Purpose of this file is for the integration of Radical Pilot with AdaptiveMD workflow.
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import os
#mongodb_address = "mongodb://rp:rp@ds015335.mlab.com:15335/rp"
#mongodb_address = "mongodb://localhost:27017/rp"
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print(os.environ['RP_ENABLE_OLD_DEFINES'])
print(os.environ['RADICAL_PILOT_DBURL'])
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# Maybe don't work due to outside call of RP in the env
#os.environ.update({"RP_ENABLE_OLD_DEFINES": "True"})
#os.environ.update({"RADICAL_PILOT_DBURL": mongodb_address})
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from adaptivemd import Project, File#, Configuration
from adaptivemd.mongodb import MongoDBStorage
from adaptivemd.engine.openmm import OpenMMEngine
from adaptivemd.analysis.pyemma import PyEMMAAnalysis
from adaptivemd.rp.client import Client
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#Project.set_dblocation("user:user@ds159013.mlab.com", 59013)
#Project.set_dblocation("user:user@two.radical-project.org", 32769)
print(MongoDBStorage._db_url)
project_name = 'rp_compat42'
configuration_file = 'rp_compat.cfg'
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Project.delete(project_name)
#[Project.delete(p) for p in Project.list()]
Project.list()
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project = Project(project_name)
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c=project.configurations.one
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[g.__dict__ for g in project.generators]
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#project = Project(project_name)
# Configuration is not a user class
# view instances via the project
#
# refer to individual configurations
#cfg = project.configurations.one
#cfg_ornl_1 = project.configurations["ornl.1"]
#
# if there is a configuration file stored in the
# default locations with project_name, initialize
# will automatically find and read it.
#project.initialize()
#
# else if there is a configuration file in a
# different location or different name
#project.initialize('path/to/config.cfg')
#
# else must do this after project.initialize():
#project.read_configurations('path/to/config.cfg')
#project.initialize(configuration_file, default_configuration)
project.initialize(configuration_file)#default_configuration='ornl')
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project.configurations.all.name
#print(project.resources._set.content_class)
#print(project.generators._set.content_class)
#print(project.configurations._set.content_class)
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# sweet!
Project.list()
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# This is not necessary for executing with RP
#pdb_file = File('file://../files/alanine/alanine.pdb').named('initial_pdb').load()
#system_file = File('file://../files/alanine/system.xml').load()
#integrator_file = File('file://../files/alanine/integrator.xml').load()
pdb_file = File('file://../files/alanine/alanine.pdb').named('initial_pdb')#.load()
system_file = File('file://../files/alanine/system.xml')#.load()
integrator_file = File('file://../files/alanine/integrator.xml')#.load()
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engine = OpenMMEngine(
pdb_file=pdb_file,
system_file=system_file,
integrator_file=integrator_file,
args='-r --report-interval 1 -p CPU'
).named('openmm')
engine.add_output_type('master', 'master.dcd', stride=10)
engine.add_output_type('protein', 'protein.dcd', stride=1, selection='protein')
modeller = PyEMMAAnalysis(
engine=engine,
outtype='protein',
features={'add_inverse_distances': {'select_Backbone': None}}
).named('pyemma')
margs = dict(tica_stride=1, tica_lag=5, tica_dim=2,
clust_stride=1, msm_states=10, msm_lag=5)
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project.generators.add(engine)
project.generators.add(modeller)
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project.set_current_configuration('local')
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project._current_configuration.wrapper.prepend()
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project.read_configurations('rp_compat.cfg')
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#g = project.storage.generators
#[g.cache[idx].__dict__ for idx in g.index]
#og = g.cache[idx]
[c.__dict__ for c in project.storage.configurations]
#[c.cache[idx].__dict__ for idx in c.index]
#oc = c.cache[idx]
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# TODO have this return resource so it can be given directly
# to the queueing function, and keep the option of using
# the resource name as well
project.request_resource(total_cpus=2, total_time=10, destination='local')
#project.request_resource(2,30, destination='ornl.titan')
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project.configurations.all.name
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project.resources.first.__dict__
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tasks=list(project.tasks)
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ta=tasks[-1]
print ta.stdout
print ta.description
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#filter(lambda c: getattr(c, 'name').find('titan') >= 0, list(project.configurations))
#c=cs[1c=project.configurations.last]
#c.name
#c.allocation
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trajectories = project.new_trajectory(engine['pdb_file'], 100, engine, 4)
project.queue(trajectories, resource_name="local.localhost")
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trajectories = project.new_ml_trajectory(engine, 500, 4)
project.queue(trajectories)
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#client = Client('mongodb://user:user@two.radical-project.org:32769/', project_name)
client = Client('mongodb://localhost:27017/', project_name)
#import os
#os.environ['RADICAL_PILOT_DBURL'] = 'mongodb://rp:rp@ds015335.mlab.com:15335/rp'
#os.system('export RP_ENABLE_OLD_DEFINES=True')
client.start()
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client.stop()
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mixedbag = project.new_ml_trajectory(engine, 1000, 3)
mtask = modeller.execute(list(project.trajectories), **margs)
mixedbag.append(mtask)
project.queue(mixedbag)#, resource_name='local.localhost')
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f = lambda: len(project.trajectories) == 4
project.wait_until(f)
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#project.execution_manager.stop()
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project.models.__len__()
m=project.models.last
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[' '.join(['{0:.2f}'.format(v) for v in row]) for row in m.data['msm']['P']]
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for ta in project.tasks:
print ta.description[:55]
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project.workers.all.execute('shutdown')
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