Merge pull request #38 from calpolyccg/cli

Create CLI

Author: ALescoulie

.gitignore

@@ -1,4 +1,6 @@
 # generated files
+psi.*.clean
+out.csv
 /timer.dat
 /resid_fixed.pdb
 /resid.pdb
@@ -111,3 +113,7 @@ ENV/
 # profraw files from LLVM? Unclear exactly what triggers this
 # There are reports this comes from LLVM profiling, but also Xcode 9.
 *profraw
+
+# MDSAPT-generated files
+timer.dat
+input.yaml

docs/index.rst

@@ -24,4 +24,3 @@ For the poster we presented at ACS Spring 2022, `click here <./_static/mdsapt_po
    optimizer
    reader
    viewer
-   scripts

docs/install.rst

@@ -1,16 +1,35 @@
 Installation
 ============
 
-MD-SAPT can be installed by cloning the GitHub repository.
+MD-SAPT can be installed from the psi4 Conda repo like so:
+
+.. code-block:: bash
+
+    conda install -c psi4/label/dev -c conda-forge mdsapt
+
+Alternatively, it can be installed by cloning the GitHub repository.
 
 .. code-block:: bash
 
     git clone https://github.com/calpolyccg/MDSAPT.git
     pip install ./MDSAPT
 
-MD-SAPT can also be installed from conda.
+To ensure it's been installed correctly, run `mdsapt` or `python3 -m mdsapt`.
 
-.. code-block:: bash
+.. code-block::
+    Warning: importing 'simtk.openmm' is deprecated.  Import 'openmm' instead.
+    2022-03-30 09:32:50,071 mdsapt       INFO     MDSAPT 1.2.0 starting
+    2022-03-30 09:32:50,071 mdsapt       INFO     Copyright (c) 2021 Alia Lescoulie, Astrid Yu, and Ashley Ringer McDonald
+    2022-03-30 09:32:50,071 mdsapt       INFO     Released under GPLv3 License
+    Usage: python -m mdsapt [OPTIONS] COMMAND [ARGS]...
+
+      MDSAPT - Molecular Dynamics Symmetry-Adapted Perturbation Theory
+
+      This command-line interface lets you easily do common MDSAPT-related tasks.
 
-    conda install -c psi4 MDSAPT
+    Options:
+      --help  Show this message and exit.
 
+    Commands:
+      generate  Generate a template input file at filename.
+      run       Run a SAPT calculation using the configuration in in_file.

docs/quick.rst

@@ -1,21 +1,25 @@
 Quickstart Guide
 ================
 
-MD-SAPT simplifies for the calculation of SAPT interaction energies from MD
-trajectories. Running it just requires MD simulation files.
+MD-SAPT simplifies the calculation of SAPT interaction energies between selected residue pairs in MD trajectories. Running it just requires MD simulation files.
 
-Basic work flow
-===============
+Prerequisites
+_____________
 
-MD-SAPT can be run as a script or in a notebook. It gives the SAPT energy
-between the specified residue pairs.
+Ensure that you have the following things set up:
 
-Setup Process
-_____________
+ - You have existing MD trajectory and topology files in any form that `MDAnalysis <https://mdanalysis.readthedocs.io/en/latest/`_ supports
+ - You have already installed MDSAPT, following the :installation guide:`install`
+
+.. note:
+    If your `PATH` environment variable is not set up to point to installed Python modules, then invoking `mdsapt` directly, as shown in this guide, may not work. In that case, try running `python3 -m mdsapt` instead.
 
-The following steps describe how to set up the input yaml file
+Generating an input file
+________________________
 
- 1. Use the `mdsapt_get_runinput.py` script to generate a blank input file
+The following steps describe how to set up the input YAML file.
+
+ 1. Run `mdsapt generate [filename]` to generate a blank Trajectory SAPT input file at the given filename. Don't worry, it will not overwrite any files unless you explicitly provide the `-f` flag.
 
  2. Specify the MD file locations in the input file
 
@@ -25,21 +29,80 @@ The following steps describe how to set up the input yaml file
 
  5. Specify trajectory, optimization, and SAPT settings
 
+Here is an example of a filled-out YAML file:
+
+.. code-block:: yaml
+    topology_path: 'testtop.psf'
+    trajectory_paths:
+      - 'testtraj.dcd'
+    selection_resid_num:
+      - 11
+      - 199
+    int_pairs:
+      # Place pair of  selections defined above in a list of lists
+      - [11, 199]
+    trajectory_settings:
+      start: 0
+      stop: 98
+      step: 1
+    system_settings:
+      ncpus: '12'
+      memory: '12GB'
+      time: '24:00:00'
+    opt_settings:
+      pH: 7
+    sapt_settings:
+      method: 'sapt0'
+      basis: 'jun-cc-pvdz'
+      settings:
+        reference: 'rhf'
+      save_psi4_output: true
+
 Running SAPT
 ____________
 
-With the input done MD-SAPT is ready to be run. The settings are read using :class:`mdsapt.reader.InputReader`  which is then passed into :class:`mdsapt.reader.Optimizer` which handles preparing residues. Finally :class:`mdsapt.reader.TrajectorySAPT` is used to run SAPT over the MD data. The results are stored in a :class:`Pandas.DataFrame`.
+Using the `mdsapt` CLI
+^^^^^^^^^^^^^^^^^^^^^^
+
+This mode is suited for:
+
+ - running on an HPC cluster
+ - running a simple input file
+
+With the input done MD-SAPT is ready to be run. Simply execute
+
+.. code-block:: bash
+   mdsapt run [filename] [output]
+
+and it will run SAPT on your trajectory using the parameters specified in your input file.
+
+Using the `mdsapt` Python library
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+This mode is suited for:
+
+ - using MD-SAPT in a notebook
+ - using MD-SAPT in your own library or applications
+
+The classes involved are as follows:
+
+ - The settings are read using :class:`mdsapt.reader.InputReader`
+ - The `InputReader` is then passed into :class:`mdsapt.reader.Optimizer` which handles preparing residues.
+ - Finally, :class:`mdsapt.reader.TrajectorySAPT` is used to run SAPT over the MD data.
+ - The results are stored in a :class:`Pandas.DataFrame` which can be accessed under the `TrajectorySAPT.results` property.
+
+Here is some code demonstrating it:
 
 .. code-block:: Python
 
     import mdsapt
 
-    Settings = mdsapt.InputReader('runinput.yaml')
 
+    Settings = mdsapt.InputReader('runinput.yaml')
     Opt = mdsapt.Optimizer(Settings)
-
     SAPT_run = mdsapt.TrajectorySAPT(Settings, Opt)
-
     SAPT_run.run(Settings.start, Settings.stop, Settings.step)
+    SAPT_run.results.to_csv('results.csv')
+
+See also `the Binder demo <https://mybinder.org/v2/gh/calpolyccg/MDSAPT_demo/master?labpath=MD-SAPT_demo.ipynb>`_ for a bigger example.
 
-    SAPT_run.results.to_csv('results.csv')

docs/scripts.rst

@@ -10,6 +10,7 @@ dependencies:
   - psi4>=1.6.1,<1.7
 
   - mdanalysis>=2.2.0,<2.3
+  - click
   - numpy
   - openmm
   - pandas

environment.yml

@@ -8,6 +8,8 @@
 from .config import Config, load_from_yaml_file
 from .sapt import TrajectorySAPT, DockingSAPT
 
+from .cli import cli
+
 # Handle versioneer
 from ._version import get_versions
 versions = get_versions()

mdsapt/__init__.py

@@ -0,0 +1,12 @@
+#!/usr/bin/env python3
+"""
+Main entrypoint for the CLI.
+"""
+
+# Note that we import directly from the CLI instead of the full package. This is an optimization
+# since some CLI tasks do not need the entire package.
+from .cli import cli
+
+
+if __name__ == '__main__':
+    cli()

mdsapt/__main__.py

@@ -0,0 +1,109 @@
+import logging
+import os
+import sys
+
+import click
+from mdsapt.config import RangeFrameSelection
+
+# Note that we do not import MDSAPT. This is a speed optimization; it is imported later.
+
+
+logger = logging.getLogger(__name__)
+
+_dir_path = os.path.dirname(os.path.realpath(__file__))
+"""Location of the mdsapt package to be used in resolving templates."""
+
+
+@click.group()
+def cli():
+    """
+    MDSAPT - Molecular Dynamics Symmetry-Adapted Perturbation Theory, by Alia Lescoulie, Astrid Yu, and Ashley Ringer McDonald.
+
+    This command-line interface lets you easily do common MDSAPT-related tasks.
+    """
+
+
+@cli.command()
+@click.argument(
+    'filename',
+    default='input.yaml',
+)
+@click.option(
+    '-t', '--template', 'template',
+    help="Template to generate from. By default, trajectory.",
+    type=click.Choice(['trajectory', 'docking'], case_sensitive=False),
+    default='trajectory',
+)
+@click.option(
+    '-f', '--force',
+    help="If provided, overwrites existing files.",
+    is_flag=True,
+)
+def generate(filename: str, template: str, force: bool):
+    """
+    Generate a template input file at filename.
+    """
+    ensure_safe_to_overwrite(filename, force)
+
+    # TODO: make a wizard for these templates
+    template_path = os.path.join(_dir_path, 'data', f'{template}_template.yaml')
+
+    with open(template_path, 'r') as template:
+        template_data = template.read()
+    with open(filename, 'w') as new_file:
+        new_file.write(template_data)
+
+    logger.info(f'Generated template input file {filename}')
+
+
+@cli.command()
+@click.argument(
+    'in_file',
+    default='input.yaml',
+)
+@click.argument(
+    'out_file',
+    default='out.csv',
+)
+@click.option(
+    '-f', '--force',
+    help="If provided, overwrites existing files.",
+    is_flag=True,
+)
+def run(in_file: str, out_file: str, force: bool):
+    """
+    Run a SAPT calculation using the configuration in in_file. Outputs will be written to
+    out_file.
+    """
+    import mdsapt
+
+    ensure_safe_to_overwrite(out_file, force)
+
+    config = mdsapt.load_from_yaml_file(in_file)
+    if isinstance(config.analysis, mdsapt.config.TrajectoryAnalysisConfig):
+        sapt = mdsapt.TrajectorySAPT(config)
+        frames = config.analysis.frames
+        sapt.run(frames.start, frames.stop, frames.step)
+    elif isinstance(config.analysis, mdsapt.config.DockingAnalysisConfig):
+        sapt = mdsapt.DockingSAPT(config)
+        sapt.run()
+
+    logger.info('saving results to CSV')
+    sapt.results.to_csv(out_file)
+
+
+def ensure_safe_to_overwrite(path: str, force: bool):
+    """
+    Helper function to ensure that it's safe to overwrite the given file, and
+    halts the program if not.
+    """
+    if not os.path.exists(path):
+        return
+
+    if force:
+        logger.warning("will overwrite existing CSV %s", path)
+        return
+
+    logger.error("Halting, file already exists: %s", path)
+    logger.error("If you want to overwrite that file, add the -f flag")
+    sys.exit(-1)