small fixes for semcog deployment

activitysim/abm/models/atwork_subtour_scheduling.py

@@ -3,6 +3,7 @@
 import logging
 
 import pandas as pd
+import numpy as np
 
 from activitysim.core import simulate
 from activitysim.core import tracing
@@ -61,7 +62,7 @@ def atwork_subtour_scheduling(
         model_settings, trace_label)
 
     # parent_tours table with columns ['tour_id', 'tdd'] index = tour_id
-    parent_tour_ids = subtours.parent_tour_id.astype(int).unique()
+    parent_tour_ids = subtours.parent_tour_id.astype(np.int64).unique()
     parent_tours = pd.DataFrame({'tour_id': parent_tour_ids}, index=parent_tour_ids)
     parent_tours = parent_tours.merge(tours[['tdd']], left_index=True, right_index=True)
 

activitysim/abm/models/trip_destination.py

@@ -322,7 +322,7 @@ def choose_trip_destination(
     t0 = print_elapsed_time("%s.trip_destination_sample" % trace_label, t0)
 
     if trips.empty:
-        return pd.Series(index=trips.index), None
+        return pd.Series(index=trips.index).to_frame('choice'), None
 
     # - compute logsums
     destination_sample = compute_logsums(

activitysim/abm/models/trip_purpose.py

@@ -73,15 +73,37 @@ def choose_intermediate_trip_purpose(trips, probs_spec, trace_hh_id, trace_label
     choosers = pd.merge(trips.reset_index(), probs_spec, on=probs_join_cols,
                         how='left').set_index('trip_id')
 
-    chunk.log_df(trace_label, 'choosers', choosers)
+    # select the matching depart range (this should result on in exactly one chooser row per trip)
+    chooser_probs = \
+        (choosers.start >= choosers['depart_range_start']) & \
+        (choosers.start <= choosers['depart_range_end'])
+
+    # if we failed to match a row in probs_spec
+    if chooser_probs.sum() < num_trips:
+        # this can happen if the spec doesn't have probs matching a trip's probs_join_cols
+        missing_trip_ids = trips.index[~trips.index.isin(choosers.index[chooser_probs])].values
+        unmatched_choosers = choosers[choosers.index.isin(missing_trip_ids)]
+        unmatched_choosers = unmatched_choosers[['person_id', 'start'] + non_purpose_cols]
+
+        # join to persons for better diagnostics
+        persons = inject.get_table('persons').to_frame()
+        persons_cols = \
+            ['age', 'is_worker', 'is_student', 'is_gradeschool', 'is_highschool', 'is_university']
+        unmatched_choosers = pd.merge(unmatched_choosers, persons[persons_cols],
+                                      left_on='person_id', right_index=True, how='left')
+
+        file_name = '%s.UNMATCHED_PROBS' % trace_label
+        logger.error("%s %s of %s trips did not match probs based on join columns  %s" %
+                     (trace_label, len(unmatched_choosers), len(choosers), probs_join_cols))
+        logger.info("Writing %s unmatched choosers to %s" % (len(unmatched_choosers), file_name,))
+        tracing.write_csv(unmatched_choosers, file_name=file_name, transpose=False)
+        raise RuntimeError("Some trips did not match probs on join columns %s." % probs_join_cols)
 
     # select the matching depart range (this should result on in exactly one chooser row per trip)
-    choosers = choosers[(choosers.start >= choosers['depart_range_start']) & (
-                choosers.start <= choosers['depart_range_end'])]
+    choosers = choosers[chooser_probs]
 
     # choosers should now match trips row for row
-    assert choosers.index.is_unique
-    assert len(choosers.index) == num_trips
+    assert choosers.index.identical(trips.index)
 
     choices, rands = logit.make_choices(
         choosers[purpose_cols],

activitysim/abm/models/util/cdap.py

@@ -638,7 +638,7 @@ def household_activity_choices(indiv_utils, interaction_coefficients, hhsize,
         utils = simulate.eval_utilities(spec, choosers, trace_label=trace_label)
 
     if len(utils.index) == 0:
-        return pd.Series()
+        return pd.Series(dtype='float64')
 
     probs = logit.utils_to_probs(utils, trace_label=trace_label)
 
@@ -752,7 +752,7 @@ def extra_hh_member_choices(persons, cdap_fixed_relative_proportions, locals_d,
     choosers = persons[persons['cdap_rank'] > MAX_HHSIZE]
 
     if len(choosers.index) == 0:
-        return pd.Series()
+        return pd.Series(dtype='float64')
 
     # eval the expression file
     values = simulate.eval_variables(cdap_fixed_relative_proportions.index, choosers, locals_d)

activitysim/abm/models/util/test/test_cdap.py

@@ -4,7 +4,7 @@
 import os.path
 
 import pandas as pd
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 import pytest
 
 from .. import cdap

activitysim/abm/models/util/test/test_mandatory_tour_frequency.py

@@ -5,7 +5,7 @@
 import pytest
 import os
 import pandas as pd
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 from ..tour_frequency import process_mandatory_tours
 
 

activitysim/abm/models/util/test/test_non_mandatory_tour_frequency.py

@@ -5,7 +5,7 @@
 import pytest
 import os
 import pandas as pd
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 from ..tour_frequency import process_non_mandatory_tours
 
 

activitysim/abm/models/util/test/test_vectorize_tour_scheduling.py

@@ -6,7 +6,7 @@
 import pandas as pd
 import numpy as np
 
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 
 from activitysim.core import inject
 

activitysim/abm/models/util/tour_frequency.py

@@ -213,6 +213,9 @@ def create_tours(tour_counts, tour_category, parent_col='person_id'):
     # for joint tours, the correct number will be filled in after participation step
     tours['number_of_participants'] = 1
 
+    # index is arbitrary but don't want any duplicates
+    tours.reset_index(drop=True, inplace=True)
+
     return tours
 
 
@@ -525,6 +528,9 @@ def process_joint_tours(joint_tour_frequency, joint_tour_frequency_alts, point_p
                           tour_category='joint',
                           parent_col='household_id')
 
+    assert not tours.index.duplicated().any()
+    assert point_persons.index.name == 'household_id'
+
     # - assign a temp point person to tour so we can create stable index
     tours['person_id'] = reindex(point_persons.person_id, tours.household_id)
     tours['origin'] = reindex(point_persons.home_taz, tours.household_id)

activitysim/abm/tables/shadow_pricing.py

@@ -634,7 +634,7 @@ def buffers_for_shadow_pricing(shadow_pricing_info):
     for block_key, block_shape in block_shapes.items():
 
         # buffer_size must be int (or p2.7 long), not np.int64
-        buffer_size = int(np.prod(block_shape))
+        buffer_size = int(np.prod(block_shape, dtype=np.int64))
 
         csz = buffer_size * np.dtype(dtype).itemsize
         logger.info("allocating shared buffer %s %s buffer_size %s bytes %s (%s)" %

activitysim/abm/test/run_mp.py

@@ -3,7 +3,7 @@
 import os
 
 import pandas as pd
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 
 from activitysim.core import pipeline
 from activitysim.core import inject

activitysim/core/chunk.py

@@ -97,7 +97,7 @@ def log_df(trace_label, table_name, df):
     else:
 
         shape = df.shape
-        elements = np.prod(shape)
+        elements = np.prod(shape, dtype=np.int64)
         op = 'add'
 
         if isinstance(df, pd.Series):

activitysim/core/test/test_logit.py

@@ -6,7 +6,7 @@
 import numpy as np
 import pandas as pd
 
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 import pytest
 
 from ..simulate import eval_variables

activitysim/core/test/test_orca.py

@@ -369,12 +369,12 @@ def test_update_col(df):
     pdt.assert_series_equal(wrapped['a'], df['a'])
 
     # test 2 - let the update method do the cast
-    wrapped.update_col_from_series('a', pd.Series(), True)
+    wrapped.update_col_from_series('a', pd.Series(dtype='float64'), True)
     pdt.assert_series_equal(wrapped['a'], df['a'])
 
     # test 3 - don't cast, should raise an error
     with pytest.raises(ValueError):
-        wrapped.update_col_from_series('a', pd.Series())
+        wrapped.update_col_from_series('a', pd.Series(dtype='float64'))
 
     wrapped.update_col_from_series('a', pd.Series([99], index=['y']))
     pdt.assert_series_equal(

activitysim/core/test/test_simulate.py

@@ -6,7 +6,7 @@
 import numpy.testing as npt
 import numpy as np
 import pandas as pd
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 import pytest
 
 from .. import inject

activitysim/core/test/test_skim.py

@@ -4,7 +4,7 @@
 import numpy as np
 import pandas as pd
 import numpy.testing as npt
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 import pytest
 
 from .. import skim

activitysim/core/test/test_timetable.py

@@ -4,7 +4,7 @@
 from builtins import range
 import numpy as np
 import pandas as pd
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 import pytest
 
 from .. import timetable as tt

activitysim/core/test/test_util.py

@@ -3,7 +3,7 @@
 
 import numpy as np
 import pandas as pd
-import pandas.util.testing as pdt
+import pandas.testing as pdt
 import pytest
 
 from ..util import reindex

activitysim/examples/example_mtc/output/trace/.gitignore

@@ -0,0 +1,3 @@
+*.csv
+*.log
+*.txt