def setUpClass(cls):
# init project and resource
import tempfile
cls.shared_path = tempfile.mkdtemp(prefix="adaptivemd")
Project.delete('example-simple-1')
cls.project = Project('example-simple-1')
# ----------------------------------------------------------------------
# CREATE THE RESOURCE
# the instance to know about the place where we run simulations
# ----------------------------------------------------------------------
cls.project.initialize({'shared_path': cls.shared_path})
if os.getenv('CONDA_BUILD', False):
# activate the conda build test environment for workers
cls.f_base = 'examples/files/alanine/'
prefix = os.getenv('PREFIX')
assert os.path.exists(prefix)
cls.project.configuration.wrapper.pre.insert(
0, 'source activate {prefix}'.format(prefix=prefix))
# TODO why does test_simple_wrapper not
# have a chdir to ci test environment?
test_tmp = prefix + '/../test_tmp/'
if os.getcwd() is not test_tmp:
os.chdir(test_tmp)
else:
# set the path for the workers to the path of the test interpreter.
import sys
cls.f_base = '../../examples/files/alanine/'
cls.project.configuration.wrapper.pre.insert(
0, 'PATH={python_path}:$PATH'.format(
python_path=os.path.dirname(sys.executable)))
return cls
def setUpClass(cls):
'''
Operations that configure the test environment
----------------------------------------------
env :
determine if local or in integration environment
pkg :
object imports and coordination
cfg :
object instantiation and building
one-time operations that set up for test
'''
# init project and resource
import tempfile
cls.shared_path = tempfile.mkdtemp(prefix="adaptivemd")
Project.delete('test-skeleton')
cls.project = Project('test-skeleton')
cls.project.initialize({'shared_path': cls.shared_path})
# ----------------------------------------------------------------------
# CREATE THE RESOURCE
# the instance to know about the place where we run simulations
# ----------------------------------------------------------------------
if os.getenv('CONDA_BUILD', False):
# activate the conda build test environment
cls.f_base = 'examples/files/alanine/'
prefix = os.getenv('PREFIX')
assert os.path.exists(prefix)
cls.project.configuration.wrapper.pre.insert(
0, 'source activate {prefix}'.format(prefix=prefix))
# TODO why does test_simple_wrapped not
# have a chdir to ci test environment?
# TODO this is dealing in relative paths
# --> should check cwd based on absolute path
test_tmp = prefix + '/../test_tmp/'
if os.getcwd() is not test_tmp:
os.chdir(test_tmp)
else:
# set the path for the workers to the path of the test interpreter.
import sys
cls.f_base = '../../examples/files/alanine/'
cls.project.configuration.wrapper.pre.insert(
0, 'PATH={python_path}:$PATH'.format(
python_path=os.path.dirname(sys.executable)))
return cls
def init_project(p_name,
sys_name=None,
m_freq=None,
p_freq=None,
platform=None,
reinitialize=False): #, dblocation=None):
#def init_project(p_name, **freq):
from adaptivemd import Project
#if p_name in Project.list():
# print("Deleting existing version of this test project")
# Project.delete(p_name)
dburl = os.environ.get("ADMD_DBURL", 0)
if dburl:
logger.info("Set ADMD_DBURL to: " + dburl)
Project.set_dburl(dburl)
# if dblocation is not None:
# Project.set_dblocation(dblocation)
if reinitialize:
logger.info(
"Project {0} exists, deleting it from database to reinialize".
format(p_name))
Project.delete(p_name)
if p_name in Project.list():
logger.info(
"Project {0} exists, reading it from database".format(p_name))
project = Project(p_name)
elif not all([sys_name, m_freq, p_freq, platform]):
raise ValueError(
"Must define all parameters [{0}] to initialize new project\nHave: {1}"
.format("sys_name,m_freq,p_freq,platform",
[sys_name, m_freq, p_freq, platform].__repr__()))
else:
project = Project(p_name)
from adaptivemd import File, OpenMMEngine
from adaptivemd.analysis.pyemma import PyEMMAAnalysis
# Initialize w/ config file: 1 of multiple options
# TODO add config filename argument
configuration_file = 'configuration.cfg'
project.initialize(configuration_file)
f_name = '{0}.pdb'.format(sys_name)
# FIXME add system specifications to configuration file
f_base = 'file:///$ADMD_FILES/{0}/'.format(sys_name)
f_structure = File(f_base + f_name).load()
f_system_2 = File(f_base + 'system-2.xml').load()
f_integrator_2 = File(f_base + 'integrator-2.xml').load()
f_system_5 = File(f_base + 'system-5.xml').load()
f_integrator_5 = File(f_base + 'integrator-5.xml').load()
sim_args = '-r -p {0}'.format(platform)
engine_2 = OpenMMEngine(f_system_2, f_integrator_2, f_structure,
sim_args).named('openmm-2')
engine_5 = OpenMMEngine(f_system_5, f_integrator_5, f_structure,
sim_args).named('openmm-5')
# FIXME this is dumb and hard for user to deal with
# TODO engine selection by name
m_freq_2 = m_freq
p_freq_2 = p_freq
m_freq_5 = m_freq * 2 / 5
p_freq_5 = p_freq * 2 / 5
engine_2.add_output_type('master', 'allatoms.dcd', stride=m_freq_2)
engine_2.add_output_type('protein',
'protein.dcd',
stride=p_freq_2,
selection='protein')
engine_5.add_output_type('master', 'allatoms.dcd', stride=m_freq_5)
engine_5.add_output_type('protein',
'protein.dcd',
stride=p_freq_5,
selection='protein')
ca_features = {'add_distances_ca': None}
#features = {'add_inverse_distances': {'select_Backbone': None}}
ca_modeller_2 = PyEMMAAnalysis(engine_2, 'protein',
ca_features).named('pyemma-ca-2')
ca_modeller_5 = PyEMMAAnalysis(engine_5, 'protein',
ca_features).named('pyemma-ca-5')
pos = [
'(rescode K and mass > 13) ' + 'or (rescode R and mass > 13) ' +
'or (rescode H and mass > 13)'
]
neg = ['(rescode D and mass > 13) ' + 'or (rescode E and mass > 13)']
ionic_features = {
'add_distances': {
'select': pos
},
'kwargs': {
'indices2': {
'select': neg
}
}
}
all_features = [ca_features, ionic_features]
inv_ca_features = {'add_inverse_distances': {'select_Ca': None}}
#ok#ionic_modeller = {'add_distances': {'select':
#ok# ['rescode K or rescode R or rescode H']},
#ok# 'kwargs': {'indices2': {'select':
#ok# 'rescode D or rescode E']}}}
#contact_features = [ {'add_inverse_distances':
# {'select_Backbone': None}},
# {'add_residue_mindist': None,
# 'kwargs': {'threshold': 0.6}}
# ]
all_modeller_2 = PyEMMAAnalysis(engine_2, 'protein',
all_features).named('pyemma-ionic-2')
all_modeller_5 = PyEMMAAnalysis(engine_5, 'protein',
all_features).named('pyemma-ionic-5')
inv_modeller_2 = PyEMMAAnalysis(
engine_2, 'protein', inv_ca_features).named('pyemma-invca-2')
inv_modeller_5 = PyEMMAAnalysis(
engine_5, 'protein', inv_ca_features).named('pyemma-invca-5')
project.generators.add(ca_modeller_2)
project.generators.add(all_modeller_2)
project.generators.add(inv_modeller_2)
project.generators.add(ca_modeller_5)
project.generators.add(all_modeller_5)
project.generators.add(inv_modeller_5)
project.generators.add(engine_2)
project.generators.add(engine_5)
#[print(g) for g in project.generators]
return project
import os
from adaptivemd import Project
from adaptivemd import OpenMMEngine
from adaptivemd import PyEMMAAnalysis
from adaptivemd import File
from adaptivemd import WorkerScheduler
import mdtraj as md
if __name__ == '__main__':
Project.delete('example-simple-1')
project = Project('example-simple-1')
# --------------------------------------------------------------------------
# CREATE THE RESOURCE
# the instance to know about the place where we run simulations
# --------------------------------------------------------------------------
project.initialize({'shared_path': '$HOME'})
# --------------------------------------------------------------------------
# CREATE THE ENGINE
# the instance to create trajectories
# --------------------------------------------------------------------------
pdb_file = File('file://../../examples/files/alanine/alanine.pdb').named(
def init_project(p_name,
sys_name,
m_freq,
p_freq,
platform,
reinitialize=False): #, dblocation=None):
#def init_project(p_name, **freq):
from adaptivemd import Project
#if p_name in Project.list():
# print("Deleting existing version of this test project")
# Project.delete(p_name)
dburl = os.environ.get("ADMD_DBURL")
if dburl:
logger.info("Set ADMD_DBURL to: " + dburl)
Project.set_dburl(dburl)
# if dblocation is not None:
# Project.set_dblocation(dblocation)
if reinitialize:
logger.info(
"Project {0} exists, deleting it from database to reinialize".
format(p_name))
Project.delete(p_name)
if p_name in Project.list():
logger.info(
"Project {0} exists, reading it from database".format(p_name))
project = Project(p_name)
else:
project = Project(p_name)
from adaptivemd import File, OpenMMEngine
from adaptivemd.analysis.pyemma import PyEMMAAnalysis
#####################################
# NEW initialize sequence
configuration_file = 'configuration.cfg'
project.initialize(configuration_file)
#
# OLD initialize sequence
#from adaptivemd import LocalResource
#resource = LocalResource('/lustre/atlas/scratch/jrossyra/bip149/admd/')
#project.initialize(resource)
#####################################
f_name = '{0}.pdb'.format(sys_name)
# only works if filestructure is preserved as described in 'jro_ntl9.ipynb'
# and something akin to job script in 'admd_workers.pbs' is used
f_base = 'file:///$ADMDRP_ADAPTIVEMD/examples/files/{0}/'.format(
sys_name)
f_structure = File(f_base + f_name).load()
f_system_2 = File(f_base + 'system-2.xml').load()
f_integrator_2 = File(f_base + 'integrator-2.xml').load()
f_system_5 = File(f_base + 'system-5.xml').load()
f_integrator_5 = File(f_base + 'integrator-5.xml').load()
sim_args = '-r -p {0}'.format(platform)
engine_2 = OpenMMEngine(f_system_2, f_integrator_2, f_structure,
sim_args).named('openmm-2')
engine_5 = OpenMMEngine(f_system_5, f_integrator_5, f_structure,
sim_args).named('openmm-5')
m_freq_2 = m_freq
p_freq_2 = p_freq
m_freq_5 = m_freq * 2 / 5
p_freq_5 = p_freq * 2 / 5
engine_2.add_output_type('master', 'allatoms.dcd', stride=m_freq_2)
engine_2.add_output_type('protein',
'protein.dcd',
stride=p_freq_2,
selection='protein')
engine_5.add_output_type('master', 'allatoms.dcd', stride=m_freq_5)
engine_5.add_output_type('protein',
'protein.dcd',
stride=p_freq_5,
selection='protein')
ca_features = {'add_distances_ca': None}
#features = {'add_inverse_distances': {'select_Backbone': None}}
ca_modeller_2 = PyEMMAAnalysis(engine_2, 'protein',
ca_features).named('pyemma-ca-2')
ca_modeller_5 = PyEMMAAnalysis(engine_5, 'protein',
ca_features).named('pyemma-ca-5')
pos = [
'(rescode K and mass > 13) ' + 'or (rescode R and mass > 13) ' +
'or (rescode H and mass > 13)'
]
neg = ['(rescode D and mass > 13) ' + 'or (rescode E and mass > 13)']
ionic_features = {
'add_distances': {
'select': pos
},
'kwargs': {
'indices2': {
'select': neg
}
}
}
all_features = [ca_features, ionic_features]
inv_ca_features = {'add_inverse_distances': {'select_Ca': None}}
#ok#ionic_modeller = {'add_distances': {'select':
#ok# ['rescode K or rescode R or rescode H']},
#ok# 'kwargs': {'indices2': {'select':
#ok# 'rescode D or rescode E']}}}
#contact_features = [ {'add_inverse_distances':
# {'select_Backbone': None}},
# {'add_residue_mindist': None,
# 'kwargs': {'threshold': 0.6}}
# ]
all_modeller_2 = PyEMMAAnalysis(engine_2, 'protein',
all_features).named('pyemma-ionic-2')
all_modeller_5 = PyEMMAAnalysis(engine_5, 'protein',
all_features).named('pyemma-ionic-5')
inv_modeller_2 = PyEMMAAnalysis(
engine_2, 'protein', inv_ca_features).named('pyemma-invca-2')
inv_modeller_5 = PyEMMAAnalysis(
engine_5, 'protein', inv_ca_features).named('pyemma-invca-5')
project.generators.add(ca_modeller_2)
project.generators.add(all_modeller_2)
project.generators.add(inv_modeller_2)
project.generators.add(ca_modeller_5)
project.generators.add(all_modeller_5)
project.generators.add(inv_modeller_5)
project.generators.add(engine_2)
project.generators.add(engine_5)
#[print(g) for g in project.generators]
return project