def init_project(p_name,
sys_name=None,
m_freq=None,
p_freq=None,
platform=None,
dbhost=None,
w_threads=None):
#def init_project(p_name, **freq):
from adaptivemd import Project
#if p_name in Project.list():
# print(project.name, "Deleting existing version of this test project")
# Project.delete(p_name)
if dbhost is not None:
Project.set_dbhost(dbhost)
project = Project(p_name)
if project.name in Project.list():
print(
project.name,
"Project {0} exists, reading it from database".format(
project.name))
else:
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:///$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)
if platform == 'CPU':
print(
project.name,
"Using CPU simulation platform with {0} threads per worker".
format(w_threads))
sim_args += ' --cpu-cpu-threads {0}'.format(w_threads)
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]
#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')
project.generators.add(ca_modeller_2)
project.generators.add(all_modeller_2)
project.generators.add(ca_modeller_5)
project.generators.add(all_modeller_5)
project.generators.add(engine_2)
project.generators.add(engine_5)
[print(g) for g in project.generators]
return project
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