Xborder

.travis.yml

@@ -18,6 +18,9 @@ install:
 - pip install .
 - pip freeze
 script:
+# build 2 and 3 zone test data
+- python activitysim/examples/example_multiple_zone/two_zone_example_data.py
+- python activitysim/examples/example_multiple_zone/three_zone_example_data.py
 - pycodestyle activitysim
 - py.test --cov activitysim --cov-report term-missing
 after_success:

activitysim/abm/misc.py

@@ -20,7 +20,7 @@ def households_sample_size(settings, override_hh_ids):
     if override_hh_ids is None:
         return settings.get('households_sample_size', 0)
     else:
-        return len(override_hh_ids)
+        return 0 if override_hh_ids is None else len(override_hh_ids)
 
 
 @inject.injectable(cache=True)
@@ -79,7 +79,7 @@ def trace_od(settings):
 
 @inject.injectable(cache=True)
 def chunk_size(settings):
-    return int(settings.get('chunk_size', 0))
+    return int(settings.get('chunk_size', 0) or 0)
 
 
 @inject.injectable(cache=True)

activitysim/abm/models/__init__.py

@@ -9,6 +9,8 @@
 from . import cdap
 from . import free_parking
 from . import initialize
+from . import initialize_tours
+from . import initialize_los
 from . import joint_tour_composition
 from . import joint_tour_destination
 from . import joint_tour_frequency
@@ -22,9 +24,12 @@
 from . import non_mandatory_tour_frequency
 from . import stop_frequency
 from . import tour_mode_choice
+from . import tour_od_choice
+from . import tour_scheduling_probabilistic
 from . import trip_destination
 from . import trip_mode_choice
 from . import trip_purpose
 from . import trip_purpose_and_destination
 from . import trip_scheduling
 from . import trip_matrices
+from . import summarize

activitysim/abm/models/accessibility.py

@@ -4,13 +4,17 @@
 
 import pandas as pd
 import numpy as np
+import os
 
 from activitysim.core import assign
 from activitysim.core import tracing
 from activitysim.core import config
 from activitysim.core import inject
 from activitysim.core import pipeline
+from activitysim.core import mem
 
+from activitysim.core import los
+from activitysim.core.pathbuilder import TransitVirtualPathBuilder
 
 logger = logging.getLogger(__name__)
 
@@ -34,9 +38,7 @@ class AccessibilitySkims(object):
 
     def __init__(self, skim_dict, orig_zones, dest_zones, transpose=False):
 
-        omx_shape = skim_dict.skim_info['omx_shape']
-        logger.info("init AccessibilitySkims with %d dest zones %d orig zones omx_shape %s" %
-                    (len(dest_zones), len(orig_zones), omx_shape, ))
+        logger.info(f"init AccessibilitySkims with {len(dest_zones)} dest zones {len(orig_zones)} orig zones")
 
         assert len(orig_zones) <= len(dest_zones)
         assert np.isin(orig_zones, dest_zones).all()
@@ -46,25 +48,29 @@ def __init__(self, skim_dict, orig_zones, dest_zones, transpose=False):
         self.skim_dict = skim_dict
         self.transpose = transpose
 
-        if omx_shape[0] == len(orig_zones) and skim_dict.offset_mapper.offset_series is None:
+        num_skim_zones = skim_dict.get_skim_info('omx_shape')[0]
+        if num_skim_zones == len(orig_zones) and skim_dict.offset_mapper.offset_series is None:
             # no slicing required because whatever the offset_int, the skim data aligns with zone list
             self.map_data = False
         else:
 
-            if omx_shape[0] == len(orig_zones):
-                logger.debug("AccessibilitySkims - applying offset_mapper")
+            logger.debug("AccessibilitySkims - applying offset_mapper")
 
-            skim_index = list(range(omx_shape[0]))
+            skim_index = list(range(num_skim_zones))
             orig_map = skim_dict.offset_mapper.map(orig_zones)
             dest_map = skim_dict.offset_mapper.map(dest_zones)
 
             # (we might be sliced multiprocessing)
             # assert np.isin(skim_index, orig_map).all()
 
-            if np.isin(skim_index, dest_map).all():
-                # not using the whole skim matrix
-                logger.info("%s skim zones not in dest_map: %s" %
-                            ((~dest_map).sum(), np.ix_(~dest_map)))
+            out_of_bounds = ~np.isin(skim_index, dest_map)
+            # if out_of_bounds.any():
+            #    print(f"{(out_of_bounds).sum()} skim zones not in dest_map")
+            #    print(f"dest_zones {dest_zones}")
+            #    print(f"dest_map {dest_map}")
+            #    print(f"skim_index {skim_index}")
+            assert not out_of_bounds.any(), \
+                f"AccessibilitySkims {(out_of_bounds).sum()} skim zones not in dest_map: {np.ix_(out_of_bounds)[0]}"
 
             self.map_data = True
             self.orig_map = orig_map
@@ -85,7 +91,6 @@ def __getitem__(self, key):
             data = data.transpose()
 
         if self.map_data:
-
             # slice skim to include only orig rows and dest columns
             # 2-d boolean slicing in numpy is a bit tricky
             # data = data[orig_map, dest_map]          # <- WRONG!
@@ -98,7 +103,7 @@ def __getitem__(self, key):
 
 
 @inject.step()
-def compute_accessibility(accessibility, skim_dict, land_use, trace_od):
+def compute_accessibility(accessibility, network_los, land_use, trace_od):
 
     """
     Compute accessibility for each zone in land use file using expressions from accessibility_spec
@@ -143,8 +148,8 @@ def compute_accessibility(accessibility, skim_dict, land_use, trace_od):
     # create OD dataframe
     od_df = pd.DataFrame(
         data={
-            'orig': np.repeat(np.asanyarray(accessibility_df.index), dest_zone_count),
-            'dest': np.tile(np.asanyarray(land_use_df.index), orig_zone_count)
+            'orig': np.repeat(orig_zones, dest_zone_count),
+            'dest': np.tile(dest_zones, orig_zone_count)
         }
     )
 
@@ -160,9 +165,16 @@ def compute_accessibility(accessibility, skim_dict, land_use, trace_od):
     locals_d = {
         'log': np.log,
         'exp': np.exp,
-        'skim_od': AccessibilitySkims(skim_dict, orig_zones, dest_zones),
-        'skim_do': AccessibilitySkims(skim_dict, orig_zones, dest_zones, transpose=True)
+        'network_los': network_los,
     }
+
+    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)
+
+    if network_los.zone_system == los.THREE_ZONE:
+        locals_d['tvpb'] = TransitVirtualPathBuilder(network_los)
+
     if constants is not None:
         locals_d.update(constants)
 
@@ -174,13 +186,16 @@ def compute_accessibility(accessibility, skim_dict, land_use, trace_od):
         data.shape = (orig_zone_count, dest_zone_count)  # (o,d)
         accessibility_df[column] = np.log(np.sum(data, axis=1) + 1)
 
+    logger.info("{trace_label} added {len(results.columns} columns")
+
     # - write table to pipeline
     pipeline.replace_table("accessibility", accessibility_df)
 
+
     if trace_od:
 
         if not trace_od_rows.any():
-            logger.warning("trace_od not found origin = %s, dest = %s" % (trace_orig, trace_dest))
+            logger.warning(f"trace_od not found origin = {trace_orig}, dest = {trace_dest}")
         else:
 
             # add OD columns to trace results

activitysim/abm/models/atwork_subtour_destination.py

@@ -27,7 +27,7 @@ def atwork_subtour_destination_sample(
         tours,
         persons_merged,
         model_settings,
-        skim_dict,
+        network_los,
         destination_size_terms,
         estimator,
         chunk_size, trace_label):
@@ -54,10 +54,12 @@ def atwork_subtour_destination_sample(
 
     logger.info("Running atwork_subtour_location_sample with %d tours", len(choosers))
 
-    # create wrapper with keys for this lookup - in this case there is a workplace_taz
-    # in the choosers and a TAZ in the alternatives which get merged during interaction
+    # create wrapper with keys for this lookup - in this case there is a workplace_zone_id
+    # in the choosers and a zone_id in the alternatives which get merged during interaction
     # the skims will be available under the name "skims" for any @ expressions
-    skims = skim_dict.wrap('workplace_taz', 'TAZ')
+    dest_column_name = destination_size_terms.index.name
+    skim_dict = network_los.get_default_skim_dict()
+    skims = skim_dict.wrap('workplace_zone_id', dest_column_name)
 
     locals_d = {
         'skims': skims
@@ -86,16 +88,16 @@ def atwork_subtour_destination_logsums(
         persons_merged,
         destination_sample,
         model_settings,
-        skim_dict, skim_stack,
+        network_los,
         chunk_size, trace_label):
     """
     add logsum column to existing atwork_subtour_destination_sample table
 
-    logsum is calculated by running the mode_choice model for each sample (person, dest_taz) pair
+    logsum is calculated by running the mode_choice model for each sample (person, dest_zone_id) pair
     in atwork_subtour_destination_sample, and computing the logsum of all the utilities
 
     +-----------+--------------+----------------+------------+----------------+
-    | person_id | dest_TAZ     | rand           | pick_count | logsum (added) |
+    | person_id | dest_zone_id | rand           | pick_count | logsum (added) |
     +===========+==============+================+============+================+
     | 23750     |  14          | 0.565502716034 | 4          |  1.85659498857 |
     +-----------+--------------+----------------+------------+----------------+
@@ -132,7 +134,7 @@ def atwork_subtour_destination_logsums(
         choosers,
         tour_purpose,
         logsum_settings, model_settings,
-        skim_dict, skim_stack,
+        network_los,
         chunk_size,
         trace_label)
 
@@ -147,7 +149,7 @@ def atwork_subtour_destination_simulate(
         destination_sample,
         want_logsums,
         model_settings,
-        skim_dict,
+        network_los,
         destination_size_terms,
         estimator,
         chunk_size, trace_label):
@@ -175,7 +177,7 @@ def atwork_subtour_destination_simulate(
         estimator.write_choosers(choosers)
 
     alt_dest_col_name = model_settings['ALT_DEST_COL_NAME']
-    chooser_col_name = 'workplace_taz'
+    chooser_col_name = 'workplace_zone_id'
 
     # alternatives are pre-sampled and annotated with logsums and pick_count
     # but we have to merge destination_size_terms columns into alt sample list
@@ -189,9 +191,10 @@ def atwork_subtour_destination_simulate(
 
     logger.info("Running atwork_subtour_destination_simulate with %d persons", len(choosers))
 
-    # create wrapper with keys for this lookup - in this case there is a TAZ in the choosers
-    # and a TAZ in the alternatives which get merged during interaction
+    # create wrapper with keys for this lookup - in this case there is a home_zone_id in the choosers
+    # and a zone_id in the alternatives which get merged during interaction
     # the skims will be available under the name "skims" for any @ expressions
+    skim_dict = network_los.get_default_skim_dict()
     skims = skim_dict.wrap(chooser_col_name, alt_dest_col_name)
 
     locals_d = {
@@ -212,7 +215,7 @@ def atwork_subtour_destination_simulate(
         locals_d=locals_d,
         chunk_size=chunk_size,
         trace_label=trace_label,
-        trace_choice_name='workplace_location',
+        trace_choice_name='atwork_subtour',
         estimator=estimator)
 
     if not want_logsums:
@@ -227,8 +230,7 @@ def atwork_subtour_destination_simulate(
 def atwork_subtour_destination(
         tours,
         persons_merged,
-        skim_dict,
-        skim_stack,
+        network_los,
         land_use, size_terms,
         chunk_size, trace_hh_id):
 
@@ -271,7 +273,7 @@ def atwork_subtour_destination(
         subtours,
         persons_merged,
         model_settings,
-        skim_dict,
+        network_los,
         destination_size_terms,
         estimator=estimator,
         chunk_size=chunk_size,
@@ -281,7 +283,7 @@ def atwork_subtour_destination(
         persons_merged,
         destination_sample_df,
         model_settings,
-        skim_dict, skim_stack,
+        network_los,
         chunk_size=chunk_size,
         trace_label=tracing.extend_trace_label(trace_label, 'logsums'))
 
@@ -291,7 +293,7 @@ def atwork_subtour_destination(
         destination_sample_df,
         want_logsums,
         model_settings,
-        skim_dict,
+        network_los,
         destination_size_terms,
         estimator=estimator,
         chunk_size=chunk_size,

activitysim/abm/models/atwork_subtour_frequency.py

@@ -10,11 +10,11 @@
 from activitysim.core import pipeline
 from activitysim.core import config
 from activitysim.core import inject
+from activitysim.core import expressions
 
 from .util import estimation
 
 from .util.tour_frequency import process_atwork_subtours
-from .util.expressions import assign_columns
 
 logger = logging.getLogger(__name__)
 
@@ -69,7 +69,7 @@ def atwork_subtour_frequency(tours,
     preprocessor_settings = model_settings.get('preprocessor', None)
     if preprocessor_settings:
 
-        assign_columns(
+        expressions.assign_columns(
             df=work_tours,
             model_settings=preprocessor_settings,
             trace_label=trace_label)