def test_cooling_pj():
print("Job directory: " + jobdir)
print("Temporary directory: " + tmpdir)
# ---- CAMPAIGN INITIALISATION ---
print("Initializing Campaign")
# Set up a fresh campaign called "cooling"
my_campaign = uq.Campaign(name='cooling', work_dir=tmpdir)
# Define parameter space
params = {
"temp_init": {
"type": "float",
"min": 0.0,
"max": 100.0,
"default": 95.0
},
"kappa": {
"type": "float",
"min": 0.0,
"max": 0.1,
"default": 0.025
},
"t_env": {
"type": "float",
"min": 0.0,
"max": 40.0,
"default": 15.0
},
"out_file": {
"type": "string",
"default": "output.csv"
}
}
output_filename = params["out_file"]["default"]
output_columns = ["te", "ti"]
# Create an encoder, decoder and collation element
encoder = uq.encoders.GenericEncoder(template_fname=COOLING_APP_DIR +
'/cooling.template',
delimiter='$',
target_filename=ENCODED_FILENAME)
decoder = uq.decoders.SimpleCSV(target_filename=output_filename,
output_columns=output_columns,
header=0)
collater = uq.collate.AggregateSamples(average=False)
# Add the PCE app (automatically set as current app)
my_campaign.add_app(name="cooling",
params=params,
encoder=encoder,
decoder=decoder,
collater=collater)
vary = {"kappa": cp.Uniform(0.025, 0.075), "t_env": cp.Uniform(15, 25)}
# Create the sampler
if uqmethod == 'pce':
my_sampler = uq.sampling.PCESampler(vary=vary, polynomial_order=2)
if uqmethod == 'qmc':
my_sampler = uq.sampling.QMCSampler(vary=vary, n_samples=10)
# Associate the sampler with the campaign
my_campaign.set_sampler(my_sampler)
print("Generating samples")
# Will draw all (of the finite set of) samples
my_campaign.draw_samples()
print("Initialising EasyPJ Executor")
# Create EasyVVUQ-QCGPJ Executor that will process the execution
qcgpjexec = Executor()
# Create QCG PJ-Manager with 4 cores (if you want to use all available resources remove the resources parameter)
# Refer to the documentation for customisation options.
qcgpjexec.create_manager(dir=my_campaign.campaign_dir, resources='4')
# Define ENCODING task that will be used for execution of encodings using encoders specified by EasyVVUQ.
# The presented specification of 'TaskRequirements' assumes the execution of each of the tasks on 1 core.
qcgpjexec.add_task(
Task(TaskType.ENCODING, TaskRequirements(cores=Resources(exact=1))))
# Define EXECUTION task that will be used for the actual execution of application.
# The presented specification of 'TaskRequirements' assumes the execution of each of the tasks on 1 core,
# but for more advanced parallel applications the resource requirements may be extended to use
# many cores or even many resources.
# Each task will execute the command provided in the 'application' parameter.
qcgpjexec.add_task(
Task(TaskType.EXECUTION,
TaskRequirements(cores=Resources(exact=1)),
application='python3 ' + APPLICATION + " " + ENCODED_FILENAME))
print("Starting the execution of QCG Pilot Job tasks")
# Execute encodings and executions for all generated samples
qcgpjexec.run(campaign=my_campaign, submit_order=SubmitOrder.RUN_ORIENTED)
# Terminate QCG PJ-Manager
print("Completing the execution")
qcgpjexec.terminate_manager()
print("Collating results")
my_campaign.collate()
print("Making analysis")
if uqmethod == 'pce':
analysis = uq.analysis.PCEAnalysis(sampler=my_sampler,
qoi_cols=output_columns)
if uqmethod == 'qmc':
analysis = uq.analysis.QMCAnalysis(sampler=my_sampler,
qoi_cols=output_columns)
my_campaign.apply_analysis(analysis)
results = my_campaign.get_last_analysis()
stats = results['statistical_moments']['te']
per = results['percentiles']['te']
dist_out = results['output_distributions']['te']
print("Stats: ")
print(stats)
print("Percentiles: ")
print(per)
print("Output distribution: ")
print(dist_out)
print("Processing completed")
return stats, per, dist_out
def test_cooling_pj():
print("Job directory: " + jobdir)
print("Temporary directory: " + tmpdir)
# ---- CAMPAIGN INITIALISATION ---
print("Initializing Campaign")
# Set up a fresh campaign called "cooling"
my_campaign = uq.Campaign(name='cooling', work_dir=tmpdir)
# Define parameter space
params = {
"temp_init": {
"type": "float",
"min": 0.0,
"max": 100.0,
"default": 95.0
},
"kappa": {
"type": "float",
"min": 0.0,
"max": 0.1,
"default": 0.025
},
"t_env": {
"type": "float",
"min": 0.0,
"max": 40.0,
"default": 15.0
},
"out_file": {
"type": "string",
"default": "output.csv"
}
}
output_filename = params["out_file"]["default"]
output_columns = ["te", "ti"]
# Create an encoder, decoder and collation element
encoder = uq.encoders.GenericEncoder(template_fname=jobdir + '/' +
TEMPLATE,
delimiter='$',
target_filename=ENCODED_FILENAME)
decoder = uq.decoders.SimpleCSV(target_filename=output_filename,
output_columns=output_columns,
header=0)
collater = uq.collate.AggregateSamples(average=False)
# Add the PCE app (automatically set as current app)
my_campaign.add_app(name="cooling",
params=params,
encoder=encoder,
decoder=decoder,
collater=collater)
vary = {"kappa": cp.Uniform(0.025, 0.075), "t_env": cp.Uniform(15, 25)}
# Create the sampler
if uqmethod == 'pce':
my_sampler = uq.sampling.PCESampler(vary=vary, polynomial_order=2)
if uqmethod == 'qmc':
my_sampler = uq.sampling.QMCSampler(vary=vary, n_samples=10)
# Associate the sampler with the campaign
my_campaign.set_sampler(my_sampler)
# Will draw all (of the finite set of samples)
my_campaign.draw_samples()
print("Starting execution")
qcgpjexec = Executor()
# Create QCG PJ-Manager with 4 cores
# (if you want to use all available resources remove resources parameter)
qcgpjexec.create_manager(dir=my_campaign.campaign_dir,
resources='4',
log_level='debug')
qcgpjexec.add_task(
Task(TaskType.ENCODING, TaskRequirements(cores=Resources(exact=1))))
qcgpjexec.add_task(
Task(TaskType.EXECUTION,
TaskRequirements(cores=Resources(exact=1)),
application='python3 ' + jobdir + "/" + APPLICATION + " " +
ENCODED_FILENAME))
qcgpjexec.run(campaign=my_campaign, submit_order=SubmitOrder.RUN_ORIENTED)
qcgpjexec.terminate_manager()
print("Collating results")
my_campaign.collate()
print("Making analysis")
if uqmethod == 'pce':
analysis = uq.analysis.PCEAnalysis(sampler=my_sampler,
qoi_cols=output_columns)
if uqmethod == 'qmc':
analysis = uq.analysis.QMCAnalysis(sampler=my_sampler,
qoi_cols=output_columns)
my_campaign.apply_analysis(analysis)
results = my_campaign.get_last_analysis()
stats = results['statistical_moments']['te']
print("Processing completed")
return stats
def urbanair_no2_pj(tmpdir):
tmpdir = str(tmpdir)
print("Job directory: " + jobdir)
print("Temporary directory: " + tmpdir)
# ---- CAMPAIGN INITIALISATION ---
# Set up a UrbanAir campagin - NO2 modelling
my_campaign = uq.Campaign(name='urbanair_no2', work_dir=tmpdir)
home = os.environ['HOME']
# Define parameter space
params = {
"cars": {
"type": "integer",
"min": 10,
"max": 10000,
"default": 860
},
"gas_engine": {
"type": "float",
"min": 0.1,
"max": 1.0,
"default": 0.72
},
"gas_usage": {
"type": "float",
"min": 4.0,
"max": 13.0,
"default": 8.0
},
"gas_density": {
"type": "float",
"min": 0.001,
"max": 0.9,
"default": 0.75
},
"gas_no2_index": {
"type": "float",
"min": 0.001,
"max": 1.0,
"default": 0.00855
},
"out_file": {
"type": "string",
"default": "output.csv"
}
}
output_filename = params["out_file"]["default"]
output_columns = ["NO2"]
# Create encoders, decoder and collation element for UrbanAir
encoder = uq.encoders.GenericEncoder(template_fname=jobdir + '/' +
TEMPLATE,
delimiter='$',
target_filename=ENCODED_FILENAME)
wind_encoder = uq.encoders.GenericEncoder(template_fname=jobdir + '/' +
WIND_TEMPLATE,
delimiter='$',
target_filename='wind.dat')
scalars_encoder = uq.encoders.GenericEncoder(template_fname=jobdir + '/' +
SCALARS_TEMPLATE,
delimiter='$',
target_filename='scalars.dat')
fort13_encoder = uq.encoders.GenericEncoder(template_fname=jobdir + '/' +
FORT13_TEMPLATE,
delimiter='$',
target_filename='fort.13')
emis_encoder = EmisEncoder(template_fname=jobdir + '/' + EMIS_TEMPLATE,
delimiter='$',
target_filename='emis.dat')
encoders = uq.encoders.MultiEncoder(encoder, wind_encoder, scalars_encoder,
fort13_encoder, emis_encoder)
decoder = uq.decoders.SimpleCSV(target_filename=output_filename,
output_columns=output_columns,
header=0)
collater = uq.collate.AggregateSamples(average=False)
# Add the app (automatically set as current app)
my_campaign.add_app(name="urbanair_no2",
params=params,
encoder=encoders,
decoder=decoder,
collater=collater)
vary = {
"gas_engine": cp.Uniform(0.1, 0.9),
"gas_usage": cp.Uniform(3.0, 13.0),
"gas_density": cp.Uniform(0.001, 0.9),
"gas_no2_index": cp.Uniform(0.01, 0.1),
}
# Create the sampler
my_sampler = uq.sampling.SCSampler(vary=vary, polynomial_order=1)
# Associate the sampler with the campaign
my_campaign.set_sampler(my_sampler)
# Will draw all (of the finite set of samples)
my_campaign.draw_samples()
# use integrator between EasyVVUQ and QCG PilotJob
qcgpjexec = easypj.Executor()
# allocate 32 nodes, 24 cores each
qcgpjexec.create_manager(dir=my_campaign.campaign_dir, resources='32:24')
# create task to sample parameters. Each task will use 1 core
# the samples will be generated in parallel
qcgpjexec.add_task(
Task(TaskType.ENCODING, TaskRequirements(cores=Resources(exact=1))))
# run the MPI application using 16 nodes, 24 cores each
# Two ensembles should be run in parallel
qcgpjexec.add_task(
Task(TaskType.EXECUTION,
TaskRequirements(nodes=Resources(exact=16),
cores=Resources(exact=24)),
application=APPLICATION))
# first generate samples, then run ensembles
qcgpjexec.run(campaign=my_campaign,
submit_order=SubmitOrder.PHASE_ORIENTED)
qcgpjexec.terminate_manager()
my_campaign.collate()
sc_analysis = uq.analysis.SCAnalysis(sampler=my_sampler,
qoi_cols=output_columns)
my_campaign.apply_analysis(sc_analysis)
results = my_campaign.get_last_analysis()
stats = results['statistical_moments']['NO2']
return stats