Fixes for new openmmtools 0.23.0 (#1203)

* change default to none

* Changing default in template yaml file

* Test null/none atom selection

* null atom selection should be empty list

* Document how to control the log level in the CLI

* Update examples/new-cli/README.md

Co-authored-by: Iván Pulido <2949729+ijpulidos@users.noreply.github.com>

* Add solvent_model kwarg to RelativeFEPSetup

* Specify solvent model input YAML/CLI

* Test openmmtools_dev

* Update CI.yaml

* Update CI.yaml

* make sure we pull in openmmtools

* forgot to add new env file

* Online analysis multiple of checkpoint interval. Fix tests.

* Using dask import inside functions

* dask import inside functions

* Pinning dask version

* set CI to just pull from normal channels since we pushed update

* Drop 3.8 testing

* Testing with ambertools < 23

* Revert "Merge branch '1192-add-solvent-model-cli' into mikemhenry-patch-3"

This reverts commit cd0e440, reversing
changes made to 1a7f712.

* Revert "Merge remote-tracking branch 'origin/mikemhenry-patch-2' into mikemhenry-patch-3"

This reverts commit 1a7f712, reversing
changes made to 1505004.

* Revert "Merge branch 'feat/set_default_to_none_for_atom_selection' into mikemhenry-patch-3"

This reverts commit 1505004, reversing
changes made to 0474f9a.

---------

Co-authored-by: Iván Pulido <2949729+ijpulidos@users.noreply.github.com>

.github/workflows/CI.yaml

@@ -23,7 +23,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.8, 3.9, "3.10"]
+        python-version: [3.9, "3.10"]
         openmm: ["8.0", "7.7"]
         include:
           - openmm: "dev"
@@ -49,12 +49,13 @@ jobs:
         with:
           environment-file: devtools/conda-envs/test_env.yaml
           environment-name: test
-          channels: jaimergp/label/unsupported-cudatoolkit-shim,conda-forge/label/openmm_dev/linux-64,conda-forge,openeye
+          channels: jaimergp/label/unsupported-cudatoolkit-shim,conda-forge/label/openmm_dev,conda-forge,openeye
           channel-priority: flexible
           cache-env: true
           cache-downloads: true
           extra-specs: |
             python==${{ matrix.python-version }}
+            openmmtools==0.23.0
             openmm==8.0.0dev3
 
       - name: Setup micromamba
@@ -68,6 +69,7 @@ jobs:
           extra-specs: |
             python==${{ matrix.python-version }}
             openmm==${{ matrix.openmm }}
+            openmmtools==0.23.0
 
       - name: Install package
         shell: bash -l {0}
@@ -103,4 +105,4 @@ jobs:
         uses: codecov/codecov-action@v1
         with:
           file: ./coverage.xml
-          fail_ci_if_error: true
+          fail_ci_if_error: true

devtools/conda-envs/test_env.yaml

@@ -3,12 +3,13 @@ channels:
   - conda-forge
   - openeye
 dependencies:
+  - ambertools <23
   - arsenic
   - autograd
   - click
   - cloudpathlib-s3 >=0.13.0
   - coverage
-  - dask
+  - dask <2023.5
   - dask-jobqueue
   - dicttoxml
   - distributed
@@ -27,7 +28,7 @@ dependencies:
   - openff-units >=0.1.8
   - openmm >=7.7
   - openmmforcefields >=0.9.0
-  - openmmtools >=0.21.5 # may need to sort out ambermini/ambertools/parmed dependencies
+  - openmmtools # may need to sort out ambermini/ambertools/parmed dependencies
   - openmoltools # may need to sort out ambermini/ambertools/parmed dependencies (we don't want ambertools)
   - parmed # may need to sort out ambermini/ambertools/parmed dependencies
   - pdbfixer

perses/app/relative_setup.py

@@ -21,8 +21,6 @@
 from openmmtools.constants import kB
 import logging
 import os
-import dask.distributed as distributed
-from collections import namedtuple
 from collections import namedtuple
 import random
 from scipy.special import logsumexp
@@ -971,6 +969,7 @@ def activate_client(self,
                         LSF = True,
                         num_processes = 2,
                         adapt = False):
+        import dask.distributed as distributed
 
         if LSF:
             from dask_jobqueue import LSFCluster
@@ -1056,6 +1055,7 @@ def wait(self, futures):
         """
         wrapper to wait until futures are complete.
         """
+        import dask.distributed as distributed
         if self.client is None:
             pass
         else:

perses/dispersed/parallel.py

@@ -1,6 +1,6 @@
 import logging
 import time
-import dask.distributed as distributed
+
 
 # Instantiate logger
 _logger = logging.getLogger("parallelism")
@@ -35,6 +35,7 @@ def activate_client(self,
         timeout : int
             number of seconds to wait to fulfill the workers order
         """
+        import dask.distributed as distributed
         self.library = library
         if library is not None:
             _logger.debug(f"library is not None")
@@ -231,6 +232,7 @@ def gather_actor_result(self, future):
         future : <generalized> future
             the future object to be collected from an actor
         """
+        import dask.distributed as distributed
         if self.client is None:
             return future
         else:
@@ -254,6 +256,7 @@ class to put on a worker
         -------
         actor : dask.distributed.Actor pointer (future)
         """
+        import dask.distributed as distributed
         if self.client is not None:
             if self.library[0] == 'dask':
                 future = self.client.submit(_class, workers = [self.workers[self.worker_counter]], actor=True)  # Create a _class on a worker
@@ -275,6 +278,7 @@ def progress(self, futures):
         futures : list of <generalized> futures
             futures that are to be gathered
         """
+        import dask.distributed as distributed
         if self.client is None:
             pass
         else:
@@ -293,6 +297,7 @@ def wait(self, futures):
         futures : list of <generalized> futures
             futures that are to be gathered
         """
+        import dask.distributed as distributed
         if self.client is None:
             pass
         else:

perses/dispersed/utils.py

@@ -17,7 +17,6 @@
 import time
 from collections import namedtuple
 from perses.annihilation.lambda_protocol import LambdaProtocol
-import dask.distributed as distributed
 from scipy.special import logsumexp
 import openmmtools.cache as cache
 
@@ -1117,6 +1116,7 @@ def activate_LocallyOptimalAnnealing(thermodynamic_state,
     """
     Function to set worker attributes for annealing.
     """
+    import dask.distributed as distributed
     supported_integrators = ['langevin', 'hmc']
 
     if remote_worker == 'remote':
@@ -1142,6 +1142,7 @@ def deactivate_worker_attributes(remote_worker):
     """
     Function to remove worker attributes for annealing
     """
+    import dask.distributed as distributed
     if remote_worker == 'remote':
         _logger.debug(f"\t\tremote_worker is True, getting worker")
         _class = distributed.get_worker()
@@ -1168,6 +1169,7 @@ def call_anneal_method(remote_worker,
     since we can only map functions with parallelisms (no actors), we need to submit a function that calls
     the LocallyOptimalAnnealing.anneal method.
     """
+    import dask.distributed as distributed
     if remote_worker == 'remote':
         _class = distributed.get_worker()
     else:

perses/tests/test_cli.py

@@ -28,6 +28,7 @@
 n_steps_per_move_application: 1
 fe_type: repex
 checkpoint_interval: 50
+offline-freq: 50
 n_cycles: 1
 n_states: 3
 n_equilibration_iterations: 0