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bstablertoliwagaBlake Rosenthal
authored and
Blake
committed
Tncs (#14)
* add tncs * lognormal_for_df broadcasts duplicate indexes * lognormal_for_df broadcasts duplicate indexes code * correct lognormal calculations and add functions to calculation lognormal location and scale * clean-up tnc wait time expressions * set taxi, tnc wait time standard deviations to zero until we have better data * add scaled option to random.lognormal_for_df * add mobility-as-a-service modes to docs * updated tnc mode constants * rename maas to ridehail Co-authored-by: Jeff Doyle <[email protected]> Co-authored-by: Blake Rosenthal <[email protected]>
1 parent f3955ec commit 4255f03

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-716
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‎.gitignore‎

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sandbox/
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example/data/*
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.idea
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.ipynb_checkpoints
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.coverage*

‎.travis.yml‎

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@@ -5,16 +5,15 @@ python:
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- '3.7'
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- '3.8'
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install:
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- wget http://repo.continuum.io/miniconda/Miniconda-3.7.0-Linux-x86_64.sh -O miniconda.sh
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- wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
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- bash miniconda.sh -b -p $HOME/miniconda
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- export PATH="$HOME/miniconda/bin:$PATH"
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- source "$HOME/miniconda/etc/profile.d/conda.sh"
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- hash -r
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- conda config --set always_yes yes --set changeps1 no
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- conda update -q conda
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- conda info -a
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- |
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conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION
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- source activate test-environment
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- conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION
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- conda activate test-environment
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- conda install pytest pytest-cov coveralls pycodestyle
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- pip install .
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- pip freeze
@@ -41,6 +40,8 @@ deploy:
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notifications:
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slack:
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on_success: never # default: change
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on_failure: always # default: always
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secure: Dpp+zBrnPGBHXrYWjwHy/bnHvhINfepSIiViwKfBZizBvTDvzSJfu6gCH+/lQ3squF3D4qTWwxB+LQ9V6KTYhuma8vQVisyneI6ARjUI/qgX6aJjuvmDDGPk6DVeDow7+aCLZ8VEHRhSjwy+dv0Ij0rxI6I94xPVwXUkk7ZjcK0=
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env:
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global:

‎activitysim/abm/models/atwork_subtour_destination.py‎

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@@ -123,7 +123,7 @@ def atwork_subtour_destination_logsums(
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tour_purpose,
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logsum_settings, model_settings,
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skim_dict, skim_stack,
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chunk_size, trace_hh_id,
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chunk_size,
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trace_label)
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destination_sample['mode_choice_logsum'] = logsums

‎activitysim/abm/models/joint_tour_destination.py‎

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tour_purpose,
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logsum_settings, model_settings,
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skim_dict, skim_stack,
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chunk_size, trace_hh_id,
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chunk_size,
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trace_label=tracing.extend_trace_label(trace_label, tour_type))
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logsums_list.append(logsums)

‎activitysim/abm/models/location_choice.py‎

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@@ -224,7 +224,7 @@ def run_location_logsums(
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tour_purpose,
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logsum_settings, model_settings,
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skim_dict, skim_stack,
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chunk_size, trace_hh_id,
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chunk_size,
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trace_label)
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# "add_column series should have an index matching the table to which it is being added"

‎activitysim/abm/models/trip_destination.py‎

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@@ -151,7 +151,7 @@ def compute_logsums(
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tours_merged,
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model_settings,
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skims,
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chunk_size, trace_hh_id,
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chunk_size,
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trace_label):
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"""
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Calculate mode choice logsums using the same recipe as for trip_mode_choice, but do it twice
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tours_merged=tours_merged,
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model_settings=model_settings,
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skims=skims,
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chunk_size=chunk_size, trace_hh_id=trace_hh_id,
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chunk_size=chunk_size,
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trace_label=trace_label)
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t0 = print_elapsed_time("%s.compute_logsums" % trace_label, t0)

‎activitysim/abm/models/util/logsums.py‎

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tour_purpose,
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logsum_settings, model_settings,
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skim_dict, skim_stack,
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chunk_size, trace_hh_id, trace_label):
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chunk_size, trace_label):
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"""
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Parameters

‎activitysim/abm/models/util/tour_destination.py‎

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tour_purpose,
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logsum_settings, model_settings,
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skim_dict, skim_stack,
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chunk_size, trace_hh_id,
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chunk_size,
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trace_label)
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destination_sample['mode_choice_logsum'] = logsums

‎activitysim/abm/tables/table_dict.py‎

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@inject.injectable()
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def rng_channels():
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# bug
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return RANDOM_CHANNELS
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‎activitysim/abm/test/test_pipeline.py‎

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return df
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EXPECT_TOUR_COUNT = 205
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EXPECT_TOUR_COUNT = 201
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def regress_tour_modes(tours_df):
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'othdiscr',
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'work',
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'work',
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'maint',
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'business',
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'work',
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'eatout',
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]
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'othmaint'
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]
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EXPECT_MODES = [
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'SHARED3FREE',
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'WALK',
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'DRIVEALONEFREE',
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'WALK',
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'WALK',
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'SHARED3FREE',
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'WALK',
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]
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'WALK_LOC',
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'WALK'
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]
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assert len(tours_df) == len(EXPECT_PERSON_IDS)
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assert (tours_df.person_id.values == EXPECT_PERSON_IDS).all()

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