Update docstrings, run in CI (#240)

* Update docstrings, run in CI * Do not necessarily assume ff14SB port is installed * Remove some references to `simtk` $ grep -r simtk . | wc -l 0 Co-authored-by: Mike Henry <[email protected]>
openmm · Oct 25, 2022 · d78f2b8 · d78f2b8
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diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml
@@ -105,6 +105,12 @@ jobs:
 
       working-directory: ./charmm
 
+    - name: Run docstrings
+      if: ${{ matrix.latest-openff-toolkit == true }}
+      continue-on-error: True
+      run: |
+        pytest --doctest-modules openmmforcefields --ignore=openmmforcefields/tests
+
     - name: Upload coverage report to CodeCov
       uses: codecov/[email protected]
       if: ${{ github.repository == 'openmm/openmmforcefields'

diff --git a/README.md b/README.md
@@ -38,7 +38,7 @@ If you're not familiar with this approach to applying parameters to biomolecular
 
 ### Using the AMBER force fields
 
-Once installed, the AMBER force fields will be registered in the `amber/` relative path searched by [`simtk.openmm.app.ForceField`](http://docs.openmm.org/latest/api-python/generated/simtk.openmm.app.forcefield.ForceField.html#simtk.openmm.app.forcefield.ForceField).
+Once installed, the AMBER force fields will be registered in the `amber/` relative path searched by [`openmm.app.ForceField`](http://docs.openmm.org/latest/api-python/generated/openmm.app.forcefield.ForceField.html#openmm.app.forcefield.ForceField).
 
 For example, to specify the newer recommended [`ff14SB`](https://pubs.acs.org/doi/abs/10.1021/acs.jctc.5b00255) force field and accompanying recommended ions and solvent models (corresponding to force fields loaded in LEaP with `leaprc.protein.ff14SB`), prepend the `amber` prefix and the `.xml` suffix:
 ```python
@@ -67,7 +67,7 @@ forcefield = ForceField('charmm/toppar_all36_prot_model.xml')
 
 ## Using AMBER GAFF 1.x and 2.x for small molecules
 
-The `openmmforcefields` package includes a [residue template generator](http://docs.openmm.org/latest/userguide/application.html#adding-residue-template-generators) for [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/simtk.openmm.app.forcefield.ForceField.html#simtk.openmm.app.forcefield.ForceField) that automatically generates OpenMM residue templates for small molecules lacking parameters using [GAFF](http://ambermd.org/antechamber/gaff.html) versions 1 or 2.
+The `openmmforcefields` package includes a [residue template generator](http://docs.openmm.org/latest/userguide/application.html#adding-residue-template-generators) for [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/openmm.app.forcefield.ForceField.html#openmm.app.forcefield.ForceField) that automatically generates OpenMM residue templates for small molecules lacking parameters using [GAFF](http://ambermd.org/antechamber/gaff.html) versions 1 or 2.
 
 ### Cheminformatics toolkits
 
@@ -78,7 +78,7 @@ The OpenEye toolkit is available [for free for academics for non-IP-generating a
 ### On-the-fly template generation for small molecules
 
 Generation of OpenMM-compatible parameters for small molecules encountered in an OpenMM `Topology` is handled through `openmmforcefields.generators.GAFFTemplateGenerator`.
-Because the [OpenMM `Topology` object](http://docs.openmm.org/latest/api-python/generated/simtk.openmm.app.topology.Topology.html#simtk.openmm.app.topology.Topology) used by [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/simtk.openmm.app.forcefield.ForceField.html#simtk.openmm.app.forcefield.ForceField) does not know the precise chemical identity of molecules represented in the topology---which contain only elements and bonds between them, without stereochemical or bond order information---it is necessary to instruct `GAFFTemplateGenerator` which small molecules it will encounter in processing the `Topology` object ahead of time; it then matches these by element and bond pattern.
+Because the [OpenMM `Topology` object](http://docs.openmm.org/latest/api-python/generated/openmm.app.topology.Topology.html#openmm.app.topology.Topology) used by [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/openmm.app.forcefield.ForceField.html#openmm.app.forcefield.ForceField) does not know the precise chemical identity of molecules represented in the topology---which contain only elements and bonds between them, without stereochemical or bond order information---it is necessary to instruct `GAFFTemplateGenerator` which small molecules it will encounter in processing the `Topology` object ahead of time; it then matches these by element and bond pattern.
 
 ### Specifying molecules
 
@@ -112,14 +112,14 @@ molecule = Molecule.from_smiles('c1ccccc1')
 from openmmforcefields.generators import GAFFTemplateGenerator
 gaff = GAFFTemplateGenerator(molecules=molecule)
 # Create an OpenMM ForceField object with AMBER ff14SB and TIP3P with compatible ions
-from simtk.openmm.app import ForceField
+from openmm.app import ForceField
 forcefield = ForceField('amber/protein.ff14SB.xml', 'amber/tip3p_standard.xml', 'amber/tip3p_HFE_multivalent.xml')
 # Register the GAFF template generator
 forcefield.registerTemplateGenerator(gaff.generator)
 # You can now parameterize an OpenMM Topology object that contains the specified molecule.
 # forcefield will load the appropriate GAFF parameters when needed, and antechamber
 # will be used to generate small molecule parameters on the fly.
-from simtk.openmm.app import PDBFile
+from openmm.app import PDBFile
 pdbfile = PDBFile('t4-lysozyme-L99A-with-benzene.pdb')
 system = forcefield.createSystem(pdbfile.topology)
 ```
@@ -152,7 +152,7 @@ Newly parameterized molecules will be written to the cache, saving time next tim
 
 ## Using the Open Force Field Initiative SMIRNOFF small molecule force fields
 
-The `openmmforcefields` package includes a [residue template generator](http://docs.openmm.org/latest/userguide/application.html#adding-residue-template-generators) for [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/simtk.openmm.app.forcefield.ForceField.html#simtk.openmm.app.forcefield.ForceField) that automatically generates OpenMM residue templates for small molecules lacking parameters using the [Open Force Field Initiative](http://openforcefield.org) [SMIRNOFF](https://open-forcefield-toolkit.readthedocs.io/en/0.6.0/smirnoff.html) small molecule force fields.
+The `openmmforcefields` package includes a [residue template generator](http://docs.openmm.org/latest/userguide/application.html#adding-residue-template-generators) for [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/openmm.app.forcefield.ForceField.html#openmm.app.forcefield.ForceField) that automatically generates OpenMM residue templates for small molecules lacking parameters using the [Open Force Field Initiative](http://openforcefield.org) [SMIRNOFF](https://open-forcefield-toolkit.readthedocs.io/en/0.6.0/smirnoff.html) small molecule force fields.
 This includes the [`openff-1.0.0` ("Parsley")](https://openforcefield.org/news/introducing-openforcefield-1.0/) small molecule force field, as well as [newer versions of this force field](https://github.com/openforcefield/openff-forcefields).
 
 The `SMIRNOFFTemplateGenerator` residue template generator operates in a manner very similar to `GAFFTemplateGenerator`, so we only highlight its differences here.
@@ -168,7 +168,7 @@ molecule = Molecule.from_smiles('c1ccccc1')
 from openmmforcefields.generators import SMIRNOFFTemplateGenerator
 smirnoff = SMIRNOFFTemplateGenerator(molecules=molecule)
 # Create an OpenMM ForceField object with AMBER ff14SB and TIP3P with compatible ions
-from simtk.openmm.app import ForceField
+from openmm.app import ForceField
 forcefield = ForceField('amber/protein.ff14SB.xml', 'amber/tip3p_standard.xml', 'amber/tip3p_HFE_multivalent.xml')
 # Register the SMIRNOFF template generator
 forcefield.registerTemplateGenerator(smirnoff.generator)
@@ -210,7 +210,7 @@ Newly parameterized molecules will be written to the cache, saving time next tim
 
 ## Using espaloma to generate small molecule force fields
 
-The `openmmforcefields` package includes a [residue template generator](http://docs.openmm.org/latest/userguide/application.html#adding-residue-template-generators) for [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/simtk.openmm.app.forcefield.ForceField.html#simtk.openmm.app.forcefield.ForceField) that can automatically generate OpenMM residue templates for small molecules lacking parameters using [espaloma](https://github.com/choderalab/espaloma) via one of its released force fields, provided `espaloma` and its dependencies are installed.
+The `openmmforcefields` package includes a [residue template generator](http://docs.openmm.org/latest/userguide/application.html#adding-residue-template-generators) for [the OpenMM `ForceField` class](http://docs.openmm.org/latest/api-python/generated/openmm.app.forcefield.ForceField.html#openmm.app.forcefield.ForceField) that can automatically generate OpenMM residue templates for small molecules lacking parameters using [espaloma](https://github.com/choderalab/espaloma) via one of its released force fields, provided `espaloma` and its dependencies are installed.
 `espaloma` uses a [graph convolutional model](https://arxiv.org/abs/2010.01196) to generate both valence parameters and fast partial charges.
 
 The `EspalomaTemplateGenerator` residue template generator operates in a manner very similar to `GAFFTemplateGenerator`, so we only highlight its differences here.
@@ -228,7 +228,7 @@ molecule = Molecule.from_smiles('c1ccccc1')
 from openmmforcefields.generators import EspalomaTemplateGenerator
 espaloma = EspalomaTemplateGenerator(molecules=molecule, forcefield='espaloma-0.2.2')
 # Create an OpenMM ForceField object with AMBER ff14SB and TIP3P with compatible ions
-from simtk.openmm.app import ForceField
+from openmm.app import ForceField
 forcefield = ForceField('amber/protein.ff14SB.xml', 'amber/tip3p_standard.xml', 'amber/tip3p_HFE_multivalent.xml')
 # Register the SMIRNOFF template generator
 forcefield.registerTemplateGenerator(espaloma.generator)
@@ -264,8 +264,8 @@ The `openmmforcefields` package provides the `openmmforcefields.generators.Syste
 Here's an example that uses GAFF 2.11 along with the new `ff14SB` generation of AMBER force fields (and compatible solvent models) to generate an OpenMM `System` object from an [Open Force Field `Topology`](https://open-forcefield-toolkit.readthedocs.io/en/latest/api/generated/openff.toolkit.topology.Topology.html#openff.toolkit.topology.Topology) object:
 ```python
 # Define the keyword arguments to feed to ForceField
-from simtk import unit
-from simtk.openmm import app
+from openmm import unit
+from openmm import app
 forcefield_kwargs = { 'constraints' : app.HBonds, 'rigidWater' : True, 'removeCMMotion' : False, 'hydrogenMass' : 4*unit.amu }
 # Initialize a SystemGenerator using GAFF
 from openmmforcefields.generators import SystemGenerator
@@ -282,7 +282,7 @@ Parameters for multiple force fields can be held in the same cache file.
 By default, `SystemGenerator` will use `PME` for periodic systems and `NoCutoff` for non-periodic systems.
 You can modify this behavior with the optional `periodic_forcefield_kwargs` and `nonperiodic_forcefield_kwargs` arguments, which are used to update `forcefield_kwargs` depending on whether the system is periodic or non-periodic:
 ```python
-from simtk.openmm import app
+from openmm import app
 system_generator = SystemGenerator(forcefields=['amber/ff14SB.xml', 'amber/tip3p_standard.xml'],
     periodic_forcefield_kwargs={'nonbondedMethod' : app.LJPME},
     nonperiodic_forcefield_kwargs={'nonbondedMethod' : app.CutoffNonPeriodic})

diff --git a/charmm/energy.py b/charmm/energy.py
@@ -2,8 +2,9 @@
 from __future__ import print_function
 import sys
 import parmed as pmd
-from simtk import openmm as mm, unit as u
-from simtk.openmm import app
+import openmm as mm
+from openmm import unit as u
+from openmm import app
 import numpy as np
 import time
 import os, re

diff --git a/charmm/test_charmm.py b/charmm/test_charmm.py
@@ -5,9 +5,9 @@
 from collections import OrderedDict
 import hashlib
 import os
-import simtk.openmm.app as app
-import simtk.openmm as mm
-import simtk.unit as u
+import openmm.app as app
+import openmm as mm
+import openmm.unit as u
 import argparse
 import csv
 import logging
@@ -100,7 +100,7 @@ def write_serialized_system(filename, system):
     ----------
     filename : str
         The name of the file to be written
-    system : simtk.openmm.System
+    system : openmm.System
         The System object to be written
 
     """
@@ -129,7 +129,7 @@ def read_box_vectors(filename):
 
     Returns
     -------
-    box_vectors : simtk.unit.Quantity with shape [3,3] and units of Angstroms
+    box_vectors : openmm.unit.Quantity with shape [3,3] and units of Angstroms
         Box vectors
     """
     with open(filename, 'r') as infile:
@@ -162,14 +162,14 @@ def compute_potential(system, positions):
 
     Parameters
     ----------
-    system : simtk.openmm.System
+    system : openmm.System
         System
-    positions : simtk.unit.Quantity of shape [nparticles,3] with units compatible with angstroms
+    positions : openmm.unit.Quantity of shape [nparticles,3] with units compatible with angstroms
         Positions
 
     Returns
     -------
-    potential : simtk.unit.Quantity with units of kJ/mol
+    potential : openmm.unit.Quantity with units of kJ/mol
         The potential energy
 
     """
@@ -202,7 +202,7 @@ def compare_energies(system_name, pdb_filename, psf_filename, ffxml_filenames, t
         Keyword arguments to pass to CharmmPsfFile.createSystem() and ForceField.CreateSystem() when constructing System objects for energy comparison
     tolerance : float, optional, default=1e-5
         Relative energy discrepancy tolerance
-    units : simtk.unit.Unit
+    units : openmm.unit.Unit
         Unit to use for energy comparison
     write_serialized_xml : bool, optional, default=False
         If True, will write out serialized System XML files for OpenMM systems to aid debugging.

diff --git a/openmmforcefields/generators/system_generators.py b/openmmforcefields/generators/system_generators.py
@@ -126,17 +126,22 @@ def __init__(self, forcefields=None, small_molecule_forcefield='openff-1.0.0', f
         If the ``cache`` argument is specified, parameterized molecules are cached in the corresponding file.
 
         >>> cache = 'db.json'
-        >>> system_generator = SystemGenerator(forcefields=forcefields, small_molecule_forcefield='gaff-2.11', forcefield_kwargs=forcefield_kwargs, cache=cache)
+        >>> system_generator = SystemGenerator(forcefields=amber_forcefields, small_molecule_forcefield='gaff-2.11', forcefield_kwargs=forcefield_kwargs, cache=cache)  # doctest: +SKIP
 
         To use a barostat, you need to define a barostat whose parameters will be copied into each system (with a different random number seed):
 
+        >>> import openmm
+        >>> from openmm import unit
         >>> pressure = 1.0 * unit.atmospheres
         >>> temperature = 298.0 * unit.kelvin
         >>> frequency = 25 # steps
         >>> system_generator.barostat = openmm.MonteCarloBarostat(pressure, temperature, frequency)
 
         Now, you can create an OpenMM ``System`` object from an OpenMM ``Topology`` object and a list of OpenFF ``Molecule`` objects
 
+        >>> from openff.toolkit import Molecule, Topology
+        >>> molecules = [Molecule.from_smiles(smiles) for smiles in ["CCO", "c1ccccc1"]]
+        >>> openmm_topology = Topology.from_molecules(molecules).to_openmm()
         >>> system = system_generator.create_system(openmm_topology, molecules=molecules)
 
         Parameters for multiple force fields can be held in the same cache file.
@@ -145,7 +150,7 @@ def __init__(self, forcefields=None, small_molecule_forcefield='openff-1.0.0', f
         simply change the ``small_molecule_forcefield`` parameter to one of the supported ``GAFFTemplateGenerator.INSTALLED_FORCEFIELDS``:
 
         >>> small_molecule_forcefield = 'openff-1.0.0'
-        >>> system_generator = SystemGenerator(forcefields=forcefields, small_molecule_forcefield=small_molecule_forcefield, forcefield_kwargs=forcefield_kwargs)
+        >>> system_generator = SystemGenerator(forcefields=amber_forcefields, small_molecule_forcefield=small_molecule_forcefield, forcefield_kwargs=forcefield_kwargs)
 
         For debugging convenience, you can also turn _off_ specific interactions during system creation, such as particle charges: