Merge remote-tracking branch 'upstream/main' into estimation_enhancem…

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RSGInc · Dec 14, 2024 · a5e137b · a5e137b
2 parents aa874f6 + 171f172
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diff --git a/activitysim/abm/models/util/logsums.py b/activitysim/abm/models/util/logsums.py
@@ -167,7 +167,10 @@ def compute_location_choice_logsums(
     )
 
     nest_spec = config.get_logit_model_settings(logsum_settings)
-    nest_spec = simulate.eval_nest_coefficients(nest_spec, coefficients, trace_label)
+    if nest_spec is not None:  # nest_spec is None for MNL
+        nest_spec = simulate.eval_nest_coefficients(
+            nest_spec, coefficients, trace_label
+        )
 
     locals_dict = {}
     # model_constants can appear in expressions

diff --git a/docs/users-guide/example_performance.md b/docs/users-guide/example_performance.md
@@ -219,7 +219,7 @@ See more complete results and discussion
 | write tables                          | 8.1     | 7.9     | 7.8      | 7.7      | 7.3      | 7.5      |
 | Total Runtime                         | 309.5   | 211.4   | 186.2    | 182.4    | 177.3    | 180      |
 
-### Single Process, Sharrow Disabled
+### Multiprocessing, Sharrow Disabled
 
 The following performance metrics were collected for the SANDAG example model,
 running on a Windows server with 24 cores and 500GB of RAM (same as the results above),

diff --git a/docs/users-guide/modelsetup.rst b/docs/users-guide/modelsetup.rst
@@ -156,15 +156,15 @@ This method is recommended for ActivitySim users who also wish to customize the
 2. Create a conda environment (basically a Python install just for this project)
 using mambaforge prompt or conda prompt depending on the package manager you use (on Windows) or the terminal (macOS or Linux)::
 
-  mamba create -n asim python=3.9 activitysim -c conda-forge --override-channels
+  mamba create -n asim python=3.10 activitysim -c conda-forge --override-channels
 
 This command will create the environment and install all the dependencies
 required for running ActivitySim.  It is only necessary to create the environment
 once per machine, you do not need to (re)create the environment for each session.
 If you would also like to install other tools or optional dependencies, it is
 possible to do so by adding additional libraries to this command.  For example::
 
-  mamba create -n asim python=3.9 activitysim jupyterlab larch -c conda-forge --override-channels
+  mamba create -n asim python=3.10 activitysim jupyterlab larch -c conda-forge --override-channels
 
 This example installs a specific version of Python, version 3.9.  A similar
 approach can be used to install specific versions of other libraries as well,