本文整理汇总了Python中radical.ensemblemd.SingleClusterEnvironment类的典型用法代码示例。如果您正苦于以下问题:Python SingleClusterEnvironment类的具体用法?Python SingleClusterEnvironment怎么用?Python SingleClusterEnvironment使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了SingleClusterEnvironment类的15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: enmd_setup_run
def enmd_setup_run(request):
from radical.ensemblemd import SingleClusterEnvironment
try:
sec = SingleClusterEnvironment(
#resource="local.localhost",
#cores=1,
#walltime=1,
resource="xsede.stampede",
cores=1,
walltime=1,
username='tg831932',
project='TG-MCB090174',
access_schema='ssh',
queue='development',
database_url='mongodb://suvigya:[email protected]:51585',
database_name='rutgers_thesis'
)
test = _TestRun(steps=1,instances=1)
ret_allocate = sec.allocate()
ret_run = sec.run(test)
ret_deallocate = sec.deallocate()
except Exception as e:
#print ret_run
raise
return ret_allocate,ret_run,ret_deallocate
示例2: test__simulation_analysis_loop_profiling
def test__simulation_analysis_loop_profiling(self):
""" Tests the Pipeline execution pattern API.
"""
cluster = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=30,
username=None,
allocation=None
)
# wait=True waits for the pilot to become active
# before the call returns. This is not useful when
# you want to take advantage of the queueing time /
# file-transfer overlap, but it's useful for baseline
# performance profiling of a specific pattern.
cluster.allocate(wait=True)
nopsa = _NopSA(
maxiterations=1,
simulation_instances=4,
analysis_instances=4,
idle_time = 10
)
cluster.run(nopsa)
pdct = nopsa.execution_profile_dict
dfrm = nopsa.execution_profile_dataframe
示例3: test__copy_input_data_single
def test__copy_input_data_single(self):
"""Check if we can copy output data to a different location on the execution host - single input.
"""
cluster = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=5
)
test = _TestCopyOutputData_Pattern(
instances=1,
output_copy_directives=["checksum.txt > {0}".format(self._output_dir)]
)
cluster.allocate()
cluster.run(test)
示例4: test__link_input_data_multi
def test__link_input_data_multi(self):
"""Check if we can link input data from a location on the execution host - multiple input.
"""
cluster = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=15
)
test = _TestLinkInputData_Pattern(
instances=1,
link_directives=["/etc/passwd", "/etc/group"],
checksum_inputfile="passwd",
download_output="CHKSUM_3"
)
cluster.allocate()
cluster.run(test)
示例5: test__link_input_data_single_rename
def test__link_input_data_single_rename(self):
"""Check if we can link input data from a location on the execution host - single input with rename.
"""
cluster = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=15
)
test = _TestLinkInputData_Pattern(
instances=1,
link_directives="/etc/passwd > input",
checksum_inputfile="input",
download_output="CHKSUM_2"
)
cluster.allocate()
cluster.run(test)
示例6: enmd_setup_run
def enmd_setup_run(request):
from radical.ensemblemd import SingleClusterEnvironment
try:
sec = SingleClusterEnvironment(
resource="local.localhost",
cores=1,
walltime=1,
database_url='mongodb://suvigya:[email protected]:51585',
database_name='rutgers_thesis'
)
test = _TestRun(steps=1,instances=1)
ret_allocate = sec.allocate()
ret_run = sec.run(test)
ret_deallocate = sec.deallocate()
except Exception as e:
print ret_run
raise
return ret_allocate,ret_run,ret_deallocate
示例7: test__single_cluster_environment_api
def test__single_cluster_environment_api(self):
""" Test the single cluster environment API.
"""
from radical.ensemblemd import SingleClusterEnvironment
sec = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=1
)
try:
sec.allocate()
sec.run("wrong_type")
assert False, "TypeError execption expected."
except Exception, ex:
pass
示例8: enmd_setup
def enmd_setup():
from radical.ensemblemd import SingleClusterEnvironment
try:
sec = SingleClusterEnvironment(
resource="local.localhost",
cores=1,
walltime=1,
database_url='mongodb://suvigya:[email protected]:51585',
database_name='rutgers_thesis'
)
ret_allocate = sec.allocate(wait=True)
ret_deallocate = False
ret_deallocate= sec.deallocate()
except Exception as e:
print 'test failed'
raise
return ret_allocate,ret_deallocate
示例9: test_pipeline_remote
def test_pipeline_remote(self,cmdopt):
#if __name__ == "__main__":
resource = cmdopt
home = expanduser("~")
try:
with open('%s/workspace/EnsembleMDTesting/config.json'%home) as data_file:
config = json.load(data_file)
#resource='xsede.stampede'
print "project: ",config[resource]['project']
print "username: ", config[resource]['username']
# Create a new static execution context with one resource and a fixed
# number of cores and runtime.
cluster = SingleClusterEnvironment(
resource=resource,
cores=1,
walltime=15,
#username='tg831932',
username=config[resource]['username'],
#project="TG-MCB090174",
#access_schema="ssh",
#queue="development",
project=config[resource]['project'],
access_schema = config[resource]['schema'],
queue = config[resource]['queue'],
database_url='mongodb://suvigya:[email protected]:51585',
database_name='rutgers_thesis',
)
os.system('/bin/echo remote > input_file.txt')
# Allocate the resources.
cluster.allocate()
# Set the 'instances' of the pipeline to 1. This means that 1 instance
# of each pipeline step is executed.
app = _TestPipeline(steps=1,instances=1)
cluster.run(app)
# Deallocate the resources.
cluster.deallocate()
f = open("%s/workspace/EnsembleMDTesting/temp_results/remote_file.txt"%home)
print "Name of file: ", f.name
print "file closed or not: ", f.closed
fname = f.readline().split()
print "fname: ", fname
assert fname == ['remote']
f.close()
os.remove("%s/workspace/EnsembleMDTesting/temp_results/remote_file.txt"%home)
except EnsemblemdError, er:
print "Ensemble MD Toolkit Error: {0}".format(str(er))
raise # Just raise the execption again to get the backtrace
示例10: test_copy_input_data_single
def test_copy_input_data_single(self):
#if __name__ == '__main__':
#resource = 'local.localhost'
try:
with open('%s/config.json'%os.path.dirname(os.path.abspath(__file__))) as data_file:
config = json.load(data_file)
# Create a new static execution context with one resource and a fixed
# number of cores and runtime.
cluster = SingleClusterEnvironment(
resource='xsede.stampede',
cores=1,
walltime=15,
#username=None,
username='tg831932',
project='TG-MCB090174',
access_schema='ssh',
queue='development',
#project=config[resource]['project'],
#access_schema = config[resource]['schema'],
#queue = config[resource]['queue'],
database_url='mongodb://suvigya:[email protected]:51585/rutgers_thesis'
)
os.system('/bin/echo passwd > input_file.txt')
# Allocate the resources.
cluster.allocate(wait=True)
# Set the 'instances' of the pipeline to 1. This means that 1 instance
# of each pipeline step is executed.
## app = _TestMyApp(instances=1,
## copy_directives="/etc/passwd",
## checksum_inputfile="passwd",
## download_output="CHKSUM_1"
## )
app = _TestMyApp(steps=1,instances=1)
cluster.run(app)
f = open("./output_file.txt")
print "Name of file: ", f.name
print "file closed or not: ", f.closed
fname = f.readline().split()
print "fname: ", fname
cluster.deallocate()
assert fname == ['passwd']
f.close()
os.remove("./output_file.txt")
except Exception as er:
print "Ensemble MD Toolkit Error: {0}".format(str(er))
raise # Just raise the execption again to get the backtrace
示例11: test__throw_on_malformed_kernel
def test__throw_on_malformed_kernel(self):
"""Test if an exception is thrown in case things go wrong in the Simulation-Analysis pattern.
"""
try:
# Create a new static execution context with one resource and a fixed
# number of cores and runtime.
cluster = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=1,
username=None,
allocation=None
)
ccount = _FaultyPattern(maxiterations=1, simulation_instances=1, analysis_instances=1)
cluster.run(ccount)
assert False, "Expected exception due to malformed URL in Pattern description."
except EnsemblemdError, er:
# Exception should pop up.
assert True
示例12: enmd_setup
def enmd_setup():
from radical.ensemblemd import SingleClusterEnvironment
try:
sec = SingleClusterEnvironment(
resource="xsede.stampede",
cores=1,
walltime=1,
username='tg831932',
project='TG-MCB090174',
access_schema='ssh',
queue='development',
database_url='mongodb://suvigya:[email protected]:51585',
database_name='rutgers_thesis'
)
ret_allocate = sec.allocate(wait=True)
ret_deallocate = False
ret_deallocate= sec.deallocate()
except Exception as e:
print 'test failed'
raise
return ret_allocate,ret_deallocate
示例13: test__copy_input_data_multi
def test__copy_input_data_multi(self):
"""Check if we can copy input data from a location on the execution host - multiple input.
"""
cluster = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=15
)
test = _TestCopyInputData_Pattern(
instances=1,
copy_directives=["/etc/passwd", "/etc/group"],
checksum_inputfile="passwd",
download_output="CHKSUM_3"
)
cluster.allocate()
cluster.run(test)
f = open("./CHKSUM_3")
csum, fname = f.readline().split()
assert "passwd" in fname
f.close()
os.remove("./CHKSUM_3")
示例14: test__upload_input_data_single_rename
def test__upload_input_data_single_rename(self):
"""Check if we can upload input data from a location on the host running these tests - single input with rename.
"""
cluster = SingleClusterEnvironment(
resource="localhost",
cores=1,
walltime=15
)
test = _TestUploadInputData_Pattern(
instances=1,
upload_directives="/etc/passwd > input",
checksum_inputfile="input",
download_output="CHKSUM_2"
)
cluster.allocate()
cluster.run(test)
f = open("./CHKSUM_2")
csum, fname = f.readline().split()
assert "input" in fname
f.close()
os.remove("./CHKSUM_2")
示例15: test_sal
def test_sal(self,cmdopt):
#if __name__ == "__main__":
resource = cmdopt
home = expanduser("~")
try:
with open('%s/workspace/EnsembleMDTesting/config.json'%home) as data_file:
config = json.load(data_file)
print 'Project: ',config[resource]['project']
print 'Username: ',config[resource]['username']
# Create a new static execution context with one resource and a fixed
# number of cores and runtime.
cluster = SingleClusterEnvironment(
resource=resource,
cores=1,
walltime=15,
username=config[resource]['username'],
project=config[resource]['project'],
access_schema = config[resource]['schema'],
queue = config[resource]['queue'],
database_url='mongodb://suvigya:[email protected]:51585/rutgers_thesis',
#database_name='myexps',
)
# Allocate the resources.
cluster.allocate()
randomsa = RandomSA(maxiterations=1, simulation_instances=1, analysis_instances=1)
cluster.run(randomsa)
cluster.deallocate()
# After execution has finished, we print some statistical information
# extracted from the analysis results that were transferred back.
for it in range(1, randomsa.iterations+1):
print "\nIteration {0}".format(it)
ldists = []
for an in range(1, randomsa.analysis_instances+1):
ldists.append(int(open("analysis-{0}-{1}.dat".format(it, an), "r").readline()))
print " * Levenshtein Distances: {0}".format(ldists)
print " * Mean Levenshtein Distance: {0}".format(sum(ldists) / len(ldists))
assert os.path.isfile("%s/workspace/EnsembleMDTesting/E2E_test/analysis-1-1.dat"%home)
os.remove("%s/workspace/EnsembleMDTesting/E2E_test/analysis-1-1.dat"%home)
except EnsemblemdError, er:
print "Ensemble MD Toolkit Error: {0}".format(str(er))
raise # Just raise the execption again to get the backtrace