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 <clint.daniels@wsp.com>
Co-authored-by: Blake <brosenthalpdx@gmail.com>
Co-authored-by: Blake Rosenthal <blake.rosenthal@rsginc.com>
Co-authored-by: Jeff Doyle <toliwaga@gmail.com>
Co-authored-by: Jeffrey Doyle <jeff.doyle@rsginc.com>
Co-authored-by: Jeffrey Newman <jeff@newman.me>

.gitignore

@@ -1,5 +1,4 @@
 sandbox/
-example/data/*
 .idea
 .ipynb_checkpoints
 .coverage*

.travis.yml

@@ -1,19 +1,19 @@
 language: python
 sudo: false
 python:
-  - '2.7'
+  - '3.6'
   - '3.7'
+  - '3.8'
 install:
-- wget http://repo.continuum.io/miniconda/Miniconda-3.7.0-Linux-x86_64.sh -O miniconda.sh
+- wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
 - bash miniconda.sh -b -p $HOME/miniconda
-- export PATH="$HOME/miniconda/bin:$PATH"
+- source "$HOME/miniconda/etc/profile.d/conda.sh"
 - hash -r
 - conda config --set always_yes yes --set changeps1 no
 - conda update -q conda
 - conda info -a
-- |
-  conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION future
-- source activate test-environment
+- conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION
+- conda activate test-environment
 - conda install pytest pytest-cov coveralls pycodestyle
 - pip install .
 - pip freeze
@@ -40,6 +40,8 @@ deploy:
 
 notifications:
   slack:
+    on_success: never # default: change
+    on_failure: always # default: always
     secure: Dpp+zBrnPGBHXrYWjwHy/bnHvhINfepSIiViwKfBZizBvTDvzSJfu6gCH+/lQ3squF3D4qTWwxB+LQ9V6KTYhuma8vQVisyneI6ARjUI/qgX6aJjuvmDDGPk6DVeDow7+aCLZ8VEHRhSjwy+dv0Ij0rxI6I94xPVwXUkk7ZjcK0=
 env:
   global:

LICENSE.txt

@@ -1,20 +1,22 @@
-ActivitySim
-Contributions prior to March 2016 Copyright (C) by UrbanSim Inc.
-Contributions subsequent to March 2016 Copyright (C) by the contributing authors
+BSD 3-Clause License
+
+Copyright (c) After March 2016, Contributing Authors
+Copyright (c) Before March 2016, UrbanSim Inc
+All rights reserved.
 
 Redistribution and use in source and binary forms, with or without
 modification, are permitted provided that the following conditions are met:
 
-* Redistributions of source code must retain the above copyright notice, this
-  list of conditions and the following disclaimer.
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
 
-* Redistributions in binary form must reproduce the above copyright notice,
-  this list of conditions and the following disclaimer in the documentation
-  and/or other materials provided with the distribution.
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
 
-* Neither the name of [project] nor the names of its
-  contributors may be used to endorse or promote products derived from
-  this software without specific prior written permission.
+3. Neither the name of the copyright holder nor the names of its
+   contributors may be used to endorse or promote products derived from
+   this software without specific prior written permission.
 
 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
@@ -25,4 +27,4 @@ DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
 SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
-OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

MANIFEST.in

@@ -1,5 +1,10 @@
 include ez_setup.py
 include README.rst
+graft notebooks
+graft activitysim/examples
+
+# required for test system
+
 include activitysim\abm\test\data\mtc_asim.h5
 include activitysim\abm\test\data\skims.omx
 include activitysim\abm\test\data\households.csv

activitysim/__init__.py

@@ -1,2 +1,5 @@
 # ActivitySim
 # See full license in LICENSE.txt.
+
+__version__ = '0.9.5'
+__doc__ = 'Activity-Based Travel Modeling'

activitysim/abm/__init__.py

@@ -1,8 +1,5 @@
 # ActivitySim
 # See full license in LICENSE.txt.
-
-from __future__ import absolute_import
-
 from . import misc
 from . import tables
 from . import models

activitysim/abm/misc.py

@@ -1,10 +1,5 @@
 # ActivitySim
 # See full license in LICENSE.txt.
-
-from __future__ import (absolute_import, division, print_function, )
-from future.standard_library import install_aliases
-install_aliases()  # noqa: E402
-
 import logging
 
 import pandas as pd

activitysim/abm/models/__init__.py

@@ -1,8 +1,5 @@
 # ActivitySim
 # See full license in LICENSE.txt.
-
-from __future__ import absolute_import
-
 from . import accessibility
 from . import atwork_subtour_destination
 from . import atwork_subtour_frequency
@@ -30,3 +27,4 @@
 from . import trip_purpose
 from . import trip_purpose_and_destination
 from . import trip_scheduling
+from . import trip_matrices

activitysim/abm/models/accessibility.py

@@ -1,10 +1,5 @@
 # ActivitySim
 # See full license in LICENSE.txt.
-
-from __future__ import (absolute_import, division, print_function, )
-from future.standard_library import install_aliases
-install_aliases()  # noqa: E402
-
 import logging
 
 import pandas as pd
@@ -51,25 +46,29 @@ 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):
-            # no slicing required
-            self.slice_map = None
+        if omx_shape[0] == 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:
-            # 2-d boolean slicing in numpy is a bit tricky
-            # data = data[orig_map, dest_map]          # <- WRONG!
-            # data = data[orig_map, :][:, dest_map]    # <- RIGHT
-            # data = data[np.ix_(orig_map, dest_map)]  # <- ALSO RIGHT
+
+            if omx_shape[0] == len(orig_zones):
+                logger.debug("AccessibilitySkims - applying offset_mapper")
 
             skim_index = list(range(omx_shape[0]))
-            orig_map = np.isin(skim_index, skim_dict.offset_mapper.map(orig_zones))
-            dest_map = np.isin(skim_index, skim_dict.offset_mapper.map(dest_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 not dest_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)))
 
-            self.slice_map = np.ix_(orig_map, dest_map)
+            self.map_data = True
+            self.orig_map = orig_map
+            self.dest_map = dest_map
 
     def __getitem__(self, key):
         """
@@ -85,10 +84,15 @@ def __getitem__(self, key):
         if self.transpose:
             data = data.transpose()
 
-        if self.slice_map is not None:
+        if self.map_data:
+
             # slice skim to include only orig rows and dest columns
-            # 2-d boolean slicing in numpy is a bit tricky - see explanation in __init__
-            data = data[self.slice_map]
+            # 2-d boolean slicing in numpy is a bit tricky
+            # data = data[orig_map, dest_map]          # <- WRONG!
+            # data = data[orig_map, :][:, dest_map]    # <- RIGHT
+            # data = data[np.ix_(orig_map, dest_map)]  # <- ALSO RIGHT
+
+            data = data[self.orig_map, :][:, self.dest_map]
 
         return data.flatten()
 
@@ -121,19 +125,12 @@ def compute_accessibility(accessibility, skim_dict, land_use, trace_od):
     logger.info("Running %s with %d dest zones" % (trace_label, len(accessibility_df)))
 
     constants = config.get_model_constants(model_settings)
-    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]
 
-    # #bug
-    #
-    # land_use_df = land_use_df[land_use_df.index % 2 == 1]
-    # accessibility_df = accessibility_df[accessibility_df.index.isin(land_use_df.index)].head(5)
-    #
-    # print "land_use_df", land_use_df.index
-    # print "accessibility_df", accessibility_df.index
-    # #bug
-
+    # don't assume they are the same: accessibility may be sliced if we are multiprocessing
     orig_zones = accessibility_df.index.values
     dest_zones = land_use_df.index.values
 
@@ -158,7 +155,6 @@ def compute_accessibility(accessibility, skim_dict, land_use, trace_od):
         trace_od_rows = None
 
     # merge land_use_columns into od_df
-    land_use_df = land_use_df[land_use_columns]
     od_df = pd.merge(od_df, land_use_df, left_on='dest', right_index=True).sort_index()
 
     locals_d = {
@@ -175,7 +171,7 @@ def compute_accessibility(accessibility, skim_dict, land_use, trace_od):
 
     for column in results.columns:
         data = np.asanyarray(results[column])
-        data.shape = (orig_zone_count, dest_zone_count)
+        data.shape = (orig_zone_count, dest_zone_count)  # (o,d)
         accessibility_df[column] = np.log(np.sum(data, axis=1) + 1)
 
     # - write table to pipeline