'household_id' not in df.columns:
+    if "household_id" not in df.columns:
         logger.error("No 'household_id' column in hh_ids file %s" % hh_ids_filename)
         return None
 
@@ -47,19 +49,23 @@ def override_hh_ids(settings):
         logger.error("No households in hh_ids file %s" % hh_ids_filename)
         return None
 
-    logger.info("Using hh_ids list with %s households from file %s" %
-                (len(household_ids), hh_ids_filename))
+    logger.info(
+        "Using hh_ids list with %s households from file %s"
+        % (len(household_ids), hh_ids_filename)
+    )
 
     return household_ids
 
 
 @inject.injectable(cache=True)
 def trace_hh_id(settings):
 
-    id = settings.get('trace_hh_id', None)
+    id = settings.get("trace_hh_id", None)
 
     if id and not isinstance(id, int):
-        logger.warning("setting trace_hh_id is wrong type, should be an int, but was %s" % type(id))
+        logger.warning(
+            "setting trace_hh_id is wrong type, should be an int, but was %s" % type(id)
+        )
         id = None
 
     return id
@@ -68,9 +74,11 @@ def trace_hh_id(settings):
 @inject.injectable(cache=True)
 def trace_od(settings):
 
-    od = settings.get('trace_od', None)
+    od = settings.get("trace_od", None)
 
-    if od and not (isinstance(od, list) and len(od) == 2 and all(isinstance(x, int) for x in od)):
+    if od and not (
+        isinstance(od, list) and len(od) == 2 and all(isinstance(x, int) for x in od)
+    ):
         logger.warning("setting trace_od should be a list of length 2, but was %s" % od)
         od = None
 
@@ -79,11 +87,11 @@ def trace_od(settings):
 
 @inject.injectable(cache=True)
 def chunk_size(settings):
-    _chunk_size = int(settings.get('chunk_size', 0) or 0)
+    _chunk_size = int(settings.get("chunk_size", 0) or 0)
 
     return _chunk_size
 
 
 @inject.injectable(cache=True)
 def check_for_variability(settings):
-    return bool(settings.get('check_for_variability', False))
+    return bool(settings.get("check_for_variability", False))

activitysim/abm/models/__init__.py

@@ -36,5 +36,9 @@
 from . import trip_scheduling_choice
 from . import trip_matrices
 from . import summarize
+from . import work_from_home
+from . import telecommute_frequency
+from . import transit_pass_subsidy
+from . import transit_pass_ownership
 from . import vehicle_allocation
 from . import vehicle_type_choice

activitysim/abm/models/accessibility.py

@@ -20,28 +20,31 @@
 
 
 def compute_accessibilities_for_zones(
-        accessibility_df,
-        land_use_df,
-        assignment_spec,
-        constants,
-        network_los,
-        trace_od,
-        trace_label):
+    accessibility_df,
+    land_use_df,
+    assignment_spec,
+    constants,
+    network_los,
+    trace_od,
+    trace_label,
+):
 
     orig_zones = accessibility_df.index.values
     dest_zones = land_use_df.index.values
 
     orig_zone_count = len(orig_zones)
     dest_zone_count = len(dest_zones)
 
-    logger.info("Running %s with %d orig zones %d dest zones" %
-                (trace_label, orig_zone_count, dest_zone_count))
+    logger.info(
+        "Running %s with %d orig zones %d dest zones"
+        % (trace_label, orig_zone_count, dest_zone_count)
+    )
 
     # create OD dataframe
     od_df = pd.DataFrame(
         data={
-            'orig': np.repeat(orig_zones, dest_zone_count),
-            'dest': np.tile(dest_zones, orig_zone_count)
+            "orig": np.repeat(orig_zones, dest_zone_count),
+            "dest": np.tile(dest_zones, orig_zone_count),
         }
     )
 
@@ -53,27 +56,32 @@ def compute_accessibilities_for_zones(
 
     # merge land_use_columns into od_df
     logger.info(f"{trace_label}: merge land_use_columns into od_df")
-    od_df = pd.merge(od_df, land_use_df, left_on='dest', right_index=True).sort_index()
+    od_df = pd.merge(od_df, land_use_df, left_on="dest", right_index=True).sort_index()
     chunk.log_df(trace_label, "od_df", od_df)
 
     locals_d = {
-        'log': np.log,
-        'exp': np.exp,
-        'network_los': network_los,
+        "log": np.log,
+        "exp": np.exp,
+        "network_los": network_los,
     }
     locals_d.update(constants)
 
     skim_dict = network_los.get_default_skim_dict()
-    locals_d['skim_od'] = skim_dict.wrap('orig', 'dest').set_df(od_df)
-    locals_d['skim_do'] = skim_dict.wrap('dest', 'orig').set_df(od_df)
+    locals_d["skim_od"] = skim_dict.wrap("orig", "dest").set_df(od_df)
+    locals_d["skim_do"] = skim_dict.wrap("dest", "orig").set_df(od_df)
 
     if network_los.zone_system == los.THREE_ZONE:
-        locals_d['tvpb'] = network_los.tvpb
+        locals_d["tvpb"] = network_los.tvpb
 
     logger.info(f"{trace_label}: assign.assign_variables")
-    results, trace_results, trace_assigned_locals \
-        = assign.assign_variables(assignment_spec, od_df, locals_d,
-                                  trace_rows=trace_od_rows, trace_label=trace_label, chunk_log=True)
+    results, trace_results, trace_assigned_locals = assign.assign_variables(
+        assignment_spec,
+        od_df,
+        locals_d,
+        trace_rows=trace_od_rows,
+        trace_label=trace_label,
+        chunk_log=True,
+    )
 
     chunk.log_df(trace_label, "results", results)
     logger.info(f"{trace_label}: have results")
@@ -87,23 +95,29 @@ def compute_accessibilities_for_zones(
     if trace_od:
 
         if not trace_od_rows.any():
-            logger.warning(f"trace_od not found origin = {trace_orig}, dest = {trace_dest}")
+            logger.warning(
+                f"trace_od not found origin = {trace_orig}, dest = {trace_dest}"
+            )
         else:
 
             # add OD columns to trace results
             df = pd.concat([od_df[trace_od_rows], trace_results], axis=1)
 
             # dump the trace results table (with _temp variables) to aid debugging
-            tracing.trace_df(df,
-                             label='accessibility',
-                             index_label='skim_offset',
-                             slicer='NONE',
-                             warn_if_empty=True)
+            tracing.trace_df(
+                df,
+                label="accessibility",
+                index_label="skim_offset",
+                slicer="NONE",
+                warn_if_empty=True,
+            )
 
             if trace_assigned_locals:
-                tracing.write_csv(trace_assigned_locals, file_name="accessibility_locals")
+                tracing.write_csv(
+                    trace_assigned_locals, file_name="accessibility_locals"
+                )
 
-    return(accessibility_df)
+    return accessibility_df
 
 
 @inject.step()
@@ -125,32 +139,45 @@ def compute_accessibility(land_use, accessibility, network_los, chunk_size, trac
     steeper than automobile or transit.  The minimum accessibility is zero.
     """
 
-    trace_label = 'compute_accessibility'
-    model_settings = config.read_model_settings('accessibility.yaml')
-    assignment_spec = assign.read_assignment_spec(config.config_file_path('accessibility.csv'))
+    trace_label = "compute_accessibility"
+    model_settings = config.read_model_settings("accessibility.yaml")
+    assignment_spec = assign.read_assignment_spec(
+        config.config_file_path("accessibility.csv")
+    )
 
     accessibility_df = accessibility.to_frame()
     if len(accessibility_df.columns) > 0:
-        logger.warning(f"accessibility table is not empty. Columns:{list(accessibility_df.columns)}")
+        logger.warning(
+            f"accessibility table is not empty. Columns:{list(accessibility_df.columns)}"
+        )
         raise RuntimeError(f"accessibility table is not empty.")
 
     constants = config.get_model_constants(model_settings)
 
     # only include the land_use columns needed by spec, as specified by land_use_columns model_setting
-    land_use_columns = model_settings.get('land_use_columns', [])
+    land_use_columns = model_settings.get("land_use_columns", [])
     land_use_df = land_use.to_frame()
     land_use_df = land_use_df[land_use_columns]
 
-    logger.info(f"Running {trace_label} with {len(accessibility_df.index)} orig zones {len(land_use_df)} dest zones")
+    logger.info(
+        f"Running {trace_label} with {len(accessibility_df.index)} orig zones {len(land_use_df)} dest zones"
+    )
 
     accessibilities_list = []
 
-    for i, chooser_chunk, chunk_trace_label in \
-            chunk.adaptive_chunked_choosers(accessibility_df, chunk_size, trace_label):
-
-        accessibilities = \
-            compute_accessibilities_for_zones(chooser_chunk, land_use_df, assignment_spec,
-                                              constants, network_los, trace_od, trace_label)
+    for i, chooser_chunk, chunk_trace_label in chunk.adaptive_chunked_choosers(
+        accessibility_df, chunk_size, trace_label
+    ):
+
+        accessibilities = compute_accessibilities_for_zones(
+            chooser_chunk,
+            land_use_df,
+            assignment_spec,
+            constants,
+            network_los,
+            trace_od,
+            trace_label,
+        )
         accessibilities_list.append(accessibilities)
 
     accessibility_df = pd.concat(accessibilities_list)