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bstablerClint DanielsBlakeBlake Rosenthaltoliwaga
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publish v0.9.5 (#340)
* update docs, drop scripts no longer needed, include example files in package * Pandas 1.0 fixes * Location and mode choice logsums (#298) * Tncs (#14) * write trip matrices (#311) * small fixes for semcog deployment (#319) * improved validation diagnostics in trip_purpose and various windows-related int32/int64 conversions * fix bug in handling of no viable trips case in choose_trip_destination * major work on phase 5 (#325) * estimation through atwork_subtour_mode_choice * Tnc updates and notebooks (#18) * move other resources into folder since examples now part of package as well * add example zone shapefile * estimation notebooks for larch (#19) * multiprocessing related logging and error checking * trip_destination handle all trips fail * skim caching with numpy memmap to speed skim loading * better chunking in vectorize_tour_scheduling * Cli (#22) * use activitysim_resources Fixed auto sufficiency conditions in tour_mode_choice.csv. (Issue #324) * correct write trip matrices sampling expansion and add vehicle occupancy to the expression file * additional updates for estimation integration (#328) * improve LICENSE (#30) * correct univ coeff template lookup (#28) Co-authored-by: Clint Daniels <[email protected]> Co-authored-by: Blake <[email protected]> Co-authored-by: Blake Rosenthal <[email protected]> Co-authored-by: Jeff Doyle <[email protected]> Co-authored-by: Jeffrey Doyle <[email protected]> Co-authored-by: Jeffrey Newman <[email protected]>
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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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language: python
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sudo: false
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python:
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- '2.7'
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- '3.6'
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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=$TRAVIS_PYTHON_VERSION future
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- source activate test-environment
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- conda create -q -n test-environment python=$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
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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:

‎LICENSE.txt‎

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ActivitySim
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Contributions prior to March 2016 Copyright (C) by UrbanSim Inc.
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Contributions subsequent to March 2016 Copyright (C) by the contributing authors
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BSD 3-Clause License
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Copyright (c) After March 2016, Contributing Authors
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Copyright (c) Before March 2016, UrbanSim Inc
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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1. Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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2. Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of [project] nor the names of its
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contributors may be used to endorse or promote products derived from
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this software without specific prior written permission.
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3. Neither the name of the copyright holder nor the names of its
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contributors may be used to endorse or promote products derived from
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this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

‎MANIFEST.in‎

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include ez_setup.py
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include README.rst
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graft notebooks
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graft activitysim/examples
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# required for test system
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include activitysim\abm\test\data\mtc_asim.h5
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include activitysim\abm\test\data\skims.omx
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include activitysim\abm\test\data\households.csv

‎activitysim/__init__.py‎

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# ActivitySim
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# See full license in LICENSE.txt.
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__version__ = '0.9.5'
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__doc__ = 'Activity-Based Travel Modeling'

‎activitysim/abm/__init__.py‎

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# ActivitySim
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# See full license in LICENSE.txt.
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from __future__ import absolute_import
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from . import misc
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from . import tables
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from . import models

‎activitysim/abm/misc.py‎

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# ActivitySim
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# See full license in LICENSE.txt.
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from __future__ import (absolute_import, division, print_function, )
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from future.standard_library import install_aliases
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install_aliases() # noqa: E402
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import logging
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import pandas as pd

‎activitysim/abm/models/__init__.py‎

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# ActivitySim
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# See full license in LICENSE.txt.
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from __future__ import absolute_import
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from . import accessibility
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from . import atwork_subtour_destination
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from . import atwork_subtour_frequency
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from . import trip_purpose
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from . import trip_purpose_and_destination
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from . import trip_scheduling
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from . import trip_matrices

‎activitysim/abm/models/accessibility.py‎

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# ActivitySim
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# See full license in LICENSE.txt.
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from __future__ import (absolute_import, division, print_function, )
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from future.standard_library import install_aliases
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install_aliases() # noqa: E402
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import logging
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import pandas as pd
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self.skim_dict = skim_dict
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self.transpose = transpose
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if omx_shape[0] == len(orig_zones):
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# no slicing required
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self.slice_map = None
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if omx_shape[0] == len(orig_zones) and skim_dict.offset_mapper.offset_series is None:
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# no slicing required because whatever the offset_int, the skim data aligns with zone list
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self.map_data = False
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else:
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# 2-d boolean slicing in numpy is a bit tricky
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# data = data[orig_map, dest_map] # <- WRONG!
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# data = data[orig_map, :][:, dest_map] # <- RIGHT
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# data = data[np.ix_(orig_map, dest_map)] # <- ALSO RIGHT
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if omx_shape[0] == len(orig_zones):
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logger.debug("AccessibilitySkims - applying offset_mapper")
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skim_index = list(range(omx_shape[0]))
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orig_map = np.isin(skim_index, skim_dict.offset_mapper.map(orig_zones))
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dest_map = np.isin(skim_index, skim_dict.offset_mapper.map(dest_zones))
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orig_map = skim_dict.offset_mapper.map(orig_zones)
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dest_map = skim_dict.offset_mapper.map(dest_zones)
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# (we might be sliced multiprocessing)
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# assert np.isin(skim_index, orig_map).all()
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if not dest_map.all():
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if np.isin(skim_index, dest_map).all():
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# not using the whole skim matrix
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logger.info("%s skim zones not in dest_map: %s" %
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((~dest_map).sum(), np.ix_(~dest_map)))
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self.slice_map = np.ix_(orig_map, dest_map)
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self.map_data = True
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self.orig_map = orig_map
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self.dest_map = dest_map
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def __getitem__(self, key):
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"""
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data = data.transpose()
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if self.map_data:
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# 2-d boolean slicing in numpy is a bit tricky - see explanation in __init__
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data = data[self.slice_map]
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# 2-d boolean slicing in numpy is a bit tricky
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# data = data[orig_map, dest_map] # <- WRONG!
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# data = data[orig_map, :][:, dest_map] # <- RIGHT
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# data = data[np.ix_(orig_map, dest_map)] # <- ALSO RIGHT
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data = data[self.orig_map, :][:, self.dest_map]
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constants = config.get_model_constants(model_settings)
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land_use_columns = model_settings.get('land_use_columns', [])
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land_use_columns = model_settings.get('land_use_columns', [])
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land_use_df = land_use.to_frame()
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land_use_df = land_use_df[land_use_columns]
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# #bug
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#
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# land_use_df = land_use_df[land_use_df.index % 2 == 1]
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# accessibility_df = accessibility_df[accessibility_df.index.isin(land_use_df.index)].head(5)
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#
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# print "land_use_df", land_use_df.index
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# print "accessibility_df", accessibility_df.index
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orig_zones = accessibility_df.index.values
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land_use_df = land_use_df[land_use_columns]
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od_df = pd.merge(od_df, land_use_df, left_on='dest', right_index=True).sort_index()
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locals_d = {
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for column in results.columns:
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data = np.asanyarray(results[column])
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data.shape = (orig_zone_count, dest_zone_count)
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data.shape = (orig_zone_count, dest_zone_count) # (o,d)
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accessibility_df[column] = np.log(np.sum(data, axis=1) + 1)
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# - write table to pipeline

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