本文整理汇总了Python中radical.ensemblemd.SingleClusterEnvironment.shared_data方法的典型用法代码示例。如果您正苦于以下问题：Python SingleClusterEnvironment.shared_data方法的具体用法？Python SingleClusterEnvironment.shared_data怎么用？Python SingleClusterEnvironment.shared_data使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类radical.ensemblemd.SingleClusterEnvironment的用法示例。
在下文中一共展示了SingleClusterEnvironment.shared_data方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: SingleClusterEnvironment
# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import shared_data [as 别名]
cluster = SingleClusterEnvironment(
resource=RPconfig.REMOTE_HOST,
cores=RPconfig.PILOTSIZE,
walltime=RPconfig.WALLTIME,
username=RPconfig.UNAME, # username
project=RPconfig.ALLOCATION, # project
queue=RPconfig.QUEUE,
database_url=RPconfig.DBURL,
)
cluster.shared_data = [
Kconfig.md_input_file,
Kconfig.lsdm_config_file,
Kconfig.top_file,
Kconfig.mdp_file,
"{0}/spliter.py".format(Kconfig.misc_loc),
"{0}/gro.py".format(Kconfig.misc_loc),
"{0}/pre_analyze.py".format(Kconfig.misc_loc),
"{0}/post_analyze.py".format(Kconfig.misc_loc),
"{0}/selection.py".format(Kconfig.misc_loc),
"{0}/reweighting.py".format(Kconfig.misc_loc),
]
cluster.allocate()
# We set the 'instances' of the simulation step to 16. This means that 16
# instances of the simulation are executed every iteration.
# We set the 'instances' of the analysis step to 1. This means that only
# one instance of the analysis is executed for each iteration
cur_path = os.path.dirname(os.path.abspath(__file__))
randomsa = Gromacs_LSDMap(
iterations=Kconfig.num_iterations,示例2: SingleClusterEnvironment
# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import shared_data [as 别名]
data.write('%s,%s,%s\n'%(coordinates.tolist()[0],coordinates.tolist()[1],coordinates.tolist()[2]))
data.close()
cluster = SingleClusterEnvironment(
resource="xsede.comet",
cores=core_count,
walltime=60,
username="solejar",
project="unc100",
#queue='debug',
database_url="mongodb://sean:[email protected]:19678/pilot_test"
)
cluster.shared_data =[
'/home/sean/midas/leaflet_finder/Vanilla/input.txt'
]
# Allocate the resources.
cluster.allocate()
#stage input data???
#make list of every window combination, to be used in atomDist
#for i in range(0,traj_count,window_size):
# for j in range(i, traj_count-1,window_size):
# list_elem = [i,j]
# window_list.append(list_elem)示例3: SingleClusterEnvironment
# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import shared_data [as 别名]
cluster = SingleClusterEnvironment(
resource=RPconfig.REMOTE_HOST,
cores=RPconfig.PILOTSIZE,
walltime=RPconfig.WALLTIME,
username = RPconfig.UNAME, #username
project = RPconfig.ALLOCATION, #project
queue = RPconfig.QUEUE,
database_url = RPconfig.DBURL,
# access_schema = config[RPconfig.REMOTE_HOST]['schema'] # This is so to support different access methods - gsissh, ssh - remove this if always running using ssh
)
cluster.shared_data = [
Kconfig.initial_crd_file,
Kconfig.md_input_file,
Kconfig.minimization_input_file,
Kconfig.top_file,
'{0}/postexec.py'.format(Kconfig.helper_scripts)
]
cluster.allocate()
coco_amber_static = Extasy_CocoAmber_Static(maxiterations=Kconfig.num_iterations, simulation_instances=Kconfig.num_CUs, analysis_instances=Kconfig.num_CUs/64)
cluster.run(coco_amber_static)
cluster.deallocate()
except EnsemblemdError, er:
print "Ensemble MD Toolkit Error: {0}".format(str(er))
raise # Just raise the execption again to get the backtrace示例4: SingleClusterEnvironment
# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import shared_data [as 别名]
# number of cores and runtime.
cluster = SingleClusterEnvironment(
resource=RPconfig.REMOTE_HOST,
cores=RPconfig.PILOTSIZE,
walltime=RPconfig.WALLTIME,
username = RPconfig.UNAME, #username
project = RPconfig.ALLOCATION, #project
queue = RPconfig.QUEUE,
database_url = RPconfig.DBURL,
# access_schema = config[RPconfig.REMOTE_HOST]['schema'] # This is so to support different access methods - gsissh, ssh - remove this if always running using ssh
)
cluster.shared_data = [
Kconfig.initial_crd_file,
Kconfig.md_input_file,
Kconfig.minimization_input_file,
Kconfig.top_file,
]
cluster.allocate()
coco_amber_static = Extasy_CocoAmber_Static(maxiterations=Kconfig.num_iterations, simulation_instances=Kconfig.num_CUs, analysis_instances=1)
cluster.run(coco_amber_static)
cluster.deallocate()
except EnsemblemdError, er:
print "Ensemble MD Toolkit Error: {0}".format(str(er))
raise # Just raise the execption again to get the backtrace
示例5:
# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import shared_data [as 别名]
resource=RPconfig.REMOTE_HOST,
cores=RPconfig.PILOTSIZE,
walltime=RPconfig.WALLTIME,
username = RPconfig.UNAME, #username
project = RPconfig.ALLOCATION, #project
queue = RPconfig.QUEUE,
database_url = RPconfig.DBURL
)
cluster.shared_data = [
Kconfig.md_input_file,
Kconfig.lsdm_config_file,
Kconfig.top_file,
Kconfig.mdp_file,
'{0}/spliter.py'.format(Kconfig.helper_scripts),
'{0}/gro.py'.format(Kconfig.helper_scripts),
'{0}/run.py'.format(Kconfig.helper_scripts),
'{0}/pre_analyze.py'.format(Kconfig.helper_scripts),
'{0}/post_analyze.py'.format(Kconfig.helper_scripts),
'{0}/selection.py'.format(Kconfig.helper_scripts),
'{0}/reweighting.py'.format(Kconfig.helper_scripts)
]
if Kconfig.ndx_file is not None:
cluster.shared_data.append(Kconfig.ndx_file)
cluster.allocate()
# We set the 'instances' of the simulation step to 16. This means that 16
# instances of the simulation are executed every iteration.
# We set the 'instances' of the analysis step to 1. This means that only