Interactively stepping through KIMMDY

Setup

Code

from kimmdy.config import Config
from kimmdy.runmanager import RunManager, State
from kimmdy.plugins import reaction_plugins, discover_plugins, parameterization_plugins
from kimmdy.analysis import concat_traj, plot_rates
from kimmdy.tasks import TaskFiles
from kimmdy_hydrolysis.reaction import HydrolysisReaction

discover_plugins()

Note, that In order for kimmdy in our python session to know about the plugins we have installed, we need to discover them (see above).

Check that your plugin is registered with kimmdy:

Code

reaction_plugins

{'hat_reaction': HATreaction.reaction.HAT_reaction,
 'dummyreaction': dummyreaction.reaction.DummyReaction,
 'hat_naive': hat_naive.reaction.NaiveHAT,
 'homolysis': homolysis.reaction.Homolysis,
 'hydrolysis': kimmdy_hydrolysis.reaction.HydrolysisReaction,
 'specbond': specbond.reaction.SpecBond}

Code

parameterization_plugins

{'grappa': kimmdy_grappa.grappa_interface.GrappaInterface}

Full kimmdy run with hydrolysis

Create a configuration object from python:

Code

config = Config(
  opts={
    "name": "run",
    "cwd": "./examples/triplehelix-hydrolysis/",
    "sequence": ["pull-short", "reactions", "pull", "reactions", "pull"],
    "reactions": {
      "hydrolysis_naive": {
        "arrhenius_equation": {
          "frequency_factor": 0.288,
          "temperature": 300
        }
      },
      "homolysis": {
        "arrhenius_equation": {
          "frequency_factor": 0.288,
          "temperature": 300
        },
        "edis": "assets/edissoc.dat",
        "itp": "assets/ffbonded.itp"
      }
    },
    "plumed": "assets/plumed.dat",
    "mds": {
      "pull-short": {
        "mdp": "pull-short.mdp",
      },
      "pull": {
        "mdp": "pull.mdp",
      },
      "relax": {
        "mdp": "relax.mdp",
      },
    },
    "topology": {
      "reactive": {"include": "SOL"},
    },
    "parameterize_at_setup": False,
    "changer": {
      "topology": {
        "parameterization": "grappa",
      },
      "coordinates": {
        "md": "relax",
        "slow_growth": True,
      },
    },
    "kmc": "rfkmc",
    "top": "triple.top",
    "gro": "triple-eq.gro",
    "ndx": "index.ndx",
    # by supplying already pre-caculated trajectories, we can skip the md part
    # for testing purposes
    "tpr": "pull.tpr",
    "xtc": "pull.xtc",
    "trr": "pull.trr"
  }
)

Explore

Code

run = RunManager(config=config)

Explore Hydrolysis

Code

hyd = HydrolysisReaction('hydrolysis_naive', run)

Code

files = TaskFiles(run.get_latest)

Code

result = hyd.get_recipe_collection(files)

Code

result.recipes[0]

We can check again what tasks are currently planned:

Code

run.tasks.queue

We could run all the tasks

Code

while run.state != State.DONE:
    next(run)

Or instead step thorugh one by one.

Note, that tasks can also add intermediate tasks to a queue that will be cleared before the next task in the tasks queue is executed. Right now it is empty:

Code

run.priority_tasks.queue

Calling the next function on the RunManager instance will execute the next task in the queue. Let’s do this three times:

Code

for i in range(2):
    next(run)

The place_reaction_tasks task should now have filled the priority_tasks queue:

Code

run.priority_tasks.queue

Because of this, the next task will be query_rection (one tasks per reaction, but in this case we only have one reaction):

Code

next(run)

priority_tasks is now empty:

Code

run.priority_tasks.queue

So the next task will decide on a Recipe based on the results it got from the reaction plugins:

Code

run.tasks.queue

Code

run.recipe_collection.recipes[:3]

Code

next(run)

Our Kinetic Monte Carlo (KMC) result is now available:

Code

run.kmcresult

So the next task will execute the chosen reaction’s recipe.

Code

next(run)

Just the reaction

Code

opts_for_just_reaction = {
    "name": "run",
    "cwd": "./examples/settles/",
    "sequence": ["reactions"],
    "reactions": {
        "hydrolysis_naive": {
            "rates_per_frame": True,
            "manual_residuetypes": False,
            "relax": False,
        }
    },
    "mds": {
        "relax": {
            "mdp": "relax.mdp",
        },
    },
    "topology": {
        "reactive": {"include": "SOL"},
    },
    "parameterize_at_setup": False,
    "changer": {
        "topology": {
            "parameterization": "grappa",
        },
        "coordinates": {
            "md": "relax",
            "slow_growth": True,
        },
    },
    "kmc": "rfkmc",
    "top": "triple.top",
    "gro": "triple-eq.gro",
    "ndx": "index.ndx",
    "tpr": "pull.tpr",
    "xtc": "pull.xtc",
    "trr": "pull.trr"
}
config = Config(opts=opts_for_just_reaction)
run = RunManager(config=config)
run.run()

Archiv

Code

opts_for_just_reaction = {
    "name": "run",
    "cwd": "./examples/triplehelix-hydrolysis/",
    "sequence": ["reactions"],
    "reactions": {
        "hydrolysis_naive": {
        }
    },
    "mds": {
        "relax": {
            "mdp": "pull-slow-growth.mdp",
        },
    },
    "topology": {
        "reactive": {"include": "SOL"},
    },
    "parameterize_at_setup": False,
    "changer": {
        "topology": {
            "parameterization": "grappa",
        },
        "coordinates": {
            "md": "relax",
            "slow_growth": True,
        },
    },
    "kmc": "rfkmc",
    "top": "triple.top",
    "gro": "triple-eq.gro",
    "ndx": "index.ndx",
    "tpr": "pull.tpr",
    "xtc": "pull.xtc",
    "trr": "pull.trr"
}

Code

run2 = RunManager(config=Config(opts=opts_for_just_reaction))

Code

for i in range(3):
    next(run2)

Code

next(run2)

Code

run2.recipe_collection

Code

run2.tasks.queue

Code

run2.kmcresult

Code

next(run2)

Code

while run2.state != State.DONE:
    next(run2)

kimmdy.3_apply_recipe INFO: Recipe: 642⚡644 131300⚡131301 131300⚡131302 131300➡642 131301➡644 131302➡64

Code

concat_traj(
  dir = "./examples/triplehelix-hydrolysis/run_010/",
  filetype="xtc",
  steps="all",
  output_group="System",
  open_vmd=True
)

Code

plot_rates(
  dir = "./examples/triplehelix-hydrolysis/run_022/",
)

--- title: Interactively stepping through KIMMDY execute: eval: false --- # Setup ```{python} #| eval: true from kimmdy.config import Config from kimmdy.runmanager import RunManager, State from kimmdy.plugins import reaction_plugins, discover_plugins, parameterization_plugins from kimmdy.analysis import concat_traj, plot_rates from kimmdy.tasks import TaskFiles from kimmdy_hydrolysis.reaction import HydrolysisReaction discover_plugins() ``` Note, that In order for kimmdy in our python session to know about the plugins we have installed, we need to discover them (see above). Check that your plugin is registered with kimmdy: ```{python} #| eval: true reaction_plugins ``` ```{python} #| eval: true parameterization_plugins ``` # Full kimmdy run with hydrolysis Create a configuration object from python: ```{python} config = Config( opts={ "name": "run", "cwd": "./examples/triplehelix-hydrolysis/", "sequence": ["pull-short", "reactions", "pull", "reactions", "pull"], "reactions": { "hydrolysis_naive": { "arrhenius_equation": { "frequency_factor": 0.288, "temperature": 300 } }, "homolysis": { "arrhenius_equation": { "frequency_factor": 0.288, "temperature": 300 }, "edis": "assets/edissoc.dat", "itp": "assets/ffbonded.itp" } }, "plumed": "assets/plumed.dat", "mds": { "pull-short": { "mdp": "pull-short.mdp", }, "pull": { "mdp": "pull.mdp", }, "relax": { "mdp": "relax.mdp", }, }, "topology": { "reactive": {"include": "SOL"}, }, "parameterize_at_setup": False, "changer": { "topology": { "parameterization": "grappa", }, "coordinates": { "md": "relax", "slow_growth": True, }, }, "kmc": "rfkmc", "top": "triple.top", "gro": "triple-eq.gro", "ndx": "index.ndx", # by supplying already pre-caculated trajectories, we can skip the md part # for testing purposes "tpr": "pull.tpr", "xtc": "pull.xtc", "trr": "pull.trr" } ) ``` ## Explore ```{python} run = RunManager(config=config) ``` ### Explore Hydrolysis ```{python} hyd = HydrolysisReaction('hydrolysis_naive', run) ``` ```{python} files = TaskFiles(run.get_latest) ``` ```{python} result = hyd.get_recipe_collection(files) ``` ```{python} result.recipes[0] ``` We can check again what tasks are currently planned: ```{python} run.tasks.queue ``` We could run all the tasks ```{python} # | eval: false while run.state != State.DONE: next(run) ``` Or instead step thorugh one by one. Note, that tasks can also add intermediate tasks to a queue that will be cleared before the next task in the `tasks` queue is executed. Right now it is empty: ```{python} run.priority_tasks.queue ``` Calling the `next` function on the `RunManager` instance will execute the next task in the queue. Let's do this three times: ```{python} for i in range(2): next(run) ``` The `place_reaction_tasks` task should now have filled the `priority_tasks` queue: ```{python} run.priority_tasks.queue ``` Because of this, the next task will be `query_rection` (one tasks per reaction, but in this case we only have one reaction): ```{python} next(run) ``` `priority_tasks` is now empty: ```{python} run.priority_tasks.queue ``` So the next task will decide on a `Recipe` based on the results it got from the reaction plugins: ```{python} run.tasks.queue ``` ```{python} run.recipe_collection.recipes[:3] ``` ```{python} next(run) ``` Our Kinetic Monte Carlo (KMC) result is now available: ```{python} run.kmcresult ``` So the next task will execute the chosen reaction's recipe. ```{python} next(run) ``` ## Just the reaction ```{python} opts_for_just_reaction = { "name": "run", "cwd": "./examples/settles/", "sequence": ["reactions"], "reactions": { "hydrolysis_naive": { "rates_per_frame": True, "manual_residuetypes": False, "relax": False, } }, "mds": { "relax": { "mdp": "relax.mdp", }, }, "topology": { "reactive": {"include": "SOL"}, }, "parameterize_at_setup": False, "changer": { "topology": { "parameterization": "grappa", }, "coordinates": { "md": "relax", "slow_growth": True, }, }, "kmc": "rfkmc", "top": "triple.top", "gro": "triple-eq.gro", "ndx": "index.ndx", "tpr": "pull.tpr", "xtc": "pull.xtc", "trr": "pull.trr" } config = Config(opts=opts_for_just_reaction) run = RunManager(config=config) run.run() ``` # Archiv ```{python} opts_for_just_reaction = { "name": "run", "cwd": "./examples/triplehelix-hydrolysis/", "sequence": ["reactions"], "reactions": { "hydrolysis_naive": { } }, "mds": { "relax": { "mdp": "pull-slow-growth.mdp", }, }, "topology": { "reactive": {"include": "SOL"}, }, "parameterize_at_setup": False, "changer": { "topology": { "parameterization": "grappa", }, "coordinates": { "md": "relax", "slow_growth": True, }, }, "kmc": "rfkmc", "top": "triple.top", "gro": "triple-eq.gro", "ndx": "index.ndx", "tpr": "pull.tpr", "xtc": "pull.xtc", "trr": "pull.trr" } ``` ```{python} run2 = RunManager(config=Config(opts=opts_for_just_reaction)) ``` ```{python} for i in range(3): next(run2) ``` ```{python} next(run2) ``` ```{python} run2.recipe_collection ``` ```{python} run2.tasks.queue ``` ```{python} run2.kmcresult ``` ```{python} next(run2) ``` ```{python} # | eval: false while run2.state != State.DONE: next(run2) ``` `kimmdy.3_apply_recipe INFO: Recipe: 642⚡644 131300⚡131301 131300⚡131302 131300➡642 131301➡644 131302➡64` ```{python} concat_traj( dir = "./examples/triplehelix-hydrolysis/run_010/", filetype="xtc", steps="all", output_group="System", open_vmd=True ) ``` ```{python} plot_rates( dir = "./examples/triplehelix-hydrolysis/run_022/", ) ```