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"default": 15.0},
"out_file": {
"type": "string",
"default": "output.csv"}}
output_filename = params["out_file"]["default"]
output_columns = ["te"]
# Create an encoder and decoder for PCE test app
encoder = uq.encoders.GenericEncoder(
template_fname='tests/cooling/cooling.template',
delimiter='$',
target_filename='cooling_in.json')
decoder = uq.decoders.SimpleCSV(target_filename=output_filename,
output_columns=output_columns,
header=0)
# Create a collation element for this campaign
collater = uq.collate.AggregateSamples(average=False)
# Create the sampler
vary = {
"kappa": cp.Uniform(0.025, 0.075),
"t_env": cp.Uniform(15, 25)
}
sampler = uq.sampling.PCESampler(vary=vary,
polynomial_order=3)
actions = uq.actions.ExecuteLocal("tests/cooling/cooling_model.py cooling_in.json")
stats = uq.analysis.PCEAnalysis(sampler=sampler,
qoi_cols=output_columns)
campaign(tmpdir, 'pce', 'pce', params, encoder, decoder, sampler,
collater, actions, stats, vary, 0, 1)
"group": ""
},
"bias2": {
"type": "file", "path": "tests/gauss/bias2.txt",
"common": False, "exists_local": True,
"target": "",
"group": ""
}
}
encoder = uq.encoders.GenericEncoder(template_fname='tests/gauss/gauss.template',
target_filename='gauss_in.json')
fixtures_encoder = uq.encoders.ApplyFixtures(fixtures=fixtures)
encoder_with_fixtures = uq.encoders.MultiEncoder(encoder, fixtures_encoder)
decoder = GaussDecoder(target_filename=params['out_file']['default'])
collater = uq.collate.AggregateSamples(average=False)
actions = uq.actions.ExecuteLocal("tests/gauss/gauss_json.py gauss_in.json")
stats = uq.analysis.EnsembleBoot(groupby=["mu"], qoi_cols=["Value"])
vary = {
"mu": cp.Uniform(1.0, 100.0),
}
sampler = uq.sampling.RandomSampler(vary=vary)
campaign(tmpdir, 'gauss', 'gauss', params, encoder, decoder, sampler,
collater, actions, stats, vary, 2, 2)
encoder = GaussEncoder(target_filename='gauss_in.json')
campaign(tmpdir, 'gauss', 'gauss', params, encoder, decoder, sampler,
collater, actions, stats, vary, 2, 2)
campaign(tmpdir, 'gauss', 'gauss', params, encoder_with_fixtures, decoder, sampler,
collater, actions, stats, vary, 2, 2)
campaign(tmpdir, 'gauss', 'gauss', params, encoder_with_fixtures, decoder, sampler,
collater, actions, stats, vary, 2, 2, db_type='json')
"velocity": {
"type": "float",
"min": 0.0,
"max": 1000.0,
"default": 10.0}}
# Create an encoder and decoder for the cannonsim app
encoder = uq.encoders.GenericEncoder(
template_fname='tests/cannonsim/test_input/cannonsim.template',
delimiter='#',
target_filename='in.cannon')
decoder = uq.decoders.SimpleCSV(
target_filename='output.csv', output_columns=[
'Dist', 'lastvx', 'lastvy'], header=0)
# Create a collation element for this campaign
collater = uq.collate.AggregateSamples(average=False)
actions = uq.actions.ExecuteLocal("/home/hpc/pn69ju/di73kuj2/cannonsim/bin/cannonsim in.cannon output.csv")
campaign.add_app(name='cannonsim',
params=params,
encoder=encoder,
decoder=decoder,
collater=collater)
stats = uq.analysis.BasicStats(qoi_cols=['Dist', 'lastvx', 'lastvy'])
# Make a random sampler
vary = {
"angle": cp.Uniform(0.0, 1.0),
"height": cp.Uniform(2.0, 10.0),
"velocity": cp.Normal(10.0, 1.0),
"mass": cp.Uniform(5.0, 1.0)
}
sampler = uq.sampling.RandomSampler(vary=vary)
campaign.set_sampler(sampler)
"out_file": {
"type": "string",
"default": "output.csv"}}
output_filename = params["out_file"]["default"]
output_columns = ["u"]
# Create an encoder, decoder and collation element
encoder = uq.encoders.GenericEncoder(
template_fname='tests/sc/sc.template',
delimiter='$',
target_filename='ade_in.json')
decoder = uq.decoders.SimpleCSV(target_filename=output_filename,
output_columns=output_columns,
header=0)
collater = uq.collate.AggregateSamples()
# Add the SC app (automatically set as current app)
my_campaign.add_app(name="sc",
params=params,
encoder=encoder,
decoder=decoder,
collater=collater)
# Create the sampler
vary = {
"Pe": cp.Uniform(100.0, 200.0),
"f": cp.Uniform(0.95, 1.05)
}
# different orders for the 2 parameters
my_sampler = uq.sampling.SCSampler(vary=vary, polynomial_order=[2, 5],
"type": "string",
"default": "output.csv"
},
}
vary = {
"mu": cp.Uniform(1.0, 100.0),
}
encoder = uq.encoders.GenericEncoder(template_fname='tests/gauss/gauss.template',
target_filename='gauss_in.json')
#decoder = JSONDecoder(target_filename='output.csv.json', output_columns=['numbers'])
decoder = uq.decoders.SimpleCSV(target_filename="output.csv",
output_columns=["numbers"],
header=0)
collater = uq.collate.AggregateSamples(average=False)
actions = uq.actions.ExecuteLocal("tests/gauss/gauss_json.py gauss_in.json")
sampler = uq.sampling.PCESampler(vary=vary, polynomial_order=4)
my_campaign = uq.Campaign(name='gauss_vector', work_dir=tmpdir)
my_campaign.add_app(name="gauss_vector",
params=params,
encoder=encoder,
decoder=decoder,
collater=collater)
my_campaign.set_sampler(sampler)
my_campaign.draw_samples()
my_campaign.populate_runs_dir()
my_campaign.apply_for_each_run_dir(actions)
my_campaign.collate()
data = my_campaign.get_collation_result()
print("===== DATA:\n ", data)
"default": 1.0},
"velocity": {
"type": "float",
"min": 0.0,
"max": 1000.0,
"default": 10.0}}
# Create an encoder, decoder and collater for the cannonsim app
encoder = uq.encoders.GenericEncoder(
template_fname='tests/cannonsim/test_input/cannonsim.template',
delimiter='#',
target_filename='in.cannon')
decoder = uq.decoders.SimpleCSV(
target_filename='output.csv', output_columns=[
'Dist', 'lastvx', 'lastvy'], header=0)
collater = uq.collate.AggregateSamples(average=False)
# Add the cannonsim app
my_campaign.add_app(name="cannonsim",
params=params,
encoder=encoder,
decoder=decoder,
collater=collater)
# Set the active app to be cannonsim (this is redundant when only one app
# has been added)
my_campaign.set_app("cannonsim")
# Make a random sampler
vary = {
"angle": cp.Uniform(0.0, 1.0),
"height": cp.DiscreteUniform(0, 100),
"out_file": {
"type": "string",
"default": "output.csv"}}
output_filename = params["out_file"]["default"]
output_columns = ["f"]
# Create an encoder, decoder and collation element
encoder = uq.encoders.GenericEncoder(
template_fname=HOME + '/sc/sobol.template',
delimiter='$',
target_filename='poly_in.json')
decoder = uq.decoders.SimpleCSV(target_filename=output_filename,
output_columns=output_columns,
header=0)
collater = uq.collate.AggregateSamples(average=False)
# Add the SC app (automatically set as current app)
my_campaign.add_app(name="sc",
params=params,
encoder=encoder,
decoder=decoder,
collater=collater)
# Create the sampler
vary = {
"x1": cp.Uniform(0.0, 1.0),
"x2": cp.Uniform(0.0, 1.0)}
# To use 'next_level_sparse_grid' below, we must select a nested
# sparse grid here
my_sampler = uq.sampling.SCSampler(vary=vary, polynomial_order=poly_order,